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This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Foods contaminated with Escherichia coli O157:H7 cause more than 63,000 foodborne illnesses in the United States every year, resulting in a significant economic impact on medical costs and product liabilities. Efforts to reduce contamination with E. coli O157:H7 have largely focused on washing, application of various antibacterial chemicals, and gamma-irradiation, each of which has practical and environmental drawbacks. A relatively recent, environmentally-friendly approach proposed for eliminating or significantly reducing E. coli O157:H7 contamination of foods is the use of lytic bacteriophages as biocontrol agents. We found that EcoShield™, a commercially available preparation composed of three lytic bacteriophages specific for E. coli O157:H7, significantly (p < 0.05) reduced the levels of the bacterium in experimentally contaminated beef by ≥ 94% and in lettuce by 87% after a five minute contact time. The reduced levels of bacteria were maintained for at least one week at refrigerated temperatures. However, the one-time application of EcoShield™ did not protect the foods from recontamination with E. coli O157:H7. Our results demonstrate that EcoShield™ is effective in significantly reducing contamination of beef and lettuce with E. coli O157:H7, but does not protect against potential later contamination due to, for example, unsanitary handling of the foods post processing.
Iron is an essential cofactor in many metabolic reactions. Mechanisms controlling iron homeostasis need to respond rapidly to changes in extracellular conditions, but they must also keep the concentration of intracellular iron under strict control to avoid the generation of damaging reactive oxygen species. Due to its role as a redox carrier in photosynthesis, the iron quota in cyanobacteria is about 10 times higher than in model enterobacteria. The molecular details of how such a high quota is regulated are obscure. Here we present experiments that shed light on the iron regulatory system in cyanobacteria. We measured time-resolved changes in gene expression after iron depletion in the cyanobacterium Synechocystis sp. PCC 6803 using a comprehensive microarray platform, monitoring both protein-coding and non-coding transcripts. In total, less than a fifth of all protein-coding genes were differentially expressed during the first 72 hr. Many of these proteins are associated with iron transport, photosynthesis, or ATP synthesis. Comparing our data with three previous studies, we identified a core set of 28 genes involved in iron stress response. Among them were genes important for assimilation of inorganic carbon, suggesting a link between the carbon and iron regulatory networks. Nine of the 28 genes have unknown functions and constitute key targets for further functional analysis. Statistical and clustering analyses identified 10 small RNAs, 62 antisense RNAs, four 5'UTRs, and seven intragenic elements as potential novel components of the iron regulatory network in Synechocystis. Hence, our genome-wide expression profiling indicates an unprecedented complexity in the iron regulatory network of cyanobacteria.
Colorectal cancer (CRC) has a complex etiology resulting from the combination of multiple genetic and environmental factors, each with small effects. Interactions among susceptibility modifier loci make many of the loci difficult to detect in human genome-wide association studies. Previous analyses in mice have used classical inbred strains, which share large portions of their genomes due to common ancestry. Herein, we used an interspecific backcross between the Mus musculus strain A/J and the Mus spretus strain SPRET/EiJ to map 6 additional CRC modifier loci (Scc16-21) and 2 suggestive loci. Three loci modify the location of tumors along the proximal-distal axis of the colon. Six CRC modifiers previously mapped in intraspecific crosses were also replicated. This work confirms genetic models suggesting that CRC is caused by many small effect alleles and brings the catalog of reported CRC modifier loci to 23 spread across 13 chromosomes. Furthermore, this work provides the foundation for large population-level epistatic interaction tests to identify combinations of low effect alleles that may have large effects on CRC susceptibility.
The Crabtree effect, in which fermentative metabolism is preferred at the expense of respiration, is a hallmark of budding yeast's glucose response and a model for the Warburg effect in human tumors. While the glucose-responsive transcriptional repressors Mig1p and Mig2p play well-characterized roles in the Crabtree effect, little function for the related Mig3p transcription factor has been uncovered, despite numerous investigations of laboratory yeast strains. Here we studied a wild isolate of Saccharomyces cerevisiae to uncover a critical role for Mig3p that has been lost in S288c-derived laboratory strains. We found that Mig3p affects the expression of hundreds of glucose-responsive genes in the oak strain YPS163, both during growth under standard conditions and upon ethanol treatment. Our results suggest that Mig3p may act as a multifunctional activator/repressor that plays separate roles under standard vs. stress conditions and that this function has been largely lost in the lab strains. Population analysis suggests that the lab strain and several wild strains harbor mutations that diminish Mig3p function. Thus, by expanding our attention to multiple genetic backgrounds, we have uncovered an important missing link in a key metabolic response.
Interactions across biological networks are often quantified under a single set of conditions; however, cellular behaviors are dynamic and interactions can be expected to change in response to molecular context and environment. To determine the consistency of network interactions, we examined the enzyme network responsible for the reduction of nicotinamide adenine dinucleotide phosphate (NADP) to NADPH across three different conditions: oxidative stress, starvation, and desiccation. Synthetic, activity-variant alleles were used in Drosophila melanogaster for glucose-6-phosphate dehydrogenase (G6pd), cytosolic isocitrate dehydrogenase (Idh), and cytosolic malic enzyme (Men) along with seven different genetic backgrounds to lend biological relevance to the data. The responses of the NADP-reducing enzymes and two downstream phenotypes (lipid and glycogen concentration) were compared between the control and stress conditions. In general, responses in NADP-reducing enzymes were greater under conditions of oxidative stress, likely due to an increased demand for NADPH. Interactions between the enzymes were altered by environmental stress in directions and magnitudes that are consistent with differential contributions of the different enzymes to the NADPH pool: the contributions of G6PD and IDH seem to be accentuated by oxidative stress, and MEN by starvation. Overall, we find that biological network interactions are strongly influenced by environmental conditions, underscoring the importance of examining networks as dynamic entities.
The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection.
The methylotrophic yeast Pichia pastoris is widely used as a bioengineering platform for producing industrial and biopharmaceutical proteins, studying protein expression and secretion mechanisms, and analyzing metabolite synthesis and peroxisome biogenesis. With the development of DNA microarray and mRNA sequence technology, the P. pastoris transcriptome has become a research hotspot due to its powerful capability to identify the transcript structures and gain insights into the transcriptional regulation model of cells under protein production conditions. The study of the P. pastoris transcriptome helps to annotate the P. pastoris transcript structures and provide useful information for further improvement of the production of recombinant proteins.
PiggyBac transposable element derived 1 (PGBD1) encodes a molecule involved in epigenetic mechanisms that have been implicated in Alzheimer's disease (AD), and recent genome-wide association studies and meta-analyses have indicated that a single nucleotide polymorphism (SNP), rs3800324, in PGBD1 could be associated with AD and the age of onset. However, no Japanese patients were examined in these studies. The aim of the present study was to replicate the previous finding in Japanese AD cases.
Histone modification plays an important role in cell differentiation and tissue development. A recent study has shown that the dimethylation of lysine 4 residue on histone 3 (H3K4me2) marks the gene body area of tissue specific genes in the human CD4+ T cells and neural cells. However, little is known of the H3k4me2 distribution dynamics through the cell differentiation and tissue development.
A number of apicomplexan genomes have been sequenced successfully in recent years and this would help in understanding the biology of apicomplexan parasites. The members of the phylum Apicomplexa are important protozoan parasites (Plasmodium, Toxoplasma and Cryptosporidium etc) that cause some of the deadly diseases in humans and animals. In our earlier studies, we have shown that the standard BLOSUM matrices are not suitable for compositionally biased apicomplexan proteins. So we developed a novel series (SMAT and PfFSmat60) of substitution matrices which performed better in comparison to standard BLOSUM matrices and developed ApicoAlign, a sequence search and alignment tool for apicomplexan proteins. In this study, we demonstrate the higher specificity of these matrices and make an attempt to improve the annotation of apicomplexan kinases and proteases.
The computational prediction of Transcription Factor Binding Sites (TFBS) remains a challenge due to their short length and low information content. Comparative genomics approaches that simultaneously consider several related species and favor sites that have been conserved throughout evolution improve the accuracy (specificity) of the predictions but are limited due to a phenomenon called binding site turnover, where sequence evolution causes one TFBS to replace another in the same region. In parallel to this development, an increasing number of mammalian genomes are now sequenced and it is becoming possible to infer, to a surprisingly high degree of accuracy, ancestral mammalian sequences.
Recent developments in high-throughput sequencing (HTS) technologies have made it feasible to sequence the complete transcriptomes of non-model organisms or metatranscriptomes from environmental samples. The challenge after generating hundreds of millions of sequences is to annotate these transcripts and classify the transcripts based on their putative functions. Because many biological scientists lack the knowledge to install Linux-based software packages or maintain databases used for transcript annotation, we developed an automatic annotation tool with an easy-to-use interface.
Microarray experiments produce expression measurements in genomic scale. A way to derive functional understanding of the data is to focus on functional sets of genes, such as pathways, instead of individual genes. While a common practice for the pathway-level analysis has been functional enrichment analysis such as over-representation analysis and gene set enrichment analysis, an alternative approach has also been explored. In this approach, gene expression data are first aggregated at pathway level to transform the original data into a compact representation in which each row corresponds to a pathway instead of a gene. Thereafter the pathway expression data can be used for differential expression and classification analyses in pathway space, leveraging existing algorithms usually applied to gene expression data. While several studies have proposed the pathway-level aggregation methods, it remains unclear how they compare with one another, since the evaluations were done to a limited extent. Thus this study presents a comprehensive evaluation of six most prominent aggregation methods.
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. Studies have correlated risk of CRC development with dietary habits and environmental conditions. Gene signatures for any disease can identify the key biological processes, which is especially useful in studying cancer development. Such processes can be used to evaluate potential drug targets. Though recognition of CRC gene-signatures across populations is crucial to better understanding potential novel treatment options for CRC, it remains a challenging task.
Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism.
Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world, and metastasis is a significant cause to the high mortality in patients with HCC. However, the molecular mechanism behind HCC metastasis is not fully understood. Study of regulatory networks may help investigate HCC metastasis in the way of systems biology profiling.
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