20 results on '"Symul, L."'
Search Results
2. Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization
- Author
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Bonhoure, N, Bounova, G, Bernasconi, D, Praz, V, Lammers, F, Canella, D, Willis, I M, Herr, W, Hernandez, N, Delorenzi, M, Deplancke, B, Desvergne, B, Guex, N, Naef, F, Rougemont, J, Schibler, U, Andersin, T, Cousin, P, Gilardi, F, Gos, P, Raghav, S, Villeneuve, D, Fabbretti, R, Vlegel, V, Xenarios, I, Migliavacca, E, David, F, Jarosz, Y, Kuznetsov, D, Liechti, R, Martin, O, Delafontaine, J, Cajan, J, Gustafson, K, Krier, I, Leleu, M, Molina, N, Naldi, A, Rib, L, Symul, L, Bonhoure, N, Bounova, G, Bernasconi, D, Praz, V, Lammers, F, Canella, D, Willis, I M, Herr, W, Hernandez, N, Delorenzi, M, Deplancke, B, Desvergne, B, Guex, N, Naef, F, Rougemont, J, Schibler, U, Andersin, T, Cousin, P, Gilardi, F, Gos, P, Raghav, S, Villeneuve, D, Fabbretti, R, Vlegel, V, Xenarios, I, Migliavacca, E, David, F, Jarosz, Y, Kuznetsov, D, Liechti, R, Martin, O, Delafontaine, J, Cajan, J, Gustafson, K, Krier, I, Leleu, M, Molina, N, Naldi, A, Rib, L, and Symul, L
- Published
- 2014
3. Differential regulation of RNA polymerase III genes during liver regeneration
- Author
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Meghdad Yeganeh, Cristian Carmeli, Dominic Villeneuve, Mauro Delorenzi, Winship Herr, Leonor Rib, Nouria Hernandez, Viviane Praz, Nicolas Guex, CycliX consortium, Hernandez, N., Delorenzi, M., Deplancke, B., Desvergne, B., Guex, N., Herr, W., Naef, F., Rougemont, J., Schibler, U., Andersin, T., Cousin, P., Gilardi, F., Gos, P., Lammers, F., Lopes, M., Mange, F., Minocha, S., Raghav, S., Villeneuve, D., Fabbretti, R., Vlegel, V., Xenarios, I., Migliavacca, E., Praz, V., David, F., Jarosz, Y., Kuznetsov, D., Liechti, R., Martin, O., Delafontaine, J., Cajan, J., Carmeli, C., Gustafson, K., Krier, I., Leleu, M., Molina, N., Naldi, A., Rib, L., Sobel, J., Symul, L., Bounova, G., and Jacquet, P.
- Subjects
Chromatin Immunoprecipitation ,Transcription, Genetic ,DNA polymerase ,DNA polymerase II ,viruses ,RNA polymerase II ,RNA polymerase III ,Histones ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Transcription (biology) ,Genetics ,Animals ,Hepatectomy ,Humans ,Gene ,030304 developmental biology ,0303 health sciences ,biology ,Cell Cycle ,Gene regulation, Chromatin and Epigenetics ,Gene Expression Regulation, Developmental ,RNA Polymerase III ,Histone-Lysine N-Methyltransferase ,Liver regeneration ,Liver Regeneration ,Housekeeping gene ,Cell biology ,Liver ,biology.protein ,RNA Polymerase II ,Cell Division ,030217 neurology & neurosurgery ,Protein Binding - Abstract
Mouse liver regeneration after partial hepatectomy involves cells in the remaining tissue synchronously entering the cell division cycle. We have used this system and H3K4me3, Pol II and Pol III profiling to characterize adaptations in Pol III transcription. Our results broadly define a class of genes close to H3K4me3 and Pol II peaks, whose Pol III occupancy is high and stable, and another class, distant from Pol II peaks, whose Pol III occupancy strongly increases after partial hepatectomy. Pol III regulation in the liver thus entails both highly expressed housekeeping genes and genes whose expression can adapt to increased demand.
- Published
- 2019
4. A multiplicity of factors contributes to selective RNA polymerase III occupancy of a subset of RNA polymerase III genes in mouse liver
- Author
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Mauro Delorenzi, Irina Krier, Teemu Andersin, Li Long, Nicolas Guex, Arnaud Fortier, David Bernasconi, Marion Leleu, Guillaume Rey, Julia Cajan, Fabrice P. A. David, Winship Herr, Fabienne Lammers, Sunil K. Raghav, Olivier Martin, Jacques Rougemont, Aurélien Naldi, Roberto Fabbretti, Eugenia Migliavacca, Pascal Gos, Viviane Praz, Robin Liechti, Ueli Schibler, Gwendal LeMartelot, Nouria Hernandez, Laura Symul, Pascal Cousin, Frederick J. Ross, Yohan Jarosz, Béatrice Desvergne, Donatella Canella, Nacho Molina, Ioannis Xenarios, Felix Naef, Lucas Sinclair, Volker Vlegel, Federica Gilardi, Gwendal Le Martelot, Bart Deplancke, Dmitry Kuznetsov, University of Zurich, Delorenzi, Mauro, CycliX Consortium, Hernandez, N., Delorenzi, M., Deplancke, B., Desvergne, B., Guex, N., Herr, W., Naef, F., Rougemont, J., Schibler, U., Andersin, T., Cousin, P., Gilardi, F., Gos, P., Le Martelot, G., Lammers, F., Canella, D., Raghav, S., Fabbretti, R., Fortier, A., Long, L., Vlegel, V., Xenarios, I., Migliavacca, E., Praz, V., David, F., Jarosz, Y., Kuznetsov, D., Liechti, R., Martin, O., Ross, F., Sinclair, L., Cajan, J., Krier, I., Leleu, M., Molina, N., Naldi, A., Rey, G., Symul, L., and Bernasconi, D.
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Male ,Chromatin Immunoprecipitation ,2716 Genetics (clinical) ,Pseudogene ,genetic processes ,Biology ,RNA polymerase III ,Mice ,chemistry.chemical_compound ,RNA, Transfer ,SX00 SystemsX.ch ,1311 Genetics ,Transcription (biology) ,RNA polymerase ,Gene expression ,Genetics ,Animals ,Humans ,SX04 CycliX ,Gene ,Genetics (clinical) ,Oligonucleotide Array Sequence Analysis ,Models, Genetic ,Gene Expression Profiling ,Research ,RNA Polymerase III ,RNA ,Genomics ,Sequence Analysis, DNA ,Molecular biology ,Mice, Inbred C57BL ,enzymes and coenzymes (carbohydrates) ,Liver ,chemistry ,Transfer RNA ,570 Life sciences ,biology ,bacteria ,Chromatin Immunoprecipitation/methods ,Genomics/methods ,Liver/metabolism ,RNA Polymerase III/genetics ,RNA Polymerase III/metabolism ,RNA, Transfer/genetics ,RNA, Transfer/metabolism ,Sequence Analysis, DNA/methods - Abstract
The genomic loci occupied by RNA polymerase (RNAP) III have been characterized in human culture cells by genome-wide chromatin immunoprecipitations, followed by deep sequencing (ChIP-seq). These studies have shown that only ∼40% of the annotated 622 human tRNA genes and pseudogenes are occupied by RNAP-III, and that these genes are often in open chromatin regions rich in active RNAP-II transcription units. We have used ChIP-seq to characterize RNAP-III-occupied loci in a differentiated tissue, the mouse liver. Our studies define the mouse liver RNAP-III-occupied loci including a conserved mammalian interspersed repeat (MIR) as a potential regulator of an RNAP-III subunit-encoding gene. They reveal that synteny relationships can be established between a number of human and mouse RNAP-III genes, and that the expression levels of these genes are significantly linked. They establish that variations within the A and B promoter boxes, as well as the strength of the terminator sequence, can strongly affect RNAP-III occupancy of tRNA genes. They reveal correlations with various genomic features that explain the observed variation of 81% of tRNA scores. In mouse liver, loci represented in the NCBI37/mm9 genome assembly that are clearly occupied by RNAP-III comprise 50 Rn5s (5S RNA) genes, 14 known non-tRNA RNAP-III genes, nine Rn4.5s (4.5S RNA) genes, and 29 SINEs. Moreover, out of the 433 annotated tRNA genes, half are occupied by RNAP-III. Transfer RNA gene expression levels reflect both an underlying genomic organization conserved in dividing human culture cells and resting mouse liver cells, and the particular promoter and terminator strengths of individual genes.
- Published
- 2012
5. Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization
- Author
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Bonhoure, Nicolas, Bounova, Gergana, Bernasconi, David, Praz, Viviane, Lammers, Fabienne, Canella, Donatella, Willis, Ian M., Herr, Winship, Hernandez, Nouria, Delorenzi, Mauro, Deplancke, Bart, Desvergne, Béatrice, Guex, Nicolas, Naef, Felix, Rougemont, Jacques, Schibler, Ueli, Andersin, Teemu, Cousin, Pascal, Gilardi, Federica, Gos, Pascal, Raghav, Sunil, Villeneuve, Dominic, Fabbretti, Roberto, Vlegel, Volker, Xenarios, Ioannis, Migliavacca, Eugenia, David, Fabrice, Jarosz, Yohan, Kuznetsov, Dmitry, Liechti, Robin, Martin, Olivier, Delafontaine, Julien, Cajan, Julia, Gustafson, Kyle, Krier, Irina, Leleu, Marion, Molina, Nacho, Naldi, Aurélien, Rib, Leonor, Symul, Laura, CycliX Consortium, Hernandez, N., Delorenzi, M., Deplancke, B., Desvergne, B., Guex, N., Herr, W., Naef, F., Rougemont, J., Schibler, U., Andersin, T., Cousin, P., Gilardi, F., Gos, P., Lammers, F., Raghav, S., Villeneuve, D., Fabbretti, R., Vlegel, V., Xenarios, I., Migliavacca, E., Praz, V., David, F., Jarosz, Y., Kuznetsov, D., Liechti, R., Martin, O., Delafontaine, J., Cajan, J., Gustafson, K., Krier, I., Leleu, M., Molina, N., Naldi, A., Rib, L., Symul, L., Bounova, G., University of Zurich, and Hernandez, N
- Subjects
Quality Control ,Normalization (statistics) ,2716 Genetics (clinical) ,Chromatin Immunoprecipitation ,Occupancy ,SX20 Research, Technology and Development Projects ,Immunoprecipitation ,Sample (material) ,Method ,Biology ,Mice ,03 medical and health sciences ,0302 clinical medicine ,SX00 SystemsX.ch ,1311 Genetics ,Genetics ,Animals ,Humans ,Genetics(clinical) ,SX04 CycliX ,Genetics (clinical) ,030304 developmental biology ,Quantile normalization ,0303 health sciences ,Computational Biology ,High-Throughput Nucleotide Sequencing ,Reproducibility of Results ,Reference Standards ,Chromatin ,570 Life sciences ,biology ,Spike (software development) ,Biological system ,Chromatin immunoprecipitation ,030217 neurology & neurosurgery - Abstract
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This “spike” chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.
- Published
- 2014
6. Rhythmic Changes in Gene Activation Power the Circadian Clock
- Author
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Gwendal Le Martelot, Donatella Canella, Laura Symul, Eugenia Migliavacca, Federica Gilardi, Robin Liechti, Olivier Martin, Keith Harshman, Mauro Delorenzi, Béatrice Desvergne, Winship Herr, Bart Deplancke, Ueli Schibler, Jacques Rougemont, Nicolas Guex, Nouria Hernandez, Felix Naef, CycliX Consortium, University of Zurich, Hernandez, Nouria, CycliX Consortium, Hernandez, N., Delorenzi, M., Deplancke, B., Desvergne, B., Guex, N., Herr, W., Naef, F., Rougemont, J., Schibler, U., Andersin, T., Cousin, P., Gilardi, F., Gos, P., Le Martelot, G., Lammers, F., Canella, D., Raghav, S., Fabbretti, R., Fortier, A., Long, L., Vlegel, V., Xenarios, I., Migliavacca, E., Praz, V., David, F., Jarosz, Y., Kuznetsov, D., Liechti, R., Martin, O., Delafontaine, J., Sinclair, L., Cajan, J., Krier, I., Leleu, M., Molina, N., Naldi, A., Rey, G., Symul, L., and Bernasconi, D.
- Subjects
Male ,Time Factors ,Transcription, Genetic ,Circadian clock ,RNA polymerase II ,Biochemistry ,Epigenesis, Genetic ,Histones ,Mice ,0302 clinical medicine ,SX00 SystemsX.ch ,Transcription (biology) ,2400 General Immunology and Microbiology ,Gene expression ,Molecular Cell Biology ,Transcriptional regulation ,RNA Processing, Post-Transcriptional ,Biology (General) ,Promoter Regions, Genetic ,Regulation of gene expression ,Genetics ,0303 health sciences ,Reverse Transcriptase Polymerase Chain Reaction ,General Neuroscience ,Systems Biology ,2800 General Neuroscience ,Genomics ,Chromatin ,Circadian Rhythm ,Liver ,DNA methylation ,Synopsis ,RNA Polymerase II ,Transcription Initiation Site ,General Agricultural and Biological Sciences ,Half-Life ,Research Article ,Chromatin Immunoprecipitation ,SX20 Research, Technology and Development Projects ,QH301-705.5 ,E-box ,1100 General Agricultural and Biological Sciences ,Biology ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Rhythm ,1300 General Biochemistry, Genetics and Molecular Biology ,Animals ,Circadian rhythm ,RNA, Messenger ,SX04 CycliX ,Gene ,Post-transcriptional regulation ,030304 developmental biology ,Chromatin Assembly and Disassembly ,DNA Methylation ,Histones/genetics ,Histones/metabolism ,Kinetics ,Liver/cytology ,Liver/metabolism ,Mice, Inbred C57BL ,Models, Genetic ,RNA Polymerase II/genetics ,RNA Polymerase II/metabolism ,RNA, Messenger/analysis ,RNA, Messenger/metabolism ,Transcriptome ,General Immunology and Microbiology ,Computational Biology ,Promoter ,biology.protein ,570 Life sciences ,biology ,Chromatin immunoprecipitation ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Genome-wide rhythms in RNA polymerase II loading and dynamic chromatin remodeling underlie periodic gene expression during diurnal cycles in the mouse liver., Interactions of cell-autonomous circadian oscillators with diurnal cycles govern the temporal compartmentalization of cell physiology in mammals. To understand the transcriptional and epigenetic basis of diurnal rhythms in mouse liver genome-wide, we generated temporal DNA occupancy profiles by RNA polymerase II (Pol II) as well as profiles of the histone modifications H3K4me3 and H3K36me3. We used these data to quantify the relationships of phases and amplitudes between different marks. We found that rhythmic Pol II recruitment at promoters rather than rhythmic transition from paused to productive elongation underlies diurnal gene transcription, a conclusion further supported by modeling. Moreover, Pol II occupancy preceded mRNA accumulation by 3 hours, consistent with mRNA half-lives. Both methylation marks showed that the epigenetic landscape is highly dynamic and globally remodeled during the 24-hour cycle. While promoters of transcribed genes had tri-methylated H3K4 even at their trough activity times, tri-methylation levels reached their peak, on average, 1 hour after Pol II. Meanwhile, rhythms in tri-methylation of H3K36 lagged transcription by 3 hours. Finally, modeling profiles of Pol II occupancy and mRNA accumulation identified three classes of genes: one showing rhythmicity both in transcriptional and mRNA accumulation, a second class with rhythmic transcription but flat mRNA levels, and a third with constant transcription but rhythmic mRNAs. The latter class emphasizes widespread temporally gated posttranscriptional regulation in the mouse liver., Author Summary In mammalian organs such as the liver, many metabolic and physiological processes occur preferentially at specific times during the 24-hour daily cycle. The timing of these rhythmic functions depends on a complex interplay between the endogenous circadian clock and environmental timing cues relayed through the master circadian clock in the suprachiasmatic nucleus, or via feeding rhythms. These rhythms can be implemented on several regulatory levels, and here we aimed at a better understanding of the transcriptional and epigenetic changes that regulate diurnal rhythms. We performed genome-wide analysis of the locations of RNA polymerase II (Pol II) and the epigenetic histone modifications H3K4me3 and H3K36me3 at specific times of day, relating these data to mRNA expression levels. Our analyses show that Pol II transcriptional rhythms are biphasic in mouse liver, having predominant peak activities in the morning and evening. Moreover, dynamic changes in histone marks lag transcription rhythms genome-wide, indicating that the epigenetic landscape can be remodeled during the 24-hour cycle. Finally, a quantitative analysis of temporal Pol II and mRNA accumulation profiles indicates that posttranscriptional regulation significantly contributes to the amplitude and phase of mRNA accumulation profiles. While many studies have analyzed how transcription and chromatin states are modified during irreversible cell differentiation processes, our work highlights how these states can evolve reversibly in a system exhibiting periodicity in time.
- Published
- 2012
7. Genome-Wide Analysis of SREBP1 Activity around the Clock Reveals Its Combined Dependency on Nutrient and Circadian Signals
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Felix Naef, Bart Deplancke, Laura Symul, Dmitry Kuznetsov, Aurélien Naldi, Winship Herr, Ioannis Xenarios, Nouria Hernandez, Federica Gilardi, Nicolas GUEX, Beatrice Desvergne, Guillaume Rey, CycliX Consortium, Hernandez, N., Delorenzi, M., Deplancke, B., Desvergne, B., Guex, N., Herr, W., Naef, F., Rougemont, J., Schibler, U., Andersin, T., Cousin, P., Gilardi, F., Gos, P., Martelot, G., Lammers, F., Canella, D., Raghav, S., Fabbretti, R., Fortier, A., Long, L., Vlegel, V., Xenarios, I., Migliavacca, E., Praz, V., David, F., Jarosz, Y., Kuznetsov, D., Liechti, R., Martin, O., Delafontaine, J., Sinclair, L., Cajan, J., Krier, I., Leleu, M., Molina, N., Naldi, A., Rey, G., Symul, L., Bernasconi, D., Baruchet, M., University of Zurich, and Guex, Nicolas
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2716 Genetics (clinical) ,Cancer Research ,lcsh:QH426-470 ,SX20 Research, Technology and Development Projects ,Circadian clock ,CLOCK Proteins ,Biology ,Mice ,SX00 SystemsX.ch ,1311 Genetics ,Circadian Clocks ,1312 Molecular Biology ,Genetics ,Transcriptional regulation ,Animals ,Homeostasis ,1306 Cancer Research ,Circadian rhythm ,SX04 CycliX ,Molecular Biology ,Transcription factor ,Genetics (clinical) ,Ecology, Evolution, Behavior and Systematics ,Regulation of gene expression ,Binding Sites ,Genome ,Lipid Metabolism ,Bacterial circadian rhythms ,Circadian Rhythm ,Sterol regulatory element-binding protein ,Cell biology ,lcsh:Genetics ,1105 Ecology, Evolution, Behavior and Systematics ,Gene Expression Regulation ,Hepatocyte Nuclear Factor 4 ,570 Life sciences ,biology ,Sterol Regulatory Element Binding Protein 1 ,Protein Binding ,Research Article - Abstract
In mammals, the circadian clock allows them to anticipate and adapt physiology around the 24 hours. Conversely, metabolism and food consumption regulate the internal clock, pointing the existence of an intricate relationship between nutrient state and circadian homeostasis that is far from being understood. The Sterol Regulatory Element Binding Protein 1 (SREBP1) is a key regulator of lipid homeostasis. Hepatic SREBP1 function is influenced by the nutrient-response cycle, but also by the circadian machinery. To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulates SREBP1 activity, we evaluated the genome-wide binding of SREBP1 to its targets throughout the day in C57BL/6 mice. The recruitment of SREBP1 to the DNA showed a highly circadian behaviour, with a maximum during the fed status. However, the temporal expression of SREBP1 targets was not always synchronized with its binding pattern. In particular, different expression phases were observed for SREBP1 target genes depending on their function, suggesting the involvement of other transcription factors in their regulation. Binding sites for Hepatocyte Nuclear Factor 4 (HNF4) were specifically enriched in the close proximity of SREBP1 peaks of genes, whose expression was shifted by about 8 hours with respect to SREBP1 binding. Thus, the cross-talk between hepatic HNF4 and SREBP1 may underlie the expression timing of this subgroup of SREBP1 targets. Interestingly, the proper temporal expression profile of these genes was dramatically changed in Bmal1 −/− mice upon time-restricted feeding, for which a rhythmic, but slightly delayed, binding of SREBP1 was maintained. Collectively, our results show that besides the nutrient-driven regulation of SREBP1 nuclear translocation, a second layer of modulation of SREBP1 transcriptional activity, strongly dependent from the circadian clock, exists. This system allows us to fine tune the expression timing of SREBP1 target genes, thus helping to temporally separate the different physiological processes in which these genes are involved., Author Summary Circadian rhythmicity is part of our innate behavior and controls many physiological processes, such as sleeping and waking, activity, neurotransmitter production and a number of metabolic pathways. In mammals, the central circadian pacemaker in the hypothalamus is entrained on a daily basis by environmental cues (i.e. light), thus setting the period length and synchronizing the rhythms of all cells in the body. In the last decades, numerous investigations have highlighted the importance of the internal timekeeping mechanism for maintenance of organism health and longevity. Indeed, the reciprocal regulation of circadian clock and metabolism is now commonly accepted, although still poorly understood at the molecular level. Our global analysis of DNA binding along the day of Sterol Regulatory Element Binding Protein 1 (SREBP1), a key regulator of lipid biosynthesis, represents the first tool to comprehensively explore how its activity is connected to circadian-driven regulatory events. We show that the regulation of SREBP1 action by nutrients relies mainly on the control of its subcellular localization, while the circadian clock influences the promoter specific activity of SREBP1 within the nucleus. Furthermore, we identify the Hepatocyte Nuclear Factor 4 (HNF4) as a putative player in the cross-talk between molecular clock and metabolic regulation.
- Published
- 2014
8. Publisher Correction: Abrupt perturbation and delayed recovery of the vaginal ecosystem following childbirth.
- Author
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Costello EK, DiGiulio DB, Robaczewska A, Symul L, Wong RJ, Shaw GM, Stevenson DK, Holmes SP, Kwon DS, and Relman DA
- Published
- 2024
- Full Text
- View/download PDF
9. Food & You: A digital cohort on personalized nutrition.
- Author
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Héritier H, Allémann C, Balakiriev O, Boulanger V, Carroll SF, Froidevaux N, Hugon G, Jaquet Y, Kebaili D, Riccardi S, Rousseau-Leupin G, Salathé RM, Salzmann T, Singh R, Symul L, Ugurlu-Baud E, de Verteuil P, and Salathé M
- Abstract
Nutrition is a key contributor to health. Recently, several studies have identified associations between factors such as microbiota composition and health-related responses to dietary intake, raising the potential of personalized nutritional recommendations. To further our understanding of personalized nutrition, detailed individual data must be collected from participants in their day-to-day lives. However, this is challenging in conventional studies that require clinical measurements and site visits. So-called digital or remote cohorts allow in situ data collection on a daily basis through mobile applications, online services, and wearable sensors, but they raise questions about study retention and data quality. "Food & You" is a personalized nutrition study implemented as a digital cohort in which participants track food intake, physical activity, gut microbiota, glycemia, and other data for two to four weeks. Here, we describe the study protocol, report on study completion rates, and describe the collected data, focusing on assessing their quality and reliability. Overall, the study collected data from over 1000 participants, including high-resolution data of nutritional intake of more than 46 million kcal collected from 315,126 dishes over 23,335 participant days, 1,470,030 blood glucose measurements, 49,110 survey responses, and 1,024 stool samples for gut microbiota analysis. Retention was high, with over 60% of the enrolled participants completing the study. Various data quality assessment efforts suggest the captured high-resolution nutritional data accurately reflect individual diet patterns, paving the way for digital cohorts as a typical study design for personalized nutrition., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Héritier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
10. Sub-communities of the vaginal microbiota in pregnant and non-pregnant women.
- Author
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Symul L, Jeganathan P, Costello EK, France M, Bloom SM, Kwon DS, Ravel J, Relman DA, and Holmes S
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- Pregnancy, Female, Infant, Newborn, Humans, Vagina, Lactobacillus metabolism, Menstrual Cycle, RNA, Ribosomal, 16S, Premature Birth, Microbiota
- Abstract
Diverse and non- Lactobacillus -dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models. Using longitudinal data from cohorts of pregnant and non-pregnant study participants, we show that topic models more accurately describe sample composition, longitudinal changes, and better predict the loss of Lactobacillus dominance. We identify several non- Lactobacillus -dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities, as well as the concentrations of half of the cytokines and 18% of metabolites. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.
- Published
- 2023
- Full Text
- View/download PDF
11. Multiscale analysis of count data through topic alignment.
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Fukuyama J, Sankaran K, and Symul L
- Abstract
Topic modeling is a popular method used to describe biological count data. With topic models, the user must specify the number of topics $K$. Since there is no definitive way to choose $K$ and since a true value might not exist, we develop a method, which we call topic alignment, to study the relationships across models with different $K$. In addition, we present three diagnostics based on the alignment. These techniques can show how many topics are consistently present across different models, if a topic is only transiently present, or if a topic splits into more topics when $K$ increases. This strategy gives more insight into the process of generating the data than choosing a single value of $K$ would. We design a visual representation of these cross-model relationships, show the effectiveness of these tools for interpreting the topics on simulated and real data, and release an accompanying R package, alto., (© The Author 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2023
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12. Abrupt perturbation and delayed recovery of the vaginal ecosystem following childbirth.
- Author
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Costello EK, DiGiulio DB, Robaczewska A, Symul L, Wong RJ, Shaw GM, Stevenson DK, Holmes SP, Kwon DS, and Relman DA
- Subjects
- Female, Pregnancy, Humans, Cytokines, Inflammation, Lactobacillus, Live Birth, Parturition, Microbiota
- Abstract
The vaginal ecosystem is closely tied to human health and reproductive outcomes, yet its dynamics in the wake of childbirth remain poorly characterized. Here, we profile the vaginal microbiota and cytokine milieu of participants sampled longitudinally throughout pregnancy and for at least one year postpartum. We show that delivery, regardless of mode, is associated with a vaginal pro-inflammatory cytokine response and the loss of Lactobacillus dominance. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At 9.5-months postpartum-the latest timepoint at which cytokines were assessed-elevated inflammation coincided with vaginal bacterial communities that had remained perturbed (highly diverse) from the time of delivery. Time-to-event analysis indicated a one-year postpartum probability of transitioning to Lactobacillus dominance of 49.4%. As diversity and inflammation declined during the postpartum period, dominance by L. crispatus, the quintessential health-associated commensal, failed to return: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Revisiting our pre-delivery data, we found that a prior live birth was associated with a lower odds of L. crispatus dominance in pregnant participants-an outcome modestly tempered by a longer ( > 18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
- Published
- 2023
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- View/download PDF
13. Labeling Self-Tracked Menstrual Health Records With Hidden Semi-Markov Models.
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Symul L and Holmes S
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- Female, Fertility, Humans, Menstrual Cycle, Pregnancy, Self Report, Time Factors, Mobile Applications
- Abstract
Globally, millions of women track their menstrual cycle and fertility via smartphone-based health apps, generating multivariate time series with frequent missing data. To leverage this type of data for studies of fertility or studies of the effect of the menstrual cycle on symptoms and diseases, it is critical to have methods for identifying reproductive events, such as ovulation, pregnancy losses or births. Here, we present a hierarchical approach relying on hidden semi-Markov models that adapts to changes in tracking behavior, explicitly captures variable- and state- dependent missingness, allows for variables of different type, and quantifies uncertainty. The accuracy on simulated data reaches 98% with no missing data and 90% with realistic missingness. On our partially labeled real-world time series, the accuracy reaches 93%. Our method also accurately predicts cycle length by learning user characteristics. Its implementation is publicly available (HiddenSemiMarkov R package) and transferable to any health time series, including self-reported symptoms and occasional tests.
- Published
- 2022
- Full Text
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14. Assessment of menstrual health status and evolution through mobile apps for fertility awareness.
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Symul L, Wac K, Hillard P, and Salathé M
- Abstract
For most women of reproductive age, assessing menstrual health and fertility typically involves regular visits to a gynecologist or another clinician. While these evaluations provide critical information on an individual's reproductive health status, they typically rely on memory-based self-reports, and the results are rarely, if ever, assessed at the population level. In recent years, mobile apps for menstrual tracking have become very popular, allowing us to evaluate the reliability and tracking frequency of millions of self-observations, thereby providing an unparalleled view, both in detail and scale, on menstrual health and its evolution for large populations. In particular, the primary aim of this study was to describe the tracking behavior of the app users and their overall observation patterns in an effort to understand if they were consistent with previous small-scale medical studies. The secondary aim was to investigate whether their precision allowed the detection and estimation of ovulation timing, which is critical for reproductive and menstrual health. Retrospective self-observation data were acquired from two mobile apps dedicated to the application of the sympto-thermal fertility awareness method, resulting in a dataset of more than 30 million days of observations from over 2.7 million cycles for two hundred thousand users. The analysis of the data showed that up to 40% of the cycles in which users were seeking pregnancy had recordings every single day. With a modeling approach using Hidden Markov Models to describe the collected data and estimate ovulation timing, it was found that follicular phases average duration and range were larger than previously reported, with only 24% of ovulations occurring at cycle days 14 to 15, while the luteal phase duration and range were in line with previous reports, although short luteal phases (10 days or less) were more frequently observed (in up to 20% of cycles). The digital epidemiology approach presented here can help to lead to a better understanding of menstrual health and its connection to women's health overall, which has historically been severely understudied., Competing Interests: Competing interestsP.H. discloses that she is a consultant and medical advisor to Clue by Biowink. The remaining authors declare no competing interests.
- Published
- 2019
- Full Text
- View/download PDF
15. Predicting pregnancy using large-scale data from a women's health tracking mobile application.
- Author
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Liu B, Shi S, Wu Y, Thomas D, Symul L, Pierson E, and Leskovec J
- Abstract
Predicting pregnancy has been a fundamental problem in women's health for more than 50 years. Previous datasets have been collected via carefully curated medical studies, but the recent growth of women's health tracking mobile apps offers potential for reaching a much broader population. However, the feasibility of predicting pregnancy from mobile health tracking data is unclear. Here we develop four models - a logistic regression model, and 3 LSTM models - to predict a woman's probability of becoming pregnant using data from a women's health tracking app, Clue by BioWink GmbH. Evaluating our models on a dataset of 79 million logs from 65,276 women with ground truth pregnancy test data, we show that our predicted pregnancy probabilities meaningfully stratify women: women in the top 10% of predicted probabilities have a 89% chance of becoming pregnant over 6 menstrual cycles, as compared to a 27% chance for women in the bottom 10%. We develop a technique for extracting interpretable time trends from our deep learning models, and show these trends are consistent with previous fertility research. Our findings illustrate the potential that women's health tracking data offers for predicting pregnancy on a broader population; we conclude by discussing the steps needed to fulfill this potential.
- Published
- 2019
- Full Text
- View/download PDF
16. FoodRepo: An Open Food Repository of Barcoded Food Products.
- Author
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Lazzari G, Jaquet Y, Kebaili DJ, Symul L, and Salathé M
- Published
- 2018
- Full Text
- View/download PDF
17. Circadian clock-dependent and -independent posttranscriptional regulation underlies temporal mRNA accumulation in mouse liver.
- Author
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Wang J, Symul L, Yeung J, Gobet C, Sobel J, Lück S, Westermark PO, Molina N, and Naef F
- Subjects
- Animals, Male, Mice metabolism, Mice, Inbred C57BL, Promoter Regions, Genetic, RNA, Messenger metabolism, Transcription, Genetic, Circadian Clocks, Gene Expression Regulation, Liver metabolism, Mice genetics, RNA, Messenger genetics
- Abstract
The mammalian circadian clock coordinates physiology with environmental cycles through the regulation of daily oscillations of gene expression. Thousands of transcripts exhibit rhythmic accumulations across mouse tissues, as determined by the balance of their synthesis and degradation. While diurnally rhythmic transcription regulation is well studied and often thought to be the main factor generating rhythmic mRNA accumulation, the extent of rhythmic posttranscriptional regulation is debated, and the kinetic parameters (e.g., half-lives), as well as the underlying regulators (e.g., mRNA-binding proteins) are relatively unexplored. Here, we developed a quantitative model for cyclic accumulations of pre-mRNA and mRNA from total RNA-seq data, and applied it to mouse liver. This allowed us to identify that about 20% of mRNA rhythms were driven by rhythmic mRNA degradation, and another 15% of mRNAs regulated by both rhythmic transcription and mRNA degradation. The method could also estimate mRNA half-lives and processing times in intact mouse liver. We then showed that, depending on mRNA half-life, rhythmic mRNA degradation can either amplify or tune phases of mRNA rhythms. By comparing mRNA rhythms in wild-type and Bmal1
-/- animals, we found that the rhythmic degradation of many transcripts did not depend on a functional BMAL1. Interestingly clock-dependent and -independent degradation rhythms peaked at distinct times of day. We further predicted mRNA-binding proteins (mRBPs) that were implicated in the posttranscriptional regulation of mRNAs, either through stabilizing or destabilizing activities. Together, our results demonstrate how posttranscriptional regulation temporally shapes rhythmic mRNA accumulation in mouse liver., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)- Published
- 2018
- Full Text
- View/download PDF
18. Non-circadian expression masking clock-driven weak transcription rhythms in U2OS cells.
- Author
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Hoffmann J, Symul L, Shostak A, Fischer T, Naef F, and Brunner M
- Subjects
- ARNTL Transcription Factors genetics, Binding Sites, CLOCK Proteins genetics, Cell Line, Tumor, Circadian Clocks, Cryptochromes genetics, Gene Expression Regulation, High-Throughput Nucleotide Sequencing, Humans, ARNTL Transcription Factors chemistry, CLOCK Proteins chemistry, Cryptochromes chemistry, Promoter Regions, Genetic
- Abstract
U2OS cells harbor a circadian clock but express only a few rhythmic genes in constant conditions. We identified 3040 binding sites of the circadian regulators BMAL1, CLOCK and CRY1 in the U2OS genome. Most binding sites even in promoters do not correlate with detectable rhythmic transcript levels. Luciferase fusions reveal that the circadian clock supports robust but low amplitude transcription rhythms of representative promoters. However, rhythmic transcription of these potentially clock-controlled genes is masked by non-circadian transcription that overwrites the weaker contribution of the clock in constant conditions. Our data suggest that U2OS cells harbor an intrinsically rather weak circadian oscillator. The oscillator has the potential to regulate a large number of genes. The contribution of circadian versus non-circadian transcription is dependent on the metabolic state of the cell and may determine the apparent complexity of the circadian transcriptome.
- Published
- 2014
- Full Text
- View/download PDF
19. The circadian clock coordinates ribosome biogenesis.
- Author
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Jouffe C, Cretenet G, Symul L, Martin E, Atger F, Naef F, and Gachon F
- Subjects
- ARNTL Transcription Factors genetics, Animals, Circadian Clocks physiology, Circadian Rhythm physiology, Cryptochromes genetics, Enzyme Activation genetics, Extracellular Signal-Regulated MAP Kinases metabolism, Gene Expression Regulation, Mechanistic Target of Rapamycin Complex 1, Mice, Mice, Inbred C57BL, Mice, Knockout, Multiprotein Complexes metabolism, Pol1 Transcription Initiation Complex Proteins biosynthesis, Pol1 Transcription Initiation Complex Proteins genetics, Protein Biosynthesis, Proto-Oncogene Proteins c-akt metabolism, RNA, Ribosomal biosynthesis, Signal Transduction, TOR Serine-Threonine Kinases metabolism, Circadian Clocks genetics, Circadian Rhythm genetics, Eukaryotic Initiation Factors biosynthesis, RNA, Messenger biosynthesis, Ribosomes metabolism
- Abstract
Biological rhythms play a fundamental role in the physiology and behavior of most living organisms. Rhythmic circadian expression of clock-controlled genes is orchestrated by a molecular clock that relies on interconnected negative feedback loops of transcription regulators. Here we show that the circadian clock exerts its function also through the regulation of mRNA translation. Namely, the circadian clock influences the temporal translation of a subset of mRNAs involved in ribosome biogenesis by controlling the transcription of translation initiation factors as well as the clock-dependent rhythmic activation of signaling pathways involved in their regulation. Moreover, the circadian oscillator directly regulates the transcription of ribosomal protein mRNAs and ribosomal RNAs. Thus the circadian clock exerts a major role in coordinating transcription and translation steps underlying ribosome biogenesis., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2013
- Full Text
- View/download PDF
20. Genome-wide RNA polymerase II profiles and RNA accumulation reveal kinetics of transcription and associated epigenetic changes during diurnal cycles.
- Author
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Le Martelot G, Canella D, Symul L, Migliavacca E, Gilardi F, Liechti R, Martin O, Harshman K, Delorenzi M, Desvergne B, Herr W, Deplancke B, Schibler U, Rougemont J, Guex N, Hernandez N, and Naef F
- Subjects
- Animals, Chromatin Assembly and Disassembly, Chromatin Immunoprecipitation, DNA Methylation, Half-Life, Histones genetics, Histones metabolism, Kinetics, Liver cytology, Liver metabolism, Male, Mice, Mice, Inbred C57BL, Models, Genetic, Promoter Regions, Genetic, RNA Polymerase II genetics, RNA Processing, Post-Transcriptional, RNA, Messenger analysis, Reverse Transcriptase Polymerase Chain Reaction, Time Factors, Transcription Initiation Site, Transcriptome, Circadian Rhythm, Epigenesis, Genetic, RNA Polymerase II metabolism, RNA, Messenger metabolism, Transcription, Genetic
- Abstract
Interactions of cell-autonomous circadian oscillators with diurnal cycles govern the temporal compartmentalization of cell physiology in mammals. To understand the transcriptional and epigenetic basis of diurnal rhythms in mouse liver genome-wide, we generated temporal DNA occupancy profiles by RNA polymerase II (Pol II) as well as profiles of the histone modifications H3K4me3 and H3K36me3. We used these data to quantify the relationships of phases and amplitudes between different marks. We found that rhythmic Pol II recruitment at promoters rather than rhythmic transition from paused to productive elongation underlies diurnal gene transcription, a conclusion further supported by modeling. Moreover, Pol II occupancy preceded mRNA accumulation by 3 hours, consistent with mRNA half-lives. Both methylation marks showed that the epigenetic landscape is highly dynamic and globally remodeled during the 24-hour cycle. While promoters of transcribed genes had tri-methylated H3K4 even at their trough activity times, tri-methylation levels reached their peak, on average, 1 hour after Pol II. Meanwhile, rhythms in tri-methylation of H3K36 lagged transcription by 3 hours. Finally, modeling profiles of Pol II occupancy and mRNA accumulation identified three classes of genes: one showing rhythmicity both in transcriptional and mRNA accumulation, a second class with rhythmic transcription but flat mRNA levels, and a third with constant transcription but rhythmic mRNAs. The latter class emphasizes widespread temporally gated posttranscriptional regulation in the mouse liver., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2012
- Full Text
- View/download PDF
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