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Predicting outcomes of steady-state ¹³C isotope tracing experiments using Monte Carlo sampling

BMC systems biology 2012年第1期6卷 9-9页

作者： Schellenberger, Jan Zielinski, Daniel C. Choi, Wing Madireddi, Sunthosh Portnoy, Vasiliy Scott, David A. Reed, Jennifer L. Osterman, Andrei L. Palsson, Bernhard T. Bioinformatics and Systems Biology Program University of California La Jolla CA 92093-0419 9500 Gilman Drive - San Diego United States Department of Bioengineering University of California La Jolla CA 92093-0412 9500 Gilman Drive - San Diego United States Bioinformatics and Systems Biology Program Sanford-Burnham Institute La Jolla CA 92037 10901 North Torrey Pines Road United States Department of Chemical and Biological Engineering University of Wisconsin Madison WI 53706-1607 1415 Engineering Drive Madison United States

Background: Carbon-13 ( 13C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experimen... 详细信息

Background: Carbon-13 ( ¹³C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experiments. We present a novel Monte Carlo algorithm for finding the optimal substrate input label for a particular experimental objective (flux or flux ratio). Unlike previous work, this method does not require assumption of the flux distribution ***: Using a large E. coli isotopomer model, different commercially available substrate labeling patterns were tested computationally for their ability to determine reaction fluxes. The choice of optimal labeled substrate was found to be dependent upon the desired experimental objective. Many commercially available labels are predicted to be outperformed by complex labeling patterns. Based on Monte Carlo Sampling, the dimensionality of experimental data was found to be considerably less than anticipated, suggesting that effectiveness of ¹³C experiments for determining reaction fluxes across a large-scale metabolic network is less than previously ***: While ¹³C analysis is a useful tool in systems biology, high redundancy in measurements limits the information that can be obtained from each experiment. It is however possible to compute potential limitations before an experiment is run and predict whether, and to what degree, the rate of each reaction can be resolved. © 2012 Schellenberger et al.;licensee BioMed Central Ltd.

关键词： METABOLIC flux analysis CARBON isotopes EXPERIMENTS PREDICTION models MONTE Carlo method BIOCHEMISTRY

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FAR-RED INSENSITIVE 219 and phytochrome B corepress shade avoidance via modulating nuclear speckle formation

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Plant physiology 2023年第2期192卷 1449-1465页

作者： Kai-Chun Peng Wei Siao Hsu-Liang Hsieh Institute of Plant Biology College of Life Science National Taiwan University Taipei 106 Taiwan. Department of Plant Biotechnology and Bioinformatics Ghent University 9052 Ghent Belgium. Center for Plant Systems Biology VIB 9052 Ghent Belgium. Department of Life Science College of Life Science National Taiwan University Taipei 106 Taiwan. Master Program in Global Agriculture Technology and Genomic Science National Taiwan University Taipei 106 Taiwan.

Plants can sense the shade from neighboring plants by detecting a reduction of the red:far-red light (R:FR) ratio. Phytochrome B (phyB) is the primary photoreceptor that perceives shade light and regulates jasmonic acid (JA) signaling. However, the molecular mechanisms underlying phyB and JA signaling integration in shade responses remain largely unknown. Here, we show the interaction of phyB and FAR-RED INSENSITIVE 219 (FIN219)/JASMONATE RESISTANT1 (JAR1) in a functional demand manner in Arabidopsis (Arabidopsis thaliana) seedling development. Genetic evidence and interaction studies indicated that phyB and FIN219 synergistically and negatively regulate shade-induced hypocotyl elongation. Moreover, phyB interacted with various isoforms of FIN219 under high and low R:FR light. Methyl jasmonate (MeJA) treatment, FIN219 mutation, and PHYBOE digalactosyldiacylglycerol synthase1-1 (dgd1-1) plants, which show increased levels of JA, altered the patterns of phyB-associated nuclear speckles under the same conditions. Surprisingly, PHYBOE dgd1-1 showed a shorter hypocotyl phenotype than its parental mutants under shade conditions. Microarray assays using PHYBOE and PHYBOE fin219-2 indicated that PHYB overexpression substantially affects defense response-related genes under shade light and coregulates expression of auxin-responsive genes with FIN219. Thus, our findings reveal that phyB substantially crosstalks with JA signaling through FIN219 to modulate seedling development under shade light.

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Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis (vol 56, pg 627, 2024)

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NATURE GENETICS 2024年第6期56卷 1319-1319页

作者： Mitra, Sneha Malik, Rohan Wong, Wilfred Rahman, Afsana Hartemink, Alexander J. Pritykin, Yuri Dey, Kushal K. Leslie, Christina S. Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York City NY USA Rye Country Day School Rye NY USA Tri-Institutional Training Program in Computational Biology and Medicine New York City NY USA Hunter College City University of New York New York City NY USA Department of Computer Science Duke University Durham NC USA Program in Computational Biology and Bioinformatics Duke University Durham NC USA Center for Genomic and Computational Biology Duke University Durham NC USA Department of Computer Science Princeton University Princeton NJ USA Lewis-Sigler Institute for Integrative Genomics Princeton University Princeton NJ USA

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC–seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene–peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

关键词： Epigenetics Population genetics Software

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia Computer Science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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A retinoic acid:YAP1 signaling axis controls atrial lineage commitment

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Cell Reports 2025年第5期44卷 115687页

作者： Abraham, Elizabeth Kostina, Aleksandra Volmert, Brett Roule, Thomas Huang, Ling Yu, Jingting Williams, April E. Megill, Emily Douglas, Aidan Pericak, Olivia M. Morris, Alex Stronati, Eleonora Larrinaga-Zamanillo, Arantza Fueyo, Raquel Zubillaga, Mikel Andrake, Mark D. Akizu, Naiara Aguirre, Aitor Estaras, Conchi Department of Cardiovascular Sciences Aging + Cardiovascular Discovery Center Lewis Katz School of Medicine Temple University Philadelphia 19140 PA United States Institute for Quantitative Health Science and Engineering Division of Developmental and Stem Cell Biology Michigan State University East Lansing 48824 MI United States Department of Biomedical Engineering College of Engineering Michigan State University East Lansing 48824 MI United States Raymond G. Perelman Center for Cellular and Molecular Therapeutics The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Integrative Genomics and Bioinformatics Core Salk Institute for Biological Studies La Jolla 92037 CA United States Cancer Epigenetics Institute Fox Chase Cancer Center Philadelphia 19111 PA United States Department of Child and Adolescence Psychiatry The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Department of Chemical and Systems Biology Stanford University School of Medicine Stanford 94305 CA United States Molecular Modeling Facility Program in Cancer Signaling and Microenvironment Fox Chase Cancer Center Philadelphia 19111 PA United States

In cardiac progenitor cells (CPCs), retinoic acid (RA) signaling induces atrial lineage gene expression and acquisition of an atrial cell fate. To achieve this, RA coordinates a complex regulatory network of downstream effectors that is not fully identified. To address this gap, we applied a functional genomics approach (i.e., scRNA-seq and snATAC-seq) to untreated and RA-treated human embryonic stem cell (hESC)-derived CPCs. Unbiased analysis revealed that the Hippo effectors YAP1 and TEAD4 are integrated with the atrial transcription factor enhancer network and that YAP1 activates RA enhancers in CPCs. Furthermore, Yap1 deletion in mouse embryos compromises the expression of RA-induced genes, such as Nr2f2, in the CPCs of the second heart field. Accordingly, in hESC-derived patterned heart organoids, YAP1 regulates the formation of an atrial chamber but is dispensable for the formation of a ventricle. Overall, our findings revealed that YAP1 cooperates with RA signaling to induce atrial lineages during cardiogenesis. © 2025 The Author(s)

关键词： atrial differentiation cardiac enhancers cardiac progenitors chamber development CP: Developmental biology heart organoids NR2F2 retinoic acid signaling SHF TEAD4 YAP1

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Quantifying interactions between real oscillators with information theory and phase models: Application to cardiorespiratory coupling

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Physical Review E 2013年第2期87卷 022709-022709页

作者： Yenan Zhu Yee-Hsee Hsieh Rishi R. Dhingra Thomas E. Dick Frank J. Jacono Roberto F. Galán Department of Neurosciences School of Medicine Case Western Reserve University Cleveland Ohio 44106 USA Systems Biology and Bioinformatics Program Case Western Reserve University Cleveland Ohio 44106 USA Department of Medicine School of Medicine Case Western Reserve University Cleveland Ohio 44106 USA Louis Stokes Cleveland VA Medical Center Cleveland Ohio 44106 USA University Hospitals Cleveland Ohio 44106 USA

Interactions between oscillators can be investigated with standard tools of time series analysis. However, these methods are insensitive to the directionality of the coupling, i.e., the asymmetry of the interactions. An elegant alternative was proposed by Rosenblum and collaborators [M. G. Rosenblum, L. Cimponeriu, A. Bezerianos, A. Patzak, and R. Mrowka, Phys. Rev. E 65, 041909 (2002); M. G. Rosenblum and A. S. Pikovsky, Phys. Rev. E 64, 045202 (2001)] which consists in fitting the empirical phases to a generic model of two weakly coupled phase oscillators. This allows one to obtain the interaction functions defining the coupling and its directionality. A limitation of this approach is that a solution always exists in the least-squares sense, even in the absence of coupling. To preclude spurious results, we propose a three-step protocol: (1) Determine if a statistical dependency exists in the data by evaluating the mutual information of the phases; (2) if so, compute the interaction functions of the oscillators; and (3) validate the empirical oscillator model by comparing the joint probability of the phases obtained from simulating the model with that of the empirical phases. We apply this protocol to a model of two coupled Stuart-Landau oscillators and show that it reliably detects genuine coupling. We also apply this protocol to investigate cardiorespiratory coupling in anesthetized rats. We observe reciprocal coupling between respiration and heartbeat and that the influence of respiration on the heartbeat is generally much stronger than vice versa. In addition, we find that the vagus nerve mediates coupling in both directions.

关键词： COUPLING reactions (Chemistry) CARDIOPULMONARY system -- Physiology RESEARCH INFORMATION theory TIME series analysis PHYSICS research

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Plant scent and plant-insect interactions—Review and outlook from a macroevolutionary perspective

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植物分类学报 2023年第3期61卷 465-486页

作者： Orlando Schwery Breanna N.Sipley Mariana P.Braga Yan Yang Roberto Rebollo Pengjuan Zu New Mexico Consortium 4200 W.Jemez RdSuite 301Los AlamosNM 87544USA Department of Biological Sciences University of Idaho875 Perimeter Dr.MS 3051MoscowID 83844USA Department of Biological Sciences Southeastern Louisiana University2400 N.Oak StHammondLA 70402USA Program for Bioinformatics and Computational Biology University of IdahoMoscowID 83844USA Department of Biology Washington University in St.LouisSt.LouisMO 63130USA Department of Ecology Swedish University of Agricultural SciencesUppsalaSweden Helsinki Life Science Institute University of HelsinkiHelsinkiFinland Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants Ministry of EducationCollege of ForestryHainan UniversityHaikou 570228P.R.China Department of Environmental Systems Science ETH ZurichSchmelzbergstrasse 9CH-8092 ZurichSwitzerland Department of Environmental Systems Science ETH ZurichSchmelzbergstrasse 9CH-8092 ZurichSwitzerland Swiss Federal Institute of Aquatic Science and Technology(Eawag) Seestrasse 79CH-6047 KastanienbaumSwitzerland

The astonishing diversity of plants and insects and their entangled interactions are cornerstones in terrestrial ***-occurring with species diversity is the diversity of plant secondary metabolites(PSMs).So far,their estimated number is more than 200 000 compounds,which are not directly involved in plant growth and development but play important roles in helping plants handle their environment including the mediation of plant-insect ***,we use plant volatile organic compounds(VOCs),a key olfactory communication channel that mediates plant-insect interactions,as a showcase of *** spite of the cumulative knowledge of the functional,ecological,and microevolutionary roles of VOCs,we still lack a macroevolutionary understanding of how they evolved with plant-insect interactions and contributed to species diversity throughout the long coevolutionary history of plants and *** first review the literature to summarize the current state-of-the-art research on this *** then present various relevant types of phylogenetic methods suitable to answer macroevolutionary questions on plant VOCs and suggest future directions for employing phylogenetic approaches in studying plant VOCs and plant-insect ***,we found that current studies in this field are still very limited in their macroevolutionary ***,with the fast-growing development of metabolome analysis techniques and phylogenetic methods,it is becoming increasingly feasible to integrate the advances of these two *** highlight promising approaches to generate new testable hypotheses and gain a mechanistic understanding of the macroevolutionary roles of chemical communication in plant-insect interactions.

关键词： coevolution

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eIF3 Associates with 80S Ribosomes to Promote Translation Elongation, Mitochondrial Homeostasis, and Muscle Health

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Journal of Cleaner Production 2020年第4期79卷 575-587.e7页

作者： Lin, Yingying Li, Fajin Huang, Linlu Polte, Christine Duan, Haoran Fang, Jianhuo Sun, Li Xing, Xudong Tian, Guiyou Cheng, Yabin Ignatova, Zoya Yang, Xuerui Wolf, Dieter A. School of Pharmaceutical Sciences Fujian Provincial Key Laboratory of Innovative Drug Target Research Xiamen University Xiamen Fujian361102 China MOE Key Laboratory of Bioinformatics Center for Synthetic & Systems Biology School of Life Sciences Tsinghua University Beijing100084 China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing100084 China Biochemistry and Molecular Biology University of Hamburg Hamburg20146 Germany State Key Laboratory of Cellular Stress Biology Xiamen University Xiamen Fujian361102 China

eIF3, a multi-subunit complex with numerous functions in canonical translation initiation, is known to interact with 40S and 60S ribosomal proteins and translation elongation factors, but a direct involvement in translation elongation has never been demonstrated. We found that eIF3 deficiency reduced early ribosomal elongation speed between codons 25 and 75 on a set of ∼2,700 mRNAs encoding proteins associated with mitochondrial and membrane functions, resulting in defective synthesis of their encoded proteins. To promote elongation, eIF3 interacts with 80S ribosomes translating the first ∼60 codons and serves to recruit protein quality-control factors, functions required for normal mitochondrial physiology. Accordingly, eIF3e+/− mice accumulate defective mitochondria in skeletal muscle and show a progressive decline in muscle strength. Hence, eIF3 interacts with 80S ribosomes to enhance, at the level of early elongation, the synthesis of proteins with membrane-associated functions, an activity that is critical for mitochondrial physiology and muscle health. © 2020 Elsevier Inc.

关键词： Elongation

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MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures

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BMC Genomics 2015年第7期16卷 S13-S13页

作者： Zhang, Yizhe He, Yupeng Zheng, Guangyong Wei, Chaochun Shanghai Jiao Tong University School of Life Sciences and Biotechnology 800 Dongchuan Road Shanghai 200240 China Shanghai Center for Bioinformation Technology 1278 Keyuan Road Pudong District Shanghai 201203 China University of California Bioinformatics and Systems Biology Program San Diego 9500 Gilman Drive La Jolla 92093 CA United States Shanghai Institutes for Biological Sciences Chinese Academy of Sciences CAS-MPG Partner Institute for Computational Biology 320 Yueyang Road Shanghai 200031 China Duke University Program in Computational Biology and Bioinformatics Durham 27708 NC United States

Background: Motifs are regulatory elements that will activate or inhibit the expression of related genes when proteins (such as transcription factors, TFs) bind to them. Therefore, motif finding is important to understand the mechanisms of gene regulation. De novo discovery of regulatory elements, like transcription factor binding sites (TFBSs), has long been a major challenge to gain insight on mechanisms of gene regulation. Recent advances in experimental profiling of genome-wide signals such as histone modifications and DNase I hypersensitivity sites allow scientists to develop better computational methods to enhance motif discovery. However, existing methods for motif finding suffer from high false positive rates and slow speed, and it's difficult to evaluate the performance of these methods systematically. Result: Here we present MOST+, a motif finder integrating genomic sequences and genome-wide signals such as intensity and shape features from histone modification marks and DNase I hypersensitivity sites, to improve the prediction accuracy. MOST+ can detect motifs from a large input sequence of about 100 Mbs within a few minutes. Systematic comparison method has been established and MOST+ has been compared with existing methods. Conclusion: MOST+ is a fast and accurate de novo method for motif finding by integrating genomic sequence and experimental signals as clues. © 2015 Zhang et al.;licensee BioMed Central Ltd.

关键词： ChIP-seq De novo Motif finding DNase I hypersensitivity sites Epigenetics Suffix tree

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Causes of evolutionary divergence in prostate cancer

arXiv

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arXiv 2025年

作者： Esentürk, Emre Sahli, Atef Haberland, Valeriia Ziuboniewicz, Aleksandra Wirth, Christopher Bova, G. Steven Bristow, Robert G. Brook, Mark N. Brors, Benedikt Butler, Adam Cancel-Tassin, Géraldine Cheng, Kevin C.L. Cooper, Colin S. Corcoran, Niall M. Cussenot, Olivier Eeles, Ros A. Favero, Francesco Gerhauser, Clarissa Gihawi, Abraham Girma, Etsehiwot G. Gnanapragasam, Vincent J. Gruber, Andreas J. Hamid, Anis Hayes, Vanessa M. He, Housheng Hansen Hovens, Christopher M. Imada, Eddie Luidy Jakobsdottir, G. Maria Jung, Chol-Hee Khani, Francesca Kote-Jarai, Zsofia Lamy, Philippe Leeman, Gregory Loda, Massimo Lutsik, Pavlo Marchionni, Luigi Molania, Ramyar Papenfuss, Anthony T. Pellegrina, Diogo Pope, Bernard Queiroz, Lucio R. Rausch, Tobias Reimand, Jüri Robinson, Brian Schlomm, Thorsten Sørensen, Karina D. Uhrig, Sebastian Weischenfeldt, Joachim Xu, Yaobo Yamaguchi, Takafumi N. Zanettini, Claudio Lynch, Andy G. Wedge, David C. Brewer, Daniel S. Woodcock, Dan J. Nuffield Department of Medicine University of Oxford United Kingdom Manchester Cancer Research Centre The University of Manchester United Kingdom Norwich Medical School University of East Anglia United Kingdom Nuffield Department of Surgical Sciences University of Oxford United Kingdom Prostate Cancer Research Center Faculty of Medicine and Health Technology Tampere University Finland Manchester Cancer Research Centre Cancer Research UK Manchester Institute The University of Manchester United Kingdom Christie NHS Foundation Trust United Kingdom Div Cancer Sciences Faculty of Biology Medicine & Health University of Manchester United Kingdom The Institute of Cancer Research United Kingdom Germany Germany Medical Faculty Heidelberg Faculty of Biosciences Heidelberg University Germany Wellcome Sanger Institute United Kingdom France Sorbonne Université GRC n°5 Predictive Onco-Urology APHP Tenon Hospital France Computational Biology Program Ontario Institute for Cancer Research Canada Department of Medical Biophysics University of Toronto Canada Department of Urology Royal Melbourne Hospital Australia Department of Surgery The University of Melbourne Australia Department of Urology Western Health Australia The Royal Marsden NHS Foundation Trust London United Kingdom University of Copenhagen Denmark Finsen Laboratory Copenhagen University Hospital - Rigshospitalet Denmark Germany Cambridge Biomedical Campus Addenbrooke's Hospital Site S Wards Building United Kingdom University of Konstanz Germany School of Medical Sciences University of Sydney Faculty of Medicine & Health Australia School of Health Systems & Public Health University of Pretoria South Africa Manchester Cancer Research Centre University of Manchester United Kingdom Princess Margaret Cancer Centre University Health Network Department of Medical Biophysics University of Toronto Canada Department of Surgery The Collaborative Centre for Genomic Cancer Medicine The University of Melbourne

Cancer progression involves the sequential accumulation of genetic alterations that cumulatively shape the tumour phenotype. In prostate cancer, tumours can follow divergent evolutionary trajectories that lead to distinct subtypes, but the causes of this divergence remain unclear. While causal inference could elucidate the factors involved, conventional methods are unsuitable due to the possibility of unobserved confounders and ambiguity in the direction of causality. Here, we propose a method that circumvents these issues and apply it to genomic data from 829 prostate cancer patients. We identify several genetic alterations that drive divergence as well as others that prevent this transition, locking tumours into one trajectory. Further analysis reveals that these genetic alterations may cause each other, implying a positive-feedback loop that accelerates divergence. Our findings provide insights into how cancer subtypes emerge and offer a foundation for genomic surveillance strategies aimed at monitoring the progression of prostate cancer. © 2025, CC BY-NC-SA.

关键词： Lung cancer

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