Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge. One type of model is a genome-scale metabolic model (GEM) that allows studying the distributions of metabolic fluxes, i.e., the "mass-flow" through the network of biochemical reactions. GEMs are nowadays widely applied and have been reconstructed for various microbial pathogens, either in a free-living state or in interaction with their hosts, with the aim to gain insight into mechanisms of pathogenicity. In this review, we first introduce the principles of systems biology and GEMs. We then describe how metabolic modeling can contribute to unraveling microbial pathogenesis and host-pathogen interactions, with a specific focus on oomycete plant pathogens and in particular . Subsequently, we review achievements obtained so far and identify and discuss potential pitfalls of current models. Finally, we propose a workflow for reconstructing high-quality GEMs and elaborate on the resources needed to advance a system biology approach aimed at untangling the intimate interactions between plants and pathogens.
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http://dx.doi.org/10.3389/fmicb.2021.748178 | DOI Listing |
Toxicol 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.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
The Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, 94608, USA.
Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement.
View Article and Find Full Text PDFNat Commun
January 2025
Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.
With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics.
View Article and Find Full Text PDFNat Commun
January 2025
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
ATR plays key roles in cellular responses to DNA damage and replication stress, a pervasive feature of cancer cells. ATR inhibitors (ATRi) are in clinical development for treating various cancers, including those with high replication stress, such as is elicited by ARID1A deficiency, but the cellular mechanisms that determine ATRi efficacy in such backgrounds are unclear. Here, we have conducted unbiased genome-scale CRISPR screens in ARID1A-deficient and proficient cells treated with ATRi.
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