Characterization Of The Integrative Precursor Protein-dna Complex Of Bacteriophage Mu

Bacteriophage Mu integrates and replicates its genome via DNA transposition. Mu transposition during integration is non-replicative (conservative) and generates simple insertions. Transposition during the lytic cycle is replicative and amplifies the Mu genome by cointegrate production. Mu therefore, must choose between these two pathways. Infecting Mu-DNA is found associated with a coinjected, 64-kDa virion protein bound noncovalently to its ends. Characterization of the protein-DNA complex is reported here.;Antiserum was prepared against the virion 64-kDa protein and used to probe an expression library of cloned Mu DNA sequences. The Mu {dollar}N{dollar} gene was mapped to the overproducing clones by physical and genetic techniques. Partial proteolysis of the N protein produced in vitro and the 64-kDa protein isolated from the protein-DNA complex showed them to be identical. The Mu {dollar}N{dollar} gene was sequenced and a region of homology to many site specific DNA binding proteins was observed.;The transposition end product produced in vitro by the N protein-Mu DNA complex isolated from Mu infected cells was examined by neutral and alkaline agarose gel electrophoresis. The protein-DNA complex was found to form an identical strand transferred end product as the mini-Mu control plasmid. The implication of these findings for Mu integration is that in vivo, the strand transferred product is probably processed by a second nick following the initial strand transfer reaction of transposition

amIcompositional: Simple Tests for Compositional Behaviour of High Throughput Data with Common Transformations

Compositional approaches are beginning to permeate high throughput biomedical sciences in the areas of microbiome, genomics, transcriptomics and proteomics. Yet non-compositional approaches are still commonly observed. Non-compositional approaches are particularly problematic in network analysis based on correlation, ordination and exploratory data analysis based on distance, and differential abundance analysis based on normalization. Here we describe the aIc R package, a simple tool that answers the fundamental question: does the dataset or normalization exhibit compositional artefacts that will skew interpretations when analyzing high throughput biomedical data? The aIc R package includes options for several of the most widely used normalizations and filtering methods. The R package includes tests for subcompositional dominance and coherence along with perturbation and scale invariance. Exploratory analysis is facilitated by an R Shiny app that makes the process simple for those not wishing to use an R console. This simple approach will allow research groups to acknowledge and account for potential artefacts in data analysis resulting in more robust and reliable inferences

Loss of nonsense mediated decay suppresses mutations in Saccharomyces cerevisiae TRA1

<p>Abstract</p> <p>Background</p> <p>Tra1 is an essential protein in <it>Saccharomyces cerevisiae</it>. It was first identified in the SAGA and NuA4 complexes, both with functions in multiple aspects of gene regulation and DNA repair, and recently found in the ASTRA complex. Tra1 belongs to the PIKK family of proteins with a C-terminal PI3K domain followed by a FATC domain. Previously we found that mutation of leucine to alanine at position 3733 in the FATC domain of Tra1 (<it>tra1-L3733A</it>) results in transcriptional changes and slow growth under conditions of stress. To further define the regulatory interactions of Tra1 we isolated extragenic suppressors of the <it>tra1-L3733A </it>allele.</p> <p>Results</p> <p>We screened for suppressors of the ethanol sensitivity caused by <it>tra1-L3733A</it>. Eleven extragenic recessive mutations, belonging to three complementation groups, were identified that partially suppressed a subset of the phenotypes caused by tra<it>1-L3733A</it>. Using whole genome sequencing we identified one of the mutations as an opal mutation at tryptophan 165 of <it>UPF1/NAM7</it>. Partial suppression of the transcriptional defect resulting from <it>tra1-L3733A </it>was observed at <it>GAL10</it>, but not at <it>PHO5</it>. Suppression was due to loss of nonsense mediated decay (NMD) since deletion of any one of the three NMD surveillance components (<it>upf1/nam7, upf2/nmd2</it>, or <it>upf3</it>) mediated the effect. Deletion of <it>upf1 </it>suppressed a second FATC domain mutation, <it>tra1-F3744A</it>, as well as a mutation to the PIK3 domain. In contrast, deletions of SAGA or NuA4 components were not suppressed.</p> <p>Conclusions</p> <p>We have demonstrated a genetic interaction between <it>TRA1 </it>and genes of the NMD pathway. The suppression is specific for mutations in <it>TRA1</it>. Since NMD and Tra1 generally act reciprocally to control gene expression, and the FATC domain mutations do not directly affect NMD, we suggest that suppression occurs as the result of overlap and/or crosstalk in these two broad regulatory networks.</p

Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology.

BACKGROUND: A normally developed placenta is integral to a successful pregnancy. Preeclampsia (PE) and intrauterine growth restriction (IUGR) are two common pregnancy related complications that maybe a result of abnormal placental development. Placental microRNAs (miRNAs) have been investigated as potential biomarkers for these complications, as they may play a role in placental development and pathophysiology by influencing gene expression. The purpose of this study is to utilize next-generation sequencing to determine miRNA and gene expression in human placental (chorionic villous) samples from three distinct patient groups with early-onset (EO) PE, IUGR, or PE + IUGR. METHODS: Placental tissues were collected from four patient groups (control [N = 21], EO-PE [N = 20], EO-IUGR [N = 18], and EO-PE + IUGR [N = 20]), and total RNA was used for miRNA and RNA sequencing on the Illumina Hiseq2000 platform. For stringent differential expression analysis multiple analysis programs were used to analyze both expression datasets in each patient group compared to gestational age-matched controls. RESULTS: Analysis revealed miRNAs and genes that are disease-specific, as well as others that were common between disease groups, which suggests common underlying placental pathologies in EO-PE and EO-IUGR. More specifically, 6 miRNAs and 22 genes were identified to be differentially expressed in all three patient groups. In addition, integrative analysis between the miRNA and gene expression datasets revealed candidate gene targets for miRNAs of interest. CONCLUSIONS: Integration of miRNA and RNA profiling in the same three subgroups of pregnancy complications, provides an alternate level of molecular information, in addition it can be used to better understand both unique and common molecular mechanisms involved in the pathophysiology of these diseases

Microbiome datasets are compositional: and this is not optional

Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.Peer ReviewedPostprint (published version

The microbiota of breast tissue and its association with breast cancer

In the United States, 1 in 8 women will be diagnosed with breast cancer in her lifetime. Along with genetics, the environmentcontributes to disease development, but what these exact environmental factors are remains unknown. We have previouslyshown that breast tissue is not sterile but contains a diverse population of bacteria. We thus believe that the host\u27s local microbiomecould be modulating the risk of breast cancer development. Using 16S rRNA amplicon sequencing, we show that bacterialprofiles differ between normal adjacent tissue from women with breast cancer and tissue from healthy controls. Women withbreast cancer had higher relative abundances of Bacillus, Enterobacteriaceae and Staphylococcus. Escherichia coli (a member ofthe Enterobacteriaceae family) and Staphylococcus epidermidis, isolated from breast cancer patients, were shown to induce DNAdouble-stranded breaks in HeLa cells using the histone-2AX (H2AX) phosphorylation (γ-H2AX) assay. We also found that microbialprofiles are similar between normal adjacent tissue and tissue sampled directly from the tumor. This study raises importantquestions as to what role the breast microbiome plays in disease development or progression and how we can manipulatethis for possible therapeutics or prevention

Impact of birth weight and postnatal diet on the gut microbiota of young adult guinea pigs.

BACKGROUND: The gastrointestinal tract (GIT) microbiota is essential to metabolic health, and the prevalence of the Western diet (WD) high in fat and sugar is increasing, with evidence highlighting a negative interaction between the GIT and WD, resulting in liver dysfunction. Additionally, an adverse METHODS: The fecal microbiota of normal birth weight (NBW) and LBW young guinea pig offspring, weaned onto either a control diet (CD) or WD was determined with 16S rRNA gene next generation sequencing at young adulthood following the early rapid growth phase after weaning. A liver blood chemistry profile was also performed. RESULTS: The life-long consumption of WD following weaning into young adulthood resulted in increased total cholesterol, triglycerides and alanine aminotransferase levels in association with an altered GIT microbiota when compared to offspring consuming CD. Neither birth weight nor sex were associated with any significant changes in microbiota alpha diversity, by measuring the Shannon\u27s diversity index. One hundred forty-eight operational taxonomic units were statistically distinct between the diet groups, independent of birth weight. In the WD group, significant decreases were detected in DISCUSSION: These results describe the GIT microbiota in a guinea pig model of LBW and WD associated metabolic syndrome and highlight several WD specific GIT alterations associated with human metabolic disease

Effect of Chemotherapy on the Microbiota and Metabolome of Human Milk: A Case Report

BACKGROUND: Human milk is an important source of bacteria for the developing infant and has been shown to influence the bacterial composition of the neonatal gut, which in turn can affect disease risk later in life. Human milk is also an important source of nutrients, influencing bacterial composition but also directly affecting the host. While recent studies have emphasized the adverse effects of antibiotic therapy on the infant microbiota, the effects of maternal chemotherapy have not been previously studied. Here we report the effects of drug administration on the microbiota and metabolome of human milk. METHODS: Mature milk was collected every two weeks over a four month period from a lactating woman undergoing chemotherapy for Hodgkin\u27s lymphoma. Mature milk was also collected from healthy lactating women for comparison. Microbial profiles were analyzed by 16S sequencing and the metabolome by gas chromatography-mass spectrometry. FINDINGS: Chemotherapy caused a significant deviation from a healthy microbial and metabolomic profile, with depletion of genera Bifidobacterium, Eubacterium, Staphylococcus and Cloacibacterium in favor of Acinetobacter, Xanthomonadaceae and Stenotrophomonas. The metabolites docosahexaenoic acid and inositol known for their beneficial effects were also decreased. CONCLUSION: With milk contents being critical for shaping infant immunity and development, consideration needs to be given to the impact of drugs administered to the mother and the long-term potential consequences for the health of the infant