ABSTRACT
Foodborne salmonellosis costs the US $2.7 billion/year, including $100.0 million in annual losses to pork producers. Pigs colonized with Salmonella are usually asymptomatic with varied severity and duration of fecal shedding. Thus, understanding the responses that result in less shedding may provide a mechanism for control. Fifty-four pigs were inoculated with Salmonella enterica serovar Typhimurium (ST) and clinical signs, fecal ST shedding, growth performance, peripheral cytokines and whole blood gene expression were measured. Persistently shedding (PS) pigs had longer pyrexia and elevated serum IL-1ß, TNF-α and IFN-γ compared with low shedding (LS) pigs, while LS pigs had brief pyrexia, less shedding that decreased more rapidly and greater serum CXCL8 than PS pigs. The PS pigs up-regulated genes involved with the STAT1, IFNB1 and IFN-γ networks on d 2, while up-regulation of genes involved in immune response regulation were only detected in LS pigs. This is the first study to examine host responses to ST infection at a clinical, performance, cytokine and transcriptomic level. The results indicated that pigs with different shedding outcomes developed distinct immune responses within the first 2 d of ST infection, and elucidated alternative mechanisms that could be targeted to reduce Salmonella shedding and spread.
Subject(s)
Salmonella typhi/physiology , Sus scrofa/immunology , Typhoid Fever/immunology , Animals , Bacterial Shedding/immunology , Blood Circulation , Cytokines/metabolism , Immunity , Interleukin-8/metabolism , Phenotype , STAT1 Transcription Factor/metabolism , Transcriptome/immunology , Typhoid Fever/microbiologyABSTRACT
BACKGROUND: The domestic pig is known as an excellent model for human immunology and the two species share many pathogens. Susceptibility to infectious disease is one of the major constraints on swine performance, yet the structure and function of genes comprising the pig immunome are not well-characterized. The completion of the pig genome provides the opportunity to annotate the pig immunome, and compare and contrast pig and human immune systems. RESULTS: The Immune Response Annotation Group (IRAG) used computational curation and manual annotation of the swine genome assembly 10.2 (Sscrofa10.2) to refine the currently available automated annotation of 1,369 immunity-related genes through sequence-based comparison to genes in other species. Within these genes, we annotated 3,472 transcripts. Annotation provided evidence for gene expansions in several immune response families, and identified artiodactyl-specific expansions in the cathelicidin and type 1 Interferon families. We found gene duplications for 18 genes, including 13 immune response genes and five non-immune response genes discovered in the annotation process. Manual annotation provided evidence for many new alternative splice variants and 8 gene duplications. Over 1,100 transcripts without porcine sequence evidence were detected using cross-species annotation. We used a functional approach to discover and accurately annotate porcine immune response genes. A co-expression clustering analysis of transcriptomic data from selected experimental infections or immune stimulations of blood, macrophages or lymph nodes identified a large cluster of genes that exhibited a correlated positive response upon infection across multiple pathogens or immune stimuli. Interestingly, this gene cluster (cluster 4) is enriched for known general human immune response genes, yet contains many un-annotated porcine genes. A phylogenetic analysis of the encoded proteins of cluster 4 genes showed that 15% exhibited an accelerated evolution as compared to 4.1% across the entire genome. CONCLUSIONS: This extensive annotation dramatically extends the genome-based knowledge of the molecular genetics and structure of a major portion of the porcine immunome. Our complementary functional approach using co-expression during immune response has provided new putative immune response annotation for over 500 porcine genes. Our phylogenetic analysis of this core immunome cluster confirms rapid evolutionary change in this set of genes, and that, as in other species, such genes are important components of the pig's adaptation to pathogen challenge over evolutionary time. These comprehensive and integrated analyses increase the value of the porcine genome sequence and provide important tools for global analyses and data-mining of the porcine immune response.
Subject(s)
Genomics , Immunity/genetics , Molecular Sequence Annotation , Swine/genetics , Swine/immunology , Animals , Cattle , Evolution, Molecular , Gene Duplication , Humans , Immunoglobulins/genetics , Mice , Models, Molecular , Protein Conformation , Receptors, Antigen, T-Cell/genetics , Receptors, KIR/genetics , Selection, Genetic , Species SpecificityABSTRACT
Transcriptomic analysis of the response to bacterial pathogens has been reported for several species, yet few studies have investigated the transcriptional differences in whole blood in subjects that differ in their disease response phenotypes. Salmonella species infect many vertebrate species, and pigs colonized with Salmonella enterica serovar Typhimurium (ST) are usually asymptomatic, making detection of these Salmonella-carrier pigs difficult. The variable fecal shedding of Salmonella is an important cause of foodborne illness and zoonotic disease. To investigate gene pathways and biomarkers associated with the variance in Salmonella shedding following experimental inoculation, we initiated the first analysis of the whole blood transcriptional response induced by Salmonella. A population of pigs (nâ=â40) was inoculated with ST and peripheral blood and fecal Salmonella counts were collected between 2 and 20 days post-inoculation (dpi). Two groups of pigs with either low shedding (LS) or persistent shedding (PS) phenotypes were identified. Global transcriptional changes in response to ST inoculation were identified by Affymetrix Genechip® analysis of peripheral blood RNA at day 0 and 2 dpi. ST inoculation triggered substantial gene expression changes in the pigs and there was differential expression of many genes between LS and PS pigs. Analysis of the differential profiles of gene expression within and between PS and LS phenotypic classes identified distinct regulatory pathways mediated by IFN-γ, TNF, NF-κB, or one of several miRNAs. We confirmed the activation of two regulatory factors, SPI1 and CEBPB, and demonstrated that expression of miR-155 was decreased specifically in the PS animals. These data provide insight into specific pathways associated with extremes in Salmonella fecal shedding that can be targeted for further exploration on why some animals develop a carrier state. This knowledge can also be used to develop rational manipulations of genetics, pharmaceuticals, nutrition or husbandry methods to decrease Salmonella colonization, shedding and spread.
Subject(s)
Bacterial Shedding/physiology , MicroRNAs/blood , Salmonella Infections, Animal/blood , Salmonella Infections, Animal/microbiology , Salmonella typhimurium/physiology , Signal Transduction/genetics , Sus scrofa/microbiology , Animals , Area Under Curve , Cluster Analysis , Gene Expression Profiling , Gene Expression Regulation , Gene Regulatory Networks/genetics , Interferon-gamma/genetics , Interferon-gamma/metabolism , MicroRNAs/genetics , Molecular Sequence Annotation , Oligonucleotide Array Sequence Analysis , Polymerase Chain Reaction , RNA, Messenger/genetics , RNA, Messenger/metabolism , Reproducibility of Results , Salmonella Infections, Animal/genetics , Sus scrofa/blood , Sus scrofa/classification , Sus scrofa/genetics , Toll-Like Receptors/genetics , Toll-Like Receptors/metabolismABSTRACT
BACKGROUND: Placental efficiency is strongly associated with litter size, fetal weight and prenatal mortality. Together with its rapid growth during late gestation, the Large White pig breed shows a significant increase in placental size and weight, but this does not occur in the highly prolific Chinese pig breeds. To understand the molecular basis of placental development during late gestation in Chinese indigenous and Western breeds with different placental efficiency, female placental samples were collected from six pregnant Erhualian gilts at gestation day 75 (E75) and day 90 (E90) and from six pregnant Large White gilts at gestation day 75 (L75) and day 90 (L90). Two female placentas from one sow were used to extract RNA and then pooled in equal volumes. Twelve pooled samples were hybridized to the porcine Affymetrix GeneChip. RESULTS: A total of 226 and 577 transcripts were detected that were differentially expressed between E75 and L75 and between E90 and L90 (p < 0.01, q < 0.2), respectively. Gene Ontology (GO) analysis revealed that these genes belong to the class of genes that participate in angiogenesis and development. Real-time RT-PCR confirmed the differential expression of eight selected genes. Significant differential expression of five genes in the VEGF pathway was also detected between the breeds. A search of chromosomal location revealed that 44 differentially expressed genes located to QTL regions related to reproduction. Differential expression of six candidate imprinted genes was also confirmed. Three of the six genes (PLAGL1, DIRAS3, and SLC38A4) showed monoallelic expression in the porcine placenta. CONCLUSION: Our study detected many genes that showed differential expression between placentas of two divergent breed of pigs, and confirmed the imprinting of three genes. These findings help to elucidate the genetic control of placental efficiency and improve the understanding of placental development.
Subject(s)
Gene Expression Profiling/methods , Placenta/metabolism , Placentation/genetics , Pregnancy, Animal/genetics , Swine/genetics , Animals , Cluster Analysis , Female , Gene Expression Regulation, Developmental , Genomic Imprinting , Oligonucleotide Array Sequence Analysis , Pregnancy , Quantitative Trait Loci , Reverse Transcriptase Polymerase Chain ReactionABSTRACT
MiRNAs (microRNAs) play critical roles in many important biological processes such as growth and development in mammals. In this study, we identified hundreds of porcine miRNA candidates through in silico prediction and analyzed their expression in developing skeletal muscle using microarray. Microarray screening using RNA samples prepared from a 33-day whole embryo and an extra embryo membrane validated 296 of the predicted candidates. Comparative expression profiling across samples of longissimus muscle collected from 33-day and 65-day post-gestation fetuses, as well as adult pigs, identified 140 differentially expressed miRNAs amongst the age groups investigated. The differentially expressed miRNAs showed seven distinctive types of expression patterns, suggesting possible involvement in certain biological processes. Five of the differentially expressed miRNAs were validated using real-time PCR. In silico analysis of the miRNA-mRNA interaction sites suggested that the potential mRNA targets of the differentially expressed miRNAs may play important roles in muscle growth and development.
Subject(s)
Gene Expression Profiling , MicroRNAs , Muscle, Skeletal/metabolism , Algorithms , Animals , Databases, Genetic , Gene Expression Regulation, Developmental , Genomics , Multigene Family , Nucleic Acid Hybridization , Oligonucleotide Array Sequence Analysis , Reverse Transcriptase Polymerase Chain Reaction , Sequence Analysis, RNA , SwineABSTRACT
BACKGROUND: MicroRNAs (miRNAs) are recognized as one of the most important families of non-coding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression. Identification of miRNAs is an important requirement for understanding the mechanisms of post-transcriptional regulation. Hundreds of miRNAs have been identified by direct cloning and computational approaches in several species. However, there are still many miRNAs that remain to be identified due to lack of either sequence features or robust algorithms to efficiently identify them. RESULTS: We have evaluated features valuable for pre-miRNA prediction, such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins. We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs. Utilizing these features and combining some improvements of the current pre-miRNA prediction methods, we implemented a computational learning method SVM (support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder. The tool was designed for genome-wise, pair-wise sequences from two related species. The method built into the tool consisted of two major steps: 1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method. Results from applying the tool for chicken/human and D. melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions. CONCLUSION: The MiRFinder can be a good alternative to current miRNA discovery software. This tool is available at http://www.bioinformatics.org/mirfinder/.