Article
Biology
Lucy Ham, Marcel Jackson, Michael P. H. Stumpf
Summary: Single-cell expression profiling reveals extensive cell-to-cell variability at the transcriptomic and proteomic level, posing challenges in inferring dynamics and causes of variability. New mathematical models and experimental set-ups are proposed to distinguish intrinsic and extrinsic noise, providing insights into understanding the origins and effects of cell-to-cell variability.
Article
Mathematical & Computational Biology
Meiling Chen, Tianshou Zhou, Jiajun Zhang
Summary: The transcription of genes in single cells is discussed as a probabilistic process, with emphasis on the relationship between variance and mean expression. It is revealed that the sign of a key parameter beta in this relationship is entirely controlled by external regulation, rather than promoter structure, and is determined by the independence or correlation of regulators as stochastic variables. The findings suggest that external regulation governs the mean-noise relationship more so than promoter sequence.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2021)
Article
Microbiology
Zhuo Chen, Brenda Zarazua-Osorio, Priyanka Srivastava, Masaya Fujita, Oleg A. Igoshin
Summary: In this study, the researchers used mathematical modeling and experiments to show that a regulator called Spo0A controls cell differentiation in Bacillus subtilis. They also explained why biofilm formation and sporulation appear to be mutually exclusive on a single-cell level.
Article
Multidisciplinary Sciences
Shih-Chiang Lo, Chao-Xuan You, Bo-Ren Chen, Ching-Chu Hsieh, Cheng-En Li, Che-Chi Shu
Summary: This study revealed that DNA in gene circuits plays a special role in resetting noise, allowing cells to switch between upstream TF and downstream products. By applying the stochastic simulation algorithm, researchers identified the parameter values that lead to this interesting phenomenon.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Renjie Wu, Bangyan Zhou, Wei Wang, Feng Li
Summary: This study categorizes the states of single eukaryotic genes, identifies 6 essential transcriptional events, and reveals how transcriptional bursting is modulated by various regulators. The results provide insights into transcriptional sensitivity, burst profiles, intrinsic transcriptional noise, and gene induction requirements.
Article
Biology
Alberto Giaretta
Summary: This study aims to theoretically study and complete the knowledge about a general basic open loop and linear modeling scheme of gene expression via alternative splicing and its connection with transcription and translation. The study shows the pivotal role of the splicing conversion rates in regulating stochastic noise and the stochastic bursts, autocorrelation, and noise power spectra in gene expression.
Article
Chemistry, Physical
Xiyan Yang, Songhao Luo, Zhenquan Zhang, Zihao Wang, Tianshou Zhou, Jiajun Zhang
Summary: Gene-expression bimodality, as a potential mechanism generating phenotypic cell diversity, can enhance the survival of cells in a fluctuating environment. The study shows that both silent-interval noise and translational burst-size noise can amplify gene-expression noise and induce diverse dynamic expression patterns.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Biochemical Research Methods
Roswitha Dolcemascolo, Lucas M. Goiriz, Roser Montagud-Martinez, Guillermo M. Rodrigo
Summary: In this study, a synthetic genetic system was engineered to investigate the stochasticity and regulation of genes at the level of translation. By monitoring the expression of both the regulator and the regulated gene at the single-cell level, it was found that a protein translation factor can achieve tight repression in single cells and buffer noise propagation from gene to gene.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Megan A. Coomer, Lucy Ham, Michael P. H. Stumpf
Summary: The Waddington epigenetic landscape is a significant representation of cellular differentiation. Recent advances in single-cell transcriptomic data have provided new opportunities for quantifying this concept and understanding the gene regulatory networks involved in cellular development. However, reconstructing the potential landscape is complex and limited due to stochastic fluctuations and the interplay between deterministic and stochastic components of the system.
Review
Genetics & Heredity
Abhishek Sarkar, Matthew Stephens
Summary: The Perspective suggests that a Poisson measurement model is sufficient for analyzing single-cell RNA sequencing data and could resolve current controversies. It argues against inconsistent terminology such as dropout and missing data. The development of methods should start with a simple Poisson model, as it is generally consistent with existing data.
Article
Physics, Fluids & Plasmas
Euan Joly-Smith, Zitong Jerry Wang, Andreas Hilfinger
Summary: Inferring functional relationships within complex networks from static snapshots of a subset of variables is a common problem in science. Researchers demonstrated a method using static population snapshots to infer properties of gene expression dynamics, and validated the theory through experiments with gene expression reporters. The study also derived correlation conditions for detecting closed-loop feedback regulation in gene regulatory networks.
Article
Biochemical Research Methods
Asia Mendelevich, Saumya Gupta, Aleksei Pakharev, Athanasios Teodosiadis, Andrey A. Mironov, Alexander A. Gimelbrant
Summary: A new spike-in approach is developed to correct technical noise in allele-specific expression analysis, which is highly accurate and cost-effective. This approach involves adding a distinct RNA as a spike-in before library preparation, allowing for efficient analysis of allele-specific expression in large studies.
Article
Biochemical Research Methods
Chance M. Nowak, Tyler Quarton, Leonidas Bleris
Summary: The study reveals that cells rapidly become asynchronous after synchronization, and the factors controlling this process are largely unknown. Through experiments and simulations, it is found that the variability in cell cycle duration is the main factor causing cell desynchronization, which provides new insights into cell cycle research.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Physics, Fluids & Plasmas
Feng Jiao, Genghong Lin, Jianshe Yu
Summary: This article introduces a stochastic gene transcription model with variable kinetic rates induced by unstable cellular conditions. The authors approximate transcription dynamics using steady-state formulas in the model and validate the robustness of the method with experimental data.
Article
Biochemical Research Methods
Joshua J. R. Burns, Benjamin T. Shealy, Mitchell S. Greer, John A. Hadish, Matthew T. McGowan, Tyler Biggs, Melissa C. Smith, F. Alex Feltus, Stephen P. Ficklin
Summary: Gene co-expression networks (GCNs) provide benefits to molecular research, but large multivariable datasets pose challenges to their construction. The use of a knowledge independent network construction toolkit can address these challenges and result in context-specific GCNs (csGCNs).
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Marion Buffard, Aurelien Naldi, Gilles Freiss, Marcel Deckert, Ovidiu Radulescu, Peter J. Coopman, Romain M. Larive
Summary: Research suggests that SYK can act as an oncogene or tumor suppressor depending on the cell and tissue type. By reconstructing and comparing signaling networks in breast cancer and Burkitt lymphoma cell lines, differences in signaling pathways and network topology were uncovered. Protein interactions were found to be rewired differently in the two types of cancer, demonstrating the complex interplays within SYK pathways affecting tumor formation and progression.
Article
Nutrition & Dietetics
Gabriela S. de Castro, Joanna Correia-Lima, Estefania Simoes, Camila E. Orsso, Jingjie Xiao, Leonardo R. Gama, Silvio P. Gomes, Daniela Caetano Goncalves, Raquel G. F. Costa, Katrin Radloff, Ulrike Lenz, Anna E. Taranko, Fang Chia Bin, Fernanda B. Formiga, Louisie G. L. de Godoy, Rafael P. de Souza, Luis H. A. Nucci, Mario Feitoza, Claudio C. de Castro, Flavio Tokeshi, Paulo S. M. Alcantara, Jose P. Otoch, Alexandre F. Ramos, Alessandro Laviano, Dario Coletti, Vera C. Mazurak, Carla M. Prado, Marilia Seelaender
Summary: This study found that the content of myokines in skeletal muscle, plasma, and tumors is impacted by cachexia, with decreased FSTL-1 expression in skeletal muscle and increased levels of FABP3, IL-15, and irisin found in cachectic patients. Additionally, indices of lumbar adipose tissue and muscularity were lower in cachexia patients.
CLINICAL NUTRITION
(2021)
Article
Biology
Ali Ekrem Yesilkanal, Dongbo Yang, Andrea Valdespino, Payal Tiwari, Alan U. Sabino, Long Chi Nguyen, Jiyoung Lee, Xiao-He Xie, Siqi Sun, Christopher Dann, Lydia Robinson-Mailman, Ethan Steinberg, Timothy Stuhlmiller, Casey Frankenberger, Elizabeth Goldsmith, Gary L. Johnson, Alexandre F. Ramos, Marsha R. Rosner
Summary: Targeting driver network signaling capacity through limited inhibition of core pathways is a more effective anti-metastatic strategy. Using a low-dose four-drug mimic can block metastatic colonization in mouse breast cancer models and increase survival. Limited inhibition of multiple pathways is necessary to overcome variation in MAPK network topology and suppress signaling output across heterogeneous tumor cells.
Article
Multidisciplinary Sciences
Katiana Tantale, Encarnation Garcia-Oliver, Adele L'Hostis, Yueyuxio Yang, Marie-Cecile Robert, Thierry Gostan, Alja Kozulic-Pirher, Jean-Christophe Andrau, Florian Mueller, Eugenia Basyuk, Ovidiu Radulescu, Edouard Bertrand, Nikolay Tsanov, Rachel Topno, Meenakshi Basu-Shrivastava, Kamalika Mukherjee, Vera Slaninova
Summary: The study reveals that in latent HIV-1 cells, RNA polymerases undergo long-lived pausing, effectively limiting viral transcription. This pausing is stochastic rather than obligatory, with only a small fraction of polymerases experiencing long-lived pausing. The stochastic pausing leads to burst-like HIV-1 transcription in latent cells, facilitating the randomness of viral reactivation.
NATURE COMMUNICATIONS
(2021)
Article
Multidisciplinary Sciences
Virginia L. Pimmett, Matthieu Dejean, Carola Fernandez, Antonio Trullo, Edouard Bertrand, Ovidiu Radulescu, Mounia Lagha
Summary: TATA-containing and INR-containing promoters exhibit distinct dynamics in early Drosophila development, requiring one or two separate rate-limiting steps respectively, with TATA-driven promoters requiring more steps. Core promoter elements play an important role in regulating the rate limiting steps of transcription.
NATURE COMMUNICATIONS
(2021)
Article
Mathematics, Applied
Niclas Kruff, Christoph Lueders, Ovidiu Radulescu, Thomas Sturm, Sebastian Walcher
Summary: This study presents a symbolic algorithmic approach for computing invariant manifolds and corresponding reduced systems for differential equations modeling biological networks, with applications in cellular biochemistry, pharmacology, epidemiology, and ecology. The reduction method is mathematically justified within a singular perturbation setting and utilizes scaling based on tropical geometry. The algorithmic test proposed for the existence of invariant manifolds is based on Hurwitz criteria.
MATHEMATICS IN COMPUTER SCIENCE
(2021)
Review
Biochemistry & Molecular Biology
Ali E. Yesilkanal, Gary L. Johnson, Alexandre F. Ramos, Marsha Rich Rosner
Summary: Targeted strategies against cancer driver molecules have advanced cancer treatment, but tumor resistance to inhibitors often reverses initial efficacy. High-dose treatments may activate resistance mechanisms, while high-dose combination therapies increase toxicity. Adopting low-dose multitarget approaches could be an effective strategy to achieve antitumor efficacy without increasing toxicity.
JOURNAL OF BIOLOGICAL CHEMISTRY
(2021)
Article
Computer Science, Theory & Methods
Guilherme C. P. Innocentini, Arran Hodgkinson, Fernando Antoneli, Arnaud Debussche, Ovidiu Radulescu
Summary: The simulation of biochemical networks requires different models based on the numbers of molecules and reaction frequencies; Piecewise-deterministic Markov processes are suitable for describing situations with infrequent reactions and small numbers of molecules; The push-forward method can help calculate the probability distribution changes in biochemical networks.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Oncology
Guilherme Giovanini, Luciana R. C. Barros, Leonardo R. Gama, Tharcisio C. Tortelli, Alexandre F. Ramos
Summary: Gene editing technologies have made significant progress in epigenetic modulation for cancer treatment. Gene networks, complex systems capable of processing dynamic information, lose their functionality in diseased states. By modulating multiple gene expression processes, it is possible to reduce heterogeneity and enhance specific treatment responses. Mathematical models are used to analyze stochastic gene expression, and simulation scenarios demonstrate the effectiveness of the approach. This method has potential for developing epigenetic-targeting treatments.
Article
Chemistry, Physical
Kun Zhang, Alexandre Ferreira Ramos, Erkang Wang, Jin Wang
Summary: In this study, the stochastic dynamics of an externally regulating gene circuit in the development of Drosophila is investigated. Different gene regulation regimes, including adiabatic, nonadiabatic, and bursting phases, are considered. It is found that the thermodynamic cost can suppress the fluctuations of the gene circuit, with higher thermodynamic cost leading to reduced fluctuations and increased stability. The study also suggests that higher thermodynamic cost is often required to sustain the emergence of more gene states and heterogeneity.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Computer Science, Hardware & Architecture
Xiaolong Huang, Alexandre F. Ramos, Yuefan Deng
Summary: The article introduces a method for designing low-latency network topologies for high-performance computing clusters by optimizing the diameters, mean path lengths, and bisection widths of circulant topologies. Benchmark tests reveal the superior performance of optimal circulant topologies in communication-intensive applications.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Multidisciplinary Sciences
Maelle Bellec, Jeremy Dufourt, George Hunt, Helene Lenden-Hasse, Antonio Trullo, Amal Zine El Aabidine, Marie Lamarque, Marissa M. Gaskill, Heloise Faure-Gautron, Mattias Mannervik, Melissa M. Harrison, Jean-Christophe Andrau, Cyril Favard, Ovidiu Radulescu, Mounia Lagha
Summary: Using quantitative imaging and monitoring transcription in living embryos, Bellec et al. provide evidence that the pioneer factor GAF acts as a stable mitotic bookmarker during early Drosophila development. GAF remains associated with its interphase targets during mitosis, which are bookmarked via histone acetylation. GAF binding competence for rapid activation upon mitotic exit is observed.
NATURE COMMUNICATIONS
(2022)
Article
Oncology
Arran Hodgkinson, Dumitru Trucu, Matthieu Lacroix, Laurent Le Cam, Ovidiu Radulescu
Summary: This study explores the relationship between melanoma cell heterogeneity and drug resistance by introducing a new mathematical formalism. Using single cell mRNA sequencing data, the researchers propose different therapeutic strategies for melanoma and predict their outcomes.
FRONTIERS IN ONCOLOGY
(2022)
Review
Virology
Alexia Damour, Vera Slaninova, Ovidiu Radulescu, Edouard Bertrand, Eugenia Basyuk
Summary: This review summarizes the current advances in understanding the role of transcriptional stochasticity in HIV-1 latency. The stochastic switching of the viral promoter between ON and OFF states is the result of random binding dynamics of transcription factors and nucleosomes. Transcriptional bursts are controlled by core transcription factors, chromatin status, and RNA polymerase II pausing. Understanding this stochasticity will be crucial for developing effective therapeutic strategies.
Review
Genetics & Heredity
Alexis German Murillo Carrasco, Guilherme Giovanini, Alexandre Ferreira Ramos, Roger Chammas, Silvina Odete Bustos
Summary: In the past decade, there has been a significant increase in autophagy research due to its role in cancer progression and treatment resistance. This study used omics-based cancer datasets to identify autophagy genes as prognostic markers in cancer and explored their clinical significance. The findings emphasize the importance of innovative approaches in analyzing tumor heterogeneity and provide potential therapeutic targets.
