Biology subjects

Gudmundsson, S.

Publications and source records attributed to Gudmundsson, S..

4 recordsLinked to original sources

bioRxiv2024

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

genomics↗

bioRxiv2021

A genome-scale metabolic reconstruction provides insight into the metabolism of the thermophilic bacterium Rhodothermus marinus

The thermophilic bacterium Rhodothermus marinus has mainly been studied for its thermostable enzymes. More recently, the potential of using the species as a cell factory and in biorefinery platforms has been explored, due to the elevated growth temperature, native production of compounds such as carotenoids and EPSs, the ability to grow on a wide range of carbon sources including polysaccharides, and available genetic tools. A comprehensive understanding of the metabolism of production organisms is crucial. Here, we report a genome-scale metabolic model of R. marinus DSM 4252T. Moreover, the genome of the genetically amenable R. marinus ISCaR-493 was sequenced and the analysis of the core genome indicated that the model could be used for both strains. Bioreactor growth data was obtained, used for constraining the model and the predicted and experimental growth rates were compared. The model correctly predicted the growth rates of both strains. During the reconstruction process, different aspects of the R. marinus metabolism were reviewed and subsequently, both cell densities and carotenoid production were investigated for strain ISCaR-493 under different growth conditions. Additionally, the dxs gene, which was not found in the R. marinus genomes, from Thermus thermophilus was cloned on a shuttle vector into strain ISCaR-493 resulting in a higher yield of carotenoids. ImportanceA biorefinery converting biomass into fuels and value-added chemicals is a sustainable alternative to fossil fuel-based chemical synthesis. Rhodothermus marinus is a bacterium that is potentially well suited for biorefineries. It possesses various enzymes that degrade biomass, such as macroalgae and parts of plants (e.g. starch and xylan) and grows at high temperatures (55-77{degrees}C) which is beneficial in biorefinery processes. In this study, we reviewed the metabolism of R. marinus and constructed a metabolic model. Such a model can be used to predict phenotypes, e.g. growth under different environmental and genetic conditions. We focused specifically on metabolic features that are of interest in biotechnology, including carotenoid pigments which are used in many different industries. We described cultivations of R. marinus and the resulting carotenoid production in different growth conditions, which aids in understanding how carotenoid yields can be increased in the bacterium.

systems biology↗

bioRxiv2020

Amplification-free long read sequencing reveals unforeseen CRISPR-Cas9 off-target activity

A much-debated concern about CRISPR-Cas9 genome editing is that unspecific guide RNA (gRNA) binding may induce off-target mutations. However, accurate prediction of CRISPR-Cas9 off-target sites and activity is challenging. Here we present SMRT-OTS and Nano-OTS, two amplification-free long-read sequencing protocols for detection of gRNA driven digestion of genomic DNA by Cas9. The methods were assessed using the human cell line HEK293, which was first re-sequenced at 18x coverage using highly accurate (HiFi) SMRT reads to get a detailed view of all on- and off-target binding regions. We then applied SMRT-OTS and Nano-OTS to investigate the specificity of three different gRNAs, resulting in a set of 55 high-confidence gRNA binding sites identified by both methods. Twenty-five (45%) of these sites were not reported by off-target prediction software, either because they contained four or more single nucleotide mismatches or insertion/deletion mismatches, as compared with the human reference. We further discovered that a heterozygous SNP can cause allele-specific gRNA binding. Finally, by performing a de novo genome assembly of the HiFi reads, we were able to re-discover 98.7% of the gRNA binding sites without any prior information about the human reference genome. This suggests that CRISPR-Cas9 off-target sites can be efficiently mapped also in organisms where the genome sequence is unknown. In conclusion, the amplification-free sequencing protocols revealed many gRNA binding sites in vitro that would be difficult to predict based on gRNA sequence alignment to a reference. Nevertheless, it is still unknown whether in vivo off-target editing would occur at these sites.

genomics↗

bioRxiv2017

Expanding The Computable Reactome In Pseudomonas putida Reveals Metabolic Cycles Providing Robustness

Genome-scale network reconstructions are organism-specific representations of metabolism and powerful tools for analyzing systemic metabolic properties. The use of reconstructions is limited by the lack of coverage of the metabolic reactome. We present an exhaustive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440, greatly expanding its computable metabolic states. The reconstruction, iJN1411, represents a significant expansion over other reconstructed bacterial metabolic networks. Computations based on the reconstruction exhibit high accuracy in predicting nutrient sources, growth rates, carbon flux distributions, and gene essentiality, thus providing a deep understanding of Pseudomonas metabolism. iJN1411 was used for: i) the assessment of the metabolic capabilities of P. putida as a species through multi-strain modeling, ii) deciphering the molecular mechanisms underlying metabolic robustness, and iii) identification of metabolic \"capacitors\" based on ATP-fueled metabolic cycles. This study represents the most complete and comprehensive bacterial metabolic reconstruction built to date, while providing computational and experimental evidence about how bacteria increase metabolic robustness, paving the way for engineering more robust biocatalysts and searching for drug targets in robust pathogens.

systems biology↗