Systemic arteriopathy in SIV-infected rhesus macaques (Macaca mulatta)

BACKGROUND: Severe disseminated vasculopathy was observed in two simian immunodeficiency virus (SIV)-infected rhesus macaques (Macaca mulatta). These animals developed clinical signs of AIDS, including lymphadenopathy, weight loss, diarrhea and collapse. RESULTS AND DISCUSSION: Grossly, both animals showed emaciation, lymphadenopathy, vegetations on the mitral valve, renal infarcts and a dilated intestine; one animal had multifocal hemorrhages in multiple organs. Histologically, both cases had disseminated arteriopathy characterized by intimal thickening and fibrosis with varying degrees of vasculitis. The lesion was prominent in the kidney, intestine, pancreas, liver, heart, lymph nodes, spleen and testis. Occasional venules had intimal thickening. Both cases had cytomegalovirus (CMV) infection with intranuclear inclusions, CMV antigen and nucleic acid; some inclusions were observed in endothelial cells within some of the vascular lesions in one of the two. These data suggest that CMV caused the unusual lesions.     

Differential roles for RIG-I-like receptors and nucleic acid-sensing TLR pathways in controlling a chronic viral infection

The necessity for pathogen recognition of viral infection by the innate immune system in initiating early innate and adaptive host defenses is well documented. However, little is known about the role these receptors play in the maintenance of adaptive immune responses and their contribution to resolution of persistent viral infections. In this study, we demonstrate a nonredundant functional requirement for both nucleic acid-sensing TLRs and RIG-I-like receptors in the control of a mouse model of chronic viral infection. Whereas the RIG-I-like receptor pathway was important for production of type I IFNs and optimal CD8(+) T cell responses, nucleic acid-sensing TLRs were largely dispensable. In contrast, optimal anti-viral Ab responses required intact signaling through nucleic acid-sensing TLRs, and the absence of this pathway correlated with less virus-specific Ab and deficient long-term virus control of a chronic infection. Surprisingly, absence of the TLR pathway had only modest effects on Ab production in an acute infection with a closely related virus strain, suggesting that persistent TLR stimulation may be necessary for optimal Ab responses in a chronic infection. These results indicate that innate virus recognition pathways may play critical roles in the outcome of chronic viral infections through distinct mechanisms.     

Hematologic abnormalities associated with simian immunodeficieny virus (SIV) infection mimic those in HIV infection

Background Studies of hematologic abnormalities in HIV‐infected patients are confounded by a multitude of factors. A retrospective data analysis of simian immunodeficieny virus (SIV)‐infected rhesus macaques (RM) of Indian origin was performed to determine the prevalence of hematologic abnormalities free of these confounds. Methods Hematologic data from RM inoculated with SIV and without antiviral therapy were examined pre‐inoculation, and throughout infection and the development of AIDS. Results Anemia, thrombocytopenia, lymphopenia, eosinophilia, and neutropenia all increased in prevalence with SIV infection. Significant increases in prevalence for both neutropenia and neutrophilia were also detected in SIV‐infected macaques. SIV‐infected macaques also had lower lymphocyte counts and increased prevalence of lymphopenia compared with non‐infected subjects. The prevalence of eosinophilia was significantly increased during SIV infection. Conclusions Concordance of hematologic abnormalities during SIV infection of macaques with similar changes in HIV infection of humans suggests that, like in HIV infection, hematologic abnormalities are major complications of SIV infection.     

A new method for inferring hidden markov models from noisy time sequences

We present a new method for inferring hidden Markov models from noisy time sequences without the necessity of assuming a model architecture, thus allowing for the detection of degenerate states. This is based on the statistical prediction techniques developed by Crutchfield et al. and generates so called causal state models, equivalent in structure to hidden Markov models. The new method is applicable to any continuous data which clusters around discrete values and exhibits multiple transitions between these values such as tethered particle motion data or Fluorescence Resonance Energy Transfer (FRET) spectra. The algorithms developed have been shown to perform well on simulated data, demonstrating the ability to recover the model used to generate the data under high noise, sparse data conditions and the ability to infer the existence of degenerate states. They have also been applied to new experimental FRET data of Holliday Junction dynamics, extracting the expected two state model and providing values for the transition rates in good agreement with previous results and with results obtained using existing maximum likelihood based methods. The method differs markedly from previous Markov-model reconstructions in being able to uncover truly hidden states.     

A change in nuclear pore complex composition regulates cell differentiation

Nuclear pore complexes (NPCs) are built from ～30 different proteins called nucleoporins or Nups. Previous studies have shown that several Nups exhibit cell-type-specific expression and that mutations in NPC components result in tissue-specific diseases. Here we show that a specific change in NPC composition is required for both myogenic and neuronal differentiation. The transmembrane nucleoporin Nup210 is absent in proliferating myoblasts and embryonic stem cells (ESCs) but becomes expressed and incorporated into NPCs during cell differentiation. Preventing Nup210 production by RNAi blocks myogenesis and the differentiation of ESCs into neuroprogenitors. We found that the addition of Nup210 to NPCs does not affect nuclear transport but is required for the induction of genes that are essential for cell differentiation. Our results identify a single change in NPC composition as an essential step in cell differentiation and establish a role for Nup210 in gene expression regulation and cell fate determination.     

Fast Carbon Footprinting for Large Product Portfolios

Publicly Available Specification 2050‐2011 (PAS 2050), the Green House Gas Product Protocol (GHGPP) standard and forthcoming guideline 14067 from the International Organization for Standardization (ISO) have helped to propel carbon footprinting from a subdiscipline of life cycle assessment (LCA) to the mainstream. However, application of carbon footprinting to large portfolios of many distinct products and services is immensely resource intensive. Even if achieved, it often fails to inform company‐wide carbon reduction strategies because footprint data are disjointed or don't cover the whole portfolio. We introduce a novel approach to generate standard‐compliant product carbon footprints (CFs) for companies with large portfolios at a fraction of previously required time and expertise. The approach was developed and validated on an LCA dataset covering 1,137 individual products from a global packaged consumer goods company. Three novel techniques work in concert in a single approach that enables practitioners to calculate thousands of footprints virtually simultaneously: (i) a uniform data structure enables footprinting all products and services by looping the same algorithm; (ii) concurrent uncertainty analysis guides practitioners to gradually improve the accuracy of only those data that materially impact the results; and (iii) a predictive model generates estimated emission factors (EFs) for materials, thereby eliminating the manual mapping of a product or service's inventory to EF databases. These autogenerated EFs enable non‐LCA experts to calculate approximate CFs and alleviate resource constraints for companies embarking on large‐scale product carbon footprinting. We discuss implementation roadmaps for companies, including further road‐testing required to evaluate the effectiveness of the approach for other product portfolios, limitations, and future improvements of the fast footprinting methodology.     

Genome mining reveals the evolutionary origin and biosynthetic potential of basidiomycete polyketide synthases

Numerous polyketides are known from bacteria, plants, and fungi. However, only a few have been isolated from basidiomycetes. Large scale genome sequencing projects now help anticipate the capacity of basidiomycetes to synthesize polyketides. In this study, we identified and annotated 111 type I and three type III polyketide synthase (PKS) genes from 35 sequenced basidiomycete genomes. Phylogenetic analysis of PKS genes suggests that all main types of fungal iterative PKS had already evolved before the Ascomycota and Basidiomycota diverged. A comparison of genomic and metabolomic data shows that the number of polyketide genes exceeds the number of known polyketide structures by far. Exploiting these results to design degenerate PCR primers, we amplified and cloned the complete sequence of armB, a PKS gene from the melleolide producer Armillaria mellea. We expect this study will serve as a guide for future genomic mining projects to discover structurally diverse mushroom-derived polyketides.