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- Karlsson, Max, et al.
(author)
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Genome-wide annotation of protein-coding genes in pig
- 2022
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In: BMC Biology. - : Springer Nature. - 1741-7007. ; 20:1
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Journal article (peer-reviewed)abstract
- Background: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. Results: An open-access pig expression map (www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. Conclusions: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource (www.rnaatlas.org), including a comparison to the expression of human orthologs.
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| 2. |
- Arif, Muhammad, et al.
(author)
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Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction
- 2021
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In: Elife. - : eLife Sciences Publications, Ltd. - 2050-084X. ; 10
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Journal article (peer-reviewed)abstract
- Myocardial infarction (MI) promotes a range of systemic effects, many of which are unknown. Here, we investigated the alterations associated with MI progression in heart and other metabolically active tissues (liver, skeletal muscle, and adipose) in a mouse model of MI (induced by ligating the left ascending coronary artery) and sham-operated mice. We performed a genomewide transcriptomic analysis on tissue samples obtained 6- and 24 hr post MI or sham operation. By generating tissue-specific biological networks, we observed: (1) dysregulation in multiple biological processes (including immune system, mitochondrial dysfunction, fatty-acid beta-oxidation, and RNA and protein processing) across multiple tissues post MI and (2) tissue-specific dysregulation in biological processes in liver and heart post MI. Finally, we validated our findings in two independent MI cohorts. Overall, our integrative analysis highlighted both common and specific biological responses to MI across a range of metabolically active tissues.
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| 3. |
- Altay, Özlem, et al.
(author)
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Revealing the Metabolic Alterations during Biofilm Development of Burkholderia cenocepacia Based on Genome-Scale Metabolic Modeling
- 2021
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In: Metabolites. - : MDPI AG. - 2218-1989 .- 2218-1989. ; 11:4
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Journal article (peer-reviewed)abstract
- Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.
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| 5. |
- Abdellah, Tebani, et al.
(author)
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Integration of molecular profiles in a longitudinal wellness profiling cohort.
- 2020
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies andimmune cell profiling, complementedwith gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.
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| 8. |
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| 9. |
- Karlsson, Max, et al.
(author)
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Genome-wide single cell annotation of the human protein-coding genes
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Other publication (other academic/artistic)abstract
- An important quest for the life science community is to deliver a complete annotation of the human building-blocks of life, the genes and the proteins. Here, we report on a genome-wide effort to annotate all protein-coding genes based on single cell transcriptomics data representing all major tissues and organs in the human body, integrated with data from bulk transcriptomics and antibody-based tissue profiling. Altogether, 25 tissues have been analyzed with single cell transcriptomics resulting in genome-wide expression in 444 single cell types using a strategy involving pooling data from individual cells to obtain genome-wide expression profiles of individual cell type. We introduce a new genome-wide classification tool based on clustering of similar expression profiles across single cell types, which can be visualized using dimensional reduction maps (UMAP). The clustering classification is integrated with a new “tau” score classification for all protein-coding genes, resulting in a measure of single cell specificity across all cell types for all individual genes. The analysis has allowed us to annotate all human protein-coding genes with regards to function and spatial distribution across individual cell types across all major tissues and organs in the human body. A new version of the open access Human Protein Atlas (www.proteinatlas.org) has been launched to enable researchers to explore the new genome-wide annotation on an individual gene level.
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| 10. |
- Liao, Xinmeng, et al.
(author)
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Open MoA : revealing the mechanism of action (MoA) based on network topology and hierarchy
- 2023
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 39:11
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Journal article (peer-reviewed)abstract
- MOTIVATION: Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA). RESULTS: We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/XinmengLiao/Open_MoA.
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