Intestinal fungi contribute to development of alcoholic liver disease

This study was supported in part by NIH grants R01 AA020703, U01 AA021856 and by Award Number I01BX002213 from the Biomedical Laboratory Research & Development Service of the VA Office of Research and Development (to B.S.). K.H. was supported by a DFG (Deutsche Forschungsgemeinschaft) fellowship (HO/ 5690/1-1). S.B. was supported by a grant from the Swiss National Science Foundation (P2SKP3_158649). G.G. received funding from the Yale Liver Center NIH P30 DK34989 and R.B. from NIAAA grant U01 AA021908. A.K. received support from NIH grants RC2 AA019405, R01 AA020216 and R01 AA023417. G.D.B. is supported by funds from the Wellcome Trust. We acknowledge the Human Tissue and Cell Research (HTCR) Foundation for making human tissue available for research and Hepacult GmbH (Munich, Germany) for providing primary human hepatocytes for in vitro analyses. We thank Dr. Chien-Yu Lin Department of Medicine, Fu-Jen Catholic University, Taiwan for statistical analysis.Peer reviewedPublisher PD

Context-dependent representation of within- and between-model uncertainty: Aggregating probabilistic predictions in infectious disease epidemiology

Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible. For example, if predictions are conditional on assumptions about how the future will unfold (e.g. possible interventions), these assumptions may never materialize, precluding any direct comparison between predictions and observations. Here, we summarize literature on aggregating probabilistic predictions, illustrate various methods for infectious disease predictions via simulation, and present a strategy for choosing an aggregation method when empirical validation cannot be used. We focus on the linear opinion pool (LOP) and Vincent average, common methods that make different assumptions about between-prediction uncertainty. We contend that assumptions of the aggregation method should align with a hypothesis about how uncertainty is expressed within and between predictions from different sources. The LOP assumes that between-prediction uncertainty is meaningful and should be retained, while the Vincent average assumes that between-prediction uncertainty is akin to sampling error and should not be preserved. We provide an R package for implementation. Given the rising importance of multi-model infectious disease hubs, our work provides useful guidance on aggregation and a deeper understanding of the benefits and risks of different approaches

Distinct Roles of ComK1 and ComK2 in Gene Regulation in Bacillus cereus

The B. subtilis transcriptional factor ComK regulates a set of genes coding for DNA uptake from the environment and for its integration into the genome. In previous work we showed that Bacillus cereus expressing the B. subtilis ComK protein is able to take up DNA and integrate it into its own genome. To extend our knowledge on the effect of B. subtilis ComK overexpression in B. cereus we first determined which genes are significantly altered. Transcriptome analysis showed that only part of the competence gene cluster is significantly upregulated. Two ComK homologues can be identified in B. cereus that differ in their respective homologies to other ComK proteins. ComK1 is most similar, while ComK2 lacks the C-terminal region previously shown to be important for transcription activation by B. subtilis ComK. comK1 and comK2 overexpression and deletion studies using transcriptomics techniques showed that ComK1 enhances and ComK2 decreases expression of the comG operon, when B. subtilis ComK was overexpressed simultaneously

An intron polymorphism of the fibronectin gene is associated with end-stage knee osteoarthritis in a Han Chinese population: two independent case-control studies

BACKGROUND: Knee osteoarthritis (OA) is a complex disease involving both biomechanical and metabolic factors that alter the tissue homeostasis of articular cartilage and subchondral bone. The catabolic activities of extracellular matrix degradation products, especially fibronectin (FN), have been implicated in mediating cartilage degradation. Chondrocytes express several members of the integrin family which can serve as receptors for FN including integrins α5β1, αvβ3, and αvβ5. The purpose of this study was to determine whether polymorphisms in the FN (FN-1) and integrin genes are markers of susceptibility to, or severity of, knee OA in a Han Chinese population. METHODS: Two independent case–control studies were conducted on 928 patients with knee OA and 693 healthy controls. Ten single nucleotide polymorphisms (SNPs) of FN-1 and the integrin αV gene (ITGAV) were detected using the ABI 7500 real-time PCR system. RESULTS: The AT heterozygote in FN-1 (rs940739A/T) was found to be significantly associated with knee OA (adjusted OR = 1.44; 95% CI = 1.16–1.80) in both stages of the study. FN-1 rs6725958C/A and ITGAV rs10174098A/G SNPs were only associated with knee OA when both study groups were combined. Stratifying the participants by Kellgren-Lawrence (KL) score identified significant differences in the FN-1 rs6725958C/A and rs940739 A/T genotypes between patients with grade 4 OA and controls. Haplotype analyses revealed that TGA and TAA were associated with a higher risk of OA, and that TAG conferred a lower risk of knee OA in the combined population. CONCLUSIONS: Our study suggests that the FN-1 rs940739A/T polymorphism may be an important risk factor of genetic susceptibility to knee OA in the Han Chinese population

Genomic organization, sequence analysis and expression of all five genes encoding the small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase from tomato

We have cloned and sequenced all five members of the gene family for the small subunit (rbcS) of ribulose-1,5-bisphosphate carboxylase/oxygenase from tomato, Lycopersicon esculentum cv. VFNT LA 1221 cherry line. Two of the five genes, designated Rbcs-1 and Rbcs-2 , are present as single genes at individual loci. Three genes, designated Rbcs-3A, Rbcs-3B and Rbcs-3C , are organized in a tandem array within 10 kb at a third independent locus. The Rbcs-2 gene contains three introns; all the other members of the tomato gene family contain two introns. The coding sequence of Rbcs-1 differs by 14.0% from that of Rbcs-2 and by 13.3% from that of Rbcs-3 genes. Rbcs-2 shows 10.4% divergence from Rbcs-3 . The exon and intron sequences of Rbcs-3A are identical to those of Rbcs-3C , and differ by 1.9% from those of Rbcs-3B . Nucleotide sequence analysis suggests that the five rbcS genes encode four different precursors, and three different mature polypeptides. S 1 nuclease mapping of the 5′ end of rbcS mRNAs revealed that the mRNA leader sequences vary in length from 8 to 75 nucleotides. Northern analysis using gene-specific oligonucleotide probes from the 3′ non-coding region of each gene reveals a four to five-fold difference among the five genes in maximal steady-state mRNA levels in leaves.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47566/1/438_2004_Article_BF00329650.pd