» Articles » PMID: 35006075

Comparative Transcriptomic Analysis Reveals Translationally Relevant Processes in Mouse Models of Malaria

Overview
Journal Elife
Specialty Biology
Date 2022 Jan 10
PMID 35006075
Authors
Affiliations
Soon will be listed here.
Abstract

Recent initiatives to improve translation of findings from animal models to human disease have focussed on reproducibility but quantifying the relevance of animal models remains a challenge. Here, we use comparative transcriptomics of blood to evaluate the systemic host response and its concordance between humans with different clinical manifestations of malaria and five commonly used mouse models. 17XL infection of mice most closely reproduces the profile of gene expression changes seen in the major human severe malaria syndromes, accompanied by high parasite biomass, severe anemia, hyperlactatemia, and cerebral microvascular pathology. However, there is also considerable discordance of changes in gene expression between the different host species and across all models, indicating that the relevance of biological mechanisms of interest in each model should be assessed before conducting experiments. These data will aid the selection of appropriate models for translational malaria research, and the approach is generalizable to other disease models.

Citing Articles

A single workflow for multi-species blood transcriptomics.

Orcel E, Hage H, Taha M, Boucher N, Chautard E, Courtois V BMC Genomics. 2024; 25(1):282.

PMID: 38493105 PMC: 10944614. DOI: 10.1186/s12864-024-10208-2.


Gene expression analyses reveal differences in children's response to malaria according to their age.

Tebben K, Yirampo S, Coulibaly D, Kone A, Laurens M, Stucke E Nat Commun. 2024; 15(1):2021.

PMID: 38448421 PMC: 10918175. DOI: 10.1038/s41467-024-46416-3.


The malarial blood transcriptome: translational applications.

Dunican C, Andradi-Brown C, Ebmeier S, Georgiadou A, Cunnington A Biochem Soc Trans. 2024; 52(2):651-660.

PMID: 38421063 PMC: 11088907. DOI: 10.1042/BST20230497.


Gene expression analyses reveal differences in children's response to malaria according to their age.

Tebben K, Yirampo S, Coulibaly D, Kone A, Laurens M, Stucke E bioRxiv. 2023; .

PMID: 37961701 PMC: 10634788. DOI: 10.1101/2023.10.24.563751.


Pathogenetic mechanisms and treatment targets in cerebral malaria.

Hadjilaou A, Brandi J, Riehn M, Friese M, Jacobs T Nat Rev Neurol. 2023; 19(11):688-709.

PMID: 37857843 DOI: 10.1038/s41582-023-00881-4.


References
1.
Mestas J, Hughes C . Of mice and not men: differences between mouse and human immunology. J Immunol. 2004; 172(5):2731-8. DOI: 10.4049/jimmunol.172.5.2731. View

2.
Aitken E, Alemu A, Rogerson S . Neutrophils and Malaria. Front Immunol. 2019; 9:3005. PMC: 6306064. DOI: 10.3389/fimmu.2018.03005. View

3.
Okiro E, Al-Taiar A, Reyburn H, Idro R, Berkley J, Snow R . Age patterns of severe paediatric malaria and their relationship to Plasmodium falciparum transmission intensity. Malar J. 2009; 8:4. PMC: 2630996. DOI: 10.1186/1475-2875-8-4. View

4.
Anders S, Pyl P, Huber W . HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 2014; 31(2):166-9. PMC: 4287950. DOI: 10.1093/bioinformatics/btu638. View

5.
Moxon C, Gibbins M, McGuinness D, Milner Jr D, Marti M . New Insights into Malaria Pathogenesis. Annu Rev Pathol. 2019; 15:315-343. DOI: 10.1146/annurev-pathmechdis-012419-032640. View