| Literature DB >> 34241667 |
Ho-Keun Kwon1, Je Kyung Seong2,3,4.
Abstract
Laboratory mice have long been an invaluable tool in biomedical science and have made significant contributions in research into life-threatening diseases. However, the translation of research results from mice to humans often proves difficult due to the incomplete nature of laboratory animal-based research. Hence, there is increasing demand for complementary methods or alternatives to laboratory mice that can better mimic human physiological traits and potentially bridge the translational research gap. Under these circumstances, the natural/naturalized mice including "wild", "dirty", "wildling", and "wilded" systems have been found to better reflect some aspects of human pathophysiology. Here, we discuss the pros and cons of the laboratory mouse system and contemplate how wild mice and wild microbiota are able to help in refining such systems to better mimic the real-world situation and contribute to more productive translational research.Entities:
Mesh:
Year: 2021 PMID: 34241667 PMCID: PMC8295133 DOI: 10.1007/s00335-021-09887-z
Source DB: PubMed Journal: Mamm Genome ISSN: 0938-8990 Impact factor: 2.957
Distinct features of the wild immune system
| Numbers | Species | Source of animals | Tissues | Major findings | Assays | References |
|---|---|---|---|---|---|---|
| 1 | Central Oklahoma (USA) | Blood | -Increased primary immunoresponsiveness to SRBC | Splenic plaque-forming cell assay | Lochmiller RL et al. ( | |
| 2 | Bristol (UK) | Blood, spleen | -Enhanced antibody production against keyhole limpet hemocyanin (KLH) immunization -Overall activation status of immune cells (T cells, B cells, DCs, and Macrophage) | KLH immunization and flow cytometric (FACs) analysis | Abolins SR et al. ( | |
| 3 | southeastern Norway | Spleen | -Primed status of NK cells (Increase of CD69, KLRG1, GRAZYME B, IFNγ and NKp46 expression, and CD27+CD11b−population) | FACs analysis | Boysen P et al. ( | |
| 4 | Minnesota and Georgia (USA) | Blood, spleen | -Primed status of CD8+ T cells (increase of CD44+CD62L− T cells) | Serological, FACs, and RNAseq analysis | Beura LK et al. ( | |
| 5 | Bristol and Stroud (UK) | Blood, spleen | -Higher level of serum Proteins (IgG, IgE, SAP, Haptoglobin) -Highly primed state of overall immune population (CD44+CD62− T cells, CD27+CD11b− NK cells) | Serological and FACs analysis | Abolins S et al. ( | |
| 6 | Maryland and Columbia (USA) | Blood, spleen, liver, vagina, skin, and gut | -Enrichment of immune responses/activation signature in PBMC | CyTOF and RNAseq analysis | Lavrinienko A et al. ( |
Distinct features of the wild microbiome
| Numbers | Species | Source of animals | Source of bacteria | Major findings | Assays | Reference |
|---|---|---|---|---|---|---|
| 1 | Cologne/Bonn and Schömberg/Langenbrand (Germany) Severac le Château, Espelette, Angers, Nancy, Louan‐Villegruis and Divonne les Bains (France) | Gut | Dominant genera (Bacteroides, Robinsoniella, and Helicobacter) Geography: key determining factor for the patterns of microbial diversity | 16S rRNA sequencing | Linnenbrink M et al. ( | |
| 2 | Gloucestershire, Bristol, London (UK) | Gut | Geography: the key determining factor for microbial diversity and composition Correlation of microbial diversity with host's weight, leptin, parasite, and virus level | 16S rRNA sequencing | Weldon L et al. ( | |
| 3 | Tucson (USA) | GI tract contents | Different microbial composition between upper and lower GI tract | 16S rRNA sequencing, Spatial bacteria composition analysis along GI tract | Suzuki and Nachman ( | |
| 4 | Minnesota and Georgia (USA) | Gut | Immune prime by co-housing in inbred mice High level of viral/fungal/worm infection in wild/pet-store mice | Infectious agent screening, Co-housing | Beura LK et al. ( | |
| 5 | Maryland and Columbia (USA) | Gut | Higher diversity/complexity of wild microbiome Enhancing host fitness to Influenza infection and colitis-associated tumorigenesis | Shotgun metagenome sequencing, 16S rRNA sequencing, FMT | Rosshart SP et al. ( | |
| 6 | New York City (USA) | Gut | Carrying gastrointestinal disease-causing microbials (Shigella, Salmonella, Clostridium difficile, and diarrheagenic Escherichia coli) Enrichment of antimicrobial resistance genes | 16S rRNA sequencing, antimicrobial resistance test | Williams SH et al. ( | |
| 7 | Chernobyl Exclusion Zone and Kyiv (Ukraine) | Gut and skin | Geography: key determining factor for skin microbiome Radioactive contamination: key determining factor for gut microbiome | 16S rRNA sequencing | Lavrinienko A et al. ( | |
| 8 | Maryland and Columbia (USA) | Gut, skin, and vagina | Higher diversity/complexity (virome and mycobiome) Resilience to environmental challenge (high fat diet, antibiotics treatment, co-housing) Assigning human-like traits (CD28 super-agonist or anti-TNFα treatment) | Shotgun metagenomic sequencing, 16S rRNA sequencing, Mycobiome sequencing, Virome sequencing, Pathogen screening, High fat diet, antibiotics treatment, and co-housing | Rosshart SP et al. ( | |
| 9 | Chuncheon (Korea) | Gut | Different microbial composition between High prevalence of Campylobacter in microbiota of | 16S rRNA sequencing | Song H et al. ( |