5PSeq Explorer Data Freeze
Documentation files
Documentation files
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
Research principal:
Data contains personal data:
No
Citation:
Language:
Method and outcome
Method and outcome
Unit of analysis:
Population:
Molecular data (775 5PSeq datasets) collected from 18 published studies interrogating various mRNA decay and translation across genetic and environmental perturbations. For Eukaryotes, the collection consists of 378 yeast samples (Ascomycota phylum) with an overrepresentation of Saccharomyces cerevisiae (n= 340). For bacteria we provide 397 samples across Actinomycetota, Bacillota, Bacteroides, Bacteroidota, Proteobacteria, Pseudomonadota and Verrucomicrobiota phyla with an overreprepresentation for Bacillus subtilis (n= 67) and Aggregatibacter actinomycetemcomitans (n=59).
Time method:
Study design:
- Preclinical study
Description of study design:
Compiled public sequencing datasets
Sampling procedure:
Description of sampling:
A collection of published molecular data was uniformly processed and relies on sampling carried out by the original study.
Time period(s) investigated:
Variables:
18
Number of individuals/objects:
775
Data collection - Experiment
Data collection - Experiment
Mode of collection:
Experiment
Description of the mode of collection:
Data collection information for each record is available in the metadata file attached. The library preparation protocol for 5Pseq, and the version of the protocol used, is noted in the metadata (attached file). All records are accompanied by a GEO_ID, SRA_ID and PubMed ID for a detailed record of the biosample, collection and experimental details.
Time period(s) for data collection:
2015 - 2024
Data collector:
- Karolinska Institutet
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ROR
Sample size:
775
Source of the data:
- Research data
- Research data: Published
Instrument
Instrument
Name:
Illumina NextSeq 2000
Type:
Technical instrument(s)
Name:
Illumina NextSeq 500
Type:
Technical instrument(s)
Name:
Illumina NovaSeq 6000
Type:
Technical instrument(s)
Name:
Illumina HiSeq 2000
Type:
Technical instrument(s)
Name:
Illumina MiSeq
Type:
Technical instrument(s)
Administrative information
Administrative information
Responsible department/unit:
Department of Microbiology, Tumor and Cell Biology [C1]
Commissioning organisation:
- Karolinska Institutet
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ROR
Funding
Funding
Funding agency:
- Swedish Research Council
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ROR
Award number:
2021-06112_VR
Award title:
Development of a novel tool for diagnosis and prevention of antimicrobial resistance
Funding information:
Antimicrobial resistance (AMR) poses a threat to global health. Infections lead to longer hospital stays and increased mortality, while recurrent infections increase the risk for appearance of deadly multidrug resistant bacterial and fungal pathogens. One of the greatest challenges in AMR is the shortcoming in their diagnosis. Classical microbiology tests are often inadequate in timely detection of infections, and thus antibiotics are prescribed in a presumptive manner. Here we propose to develop a novel molecular approach able to diagnose bacterial and fungal infections and associated AMR integrating molecular biology, high-throughput sequencing and machine learning approaches. We will pilot the use of mRNA degradation signatures (metadegradomics) as phenotypic molecular reporter of antimicrobial resistance and develop a cost-effective diagnosis method for their identification. Simultaneously, we will measure patient-specific microbiomes to predict infection recurrence, understand how it modulates the appearance of AMR strains and aid on the clinical management of patients. We will demonstrate the viability of the developed diagnosis approach utility by applying it to both intensive care unit patients and by improve our understanding of recurrent vaginosis in women. Our work aims to dramatically accelerate AMR diagnosis (< 24h), improve patient survival and contribute to rationalizing the infection treatments.
Funding agency:
- Wallenberg Academy Fellowship
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ROR
Award number:
2021.0167
Funding agency:
- Karolinska Institutet
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ROR
Award number:
SciLifeLab, SFO, KID and KI funds
Funding agency:
- Swedish Research Council
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ROR
Award number:
2022-05272_VR
Award title:
Development of a molecular kit for the simplified detection of phenotypic antimicrobial resistance.
Funding information:
The emergence of antibiotic-resistant microorganisms (AMR) poses a threat to global health. Fast and accurate diagnosis is key to contain the rise of AMR, limit its spread and provide adequate treatment to patients. However, classic microbiology approaches are often inadequate in timely detection of infections. Here we propose to pilot the clinical usability and explore the commercial potential of a novel molecular approach able to detect AMR independent of the drug resistance mechanism or the presence of known markers.Based on our discovery that changes in mRNA degradation inform about strain-specific response to antimicrobials, we will develop a simplified molecular kit to measure AMR. The proposed strategy will be fast (<4h), use instruments present in most laboratories and be compatible with current diagnostic workflows. We will validate this approach and assess its utility in collaboration with the healthcare sector. Next, we will explore its future implementation in the context of the new EU regulation for In vitro Diagnosis. During this project we aim to obtain sufficient preliminary data to spin-off this technology to the Swedish biotech sector.In summary, we aim to develop a simplified platform to provide fast diagnosis for bacterial infections and actionable recommendation for antibiotic usage. Our work has the potential to dramatically accelerate diagnosis, improve patient survival, and contribute to individualized and rational use of antibiotics.
Funding agency:
- Swedish Research Council
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ROR
Award number:
2023-02026_VR
Award title:
Scalable Label-free electric detection of pathogens
Funding information:
Virus-caused infections are a leading cause of illness around the world. Rapid diagnosis of infectious diseases is critical for appropriate and timely treatment of infected patients, for disease surveillance and to prevent the rapid spread of infectious diseases. Here we propose to develop a novel and scalable approach for label-free electric detection of virus. We will use a modified RT-LAMP to amplify viral genetic material and self-assemble the product into DNA nanoballs. Next, the generated nanoballs will be detected by measuring changes in electric impedance as they flow passively through a microfluidic channel. We expect that the combination of RT-LAMP and DNA nanoball generation provides higher specificity and sensitivity than current approaches. By avoiding the need of fluorescence and by using electric impedance that can be easily miniaturized, we aim to develop an affordable point of care system. We will validate this approach with SARS-CoV-2 and demonstrate its wide applicability and intrinsic flexibility by applying it to multiple pathogens (HIV, Influenza, RSV, measles…). Finally, we will benchmark this approach and validate its utility in collaboration with a hospital clinical microbiology laboratory. In summary, we propose to develop a new diagnostic method that has the potential to provide a sensitive, cheap and scalable point-of-care system to help address the growing diagnostic challenges in the coming decades.
Funding agency:
- Swedish Research Council
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ROR
Award number:
2024-03210_VR
Award title:
Molecular dissection of nutrition-induced ribosome frameshifts, from cancer to aging.
Funding information:
We have recently discovered a novel mechanism by which, in response to low nutrient conditions, most ribosomes experience a -1 ribosome frameshift. This process affects most genes causing a drastic acceleration of mRNA decay and the production of aberrant proteins. Here we aim to improve our mechanistic understanding of this process using genomic and proteomic methods.First, we will characterize the accumulation of Ct truncated aberrant proteins derived from nutrition-induced frameshift events and their impact on cellular fitness. As our preliminary data shows that this phenomenon occurs also in cancer cells under amino acid starvation, we will characterize the impact of nutrition-induced frameshift in cancer regulation. We will focus on understanding how frameshift events result in the generation of cancer neoantigens. Preliminary evidence suggest that older cells are more prone to experience nutrition-induced frameshift. Thus, we will study this using aging models for yeast and humans. Finally, as the level of nutrition-induced frameshift can be easily modulated, we will pilot the development of novel intervention strategies to increase the expression of neoantigens in cancer cells and minimise proteostasis problems during aging.In essence, our project aims to illuminate a novel layer of gene expression regulation and examine its manipulation for combating cancer and age-related diseases.
Topic and keywords
Topic and keywords
CESSDA topic classification:
Swedish Standard Classification of Research Subjects 2025:
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