Archivos de la categoría immunity

Virtual Cell testing integrates bioinformatic alternatives to replace animal trials

Virtual Cell testing integrates bioinformatic alternatives to replace animal trials

 

Step into a world where scientific discovery doesn’t require animal testing opens up endless possibilities for ethical and innovative research. It may sounds like sci-fi, but today it is a feasible reality, where virtual cells can actually replace live animal testing.

Virtual cell testing is based on the data obtained from in vitro trials using cell lines, which enables the development of in silico prediction models. By leveraging in vitro experiments, one can gain a deeper understanding of the interactions between time, external stimuli, and compound concentration-dependent mechanisms, enabling the prediction of outcomes through computer models.

But how does this data is transformed into virtual predictions? How can we develop accurate prediction methods and learning algorithms?

Firstly, a large amount of in vitro experimental data must be incorporated into cutting-edge computer simulations to generate accurate virtual organisms. This integration enables the anticipation of the effects of various compounds and/or environmental conditions on cells, leading to significant advancements in preventing animal testing.

In vitro testing

Featured image: DNY59, iStock license.

Secondly, the ever-evolving advancements in biotechnology, including organ-on-a-chip technology, high-throughput screening experiments, multi-omics, and mathematical biology, facilitate the implementation of automatic learning algorithms. The incorporation these innovations not only provide a holistic view of an organism’s potential response to treatments. They can also be used to futher refine the prediction of outcomes.

Virtual Cell testing holds the potential to transform animal health and nutrition trials by accelerating research advancements.

The virtual cell is a promising approach to effectively reduce animal trial costs, enable comparisons of a greater number of treatments and conditions, and speed up the results. However, like any new technology, virtual cell testing also has drawbacks and limitations. These include the dependency on animal cell culture protocols and limited data availability across different species and organs.

To overcome these limitations, a vast amount of data derived from in vitro approaches needs to be leveraged in order to develop more robust in silico prediction models.

For instance, the availability of culture cell lines that retain several properties observed in live rainbow trout (Oncorhynchus mykiss), has facilitated deeper insights into the basic functions of the digestive tract and the effects of functional feed ingredients, host intestinal immune response, barrier function, digestion and complexity of intestinal microenvironment in this species.

Recent exciting news from the Swiss Aquatic Research Institute Eawag and the University of Utrecht has introduced the idea of a «virtual animal». This concept entails building a virtual test using in vitro data from fish gill cells by recollecting data from the major organs’ cells into a single computer model. So, by observing how toxic certain chemicals are to fish cells, researchers were able to build a computer model that enables the in silico prediction on how the chemical could affect a living fish.

Whereas more research is in progress to add to the test more important organs, such intestine and nervous system, the test based on rainbow trout gill cells has been already released by the OECD as the last guideline in the field of environmental toxicology.

Moreover, multi-omics techniques such as transcriptomics, proteomics and metabolomics, can be further explored to improve learning algorithms and prediction models. With extensive molecular databases and cell lines at our disposal, we are able to advance toward more humane and precise research practices, ultimately reducing our dependence on animal testing.

In conclusion, the virtual cell is an exciting journey into a new era of scientific innovation toward the application of the 3R principles (Replacement, Reduction, and Refinement) in animal experimentation.

 

3R principles in animal experimentation

Do you work in animal nutrition, health or reproduction? Are you thinking of developing in silico prediction model to study new feed effects on gut health and reproduction traits? Are you wondering how omics technologies can be further explored in vitro and in silico studies?

 

 

Reach out to us, and let’s bring your vision to reality!

In silico tools to boost shrimp farming

In silico tools to boost shrimp farming

 

In the past few months, we have been working a lot with the immunological responses of shrimps, and that is why we always have at hand the review of Fajardo & colleagues (2021)

We like it so much that we’d like to share some aspects of the review on our blog today, for customers who haven’t taken full advantage of their trials and challenges, or for omics enthusiasts like us  (the passionomics ☺).

Thanks to the progress made in the field of transcriptomic analysis through massive mRNA sequencing technology, currently exists a significant amount of data about the crustacean immune system.

The review showed shrimps’ genes and metabolic pathways associated with the immune system through the development of a meta-analysis. The researchers analyzed 1,195 transcriptomic data sets from 14 species from the Penaeus genus from the Sequence Read Archive (SRA) database of the National Center for Biotechnology Information (NCBI). 

The literature about these data sets explored how the shrimp’s immune response changes owing to challenges with pathogens, abiotic stressors (ammonia, temperature, salinity, oxygen deprivation, and pH), dietary factors, and beneficial microbes (pre-and probiotics).

Certainly, the in silico information from sequences’ database can be converted into commercial applications to boost shrimp farming, develop more sustainable feeds, and select more disease-resistant strains… But such a vast amount of information needs to be analyzed using multidisciplinary approaches and reliable data analysis tools.

This is particularly important in the so-called training immunology, a concept that has been studied in P. vannamei, P. monodon, P. japonicus, and Procambarus clarkia and that considers the effects of ‘vaccines’ on the memory of the innate immune system and in nutrigenomics, a new discipline that studies metabolic pathways to get better combinations of nutrients and optimize feeds.

Furthermore, NGS technology, which generated massive amounts of sequencing data, requires more computing capacity and more efficient software to produce accurate results, or the incorporation of algorithms based on artificial intelligence (AI) and machine learning, which can aid in the use of such large data sets by allowing the understanding of immune responses, for example.

At the same time, cloud-based services can also be useful since they can incorporate AI-based approaches to provide vast graphical processing units to support AI applications. This, in conjunction with next-generation AI pipelines, is introducing new algorithms to obtain predictive models, allowing researchers to design better tests and obtain better data to improve future iterations.

Finally, the review highlights the importance of unifying shrimp databases to establish ‘multi-omic’ pipelines to be used by industry and academia to develop tools that can be used to improve shrimp farming. 

Every day researchers advance more and more with complete genome assemblies, enabling the industry to have a better comprehension of genes’ function, but, can anyone manage all of this information alone?

 

Do your department need help? 

If you are interested in exploring training immunology, nutrigenomics or have a try with artificial intelligence and machine learning,

Contact us!

 

References:

Fajardo C, Martinez-Rodriguez G, Costas B, et al. Shrimp immune response: A transcriptomic perspective. Rev Aquac. 2022.

Roy S, Bossier P, Norouzitallab P, Vanrompay D. Trained immunity and perspectives for shrimp aquaculture. Rev Aquac. 2019;12(4):2351-2370. https://doi.org/10.1111/raq.12438 

Santos CA, Blanck DV, de Freitas PD. RNA-seq as a powerful tool for penaeid shrimp genetic progress. Front Genet. 2014;5:298.