Tumour risks and genotype-phenotype correlations associated with germline variants in succinate dehydrogenase subunit genes SDHB, SDHC and SDHD.

BACKGROUND: Germline pathogenic variants in SDHB/SDHC/SDHD are the most frequent causes of inherited phaeochromocytomas/paragangliomas. Insufficient information regarding penetrance and phenotypic variability hinders optimum management of mutation carriers. We estimate penetrance for symptomatic tumours and elucidate genotype-phenotype correlations in a large cohort of SDHB/SDHC/SDHD mutation carriers. METHODS: A retrospective survey of 1832 individuals referred for genetic testing due to a personal or family history of phaeochromocytoma/paraganglioma. 876 patients (401 previously reported) had a germline mutation in SDHB/SDHC/SDHD (n=673/43/160). Tumour risks were correlated with in silico structural prediction analyses. RESULTS: Tumour risks analysis provided novel penetrance estimates and genotype-phenotype correlations. In addition to tumour type susceptibility differences for individual genes, we confirmed that the SDHD:p.Pro81Leu mutation has a distinct phenotype and identified increased age-related tumour risks with highly destabilising SDHB missense mutations. By Kaplan-Meier analysis, the penetrance (cumulative risk of clinically apparent tumours) in SDHB and (paternally inherited) SDHD mutation-positive non-probands (n=371/67 with detailed clinical information) by age 60 years was 21.8% (95% CI 15.2% to 27.9%) and 43.2% (95% CI 25.4% to 56.7%), respectively. Risk of malignant disease at age 60 years in non-proband SDHB mutation carriers was 4.2%(95% CI 1.1% to 7.2%). With retrospective cohort analysis to adjust for ascertainment, cumulative tumour risks for SDHB mutation carriers at ages 60 years and 80 years were 23.9% (95% CI 20.9% to 27.4%) and 30.6% (95% CI 26.8% to 34.7%). CONCLUSIONS: Overall risks of clinically apparent tumours for SDHB mutation carriers are substantially lower than initially estimated and will improve counselling of affected families. Specific genotype-tumour risk associations provides a basis for novel investigative strategies into succinate dehydrogenase-related mechanisms of tumourigenesis and the development of personalised management for SDHB/SDHC/SDHD mutation carriers

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

mCSM-NA: predicting the effects of mutations on protein-nucleic acids interactions

Submitted by Nuzia Santos ([email protected]) on 2018-05-18T17:59:22Z No. of bitstreams: 1 mCSM-NA.pdf: 3452123 bytes, checksum: bdc3d766f66a0fe2cb5e3917382bfa9e (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2018-05-18T18:01:31Z (GMT) No. of bitstreams: 1 mCSM-NA.pdf: 3452123 bytes, checksum: bdc3d766f66a0fe2cb5e3917382bfa9e (MD5)Made available in DSpace on 2018-05-18T18:01:32Z (GMT). No. of bitstreams: 1 mCSM-NA.pdf: 3452123 bytes, checksum: bdc3d766f66a0fe2cb5e3917382bfa9e (MD5) Previous issue date: 2017Fundação Oswaldo Cruz. Instituto Rene Rachou. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Instituto Rene Rachou. Belo Horizonte, MG, Brasil / Department of Biochemistry, University of Cambridge. Cambridge, UK / Department of Biochemistry and Molecular Biology. University of Melbourne. Melbourne, Australia.Over the past two decades, several computational methods have been proposed to predict how missense mutations can affect protein structure and function, either by altering protein stability or interactions with its partners, shedding light into potential molecular mechanisms giving rise to different phenotypes. Effectively and efficiently predicting consequences of mutations on protein–nucleic acid interactions, however, remained until recently a great and unmet challenge. Here we report an updated webserver for mCSM–NA, the only scalable method we are aware of capable of quantitatively predicting the effects of mutations in protein coding regions on nucleic acid binding affinities. We have significantly enhanced the original method by including a pharmacophore modelling and information of nucleic acid properties into our graph-based signatures, considering the reverse mutation and by using a refined, more reliable data set, based on a new release of the ProNIT database, which has significantly improved the reliability and applicability of the methodology. Our new predictive model was capable of achieving a correlation coefficient of up to 0.70 on cross-validation and 0.68 on blind-tests, outperforming its previous version. The server is freely available via a user-friendly web interface at: http://structure.bioc.cam.ac.uk/mcsm_na

CSM-lig: a web server for assessing and comparing protein–small molecule affinities.

Submitted by Nuzia Santos ([email protected]) on 2016-08-25T14:11:12Z No. of bitstreams: 1 ve_Pires_Douglas_CSM-lig_CPqRR_2016.pdf: 2525130 bytes, checksum: cca7594165cbcdec7a5885f95986d2d2 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2016-08-25T14:15:24Z (GMT) No. of bitstreams: 1 ve_Pires_Douglas_CSM-lig_CPqRR_2016.pdf: 2525130 bytes, checksum: cca7594165cbcdec7a5885f95986d2d2 (MD5)Made available in DSpace on 2016-08-25T14:15:24Z (GMT). No. of bitstreams: 1 ve_Pires_Douglas_CSM-lig_CPqRR_2016.pdf: 2525130 bytes, checksum: cca7594165cbcdec7a5885f95986d2d2 (MD5) Previous issue date: 2016Fundacao Oswaldo Cruz. Centro de Pesquisas Rene Rachou. Belo Horizonte, MG, BrasilUniversity of Cambridge. Department of Biochemistry. Cambridge, UK/University of Melbourne. Department of Biochemistry. Victoria, AustraliaDetermining the affinity of a ligand for a given protein is a crucial component of drug development and understanding their biological effects. Predicting binding affinities is a challenging and difficult task, and despite being regarded as poorly predictive, scoring functions play an important role in the analysis of molecular docking results. Here, we present CSM-Lig (http://structure.bioc.cam.ac.uk/csm_lig), a web server tailored to predict the binding affinity of a protein-small molecule complex, encompassing both protein and small-molecule complementarity in terms of shape and chemistry via graph-based structural signatures. CSM-Lig was trained and evaluated on different releases of the PDBbind databases, achieving a correlation of up to 0.86 on 10-fold cross validation and 0.80 in blind tests, performing as well as or better than other widely used methods. The web server allows users to rapidly and automatically predict binding affinities of collections of structures and assess the interactions made. We believe CSM-lig would be an invaluable tool for helping assess docking poses, the effects of multiple mutations, including insertions, deletions and alternative splicing events, in protein-small molecule affinity, unraveling important aspects that drive protein-compound recognition

Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

Submitted by Nuzia Santos ([email protected]) on 2019-08-27T17:30:09Z No. of bitstreams: 1 Human LC3 and GABARAP subfamily members.pdf: 8112205 bytes, checksum: eb1f2e99dfc8034ef553f8c671335818 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2019-08-27T17:33:36Z (GMT) No. of bitstreams: 1 Human LC3 and GABARAP subfamily members.pdf: 8112205 bytes, checksum: eb1f2e99dfc8034ef553f8c671335818 (MD5)Made available in DSpace on 2019-08-27T17:33:36Z (GMT). No. of bitstreams: 1 Human LC3 and GABARAP subfamily members.pdf: 8112205 bytes, checksum: eb1f2e99dfc8034ef553f8c671335818 (MD5) Previous issue date: 2019CSIR-Institute of Genomics and Integrative Biology. Mathura Road, New Delhi, India.Department of Biochemistry and Molecular Biology. Bio21 Institute. University of Melbourne. Melbourne, Victoria, Australia / University of Cambridge. Department of Biochemistry. Cambridgeshire, UK / Fundação Oswaldo Cruz. Instituto René Rachou. Belo Horizonte, MG, Brasil.Department of Biochemistry and Molecular Biology. Bio21 Institute. University of Melbourne. Melbourne, Victoria, Australia / Fundação Oswaldo Cruz. Instituto René Rachou. Belo Horizonte, MG, Brasil.National Institute of Immunology. Aruna Asif Ali Marg. New Delhi, India.CSIR-Institute of Genomics and Integrative Biology. Mathura Road, New Delhi, India / Academy of Scientific and Innovative Research (AcSIR). CSIR-Institute of Genomics and Integrative Biology. Mathura Road, New Delhi, India / Interdisciplinary Center for Scientific Computing. University of Heidelberg. Im Neuenheimer Feld 205. Heidelberg, Germany.Autophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators. Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3

Correction: Variation in Human Cytochrome P-450 Drug-Metabolism Genes: A Gateway to the Understanding of Plasmodium vivax Relapses.

[This corrects the article DOI: 10.1371/journal.pone.0160172.]

Variation in Human Cytochrome P-450 Drug-Metabolism Genes: A Gateway to the Understanding of Plasmodium vivax Relapses

Submitted by Nuzia Santos ([email protected]) on 2017-07-04T18:47:03Z No. of bitstreams: 1 Variation in Human Cytochrome P-450 Drug-Metabolism Genes_ A Gateway to the Understanding of Plasmodium vivax Relapses - pone.pdf: 5199113 bytes, checksum: 3de7aae9f22738fbbff5816b6cbd50bc (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2017-07-04T18:53:35Z (GMT) No. of bitstreams: 1 Variation in Human Cytochrome P-450 Drug-Metabolism Genes_ A Gateway to the Understanding of Plasmodium vivax Relapses - pone.pdf: 5199113 bytes, checksum: 3de7aae9f22738fbbff5816b6cbd50bc (MD5)Made available in DSpace on 2017-07-04T18:53:35Z (GMT). No. of bitstreams: 1 Variation in Human Cytochrome P-450 Drug-Metabolism Genes_ A Gateway to the Understanding of Plasmodium vivax Relapses - pone.pdf: 5199113 bytes, checksum: 3de7aae9f22738fbbff5816b6cbd50bc (MD5) Previous issue date: 2016Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Grupo de Pesquisa em Informatica de Biosistemas. Belo Horizonte, MG, Brazil/University of Cambridge. Department of Biochemistry. Cambridge, United KingdomFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Grupo de Pesquisa em Informatica de Biosistemas. Belo Horizonte, MG, BrazilUniversidade Federal de Mato Grosso. Hospital Julio Muller Cuiabá, MT, BrazilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Biologia Molecular e Grupo de Pesquisa Imunologia em Malária. Belo Horizonte, MG, BrasilAlthough Plasmodium vivax relapses are classically associated with hypnozoite activation, it has been proposed that a proportion of these cases are due to primaquine (PQ) treatment failure caused by polymorphisms in cytochrome P-450 2D6 (CYP2D6). Here, we present evidence that CYP2D6 polymorphisms are implicated in PQ failure, which was reinforced by findings in genetically similar parasites, and may explain a number of vivax relapses. Using a computational approach, these polymorphisms were predicted to affect the activity of CYP2D6 through changes in the structural stability that could lead to disruption of the PQ-enzyme interactions. Furthermore, because PQ is co-administered with chloroquine (CQ), we investigated whether CQ-impaired metabolism by cytochrome P-450 2C8 (CYP2C8) could also contribute to vivax recurrences. Our results show that CYP2C8-mutated patients frequently relapsed early (<42 days) and had a higher proportion of genetically similar parasites, suggesting the possibility of recrudescence due to CQ therapeutic failure. These results highlight the importance of pharmacogenetic studies as a tool to monitor the efficacy of antimalarial therapy

Variant type is associated with disease characteristics in SDHB, SDHC and SDHD-linked phaeochromocytoma-paraganglioma

Background Pathogenic germline variants in subunits of succinate dehydrogenase (SDHB, SDHC and SDHD) are broadly associated with disease subtypes of phaeochromocytoma-paraganglioma (PPGL) syndrome. Our objective was to investigate the role of variant type (ie, missense vs truncating) in determining tumour phenotype. Methods Three independent datasets comprising 950 PPGL and head and neck paraganglioma (HNPGL) patients were analysed for associations of variant type with tumour type and age-related tumour risk. All patients were carriers of pathogenic germline variants in the SDHB, SDHC or SDHD genes. Results Truncating SDH variants were significantly over-represented in clinical cases compared with missense variants, and carriers of SDHD truncating variants had a significantly higher risk for PPGL (p<0.001), an earlier age of diagnosis (p<0.0001) and a greater risk for PPGL/HNPGL comorbidity compared with carriers of missense variants. Carriers of SDHB truncating variants displayed a trend towards increased risk of PPGL, and all three SDH genes showed a trend towards over-representation of missense variants in HNPGL cases. Overall, variant types conferred PPGL risk in the (highest-to-lowest) sequence SDHB truncating, SDHB missense, SDHD truncating and SDHD missense, with the opposite pattern apparent for HNPGL (p<0.001). Conclusions SDHD truncating variants represent a distinct group, with a clinical phenotype reminiscent of but not identical to SDHB. We propose that surveillance and counselling of carriers of SDHD should be tailored by variant type. The clinical impact of truncating SDHx variants is distinct from missense variants and suggests that residual SDH protein subunit function determines risk and site of disease