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Metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon)

Metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon)

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By: Aquaculture Magazine Editorial Team*

The importance of the size of white leg shrimp has been previously reported, where a strong correlation was found between size and metabolome data. Here we present a metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon).

The advancement of technology in aquaculture industries has increased the sense of urgency to re-evaluate the quality parameters of commercial shrimp products. Several studies have emphasized the improvement in production at the upstream level (shrimp cultivation), including the optimization of environmental water quality parameters and shrimp disease management.

However, publications focusing on the downstream level are still lacking, particularly in the effort to connect the quality of commercial shrimp to its economic aspect.

Currently, shrimp body weight is utilized as a grading unit, which is known to affect prices in the market. Count size, a unit that is commonly used to sell headless shell-on (HLSO), indicates the edible portion of shrimp. To obtain shrimps in large commercial sizes, shrimp farmers often have to perform partial harvesting or to prolong the period of culture.

Metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon)

These practices pose them to a higher risk of loss. For this reason, the count size grading unit not only implies the needed operational cost, but also reflects the quality of the management of the farming and aquaculture systems. From a consumer perspective, a large size is perceived as highly palatable and attractive.

In addition, large size has been associated with product value, creating a so-called value-based pricing system while the quality remains questionable. Therefore, there is a need to justify whether size reflects the quality of shrimp.

The importance of the size of white leg shrimp has been previously reported, where a strong correlation was found between size and metabolome data. In this study, the researchers aimed to improve the predictive power of the orthogonal projection to latent structure (OPLS) model by expanding the metabolite coverage using liquid chromatography mass-spectrometry (LC/MS) and gas chromatography-mass spectrometry (GC/MS) analysis.

Materials and methods

Two different species of farmed shrimp were analyzed: white leg shrimp and black tiger shrimp. All samples were collected as head-less shell-on (HLSO) shrimp. The range of shrimp count size was determined according to the availability of samples on the day of purchase.

The sample extraction step for GC/MS analysis was change to improve the removal of protein and prevent saturated peak as the potential damage to the machine in the long term. The optimized extraction method was carried out in a stepwise manner using 80% ethanol. All samples were analyzed in triplicate (n ¼ 3). GC/MS analysis and LC/MS/MS analysis were performed.

Results and Discussion

Metabolite profile of white leg shrimp retrieved from the same pond

In total, 118 metabolites were putatively annotated from both instruments, of which 39 and 59 metabolites were unique to GC/MS and LC/MS ion pairs, respectively. The first two principal components, which accounted for 47.3% of the variance, were able single out the smaller shrimps (count size 41/50) from the other larger samples (count size 31/40-21/25).

This result confirmed the reproducibility of the metabolite trend reported in the previous study. From the loading plot count sizes of 31/40 and 26/30 resulted in a higher level of phosphate and phosphate-related compounds, such as nucleotides and sugar phosphates.

“Previous GC/ MS-based analysis were only able to detect phosphate in large white leg shrimp. Therefore, this result suggests that the phosphate-related metabolites such as nucleotides, nucleosides, and sugar phosphate derived from LC/MS corresponded with the phosphate detected by GC/MS.”

This result shows that a reproducible metabolite trend can be achieved even in a larger data set. Following this, OPLS analysis was performed after excluding samples with an overlapped-body weight.

Validation of the size-based prediction OPLS regression model

We aimed to further validate the robustness of the prediction model using the expanded metabolites. In this current model (Figure 1), the model was built from all Indonesian shrimp samples. The estimated parameters were then used to predict the sample purchased from commercial market.

Metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon)

The constructed OPLS model complied with the parameters, and therefore, a robust size-based prediction model was obtained. This result marked the accomplishment of the first objective, in which the robustness of the model improved through the expansion of metabolite coverage.

Although a further study is required, we hypothesize that the accumulation of AMP and IMP along with the increase in size might be indicative of reduced purine catabolism, as a strategy to preserve adenine nucleotide pools that might be linked to the recovery of high-energy phosphate.

“The positive and negative predictors metabolites were able to characterize the shrimp based on the size.”

Therefore, VIP metabolites that exhibit specific accumulation patterns over the size of shrimp can be defined as size-dependent metabolites as they show a constant trend despite variations in sampling locations, origin, and shrimp processing.

Validation of the OPLS model using black tiger shrimp

The second validation was performed to assess the robustness of the constructed model in a non-species-specific manner. As we aimed to provide a universal metabolite marker of shrimp size, the resulting model could be a promising tool to further justify the overall quality of commercial shrimp with regard to market price. The second most economic important shrimp species in the aquaculture industry, black tiger shrimp, was used in a second validation set.

Although the effect of species was plausible, both of the large shrimp species exhibited similar metabolite profiles with higher accumulation of phosphate-related compounds, which has been reported for white leg shrimp. Using this information as a basis, black tiger shrimp was further subjected to a validation set with the white leg shrimp dataset assigned as a training set.

OPLS model of commercial tropical penaeid shrimps

A size-based prediction model for commercial shrimp and its evaluation parameters are summarized in Figure 2.

Metabolomics approach to elucidate the importance of count size in commercial penaeid shrimps: white leg shrimp (Litopenaeus vannamei) and black tiger shrimp (Penaeus monodon)

Good linearity was observed in the model as the R2Y and Q2 scores were higher than 0.8. However, the RMSEE and RMSEP scores were 1.835 and 7.216, respectively, suggesting that the difference between the observed and predicted values was larger than 10%. A high RMSEP score indicated that the training set built from white leg shrimp metabolome data failed to predict commercial black tiger shrimps (count size 31/40-13/15), as they were all predicted as a single value (Figure 2b).

“A robust sized-based OPLS model of white leg shrimp, which was validated using a set of commercial white leg shrimp purchased from the market, was successfully constructed (Figure 1).”

The expansion of metabolite coverage using the LC/MS ion pair enabled us to carry out a more comprehensive discussion that could not be achieved using GC/MS data.

However, the second validation of the OPLS model performed using commercial black tiger shrimp failed to predict the size of shrimp (Figure 2).

The importance of size in relation to the metabolome profile was identified to be species specific. However, other factors might explain the metabolome changes in black tiger shrimp.

Conclusion

It is suggested that a count size of 31/40 is most suitable for commercial farms based on visual palatability, time, and production cost. Consistently, a count size of 31/40 was reported to be highly produced by exporting countries.

According to the metabolic profile, most of the tasteactive metabolites were retained in medium-sized shrimp with a higher accumulation of IMP and AMP, as umami-contributing metabolites might reflect higher acceptability.

This study is a part of a bigger research framework that pursues the development of novel parameters to evaluate shrimp quality. One strategy is to investigate the metabolite markers of various commercial shrimp sizes that come at different prices.

Through a strong correlation between shrimp size and metabolome data, we can expect the accumulation of size-dependent metabolites within a specified commercial size range.

These size-dependent metabolites not only serve as a potential marker to assess the quality of shrimp, but also help the shrimp farmers to improve the cultivation strategy in producing commercial-sized shrimps.

This is a summarized version developed by the editorial team of Aquaculture Magazine based on the review article titled “METABOLOMICS APPROACH TO ELUCIDATE THE IMPORTANCE OF COUNT SIZE IN COMMERCIAL PENAEID SHRIMPS: WHITE LEG SHRIMP (LITOPENAEUS VANNAMEI) AND BLACK TIGER SHRIMP (PENAEUS MONODON)” developed by: ERLANGGA PUTRI, S. – Osaka University; SUANTIKA, G. and LENNY SITUMORANG, M. – Institut Teknologi Bandung; PRAMA PUTRI, S. – Osaka University; FUKUSAKI, E. – Osaka University and Institut Teknologi Bandung.
The original article was published, including tables and figures, on MARCH, 2022, through JOURNAL OF BIOSCIENCE AND BIOENGINEERING.
The full version can be accessed online through this link: https://doi.org/10.1016/j.jbiosc.2022.01.010.

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