Background: Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network.
Results: We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results.
Software: A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC.
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http://dx.doi.org/10.1186/s13015-014-0028-y | DOI Listing |
Microbiol Spectr
January 2025
School of Pharmacy, Lanzhou University, Lanzhou, China.
Colorectal cancer (CRC) is a common cancer accompanied by microbiome dysbiosis. Exploration of probiotics against oncogenic microorganisms is promising for CRC treatment. Here, differential microorganisms between CRC and healthy control were analyzed.
View Article and Find Full Text PDFGenes (Basel)
January 2025
Department of Physics and Astronomy, College of Science, Clemson University, Clemson, SC 29634, USA.
Background/objectives: Predicting the effects of protein and DNA mutations on the binding free energy of protein-DNA complexes is crucial for understanding how DNA variants impact wild-type cellular function. As many cellular interactions involve protein-DNA binding, accurately predicting changes in binding free energy (ΔΔG) is valuable for distinguishing pathogenic mutations from benign ones.
Methods: This study describes the development and optimization of the SAMPDI-3Dv2 machine learning method, which is trained on an expanded database of experimentally measured ΔΔGs.
mSystems
January 2025
Biosystems and Bioprocess Engineering, IIM-CSIC, Vigo, Spain.
During batch fermentation, a variety of compounds are synthesized, as microorganisms undergo distinct growth phases: lag, exponential, growth-no-growth transition, stationary, and decay. A detailed understanding of the metabolic pathways involved in these phases is crucial for optimizing the production of target compounds. Dynamic flux balance analysis (dFBA) offers insight into the dynamics of metabolic pathways.
View Article and Find Full Text PDFToxicol Sci
January 2025
Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, 21702, USA.
Because the liver plays a vital role in the clearance of exogenous chemical compounds, it is susceptible to chemical-induced toxicity. Animal-based testing is routinely used to assess the hepatotoxic potential of chemicals. While large-scale high-throughput sequencing data can indicate the genes affected by chemical exposures, we need system-level approaches to interpret these changes.
View Article and Find Full Text PDFNat Commun
January 2025
Institute of Marine Science and Technology, Shandong University, Qingdao, China.
Lignin, as the abundant carbon polymer, is essential for carbon cycle and biorefinery. Microorganisms interact to form communities for lignin biodegradation, yet it is a challenge to understand such complex interactions. Here, we develop a coastal lignin-degrading bacterial consortium (LD), through "top-down" enrichment.
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