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The apicomplexan Cryptosporidium is a protozoan parasite of humans and other mammals. Cryptosporidium species cause acute gastroenteritis and diarrheal disease in healthy humans and animals, and cause life-threatening infection in immunocompromised individuals such as people with AIDS. The parasite has a one-host life cycle and commonly invades intestinal epithelial cells. The current genome annotation of C. hominis, the most serious human pathogen, predicts 3884 genes of which ca. 1581 have predicted functional annotations. Using a combination of bioinformatics analysis, biochemical evidence, and high-throughput data, we have constructed a genome-scale metabolic model of C. hominis. The model is comprised of 213 gene-associated enzymes involved in 540 reactions among the major metabolic pathways and provides a link between the genotype and the phenotype of the organism, making it possible to study and predict behavior based upon genome content. This model was also used to analyze the two life stages of the parasite by integrating the stage-specific proteomic data for oocyst and sporozoite stages. Overall, this model provides a computational framework to systematically study and analyze various functional behaviors of C. hominis with respect to its life cycle and pathogenicity.
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http://dx.doi.org/10.1002/cbdv.200900323 | DOI Listing |
FEMS Yeast Res
March 2025
McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX, USA.
Yeasts have emerged as well-suited microbial cell factory for the sustainable production of biofuels, organic acids, terpenoids, and specialty chemicals. This ability is bolstered by advances in genetic engineering tools, including CRISPR-Cas systems and modular cloning in both conventional (Saccharomyces cerevisiae) and non-conventional (Yarrowia lipolytica, Rhodotorula toruloides, Candida krusei) yeasts. Additionally, genome-scale metabolic models (GEMs) and machine learning approaches have accelerated efforts to create a broad range of compounds that help reduce dependency on fossil fuels, mitigate climate change, and offer sustainable alternatives to petrochemical-derived counterparts.
View Article and Find Full Text PDFBiotechnol Adv
March 2025
Frontiers Science Center of Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China; State Key Laboratory of Biotherapy and Cancer Centre/Collaborative Innovation Centre for Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China; Department of Hematology, West China Hospital, Sichuan University, Chengdu 610041, China. Electronic address:
Yeast Saccharomyces cerevisiae (S. cerevisiae) is a crucial industrial platform for producing a wide range of chemicals, fuels, pharmaceuticals, and nutraceutical ingredients. It is also commonly used as a model organism for fundamental research.
View Article and Find Full Text PDFMetab Eng
March 2025
Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany; Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany; Bioinformatics and Mathematical Modeling Department, Center of Plant Systems Biology and Biotechnology, 4000 Plovdiv, Bulgaria. Electronic address:
Advances in genomics technologies have generated large data sets that provide tremendous insights into the genetic diversity of taxonomic groups. However, it remains challenging to pinpoint the effect of genetic diversity on different traits without performing resource-intensive phenotyping experiments. Pan-genome-scale metabolic models (panGEMs) extend traditional genome-scale metabolic models by considering the entire reaction repertoire that enables the prediction and comparison of metabolic capabilities within a taxonomic group.
View Article and Find Full Text PDFFEMS Yeast Res
March 2025
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
Komagataella phaffii has gained recognition as a versatile platform for recombinant protein production, with applications covering biopharmaceuticals, industrial enzymes, food additives, etc. Its advantages include high-level protein expression, moderate post-translational modifications, high-density cultivation, and cost-effective methanol utilization. Nevertheless, it still faces challenges for the improvement of production efficiency and extension of applicability.
View Article and Find Full Text PDFPLoS Comput Biol
March 2025
Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.
Advancements with cost-effective, high-throughput omics technologies have had a transformative effect on both fundamental and translational research in the medical sciences. These advancements have facilitated a departure from the traditional view of human red blood cells (RBCs) as mere carriers of hemoglobin, devoid of significant biological complexity. Over the past decade, proteomic analyses have identified a growing number of different proteins present within RBCs, enabling systems biology analysis of their physiological functions.
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