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!

The Potential of Hi-c Sequencing for Unlocking Plasmid-Bacteria Host Interactions in Animal Health Research

The Game-Changing Potential of Hi-c Sequencing for Unlocking Plasmid-Bacteria Host Interactions in Animal Health Research


At DataOmics, we are always eager to learn about new technologies and techniques in bioinformatics with application to animal science. That’s why we are thrilled to explore the potential of Hi-c sequencing applications in microbiome and animal health research.

So, if you are interested in applying the latest and most creative solutions to develop more effective strategies for promoting animal health, we invite you to join us and learn more about Hi-C sequencing and its benefits.

Hi-C sequencing combines Chromosome Conformation Capture (3C) technology with next-generation sequencing (NGS) to study the three-dimensional structure of chromosomes. This method gives a detailed and extensive view at how genes interact throughout the whole genome, allowing researchers to understand the importance of genome organization on various levels for different organisms and cell types.

One of the most promising applications of Hi-C sequencing is elucidating plasmid-bacteria host interactions. This method explores the cross-links between plasmid genes (and other elements)  and their host bacteria and how these interactions affect genetic processes such as gene regulation and expression.

Plasmids are mobile genetic elements that can carry not only genes related to beneficial traits but also antibiotic resistance genes among others, which are particularly relevant to animal health.  Therefore, as a practical example, the Hi-c proximity-ligation method can helps us recognize the bacterial hosts more likely to carry antibiotic resistance genes and track how these genes spread among bacterial populations.

Moreover, the Hi-c chromatin-level contact probability maps can also be used to reconstruct the individual genomes of microbial species obtained from metagenomic shotgun sequencing. Hi-C data provides intracellular contiguity information and contains both intrachromosomal and interchromosomal data, making it a powerful tool for species-level deconvolution of microbiota that inhabits an animal gut.

Featured figure adapted from Maximiliam et al. 2017: copyright available under a CC-BY-NC-ND 4.0 International license. Closer look at the chromatin-level DNA cross-links, e.g. plasmid genes and bacteria chromosome (red highlighted), in a microbiota metagenome and sequencing linkages between DNA contigs or scaffolds are used to deconvolute DNAs derived from the same organisms.

Featured figure adapted from Maximiliam et al. 2017: copyright available under a CC-BY-NC-ND 4.0 International license. Closer look at the chromatin-level DNA cross-links, e.g. plasmid genes and bacteria chromosome (red highlighted), in a microbiota metagenome and sequencing linkages between DNA contigs or scaffolds are used to deconvolute DNAs derived from the same organisms.

But not only that; Hi-C sequencing combined with long-read sequencing holds the potential to improve De novo genome assembly for species without a high-quality reference genome. For instance, it can be particularly useful in aquaculture R&D, as demonstrated by recent studies. The potential of incorporating Hi-c data to perform De novo assemblies was successfully exemplified by the high-quality genome assemblies of Trachidermus fasciatue and Pelteobagrus vachelli genomes.


Additionally, ultra-long-range Hi-c chromatin interaction data used by a phasing tool enables the generation of haplotype-resolved genome assemblies. It works as an alternative to other complex and unfeasible protocols, such as cultured cells that contain a single-haplotype (haploid) genome, single cells where haplotypes are separated, or co-sequencing of parental genomes in a trio-based approaches.

There is no doubt that Hi-c sequencing is a game-changing technology with a broad range of applications. It is specially true in the genomic research of non-model species and exploring the effect of feeds and additives on animal gut microbiota and health.

Although Hi-c data can be highly complex and require careful experimental design, appropriate data processing, and bioinformatic analysis, DataOmics team has experience working with Hi-c sequencing data and can provide the necessary computational resources and bioinformatics services to handle the demanding nature of this technology.


If you’re interested in Hi-C technology, DataOmics experts can help your team overcome these challenges and make the most of this groundbreaking technology for your research.


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Can aquafeeds be specifically designed to induce desirable epigenetic modifications?

Can aquafeeds be specifically designed to induce desirable epigenetic modifications?


The year 2023 has started and we are enthusiastically about new projects that always spark our curiosity to learn more!

Today, we want to share a fascinating and hot topic: the intricate relationship between epigenetics and nutritional programming, and how they can have significant, life-long and, in some cases, intergenerational effects on animal health and productivity.

First of all, let’s explain what epigenetics is. Epigenetics refers to the regulation of gene expression through modifications to the epi-genome, i.e. without changing DNA sequence. When we think about gene dynamics, we have to think of epigenetic modifications as switches, like lights. As switches can turn the lights dimmer or brighter, epigenetic modifications can turn gene expression up or down, which may result in variations in physical or fitness traits.

Epigenetic modifications can arise from exposure to environmental factors such as diet, toxins, stress, and disease, and they can have significant impacts on an organism’s traits and health. At the cellular level, it is achieved through histone modifications, DNA methylation, and through the interaction of DNA with noncoding RNAs such as miRNA or regulatory elements (e.g. enhancers, promoters and transcription factors).

Featured image: Thiago Petagna, Pexels license.

One of the most powerful environmental factors that affects performance and health traits in farmed fish is the diet. Changes in feed ingredients can result in alterations to DNA methylation which in turn improves certain traits. For instance, Saito and colleagues (2021) showed that micronutrients in the feed can directly affect the epigenome of farmed salmon in a dose-dependent manner, in particularly the regulation of genes related to lipid metabolism.

Adam and colleagues (2022) showed that feed given at the pre-smolt stage may introduce life-long changes in epigenetic profiles, potentially improving post-molt growth. This study highlights the possibility of early nutritional programming to improve long-term performance. 

It also has been reported that the environmental alterations in broodstock spawning season play a crucial role in fine-tuning the epigenetic modifications that influence the nutrient status of the next generation via nutritional and metabolic programming.

Even if fish are fed a nutritional balanced diet, changes in abiotic factors will alter the nutritional status in tissues and organs which can direct future programming with intergenerational epigenetic and phenotypic consequences in mature offspring. The research also revealed that the epigenetic modifications in male DNA in gonadal tissue are highly sensitive to nutritional factors.

Factors such as maternal nutrition, feeding regimes, nutrient status, temperature, and light must be controlled to fine-tune the epigenetic tags in the offspring to achieve specific desired traits or prevent undesirable phenotypes regarding the nutrient composition of the egg.

In summary, epigenetic has become a hot research topic in animal nutrition, genetics and breeding due to its great potential to positively induce disease resistance, stress tolerance and attain better sex ratios in the aquatic organism though changes in farming environment.

By understanding the environmental factors that impact major epigenetic mechanisms, we can harness this knowledge to create more favorable phenotypes in farmed fish and shellfish in aquaculture.

Although the study of epigenetics in aquaculture species is still in its early stages, it holds tremendous potential for the future. Despite the many questions that remain unanswered, the research in this field should be prioritized. It may play a significant role in the future of aquaculture through epigenetic programing by fostering better coordination between feeds producers and hatcheries.

Are you ready to discover boundless potential of epigenetics in the future of aquaculture? We are here to offer you the best advice about this topic.

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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,

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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. 

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


DataOmics on Aquafeed!

DataOmics on Aquafeed


We are very excited to share in our blog some results from our collaboration with Adisseo. A study about the health-promoting properties of Sanacore® GM in farmed seabream has been included in the latest Aquafeed Vol 14 Issue 4 2022.

Feed manufacturers and fish farmers are aware of the importance of health-promoting additives to prevent diseases in aquaculture and maintain successful production. But, are the mechanisms that are responsible for the diminution of the infection known to them?

Genomics, metabolomics, and proteomics, ‘Omics’ as we love to call them at DataOmics, can facilitate the characterization and quantification of millions of biological molecules. The genes’ expression and their interaction with them and with other molecules can define the immunocompetence and healthy status of a fish. 


Similarly, the response to diseases, stress and even nutritional challenges can be explored in-depth through the detection and quantification of proteins, including the characterization of their metabolic pathways and interaction patterns. 


Understanding such complex relationships can help identify what happens in the fish under specific conditions. This knowledge can be used to develop more suitable health-promoting products to improve fish health status and productive performance. 


At DataOmics, we performed shotgun proteomics for Adisseo, to better understand the health-promoting properties of Sanacore® GM in gilthead seabream and recollect accurate information about the physiological status of three key tissues of fish health and performance: the anterior intestine, liver, and head kidney.


The proteomics analysis carried out by DataOmics provided a snapshot into the mechanisms of action of Sanacore® GM in gilthead seabream under healthy conditions. We shed light on how Sanacore® GM could improve fish’s ability to ward off illnesses through the modulation of almost 1.500 proteins across the head-kidney, intestine, and liver.


We observed modifications in the level of proteins that participate in important immune functions that are relevant to interconnected mechanisms within innate and acquire immunity. By the shotgun proteomics performed at DataOmics, Adisseo demonstrated that Sanacore® GM seabream supplementation stimulates proteins linked with integrity and immune response in the intestine and impacted proteins linked with innate and acquired immunity in the liver offering an optimal degree of protection to the fish.


Furthermore, we observed the highest number of altered proteins abundances in the head-kidney in fish-fed Sanacore® GM evidencing the regulation of innate immunity mechanisms such as the destruction of damaged or infected cells via apoptosis and the inhibition of pro-inflammatory cytokines. By the shotgun proteomics performed at DataOmics, Adisseo also demonstrated that Sanacore® GM could enable the elimination of injured cells being a useful resource to restore immunocompetence and support fish in dealing with production conditions. 


You find these results stimulating! Don’t you? 


And what do you think about the potential of ‘Omics? Can they be useful in your research?

If you are interested in exploring all the pluses that genomics, metabolomics, and proteomics can bring to your research do not waste time and contact us!



Proteomics to gain insight into the mechanism of action of a health-promoting additive. Rayner Gonzalez-Prendes, Carla Dos Anjos de Souza, DataOmics, Waldo G. Nuñez-Ortín, Adisseo.