Monitoring the immune response to vaccination with an inactivated vaccine associated to bovine neonatal pancytopenia by deep sequencing transcriptome analysis in cattle

Bovine neonatal pancytopenia (BNP) is a new fatal, alloimmune/alloantibody mediated disease of new-born calves induced by ingestion of colostrum from cows, which had been vaccinated with a specific vaccine against the Bovine Virus Diarrhoea Virus (BVDV). The hypothesis of pathogenic MHC class I molecules in the vaccine had been put up, but no formal proof of specific causal MHC class I alleles has been provided yet. However, the unique features of the vaccine obviously result in extremely high specific antibody titres in the vaccinated animals, but apparently also in further molecules inducing BNP. Thus, a comprehensive picture of the immune response to the vaccine is essential. Applying the novel approach of next generation RNA sequencing (RNAseq), our study provides a new holistic, comprehensive analysis of the blood transcriptome regulation after vaccination with the specific BVDV vaccine. Our RNAseq approach identified a novel cytokine-like gene in the bovine genome that is highly upregulated after vaccination. This gene has never been described before in any other species and might be specific to ruminant immune response. Furthermore, our data revealed a very coordinated immune response to double-stranded (ds) RNA or a dsRNA analogue after vaccination with the inactivated single-stranded (ss) RNA vaccine. This would suggest either a substantial contamination of the vaccine with dsRNA from host cells after virus culture or a dsRNA analogue applied to the vaccine. The first option would highlight the potential risks associated with virus culture on homologous cells during vaccine production; the latter option would emphasise the potential risks associated with immune stimulating adjuvants used in vaccine production

MicroRNA expression profiling of porcine mammary epithelial cells after challenge with Escherichia coli in vitro

Background Coliform mastitis is a symptom of postpartum dysgalactia syndrome (PDS), a multifactorial infectious disease of sows. Our previous study showed gene expression profile change after bacterial challenge of porcine mammary epithelial cells (PMECs). These mRNA expression changes may be regulated through microRNAs (miRNAs) which play critical roles in biological processes. Therefore, miRNA expression profile was investigated in PMECs. Results PMECs were isolated from three lactating sows and challenged with heat-inactivated potential mastitis-causing pathogen Escherichia coli (E. coli) for 3 h and 24 h, in vitro. At 3 h post-challenge with E. coli, target gene prediction identified a critical role of miRNAs in regulation of host immune responses and homeostasis of PMECs mediated by affecting pathways including cytokine binding (miR-202, miR-3277, miR-4903); IL-10/PPAR signaling (miR-3277, miR-4317, miR-548); and NF-ĸB/TNFR2 signaling (miR-202, miR-2262, miR-885-3p). Target genes of miRNAs in PMECs at 24 h were significantly enriched in pathways associated with interferon signaling (miR-210, miR-23a, miR-1736) and protein ubiquitination (miR-125, miR-128, miR-1280). Conclusions This study provides first large-scale miRNA expression profiles and their predicted target genes in PMECs after contact with a potential mastitis-causing E. coli strain. Both, highly conserved miRNAs known from other species as well as novel miRNAs were identified in PMECs, representing candidate predictive biomarkers for PDS. Time-dependent pathogen clearance suggests an important role of PMECs in inflammatory response of the first cellular barrier of the porcine mammary gland

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches

Dysphagia as a manifestation of esophageal tuberculosis: a report of two cases

<p>Abstract</p> <p>Introduction</p> <p>Esophageal involvement by <it>Mycobacterium tuberculosis </it>is rare and the diagnosis is frequently made by means of an esophageal biopsy during the evaluation of dysphagia. There are few cases reported in the literature.</p> <p>Case presentation</p> <p>We present two cases of esophageal tuberculosis in 85- and 65-year-old male Caucasian patients with initial complaints of dysphagia and epigastric pain. Upper gastrointestinal endoscopy resulted in the diagnosis of esophageal tuberculosis following the biopsy of lesions of irregular mucosa in one case and a sessile polyp in the other. Pulmonary tuberculosis was detected in one patient. In one patient esophageal stricture developed as a complication. Antituberculous therapy was curative in both patients.</p> <p>Conclusion</p> <p>Although rare, esophageal tuberculosis has to be kept in mind in the differential diagnosis of dysphagia. Pulmonary involvement has important implications for contact screening.</p