Discrimination of Spore-Forming Bacilli Using spoIVA

A method of discriminating between spore-forming and non-spore-forming bacteria is based on a combination of simultaneous sporulation-specific and non-sporulation-specific quantitative polymerase chain reactions (Q-PCRs). The method was invented partly in response to the observation that for the purposes of preventing or reducing biological contamination affecting many human endeavors, ultimately, only the spore-forming portions of bacterial populations are the ones that are problematic (or, at least, more problematic than are the non-spore-forming portions). In some environments, spore-forming bacteria constitute small fractions of the total bacterial populations. The use of sporulation-specific primers in Q-PCR affords the ability to assess the spore-forming fraction of a bacterial population present in an environment of interest. This assessment can provide a more thorough and accurate understanding of the bacterial contamination in the environment, thereby making it possible to focus contamination- testing, contamination-prevention, sterilization, and decontamination resources more economically and efficiently. The method includes the use of sporulation-specific primers in the form of designed, optimized deoxyribonucleic acid (DNA) oligonucleotides specific for the bacterial spoIVA gene (see table). [In "spoIVA," "IV" signifies Roman numeral four and the entire quoted name refers to gene A for the fourth stage of sporulation.] These primers are mixed into a PCR cocktail with a given sample of bacterial cells. A control PCR cocktail into which are mixed universal 16S rRNA primers is also prepared. ["16S rRNA" denotes a ribosomal ribonucleic acid (rRNA) sequence that is common to all organisms.] Following several cycles of heating and cooling according to the PCR protocol to amplify amounts of DNA molecules, the amplification products can be analyzed to determine the types of bacterial cells present within the samples. If the amplification product is strong, relative to the product of a control PCR sequence, then it is concluded that the bacterial population in the sample consists predominantly of spore-forming cells. If the amplification product is weak or nonexistent, then it is concluded that the bacterial population in the sample consists predominantly or entirely of non-spore-forming cells

The nature of practice-based knowledge and understanding

The chapter situates teaching as a practice in which the knowledge and understanding required of expert practitioners is neither wholly practicol nor wholly theoretical. The chapter discusses the natuire of teacher knowledge and understanding and the importance of the development of practical judgement,which might characterised as a capacity to do the right thing at the right time, to respond flexibly and appropriately in the moment. Judgement is a fundamental capacity for teachers

Q-PCR Based Bioburden Assessment of Drinking Water Throughout Treatment and Delivery to the International Space Station

Previous studies indicated evidence of opportunistic pathogens samples obtained during missions to the International Space Station (ISS). This study utilized TaqMan quantitative PCR to determine specific gene abundance in potable and non-potab[e ISS waters. Probe and primer sets specific to the small subunit rRNA genes were used to elucidate overall bacterial rRNA gene numbers. while those specific for Burkholderia cepacia and Stenotrophomonas maltophilia were optimized and used to probe for the presence of these two opportunistic pathogens. This research builds upon previous microbial diversity studies of ISS water and demonstrates the utility of Q-PCR tool to examine water quality

Allelic variation in <i>HAP1</i> affects ethanol-induced cross protection against H₂O₂.

<p>(A) Schematic of reciprocal hemizygosity analysis. Each block represents a gene, and each hybrid strain contains a single-copy deletion of <i>hap1</i> or <i>top3</i>, and a single copy of the respective S288c (lab) or YPS163 (oak) allele. (B) Representative acquired H₂O₂ resistance assays for wild-type YPS163, the YPS163-S288c hybrid, and the reciprocal hemizygotes. (C) Each survival score plot shows the mean and standard deviation of biological triplicates. Asterisks represent significant differences in acquired resistance between denoted strains (** <i>P</i> < 0.01, *** <i>P</i> < 0.001, ns = not significant (<i>P</i> > 0.05), <i>t</i>-test).</p

Natural variation in ethanol-induced cross protection against H₂O₂.

<p>(A) A representative acquired H₂O₂ resistance assay is shown. S288c (lab strain–DBY8268) and YPS163 (wild oak strain) were exposed to 5% ethanol or mock (5% water) pretreatment for 60 min, washed, exposed to 11 doses of severe H₂O₂ for 2 hr, and then plated to score viability. (B) A single survival score was calculated from the viability at all H₂O₂ doses (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#sec007" target="_blank">Materials and Methods</a>). Each plot shows the mean and standard deviation of 4 independent biological replicates. The replicates for mock-treated YPS163 all had the same tolerance score and thus zero standard deviation (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#pgen.1007335.s006" target="_blank">S1 Table</a> for raw numerical data). Asterisks represent resistance that was significantly different from mock-treated cells (*** <i>P</i> < 0.001, <i>t</i>-test).</p

A Fosmid Cloning Strategy for Detecting the Widest Possible Spectrum of Microbes from the International Space Station Drinking Water System

In this study, fosmid cloning strategies were used to assess the microbial populations in water from the International Space Station (ISS) drinking water system (henceforth referred to as Prebiocide and Tank A water samples). The goals of this study were: to compare the sensitivity of the fosmid cloning strategy with that of traditional culture-based and 16S rRNA-based approaches and to detect the widest possible spectrum of microbial populations during the water purification process. Initially, microbes could not be cultivated, and conventional PCR failed to amplify 16S rDNA fragments from these low biomass samples. Therefore, randomly primed rolling-circle amplification was used to amplify any DNA that might be present in the samples, followed by size selection by using pulsed-field gel electrophoresis. The amplified high-molecular-weight DNA from both samples was cloned into fosmid vectors. Several hundred clones were randomly selected for sequencing, followed by Blastn/Blastx searches. Sequences encoding specific genes from Burkholderia, a species abundant in the soil and groundwater, were found in both samples. Bradyrhizobium and Mesorhizobium, which belong to rhizobia, a large community of nitrogen fixers often found in association with plant roots, were present in the Prebiocide samples. Ralstonia, which is prevalent in soils with a high heavy metal content, was detected in the Tank A samples. The detection of many unidentified sequences suggests the presence of potentially novel microbial fingerprints. The bacterial diversity detected in this pilot study using a fosmid vector approach was higher than that detected by conventional 16S rRNA gene sequencing

<i>HAP1</i> is required for full induction of <i>CTT1</i> gene expression and cellular peroxidase activity during ethanol stress.

<p>(A) Fold induction of <i>CTT1</i> mRNA in indicated strains following 30 min ethanol stress compared to unstressed cells, assessed by qPCR. (B) Peroxidase activity measured in cell-free extracts in either mock-treated or ethanol-stressed cells. The plots indicate the mean and standard deviation of biological triplicates (mRNA) or quadruplicates (peroxidase activity). Asterisks represent significant differences in <i>CTT1</i> mRNA induction or peroxidase activity between denoted strains (* <i>P</i> < 0.05, ** <i>P</i> < 0.01, paired <i>t</i>-test).</p

<i>CTT1</i> function is necessary for ethanol-induced cross protection against H₂O₂.

<p>(A) Representative acquired H₂O₂ resistance assays for wild-type YPS163 and the YPS163 <i>ctt1Δ</i> mutant. (B) Survival score plots indicating the mean and standard deviation of biological triplicates. Asterisks represent significant differences in acquired resistance between denoted strains (*** <i>P</i> < 0.001, <i>t</i>-test).</p

Expression variation in Hap1p regulatory targets implicates oxidative stress defense genes as the direct effectors of ethanol-induced cross protection against H₂O₂.

<p>(A) Overlap between genes that were <i>HAP1</i> eQTL hotspot targets from [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#pgen.1007335.ref064" target="_blank">64</a>], genes with defective induction in S288c vs. YPS163 from [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#pgen.1007335.ref064" target="_blank">64</a>], and direct targets of <i>HAP1</i> identified via ChIP experiments compiled from [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#pgen.1007335.ref081" target="_blank">81</a>]. (B) Descriptions of the eight genes that overlapped for all three criteria. (C) Previous eQTL mapping of the yeast ethanol response (newly plotted here using data described in [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007335#pgen.1007335.ref064" target="_blank">64</a>]), implicated <i>HAP1</i> as causative for natural variation in <i>CTT1</i> induction levels during ethanol stress.</p