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Camacho-Zaragoza, J. M.

Publications and source records attributed to Camacho-Zaragoza, J. M..

2 recordsLinked to original sources

Multiplex genome editing eliminates the Warburg Effect without impacting growth rate in mammalian cells

The Warburg effect is ubiquitous in proliferative mammalian cells, including cancer cells, but poses challenges for biopharmaceutical production, as lactate accumulation inhibits cell growth and protein production. Previous efforts to eliminate lactate production via knockout have failed in mammalian bioprocessing since lactate dehydrogenase has proven essential. However, here we eliminated the Warburg effect in Chinese hamster ovary (CHO) and HEK293 cells by simultaneously knocking out lactate dehydrogenase and regulators involved in a negative feedback loop that typically inhibits pyruvate conversion to acetyl-CoA. In contrast to long-standing assumptions about the role of aerobic glycolysis, Warburg-null cells maintain wildtype growth rate while producing negligible lactate. Further characterization of Warburg-null CHO cells showed a compensatory increase in oxygen consumption, a near total reliance on oxidative metabolism, and higher cell densities in fed-batch cell culture. These cells remained amenable for production of diverse biotherapeutic proteins, reaching industrially relevant titers and maintaining product glycosylation. Thus, the ability to eliminate the Warburg effect is an important development for biotherapeutic production and provides a tool for investigating a near-universal metabolic phenomenon.

bioengineering↗

MCO: towards an ontology and unified vocabulary for a framework-based annotation of microbial growth conditions

MotivationA major component in our understanding of the biology of an organism is the mapping of its genotypic potential into the repertoire of its phenotypic expression profiles. This genotypic to phenotypic mapping is executed by the machinery of gene regulation that turns genes on and off, which in microorganisms is essentially studied by changes in growth conditions and genetic modifications. Although many efforts have been made to systematize the annotation of experimental conditions in microbiology, the available annotation is not based on a consistent and controlled vocabulary for the unambiguous description of growth conditions, making difficult the identification of biologically meaningful comparisons of knowledge generated in different experiments or laboratories, a task urgently needed given the massive amounts of data generated by high throughput (HT) technologies.\n\nResultsWe curated terms related to experimental conditions that affect gene expression in E. coli K-12. Since this is the best studied microorganism, the collected terms are the seed for the first version of the Microbial Conditions Ontology (MCO), a controlled and structured vocabulary that can be expanded to annotate microbial conditions in general. Moreover, we developed an annotation framework using the MCO terms to describe experimental conditions, providing the foundation to identify regulatory networks that operate under a particular condition. MCO supports comparisons of HT-derived data from different repositories. In this sense, we started to map common RegulonDB terms and Colombos bacterial expression compendia terms to MCO.\n\nAvailability and ImplementationAs far as we know, MCO is the first ontology for growth conditions of any bacterial organism and it is available at http://regulondb.ccg.unam.mx/. Furthermore, we will disseminate MCO throughout the Open Biomedical Ontology (OBO) Foundry in order to set a standard for the annotation of gene expression data derived from conventional as well as HT experiments in E. coli and other microbial organisms. This will enable the comparison of data from diverse data sources.\n\nContactsgama@ccg.unam.mx, collado@ccg.unam.mx

bioinformatics↗