Aby wyświetlić tę treść, wymagana jest subskrypcja JoVE. Zaloguj się lub rozpocznij bezpłatny okres próbny.
Method Article
This study involves methods to reveal effects on a model fish host following alteration of the skin and gut microbiome communities composition by an antibiotic.
The commonality of antibiotic usage in medicine means that understanding the resulting consequences to the host is vital. Antibiotics often decrease host microbiome community diversity and alter the microbial community composition. Many diseases such as antibiotic-associated enterocolitis, inflammatory bowel disease, and metabolic disorders have been linked to a disrupted microbiota. The complex interplay between host, microbiome, and antibiotics needs a tractable model for studying host-microbiome interactions. Our freshwater vertebrate fish serves as a useful model for investigating the universal aspects of mucosal microbiome structure and function as well as analyzing consequential host effects from altering the microbial community. Methods include host challenges such as infection by a known fish pathogen, exposure to fecal or soil microbes, osmotic stress, nitrate toxicity, growth analysis, and measurement of gut motility. These techniques demonstrate a flexible and useful model system for rapid determination of host phenotypes.
It has been established that antibiotics can disrupt the human microbiome leading to dysbiosis, meaning a microbial community imbalance. The microbiota's compositional alteration after antibiotic treatments has been shown to lower the community's diversity, reduce key members, and alter community metabolism, especially in the gut1,2. Antibiotic disturbance of the gut microbiome can reduce colonization resistance to Clostridium difficile3,4 and Salmonella5.
Additionally, the disruption of the microbiota has been linked to the development of many syndromes and diseases in humans (e.g., antibiotic-associated enterocolitis, inflammatory bowel disease, metabolic disorders, etc.). Antibiotics are also widely implemented in agriculture as growth promoters in livestock and poultry production6. The usage of these powerful tools is not without collateral effects, which is evident in the rapid rise of antibiotic resistance, as well as the effects of a disrupted microbiome has with its inhabited host. Many studies have shown that broad-spectrum antibiotic usage has long lasting consequences to the structure and function of the microbiota, yet the side effects from an antibiotic-disrupted microbiome impacting host physiology are only speculations which have yet to be supported.
The interplay between host, microbiota, and antibiotics is far from being understood in a concise manner. Therefore, a simple and more tractable model is advantageous to shedding light on the highly complex mammalian system. Mucosal surfaces in humans, including the gut, harbor the highest density and diversity of microbes, and also the most intimate microbe-host interactions. The mucosal skin microbiome of fish offers several advantages as a model system. The Teleostei (bony fish) is one of the earliest lineages to diverge within the Vertebrata meaning that teleosts have both innate and acquired immune systems that have co-evolved a relationship with commensal bacterial communities7. Fish skin shares many characteristics with type 1 mucosal surfaces of mammals, such as physiological functions, immunity components, and arrangement of mucus-producing cells8. The external location of the fish skin mucosal surface offers a microbiome easy to experimentally manipulate and sample.
The Western mosquitofish, Gambusia affinis (G. affinis), is a model fish that has been used in the past for studying mating and toxicology9,10,11. Given the small size, population abundance in the wild as an invasive species, minimal care cost, and hardy nature, we have developed G. affinis as a mucosal microbiome model. Further, Gambusia share the physiology of giving birth to live young with viviparous mammals, which is uncommon in fish species. We completed the most extensive study at the time of fish skin normal microbiota using 16S profiling with Gambusia12. Further work demonstrated three negative effects on the host following disruption of the skin and gut microbiota using a broad-spectrum antibiotic13.
Five different effects were examined in the fish following antibiotic exposure. The most well established host benefit of the microbiome is competitive exclusion of pathogens. The fish pathogen Edwardsiella ictaluri is known to cause outbreaks of enteric septicemia in commercial catfish farms14. E. ictaluri has also been shown to lethally infect zebrafish15,16 and Gambusia17. A challenge with this pathogen from the water column can serve as a measure of exclusion. As a comparison to susceptibility to an individual pathogen, survival during exposure to a high density of mixed organisms was also carried out. Feces and organic-rich soil were used as commonly-encountered sources of microbial communities.
Another established role the bacterial gut community performs is nutrient processing and energy harvest, thus affecting the overall nutritional uptake for the host. As a gross measurement of nutrition, fish body weight was compared before and after one month of being fed a standard diet. Antibiotic-treated fish as an average lost weight while control fish on average gained weight over the month. The mechanism for this lack of weight gain is unclear. One possible contributing factor is transit time of food in the gut. A GI motility method was adapted from zebrafish (Adam Rich, SUNY Brockport, personal communication) to determine transit time. It has not yet been determined if antibiotic-treated fish have an altered transit time.
A common challenge experienced in the natural environment by all organisms, especially fish, is osmotic stress. Gambusia have been shown to quickly adapt when acutely stressed in high concentrations of salinity18. Surprisingly, fish with an antibiotic-altered microbiome exhibited lowered survival to a high salt stress. The mechanism for this novel phenotype is under investigation. Another common stress on aquatic animals, especially in aquaria, is toxic forms of nitrogen (ammonia, nitrate, and nitrite). Survival against nitrate was not significantly different between antibiotic-treated and control fish. The methods presented in this manuscript can be used with Gambusia or similar fish model organisms, such as zebrafish and medaka, to measure phenotypes in the fish following experimental manipulation.
All animal experiments were conducted under approval of IACUC protocols, numbered 14-05-05-1018-3-01, 13-04-29-1018-3-01, and 14-04-17-1018-3-01.
1. Animal Collection, Handling, and Ethical Care
2. Initial Antibiotic Exposure for All Experiments
3. Microbiome Extraction
4. Infection Model Preparation and Bath of a Specific Pathogen
5. Polymicrobial Challenge with Feces & Soil
6. Osmotic Stress Challenge
7. Nitrate Toxicity Challenge
8. Growth Analysis of Individualized or Grouped Fish
9. Gut Transit Time
An overall schematic diagram of the experimental system used to study fish host effects from antibiotic exposure13 is represented in Figure 1A and includes the technique for extracting the skin (Figure 1B) and gut (Figure 1C) microbiomes from the fish. Three days was selected as the antibiotic period of exposure because previous data reveals that while the total skin culturable number drops early in treatment, it h...
Some challenges require a rest period in clean APW after antibiotic treatment for the drug to be depleted in fish tissues. If the rest period is skipped then antibiotic presence can confound the results, especially when the assay involves exposure to bacteria. In order to examine effects from an altered microbiome composition without large changes in the total number of microbes on the host, preliminary experiments monitoring microbiome composition (16S profiling or whole genome sequencing) and population density (16S qu...
The authors have nothing to disclose.
This project was partially funded by a FAST (Faculty and Student Team) Award to TPP and JMC from EURECA (Center for Enhancing Undergraduate Research Experiences and Creative Activities) at Sam Houston State University.
Name | Company | Catalog Number | Comments |
Rifampicin | Calbiochem | 557303-1GM | |
Sodium Nitrate | Sigma Aldrich | S5506 | |
Fluorescein-labeled 70 kDa anionic dextran | ThermoFisher Scientific | D1823 | |
Phosphate-buffered Saline (PBS) tablets | Calbiochem | 6500-OP | tablets dissolve in water to make PBS |
Zapytaj o uprawnienia na użycie tekstu lub obrazów z tego artykułu JoVE
Zapytaj o uprawnieniaThis article has been published
Video Coming Soon
Copyright © 2025 MyJoVE Corporation. Wszelkie prawa zastrzeżone