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Nucleic acids research.
Hiley SL, Jackman J, Babak T, Trochesset M, Morris QD, Phizicky E, Hughes TR      2005     >Caption source<
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Detection and discovery of RNA modifications using microarrays.
Figure 1 Detection of covalent modification by microarray. (A) Modification disrupts base pairing between RNA and probe. Wild-type tRNA LysCTT (top) contains a dimethylguanosine residue at position 26, which disrupts pairing with the probe. trm1-{{Delta}} tRNA LysCTT (bottom) lacks this modification and can pair completely with the probe (see also Figure 2B). A schematic diagram of the tRNA is shown below. Rectangles represent probes complementary to tRNA sequence, and thin lines represent probes complementary to 5' and 3' genomic flanking regions. The relative fluorescence of each probe is indicated by color-coded rectangles above the schematic diagram (according to the scale on the right); the tRNA nucleotides covered by each oligo are shown. (B) Analysis of strains defective for tRNA modification. tRNA oligos (ordered from 5' to 3') versus individual experiments (described below the figure) are plotted. Oligos to which there was significantly better binding in the mutant tRNA samples are indicated by red color, as shown by the color-bar in (A). Groups of probes covering tRNA nucleotides modified by each enzyme are outlined in blue rectangles. The type of modification and positions known to be modified by each enzyme are shown. Only tRNA probes with ratios at least 2-fold above wild type are shown.
  • Spreadsheets containing the data displayed in Figures 1B and 2A are also available on the website.
  • One tRNA from each of the experiments in which the methylation defect was detected is shown in schematic form as described in Figure 1A.
  • The fluorescence in each channel was measured and compared as a ratio [(mutant RNA fluorescence)/(wild-type RNA fluorescence)] (for details see Materials and Methods). Figure 1A shows an example of a detectable modification: the presence of at position 26 of LysCTT tRNA appears to interfere with binding to the probe sequence, because in probes overlapping position 26 there is a relative increase in binding of the tRNA in the trm1- mutant strain (which lacks the modification) compared with the wild-type.
  • The results from microarray analysis of 19 tRNA modifying enzymes are summarized in Figure 1B.
  • Whereas Figure 1A shows all oligos corresponding to a single tRNA (and emphasizes the specificity of the technique), this Figure summarizes the differential hybridization to all 70 tRNA sequences across 21 experiments (and shows the ability of technique to detect trends that emerge across all experiments).
Nucleic acids research.
Hiley SL, Jackman J, Babak T, Trochesset M, Morris QD, Phizicky E, Hughes TR      2005     >Caption source<
Extra large 
Detection and discovery of RNA modifications using microarrays.
Figure 2 tRNA methylation analyzed by microarray. (A) Three different types of detectable methylation. Unique tRNA probes with ratios of at least 2 are color-coded according to the scale shown and displayed from 5' to 3' of the tRNA sequence. The tRNA isoforms and specific nucleotides covered are shown to the right of the figure. Oligos predicted to be affected in the each experiment are outlined with blue rectangles. (B) Schematic representation of selected tRNAs. One tRNA from each of the experiments in which the methylation defect was detected is shown in schematic form as described in Figure 1A. Functional groups involved in Watson–Crick base pairing are circled in blue; modifications are circled in red.
  • Spreadsheets containing the data displayed in Figures 1B and 2A are also available on the website.
  • Wild-type tRNA LysCTT (top) contains a dimethylguanosine residue at position 26, which disrupts pairing with the probe. trm1- tRNA LysCTT (bottom) lacks this modification and can pair completely with the probe (see also Figure 2B).
  • Figure 2A shows a detailed view of the successfully detected methylation modifications.
  • Selected tRNAs from each of these mutant strains are shown in detail in Figure 2B.
Nucleic acids research.
Hiley SL, Jackman J, Babak T, Trochesset M, Morris QD, Phizicky E, Hughes TR      2005     >Caption source<
Extra large 
Detection and discovery of RNA modifications using microarrays.
Figure 4 Novel modification events. (A) Potential new targets for Trm5 and the Gcd10/Gcd14 complex. Modifications and target sites are proposed for three tRNAs whose RNA sequences have not been published and RNA modification profiles are unknown. (B) Demonstration of m1A58 modification in tRNAGlnCUG. Inferred RNA sequence of tRNAGlnCUG showing the position of the primer used to detect m1A modification at position 58 (highlighted in blue). The four positions that are underlined are the residues of this minor tRNA species that differ from the sequence of the other two previously characterized tRNAGln isoforms (both tRNAGlnUUG). The residues found at those positions in tRNAGlnUUG are shown in parentheses above. (C) Primer extension analysis of RNA derived from either gcd14-{{Delta}} (lane 1) or wild-type cells (lane 2). Lanes C, T, A and G are sequencing lanes of the primer extended RNA. (D) Two elongation-specific tRNA Met oligos show formamide-dependent differential hybridization in GCD10/GCD14 mutants. A schematic diagram and the corresponding values in the chart show that probes covering Mete nucleotides 11–25 and 16–30 exhibited high ratios in both experiments targeting the GCD10–GCD14 complex. tRNA and probe sequences are shown below; the overlapping region, Mete 16-25, is outlined in red. The table to the right shows the difference in ratio of representative probes for two formamide concentrations.
  • In the case of the Gcd10–Gcd14 complex, these probes correspond to MetCAT oligos, examined in detail in Figure 4D.
  • Schematic diagrams of each of these tRNAs with ratios from the relevant array are shown in Figure 4A.
  • To rule out the possibility of contamination by hybridization to the major tRNA GlnUUG species (which were already known to contain m1A 58), we used a probe for primer extension that spanned a region at the 3' end which overlaps one of the positions that differs between tRNAUUG and tRNACUG species (Figure 4B).
  • Using this primer, a block is observed at position A59 in the RNA from wild-type cells (Figure 4C, lane 2), consistent with the presence of m1A 58; this block is absent in RNA from mutant cells (Figure 4C, lane 1), which extends to the 5' end of the tRNA.
  • The sequencing reactions demonstrate the specificity of the primer for this tRNA species (Figure 4C, lanes C, T, A and G) since the sequence at the positions indicated by arrows are all those of the tRNAGlnCUG isoform (C34, A42 and A52).
  • We noted that in addition to position 58-specific probes, oligos specific for the elongator Met tRNA nucleotides 11–25 and 16–30 had high ratios in both the TetO7-GCD10 and gcd14-1ts arrays (Figure 4C).
  • Unlike other high-ratio oligos, differential binding to these probes was sensitive to the formamide concentration in the hybridization buffer; the ratios of probes 2125 and 2126 were significantly higher on arrays hybridized in 33% formamide than 25% (Figure 4C; see text below).
Nucleic acids research.
Hiley SL, Jackman J, Babak T, Trochesset M, Morris QD, Phizicky E, Hughes TR      2005     >Caption source<
Extra large 
Detection and discovery of RNA modifications using microarrays.
Figure 3 18S rRNA modification by Dim1p. A schematic diagram of the 3' portion of 18S RNA from the dim1-Y131G microarray is shown. The 18S oligo with the highest ratio was 11157, complementary to the modified adenosines in the 3' terminal loop of the RNA, shown below.
  • Probes with unusual behavior on the trm1- microarray have previously been observed as false-positives [see (9) Figure 3, dus2-].
  • One of these modifications is the formation at consecutive nucleotides in the 3' terminal of 18S rRNA (17) by Dim1p, as was successfully detected by microarray analysis of a catalytic knockout (Y131G) of DIM1 (Figure 3).
Nucleic acids research.
Ou HY, Smith R, Lucchini S, Hinton J, Chaudhuri RR, Pallen M, Barer MR, Rajakumar K      2005     >Caption source<
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ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes.
Figure 1 Microarray-Assisted mobilome Prospecting (MAmP): a method for determining the discrepancy between the physical genome size and that accounted for by known genes represented on an expanded species-specific microarray. (a) A schematic representation of a microarray-based CGI output for an hypothetical region of the genome in a strain under investigation by the MAmP technique. Scanned raw data are normalized permitting classification of microarray-represented genes as ‘Present (+)’ or ‘Absent (–)’ in individual test strains. (b) The arrows represent the genetic organization of these CDS within E.coli K-12 MG1655, E.coli K-12 W3110, E.coli O157 EDL933, S.flexneri 2a Sf301 or other virulence-associated gene clusters included on the MG1655, W3110 or ShE.coli microarrays. (c) Contiguous CDS classified as ‘Present’ are merged into an IC with intergenic non-coding segments between the contiguous CDS included in the corresponding IC. Each IC was then extended in both directions by lengths equal to half the flanking 5' and 3' intergenic segments, as indicated by the double-headed arrows of lengths 0.5x and 0.5y in the examples shown. When the ShE.coli meta-array sequences were used, each probe was mapped onto a single source reference template to allow for the generation of specific ICs. (d) The size of the MVG was calculated as the sum of all IC lengths. Consequently, the size of the non-microarray-borne novel mobilome was estimated as equal to the discrepancy between the pulsed-field gel electrophoresis-determined physical genome size and the MVG size. Figure not drawn to scale.
  • The MAmP approach combines CGI, ArrayOme and pulsed-field gel electrophoresis (PFGE) to predict the size of the novel, non-microarray-borne mobilome in a test strain (Figure 1).
  • The method used is schematically shown in Figure 1.
  • Inputs of these data into ArrayOme produced 113 or 193 ICs (see Figure 1) scattered along the MG1655 template chromosome depending on whether the ‘Indeterminate’ CDS were classified as ‘Present’ or ‘Absent’, respectively.
  • Importantly, the ArrayOme approach takes account of likely lost intergenic sequences (Figure 1).
Nucleic acids research.
Ou HY, Smith R, Lucchini S, Hinton J, Chaudhuri RR, Pallen M, Barer MR, Rajakumar K      2005     >Caption source<
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ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes.
Figure 2 A flow diagram of the logic steps used for in silico CGI. CDS, P, H and S denote CDS mapped onto specific probes, individual microarray-borne amplicon probes, H-values and Bit scores, respectively. P i and P j denote distinct individual probes, with the subscripts i and j identify matching CDS, H-values and Bit scores. The steps involved in the primary similarity search are shown in (a), while the cross-hybridization algorithm that re-categorizes CDS from ‘Putatively Present’ to ‘Present’ or ‘Absent’ are shown in (b). A direct comparison of in silico generated data and true experimental CGI data for E.coli EDL933 obtained using the MG1655 microarray was used to validate the algorithm. The key threshold values, H 0 = 0.40 and Hx = 0.96, were set to optimize the sensitivity and specificity of identifying genes as ‘Present’ when using the in silico as compared to experimental approach (see Figure 3).
  • The in silico CGI procedure applied included the following steps (Figure 2): Each of the DNA sequences of the probes was used as a query in a similarity search against a test genome sequence using a locally installed version of BLASTN (35) and default NCBI BLASTN parameters.
  • Based on the observed spread of H-values corresponding to the true experimental data, the threshold value, H 0 = 0.40, was selected as the primary discriminant between CDS designated as ‘Putatively Present’ and those classed as ‘Absent’ (Figures 2 and 3).
  • The Hx threshold value was set at a high value of 0.96 to minimize the likelihood of miscalling a CDS as ‘Present’ when sequence similarity existed between its probe and a second microarray-borne probe(s) mapped onto an alternate CDS (Figure 2).
  • In subsequent in silico hybridization simulations, CDS were judged to be ‘Present’ or ‘Absent’ using the algorithm shown in Figure 2 with the threshold values set at H 0 = 0.40 and Hx = 0.96.
  • The total sets of MG1655 and ShE.coli microarray DNA probes were subjected to BLASTN analysis against each of the six completed genomes and the results interpreted using the logic steps shown in Figure 2.
Nucleic acids research.
Ou HY, Smith R, Lucchini S, Hinton J, Chaudhuri RR, Pallen M, Barer MR, Rajakumar K      2005     >Caption source<
Extra large 
ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes.
Figure 3 The distribution of H-values corresponding to 4264 amplicon probes spotted onto the MG1655 microarray obtained following a BLASTN similarity search against the EDL933 chromosomal sequence are shown. Interval-grouped H-values are plotted with the data stratified into the experimental CGI categories of ‘Present’ (3775), ‘Absent’ (400) and ‘Indeterminate’ (89). The selected threshold values for in silico CGI, H 0 = 0.40 and Hx = 0.96, are as indicated. The numbers in the boxes at the top right corner correspond to the ‘Number of CDS’ associated with the two bars that extend beyond the limits of the graph. The inset table shows a direct comparison of experimental CGI data derived by Anjum et al. (18) and in silico CGI data for the CDS classified as ‘Present’ or ‘Absent’ only. The sensitivity (Sn ) and specificity (Sp ) of identifying genes as ‘Present’ when using the in silico as compared to experimental approach, are shown on the right-hand side.
  • The key threshold values, H 0 = 0.40 and Hx = 0.96, were set to optimize the sensitivity and specificity of identifying genes as ‘Present’ when using the in silico as compared to experimental approach (see Figure 3).
  • The distribution of H-values corresponding to probes was bipolar with the average H-value for the 400 ‘Absent’ CDS (0.087; SD = 0.009) being significantly less than that for the 3775 CDS identified as ‘Present’ (0.962; SD = 0.110) and the 89 microarray-represented CDS of ‘Indeterminate’ status (0.852; SD = 0.309) (Figure 3).
  • Based on the observed spread of H-values corresponding to the true experimental data, the threshold value, H 0 = 0.40, was selected as the primary discriminant between CDS designated as ‘Putatively Present’ and those classed as ‘Absent’ (Figures 2 and 3).
  • With the EDL933 data set, this algorithm correctly predicted 389/400 ‘Absent’ and 3714/3775 ‘Present’ CDS for EDL933, yielding satisfactory sensitivity (98.4%) and specificity rates (99.7%) in the in silico CGI classification of CDS as ‘Present’ (Figure 3).
Nucleic acids research.
Sato K, Hosokawa K, Maeda M      2005     >Caption source<
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Non-cross-linking gold nanoparticle aggregation as a detection method for single-base substitutions.
Figure 1 Titration experiments. (a) Sequences of the probe and the two samples: complementary strand (CS) and typing primer (TP). (b and c) Titration plots. The abscissas express the final concentrations. (b) The complementary strand. (c) Mixture of the two samples.
  • Performance of the NCL GNP aggregation assay was evaluated by titration experiments (Figure 1).
  • As shown in Figure 1b, 100 nM of the complementary strand was detectable with the spectrometer.
  • Second, mixtures of the complementary strand and the typing primer were tested in the same way (Figure 1c).
Nucleic acids research.
Sato K, Hosokawa K, Maeda M      2005     >Caption source<
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Non-cross-linking gold nanoparticle aggregation as a detection method for single-base substitutions.
Figure 2 Schematic diagram for the detection of single-base substitution at target base X using NCL GNP aggregation assay. In Step 3, the same (not the complementary) kind of ddNTP as X is attached to the primer. This notation is used throughout this paper.
  • Figure 2 shows steps for the detection of single-base substitution using NCL GNP aggregation.
  • Other three products make single-base mismatches at the free ends of the duplexes. Figure 2 illustrates an example of adenine-ended probe.
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