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Kallehauge, T. B.

Publications and source records attributed to Kallehauge, T. B..

4 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↗

CRISPRi screen for enhancing heterologous α-amylase yield in Bacillus subtilis

Enhancing yield during bacterial enzyme production could have positive economic and environmental impacts. For cell factories, such improvements in yields could potentially be obtained by fine-tuning the metabolic processes and their regulatory mechanisms for gene candidates. In pursuit of such candidates, we performed RNA-sequencing of two -amylase producing Bacillus strains and predict hundreds of putative novel non-coding transcribed regions. Complex operons that are regulated by a wide variety of transcription factors, non-coding and structured RNAs add to the challenge of finding yield-affecting candidates. Surprisingly, we found that non-coding genomic regions are proportionally undergoing the highest changes in expression during fermentation (75% of novel RNA predictions had absolute logFC > 2). Since these classes of RNA are also understudied, we targeted the corresponding genomic regions with CRIPSRi knockdown to test for any potential impact on the yield. From differentially expressed annotations, including both novel candidate and prior annotated ncRNAs, we selected 53 non-coding candidates. The targeting with CRISPRi knockdowns transcription in a genomic region on both the sense and the antisense strand. Thus, the CRISPRi experiment cannot link causes for yield changes to the sense or antisense disruption. Nevertheless, we observed on several instances with strong changes in enzyme yield. The knockdown targeting the genomic region for a putative antisense RNA of the 3 UTR of the skfA-skfH operon led to a 21% increase in yield. In contrast, the knockdown targeting the genomic regions of putative antisense RNAs of the cytochrome c oxidase subunit 1 (ctaD), the sigma factor sigH, and the uncharacterized gene yhfT decreased yields by 31 to 43%.

microbiology↗

The BSGatlas: An enhanced annotation of genes and transcripts for the Bacillus subtilis genome with improved information access

The genome of Bacillus subtilis continues to provide exiting genomic insights. However, the growing collective genomic knowledge about this micro-organism is spread across multiple annotation resources. Thus, the full annotation is not directly accessible neither for specific genes nor for large-scale high-throughput analyses. Furthermore, access to annotation of non-coding RNA genes (ncRNAs) and polycistronic mRNAs is difficult. To address these challenges we introduce the Bacillus subtilis genome atlas, BSGatlas, in which we integrate and unify multiple existing annotation resources. Our integration provides twice as many ncRNAs than the individual resources, improves the positional annotation for 70% of the combined ncRNAs, and makes it possible to infer specific ncRNA types. Moreover, we unify known transcription start sites, termination, and transcriptional units (TUs) as a comprehensive transcript map. This transcript map implies 815 new TUs and 6, 164 untranslated regions (UTRs), which is a five-fold increase over existing resources. We furthermore, find 2, 309 operons covering the transcriptional annotation for 93% of all genes, corresponding to an improvement by 11%. The BSGatlas is available in multiple formats. A user can either download the entire annotation in the standardized GFF3 format, which is compatible with most bioinformatics tools for omics and high-throughput studies, or view the annotation in an online browser at http://rth.dk/resources/bsgatlas.\n\nImportanceThe Bacillus subtilis genome has been studied in numerous context and consequently multiple efforts have been made in providing a complete annotation. Unfortunately, a number of resources are no longer maintained, and (i) the collective annotation knowledge is dispersed over multiple resources, of which each has a different focus of what type of annotation information they provide. (ii) Thus, it is difficult to easily and at a large scale obtain information for a genomic region or genes of interest. (iii) Furthermore, all resources are essentially incomplete when it comes to annotating non-coding and structured RNA, and transcripts in general. Here, we address all three problems by first collecting existing annotations of genes and transcripts start and termination sites; afterwards resolving discrepancies in annotations and combining them, which doubled the number of ncRNAs; inferring full transcripts and 2,309 operons from the combined knowledge of known transcript boundaries and meta-information; and critically providing it all in a standardized UCSC browser. That interface and its powerful set of functionalities allow users to access all the information in a single resource as well as enables them to include own data on top the full annotation.

genomics↗

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

systems biology↗