Sustaining Interferon Induction by a High-Passage Atypical Porcine Reproductive and Respiratory Syndrome Virus Strain

Partial funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.Porcine reproductive and respiratory syndrome virus (PRRSV) strain A2MC2 induces type I interferons in cultured cells. The objective of this study was to attenuate this strain by serial passaging in MARC-145 cells and assess its virulence and immunogenicity in pigs. The A2MC2 serially passaged 90 times (A2MC2-P90) retains the feature of interferon induction. The A2MC2-P90 replicates faster with a higher virus yield than wild type A2MC2 virus. Infection of primary pulmonary alveolar macrophages (PAMs) also induces interferons. Sequence analysis showed that the A2MC2-P90 has genomic nucleic acid identity of 99.8% to the wild type but has a deletion of 543 nucleotides in nsp2. The deletion occurred in passage 60. The A2MC2-P90 genome has a total of 35 nucleotide variations from the wild type, leading to 26 amino acid differences. Inoculation of three-week-old piglets showed that A2MC2-P90 is avirulent and elicits immune response. Compared with Ingelvac PRRS® MLV strain, A2MC2-P90 elicits higher virus neutralizing antibodies. The attenuated IFN inducing A2MC2-P90 should be useful for development of an improved PRRSV vaccine

Investigating porcine parvoviruses genogroup 2 infection using in situ polymerase chain reaction

Abstract Background Porcine parvovirus 2 (PPV2) was detected in swine serum without showing any relationship with disease. The emergence of the virus seemed to be a unique event until other genetically highly similar parvoviruses were identified in China and, later in 2012, the presence of the virus was also described in Europe. PPV2 is widely distributed in pig populations where it is suspected to be involved in respiratory conditions, based on its frequent detection in lung samples. In order to investigate the potential pathogenic involvement of PPV2, 60 dead pigs were examined from two farms. They were necropsied and tested for PPV2 and PCV2 (Porcine circovirus type 2) by PCR; by Brown and Brenn (B&B) staining for bacteria; by immunohistochemistry (IHC) to detect CD3, Swine leukocyte antigen class II DQ (SLAIIDQ), lysozyme, porcine reproductive and respiratory syndrome virus (PRRSV), swine influenza (SIV), Mycoplasma hyopneumoniae (Mhyo); and by in situ hybridization (ISH) to detect ssDNA and dsDNA of PCV2. PPV2 positive samples were subjected to in situ polymerase chain reaction (IS-PCR) including double staining method to detect PPV2 and host cell markers. To calculate statistical difference we used GENMOD or LOGISTIC procedures in Statistical Analysis System (SAS®). Results We found that the PPV2 was localized mostly in lymphocytes in lungs, lymph nodes and liver. Neither CD3 antigen nor lysozyme was expressed by these infected cells. In contrast, low levels of SLAIIDQ were expressed by infected cells, suggesting that PPV2 may have a specific tropism for immature B lymphocytes and/or NK lymphocytes though possibly not T lymphocytes. Conclusion The overall conclusion of this study indicates that PPV2 may contribute to the pathogenesis of pneumonia

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO 2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45863/1/382_2006_Article_111.pd

Analysis of the Slab-Ocean El Nino Atmospheric Feedbacks in Observed and Simulated ENSO Dynamics

In a recent study it was illustrated that the El Nino Southern Oscillation (ENSO) mode can exist in the absence of any ocean dynamics. This oscillating mode exists just due to the interaction between atmospheric heat fluxes and ocean heat capacity. The primary purpose of this study is to further explore these atmospheric Slab Ocean ENSO dynamics and therefore the role of positive atmospheric feedbacks in model simulations and observations. The positive solar radiation feedback to sea surface temperature (SST), due to reduced cloud cover for anomalous warm SSTs, is the main positive feedback in the Slab Ocean El Nino dynamics. The strength of this positive cloud feedback is strongly related to the strength of the equatorial cold tongue. The combination of positive latent and sensible heat fluxes to the west and negative ones to the east of positive anomalies leads to the westward propagation of the SST anomalies, which allows for oscillating behavior with a preferred period of 6-7 years. Several indications are found that parts of these dynamics are indeed observed and simulated in other atmospheric or coupled general circulation models (AGCMs or CGCMs). The CMIP3 AGCM-slab ensemble of 13 different AGCM simulations shows unstable ocean-atmosphere interactions along the equatorial Pacific related to stronger cold tongues. In observations and in the CMIP3 and CMIP5 CGCM model ensemble the strength and sign of the cloud feedback is a function of the strength of the cold tongue. In summary, this indicates that the Slab Ocean El Nino dynamics are indeed a characteristic of the equatorial Pacific climate that is only dominant or significantly contributing to the ENSO dynamics if the SST cold tongue is sufficiently strong. In the observations this is only the case during strong La Nina conditions. The presence of the Slab Ocean ENSO atmospheric feedbacks in observations and CGCM model simulations implies that the family of physical ENSO modes does have another member, which is entirely driven by atmospheric processes and does not need to have the same spatial pattern nor the same time scales as the main ENSO dynamics