Tonsils of the soft palate do not mediate the response of pigs to oral vaccination with heat-inactivated Mycobacterium bovis

Mycobacterium bovis causes animal tuberculosis (TB) in cattle, humans, and other mammalian species, including pigs. The goal of this study was to experimentally assess the responses of pigs with and without a history of tonsillectomy to oral vaccination with heat-inactivated M. bovis and challenge with a virulent M. bovis field strain, to compare pig and wild boar responses using the same vaccination model as previously used in the Eurasian wild boar (Sus scrofa), to evaluate the use of several enzyme-linked immunosorbent assays (ELISAs) and lateral flow tests for in vivo TB diagnosis in pigs, and to verify if these tests are influenced by oral vaccination with inactivated M. bovis. At necropsy, the lesion and culture scores were 20% to 43% higher in the controls than those in the vaccinated pigs. Massive M. bovis growth from thoracic tissue samples was observed in 4 out of 9 controls but in none of the 10 vaccinated pigs. No effect of the presence or absence of tonsils was observed on these scores, suggesting that tonsils are not involved in the protective response to this vaccine in pigs. The serum antibody levels increased significantly only after challenge. At necropsy, the estimated sensitivities of the ELISAs and dual path platform (DPP) assays ranged from 89% to 94%. In the oral mucosa, no differences in gene expression were observed in the control group between the pigs with and without tonsils. In the vaccinated group, the mRNA levels for chemokine (C-C motif) receptor 7 (CCR7), interferon beta (IFN-β), and methylmalonyl coenzyme A mutase (MUT) were higher in pigs with tonsils. Complement component 3 mRNA levels in peripheral blood mononuclear cells (PBMC) increased with vaccination and decreased after M. bovis challenge. This information is relevant for pig production in regions that are endemic for M. bovis and for TB vaccine research.

Simulation of the energy performance of maize production integrated to pig farming

The study evaluated the energy performance of pig farming integrated with maize production in mechanized no-tillage system. In this proposed conception of integration, the swine excrement is used as fertilizers in the maize crop. The system was designed involving the activities associated to the pig management and maize production (soil management, cultivation and harvest). A one-year period of analysis was considered, enabling the production of three batches of pigs and two crops of maize. To evaluate the energy performance, three indicators were created: energy efficiency, use of non-renewable resources efficiency and cost of non-renewable energy to produce protein. The energy inputs are composed by the inputs and infrastructure used by the breeding of pigs and maize production, as well as the solar energy incident on the agroecosystem. The energy outputs are represented by the products (finished pigs and maize). The results obtained in the simulation indicates that the integration improves the energy performance of pig farms, with an increase in the energy efficiency (186%) as well as in the use of the non-renewable energy resources efficiency (352%), while reducing the cost of non-renewable energy to produce protein (‑58%).

Simulation of the energy performance of maize production integrated to pig farming

Foi avaliado o desempenho energético da suinocultura integrada à produção de milho em grão em sistema de plantio direto mecanizado. Nesta concepção de integração proposta, os dejetos suínos são utilizados como fertilizantes na produção de milho. O sistema foi delimitado envolvendo as atividades associadas ao manejo dos suínos e de produção do milho (manejo do solo, cultivo e colheita). O período de análise considerado foi de um ano, o que possibilita a produção de três lotes de suínos e duas safras de milho. Para avaliar o desempenho energético, foram criados três indicadores: eficiência energética, eficiência de uso de fontes não renováveis e o custo de energia não renovável para a produção de proteína. As entradas energéticas são compostas pelos insumos e pela infraestrutura, utilizados na criação dos suínos e na produção de milho, e pela radiação solar incidente no agrossistema. Já as saídas são representadas pelos seus produtos (suínos terminados e o milho). Os resultados obtidos nas simulações apontam que a integração melhora o desempenho energético das granjas suinícolas, aumentando a eficiência energética (186%) e a eficiência não renovável (352%), além de reduzir o custo de energia não renovável para a produção de proteína (‑58%).

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Effects of asbestos and silica on superoxide anion production in the guinea pig alveolar macrophage

Asbestos and silica are important industrial hazards. Exposure to these dusts can result in pulmonary fibrosis and, in the case of asbestos, cancer. Although the hazards of asbestos and silica exposure have long been known, the pathogenesis of dust-related disease is not well understood. Both silica and asbestos are thought to alter the function of the alveolar macrophage, but the nature of the biochemical alteration is unknown. Therefore, this study examined the effect of asbestos and silica on the activation pathway of the guinea pig alveolar macrophage. Activation of macrophages by physiological agents results in stimulation of phospholipase C causing phosphatidyl inositol turnover and intracellular calcium mobilization. Phosphatidyl inositol turnover produces diacylglycerol which activates protein kinase C causing superoxide anion production.^ Chrysotile stimulated alveolar macrophages to produce superoxide anion. This stimulation proceeded via phospholipase C, since chrysotile stimulated phosphatidyl inositol turnover and intracellular calcium mobilization. The possible involvement of a coupling protein was evaluated by pretreating cells with pertussis toxin. Pertussis toxin pretreatment partially inhibited chrysotile stimulation, suggesting that chrysotile activates a coupling protein in an non-classical manner. Potential binding sites for chrysotile stimulation were examined using a series of nine lectins. Chrysotile-stimulated superoxide anion production was blocked by pretreatment with lectins which bound to N-acetylglucosamine, but not by lectins which bound to mannose, fucose, or N-acetylgalactosamine. In addition, incubation with the N-acetylglucosamine polymer, chitin, inhibited chrysotile-stimulated superoxide anion production, suggesting that chrysotile stimulated superoxide anion production by binding to N-acetylglucosamine residues.^ On the other hand, silica did not stimulate superoxide anion production. The effect of silica on agonist stimulation of this pathway was examined using two stimulants of superoxide anion production, N-formyl-nle-leu-phe (FNLP, which stimulates through phospholipase C) and phorbol-12,13-dibutyrate (which directly activates protein kinase C). Sublethal doses of silica inhibited FNLP-stimulated superoxide anion production, but did not affect phorbol-12,13-dibutyrate-stimulated superoxide anion production, suggesting that the site of inhibition precedes protein kinase C. This inhibition was not due to cell membrane damage, since cell permeability to calcium-45 and rubidium-86 was not increased. It is concluded that chrysotile binds to N-acetylglucosamine residues on macrophage surface glycoproteins to stimulate the physiological pathway resulting in superoxide anion production. In contrast, silica does not stimulate superoxide anion production, but it did inhibit FNLP-stimulated superoxide anion production. ^

Validation of PigBal model predictions for pig manure production

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and –0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal’s capabilities for more accurately assessing nutrient loads. However, PigBal’s satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions.

Validation of PigBal model predictions for pig manure production

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and -0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal's capabilities for more accurately assessing nutrient loads. However, PigBal's satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions. © CSIRO 2016.