135 research outputs found
Annotation of genomics data using bidirectional hidden Markov models unveils variations in Pol II transcription cycle
DNA replication, transcription and repair involve the recruitment of protein complexes that change their composition as they progress along the genome in a directed or strand-specific manner. Chromatin immunoprecipitation in conjunction with hidden Markov models (HMMs) has been instrumental in understanding these processes, as they segment the genome into discrete states that can be related to DNA-associated protein complexes. However, current HMM-based approaches are not able to assign forward or reverse direction to states or properly integrate strand-specific (e.g.,RNA expression) with non-strand-specific (e.g.,ChIP) data, which is indispensable to accurately characterize directed processes. To overcome these limitations, we introduce bidirectional HMMs which infer directed genomic states from occupancy profiles de novo. Application to RNA polymerase II-associated factors in yeast and chromatin modifications in human T cells recovers the majority of transcribed loci, reveals gene-specific variations in the yeast transcription cycle and indicates the existence of directed chromatin state patterns at transcribed, but not at repressed, regions in the human genome. In yeast, we identify 32 new transcribed loci, a regulated initiation-elongation transition, the absence of elongation factors Ctk1 and Paf1 from a class of genes, a distinct transcription mechanism for highly expressed genes and novel DNA sequence motifs associated with transcription termination. We anticipate bidirectional HMMs to significantly improve the analyses of genome-associated directed processes
Accurate Promoter and Enhancer Identification in 127 ENCODE and Roadmap Epigenomics Cell Types and Tissues by GenoSTAN
Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today's largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN generally identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine
Occupational exposure to fungi and mycotoxins in cork industry: an exploratory study
Cork oak is the second most dominant forest species in Portugal and makes this country the work leader in cork export. This type of industry has already been associated with occupational exposure to several fungal species, most commonly with Penicillium globrum (belonging to Penicillium section Aspergilloides) and Chrysonilia sitophila. However, occupational exposure to mycotoxins has never been studied. Here we describe an exploratory work developed in a cork industry located in Portugal aiming at assessing exposure to fungi and mycotoxins.info:eu-repo/semantics/publishedVersio
Interaction of Ochratoxin A and Its Thermal Degradation Product 2′R-Ochratoxin A with Human Serum Albumin
Ochratoxin A (OTA) is a toxic secondary metabolite produced by several fungal species of the genus Penicillium and Aspergillus. 2′R-Ochratoxin A (2′R-OTA) is a thermal isomerization product of OTA formed during food processing at high temperatures. Both compounds are detectable in human blood in concentrations between 0.02 and 0.41 µg/L with 2′R-OTA being only detectable in the blood of coffee drinkers. Humans have approximately a fifty-fold higher exposure through food consumption to OTA than to 2′R-OTA. In human blood, however, the differences between the concentrations of the two compounds is, on average, only a factor of two. To understand these unexpectedly high 2′R-OTA concentrations found in human blood, the affinity of this compound to the most abundant protein in human blood the human serum albumin (HSA) was studied and compared to that of OTA, which has a well-known high binding affinity. Using fluorescence spectroscopy, equilibrium dialysis, circular dichroism (CD), high performance affinity chromatography (HPAC), and molecular modelling experiments, the affinities of OTA and 2′R-OTA to HSA were determined and compared with each other. For the affinity of HSA towards OTA, a logK of 7.0–7.6 was calculated, while for its thermally produced isomer 2′R-OTA, a lower, but still high, logK of 6.2–6.4 was determined. The data of all experiments showed consistently that OTA has a higher affinity to HSA than 2′R-OTA. Thus, differences in the affinity to HSA cannot explain the relatively high levels of 2′R-OTA found in human blood sample
Projeto ExPOSE: criação de protocolos para avaliação da exposição ocupacional ao microbiota em ambientes clínicos
FCT - 02/SAICT/2016 – Project nº 23222Nas últimas décadas, tem sido enfatizada a importância dos bioaerossóis em ambientes interiores, pelos efeitos adversos que causam na saúde humana e consequente impacto na saúde pública. Os hospitais e restantes unidades de saúde, pelas caraterísticas inerentes aos mesmos podem potenciar a contaminação microbiana, pelo que requerem uma atenção e intervenção especial para proteger, não só os pacientes mas também os profissionais de saúde, das infeções associadas aos cuidados de saúde e das doenças profissionais. O projeto ExPOSE tem como objetivo avaliar a exposição dos trabalhadores ao microbiota em unidades de cuidados de saúde e consequente elaboração de orientações para a redução dessa exposição.info:eu-repo/semantics/publishedVersio
Interaction of 2′R-ochratoxin A with Serum Albumins: Binding Site, Effects of Site Markers, Thermodynamics, Species Differences of Albumin-binding, and Influence of Albumin on Its Toxicity in MDCK Cells
Ochratoxin A (OTA) is a nephrotoxic mycotoxin. Roasting of OTA-contaminated coffee results in the formation of 2′R-ochratoxin A (2′R-OTA), which appears in the blood of coffee drinkers. Human serum albumin (HSA) binds 2′R-OTA (and OTA) with high affinity; therefore, albumin may influence the tissue uptake and elimination of ochratoxins. We aimed to investigate the binding site of 2′R-OTA (verses OTA) in HSA and the displacing effects of site markers to explore which molecules can interfere with its albumin-binding. Affinity of 2′R-OTA toward albumins from various species (human, bovine, porcine and rat) was tested to evaluate the interspecies differences regarding 2′R-OTA-albumin interaction. Thermodynamic studies were performed to give a deeper insight into the molecular background of the complex formation. Besides fluorescence spectroscopic and modeling studies, effects of HSA, and fetal bovine serum on the cytotoxicity of 2′R-OTA and OTA were tested in MDCK kidney cell line in order to demonstrate the influence of albumin-binding on the cellular uptake of ochratoxins. Site markers displaced more effectively 2′R-OTA than OTA from HSA. Fluorescence and binding constants of 2′R-OTA-albumin and OTA-albumin complexes showed different tendencies. Albumin significantly decreased the cytotoxicity of ochratoxins. 2′R-OTA, even at sub-toxic concentrations, increased the toxic action of OTA
In vitro Metabolism of Grandisin, a Lignan with Anti-chagasic Activity
Tetrahydrofuran lignans represent a well-known group of phenolic compounds capable of acting as antiparasitic agents. In the search for new medicines for the treatment of Chagas disease, one promising compound is grandisin which has shown significant activity on trypomastigote forms of Trypanosoma cruzi. In this work, the in vitro metabolism of grandisin was studied in the pig cecum model and by biomimetic phase I reactions, aiming at an ensuing a preclinical pharmacokinetic investigation. Although grandisin exhibited no metabolization by the pig microbiota, one putative metabolite was formed in a biomimetic model using Jacobsen catalyst. The putative metabolite was tested against T. cruzi revealing loss of activity in comparison to grandisin.FINEPFINEPFAPESPFAPESPCAPESCAPESCNPqCNP
International interlaboratory study to normalize liquid chromatography-based mycotoxin retention times through implementation of a retention index system
Monitoring for mycotoxins in food or feed matrices is necessary to ensure the safety and security of global food systems. Due to a lack of standardized methods and individual laboratory priorities, most institutions have developed their own methods for mycotoxin determinations. Given the diversity of mycotoxin chemical structures and physicochemical properties, searching databases, and comparing data between institutions is complicated. We previously introduced incorporating a retention index (RI) system into liquid chromatography mass spectrometry (LC-MS) based mycotoxin determinations. To validate this concept, we designed an interlaboratory study where each participating laboratory was sent N-alkylpyridinium-3-sulfonates (NAPS) RI standards, and 36 mycotoxin standards for analysis using their pre-optimized LC-MS methods. Data from 44 analytical methods were submitted from 24 laboratories representing various manufacturer platforms, LC columns, and mobile phase compositions. Mycotoxin retention times (tR) were converted to RI values based on their elution relative to the NAPS standards. Trichothecenes (deoxynivalenol, 3-acetyldeoxynivalenol, 15-acetyldeoxynivalenol) showed tR consistency (± 20–50 RI units, 1–5 % median RI) regardless of mobile phase or type of chromatography column in this study. For the remaining mycotoxins tested, the RI values were strongly impacted by the mobile phase composition and column chemistry. The ability to predict tR was evaluated based on the median RI mycotoxin values and the NAPS tR. These values were corrected using Tanimoto coefficients to investigate whether structurally similar compounds could be used as anchors to further improve accuracy. This study demonstrated the power of employing an RI system for mycotoxin determinations, further enhancing the confidence of identifications.Genome Canada, FWF Austrian Science Fund, Agriculture and Agri-Food Canada, Ministry of Education, Universities and Research, National Research Council Canada, MitacsThis research was supported by the NRC (Biotoxin Metrology, Nova Scotia), the ALIFAR project (Italian Ministry of University, Dipartimenti di Eccellenza 2023–2027), Genome Canada Technology Development Grant and MITACS scholarship, with resources provided by the VetCore Facility (Mass Spectrometry) of the University of Veterinary Medicine Vienna.Moreover, this research was supported by the Austrian Science Fund (FWF, P33188), the Mass Spectrometry Centre of the Faculty of Chemistry and the Exposome Austria Research Infrastructure at the University of Vienna.Journal of Chromatography
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
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