ABSTRACT
Here, we analyzed the fast-twitch muscle of juvenile Piaractus mesopotamicus (pacu) submitted to prolonged fasting (30d) and refeeding (6h, 24h, 48h and 30d). We measured the relative rate of weight and length increase (RRIlength and RRIweight), performed shotgun proteomic analysis and did Western blotting for PVALB after 30d of fasting and 30d of refeeding. We assessed the gene expression of igf-1, mafbx and pvalb after 30d of fasting and after 6h, 24h, 48h and 30d of refeeding. We performed a bioinformatic analysis to predict miRNAs that possibly control parvalbumin expression. After fasting, RRIlength, RRIweight and igf-1 expression decreased, while the mafbx expression increased, which suggest that prolonged fasting caused muscle atrophy. After 6h and 24h of refeeding, mafbx was not changed and igf-1 was downregulated, while after 48h of refeeding mafbx was downregulated and igf-1 was not changed. After 30d of refeeding, RRIlength and RRIweight were increased and igf-1 and mafbx expression were not changed. Proteomic analysis identified 99 proteins after 30d of fasting and 71 proteins after 30d of refeeding, of which 23 and 17, respectively, were differentially expressed. Most of these differentially expressed proteins were related to cytoskeleton, muscle contraction, and metabolism. Among these, parvalbumin (PVALB) was selected for further validation. The analysis showed that pvalb mRNA was downregulated after 6h and 24h of refeeding, but was not changed after 30d of fasting or 48h and 30d of refeeding. The Western blotting confirmed that PVALB protein was downregulated after 30d of fasting and 30d of refeeding. The downregulation of the protein and the unchanged expression of the mRNA after 30d of fasting and 30d of refeeding suggest a post-transcriptional regulation of PVALB. Our miRNA analysis predicted 444 unique miRNAs that may target pvalb. In conclusion, muscle atrophy and partial compensatory growth caused by prolonged fasting followed by refeeding affected the muscle proteome and PVALB expression.
Subject(s)
Characiformes/metabolism , Fish Proteins/biosynthesis , Gene Expression Regulation/physiology , Muscle Fibers, Fast-Twitch/metabolism , Parvalbumins/biosynthesis , Proteome/biosynthesis , AnimalsABSTRACT
Protocols that improve growth performance in fish while assuring product quality are important for aquaculture. Fasting followed by refeeding may promote compensatory growth, thus optimizing growth performance. During fasting and refeeding, fast-twitch muscle, which comprises most of fish fillet, undergoes intense plasticity. In this work, we studied the proteome of pacu (Piaractus mesopotamicus) fast-twitch muscle after 30â¯days of fasting (D30), 30â¯days of refeeding (D60) and 60â¯days of refeeding (D90) with two-dimensional electrophoresis, mass spectrometry and bioinformatics. Body mass, growth rate and muscle histology were also assessed. At D30, fish presented muscle catabolism and decreased growth. Proteomic analysis showed that metabolism proteins were the most affected, up and downregulated. Cytoskeleton and amino acid biosynthesis proteins were downregulated, while nuclear and regulatory proteins were upregulated. At D60, fish showed accelerated growth, despite the body mass not completely recovering. Metabolism proteins were still the most affected. Amino acid biosynthesis proteins became upregulated, while cytoskeleton proteins remained downregulated. At D90, the fish presented total compensatory growth. Many metabolic proteins were up or downregulated. Few cytoskeleton proteins remained differentially expressed. Amino acid biosynthesis proteins were mostly upregulated, but less than at D60. Prolonged fasting followed by refeeding also led to the regulation of possible meat quality biomarkers, such as antioxidant enzymes. This fact suggests possible consequences of this protocol on fish meat quality. Our work also enriches our knowledge on proteomic changes during muscle plasticity that occur during fasting and refeeding diet protocols.
Subject(s)
Characiformes/growth & development , Fish Proteins/metabolism , Muscle, Skeletal/growth & development , Animal Feed/analysis , Animal Nutritional Physiological Phenomena , Animals , Aquaculture , Characiformes/physiology , Fasting , Muscle, Skeletal/physiology , ProteomicsABSTRACT
BACKGROUND: Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. METHODS: Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. RESULTS: Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. CONCLUSION: The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.