Location of norflurazon resistance mutations on the PDS protein.

<p>(<b>A</b>) Primary structure of <i>C. reinhardtii</i> prePDS protein showing plastid transit peptide, dinucleotide binding Rossmann-like domain, and amino acid substitutions affecting PDS function (see Fig. 8). The same colour coding is used throughout <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099894#pone-0099894-g007" target="_blank">Figs 7</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099894#pone-0099894-g008" target="_blank">8</a>. (<b>B</b>) Ribbon representation of the predicted three-dimensional structure of <i>C. reinhardtii</i> PDS. Left: Phyre-based 3DLigandSite model; middle: Modeller-based BioSerf predicted structure; right: SwissModel predicted structure. Amino acids shown in A are indicated. The conserved Rossmann-like domain is shown as a yellow ribbon. (<b>C</b>) Residues in the predicted FAD-binding domain. Amino acids in the Rossmann-like domain are shaded yellow. Amino acids conferring norflurazon resistance lie adjacent to (F131/red, L505/green) or are part of the predicted domain (V472/pink). (<b>D</b>) 3D structure of the predicted FAD-binding region. Bound FAD is shown in the centre of the structure as a ball stick model. Yellow atoms are part of the Rossmann-like domain. F131, R268, V472, L505 and L517 are shown.</p

The influence of increasing norflurazon concentration on growth of <i>C. reinhardtii</i>.

<p>Cultures were inoculated to a density of 1×10⁵ cells/ml on day 0 and optical density at 750 nm used to estimate cell density. (<b>A</b>) WT progenitor <i>PDS1</i> strain. (<b>B</b>) NFR1 mutant <i>pds1-nfr1d</i> strain. The mean values of three experiments were plotted. Standard error bars are shown.</p

Resistance levels of pNFR1 transformants to norflurazon.

<p>Cells were inoculated at an initial OD750 of 0.05 and were grown in TAP media with varying concentrations of norflurazon. (<b>A</b>) Norflurazon resistance of cw92 (norflurazon sensitive non-transformed strain) and pNFR1 A2, A10, 1A1 and 2A1 transformants. Optical density was measured after 7 days of growth. (<b>B–C</b>) Growth curves of NFR1 cw92 transformants and non-transformed cw92 strain in liquid TAP media without norflurazon (<b>B</b>) or with 150 µM norflurazon (<b>C</b>). Green line: cw92; blue line: A2; yellow line: A10; purple line 1A1; red line: 2A1. The mean values of three cultures were plotted. Standard error bars are shown.</p

Localisation of the norflurazon resistance mutation in the NFR1 strain.

<p>(<b>A</b>) Section of Chromosome 12 of <i>C. reinhardtii</i> containing the <i>PDS1</i> gene (Cre12.g509650). Exons are shown as boxes; white boxes represent coding regions and black boxes UTRs. Base one is the adenine in the ATG start codon. At base 476 in exon 2, the WT thymine is replaced by guanine in the <i>pds1-nfr1d</i> allele resulting in a phenylalanine to valine missense mutation. Primers used to amplify the gene and an inserted <i>Cla I</i> site are shown. (<b>B</b>) The F131V substitution (red) is found within a highly conserved region of the PDS protein. Coordinates correspond to the <i>C. reinhardtii</i> PDS sequence, where amino acid one is the initiator methionine at the start of the transit peptide.</p

DNA blot showing Gulliver transposon bands in Hind III digests of total DNA from parental NFR1a and PQR20 strains and a diploid strain.

<p>Letters on the left represent Gulliver transposons <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099894#pone.0099894-Ferris1" target="_blank">[26]</a>. Arrowheads indicate bands unique to either parent strain.</p

Nuclear transformation vector and analysis of pNFR1 transformants.

<p>(<b>A</b>) pNFR1 and pWTPDS1 transformation vectors. The two vectors are distinguished by a single base substitution conferring norflurazon resistance in pNFR1. Shown are coding regions (black boxes), pBluescript vector backbone (thin grey line), extent of cDNA probe used for DNA hybridization and restriction enzyme sites. (<b>B</b>) Map of the <i>PDS1</i> gene (white box) located on chromosome 12 (Chr12). Restriction sites and overlap region of the cDNA probe are shown. (<b>C</b>) Blots of digested DNA from pNFR1 transformants and untransformed cw92 strain hybridized with a <i>PDS1</i> cDNA probe. Restriction enzyme used, band sizes and MW standards are indicated. (<b>D</b>) Protein blot of fractionated total cell protein from pNFR1 cw92 transformants, the cc621 WT strain and the non-transformed cw92 strain incubated with an affinity-purified polyclonal antibody raised against a PDS peptide. The PDS band is arrowed.</p

Location of mutations on the <i>C. reinhardtii</i> PDS sequence.

<p>Shown are amino acid residue numbers in <i>C.reinhardtii</i> PDS, species in which the missense mutation was isolated, numbering of the original substitutions in homologous PDS proteins and phenotype of the substitutions. Synechococcus PCC7942 and Synechocystis PCC 6803 are listed. Colour coding of amino acids is the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099894#pone-0099894-g007" target="_blank">Figure 7</a>.</p

An overview of the implementation of alphabetr.

(A) From the population of interest, multiple samples of 10–300 T cells are sorted into 96-well plates. This design allows for a given clone to be sampled in multiple wells. (B) Multiplex RT-PCR is used to create cDNA libraries of CDR3α and CDR3β from each well, and (C) high-throughput sequencing is used to recover the unpaired CDR3α and CDR3β sequences of the clones sampled in each well. (D)(i) A random subset of the wells is chosen, (ii) association scores between every unique α and β found across the wells within this sample are calculated, and (iii) the set of unique αβ pairs that maximises the sum of association scores is identified using the Hungarian algorithm [39]. Step (iii) is illustrated for a particular set of CDR3α and CDR3β recovered from one well, as a matrix of association scores calculated across all wells in the subsample. (E) Steps D(i)-(iii) are repeated to generate a consensus list of pairs, filtering out candidates that appear rarely across replicates. (F) The frequencies of each remaining candidate αβ pair within the parent population are estimated using a maximum-likelihood approach, assuming only sharing (no dual TCR). Dual TCRα clones α1 α2 β1 are then distinguished from clones apparently sharing a TCRβ chain (α1 β1 and α2 β1), by examining the patterns of co-occurrences of the three chains, and the frequencies of these clones are re-calculated. (G) The output of the algorithm is a list of single and dual TCRα clones, each with their estimated frequency within the parent population. See text and Methods for more details.</p

Depth and accuracy of <i>αβ</i> pairings generated by alphabetr, for a range of overall sample sizes, sampling strategies and underlying distributions of clone sizes.

<p>Simulations were performed using <i>in silico</i> data sets of one or five plates using six different sampling strategies (see text) and different degrees of skewness in clonal frequencies, as indicated by the number of clones comprising 50% of the population when ranked by frequency. ‘Threshold’ refers to the stringency of pair association, <i>T</i> (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005313#sec014" target="_blank">Methods</a>). <b>(A)</b> The proportion of the most abundant 50% of clones that were identified. <b>(B)</b> The proportion of the least abundant 50% of clones that were identified. <b>(C)</b> The overall depth was influenced strongly by the tail depth, indicating that data from one plate may be sufficient for recovering the most common clones. <b>(D)</b> The rate at which CDR3<i>α</i> and CDR3<i>β</i> sequences were incorrectly paired (false positive rate, FPR).</p

Comparison of well occupancy patterns of the clones identified by alphabetr and in ref. [22].

<p>For each method, TCR<i>αβ</i> pairs identified for all tumour samples were combined to estimate the distribution of the number of wells in which the chains co-appeared. The differences between these distributions indicate the relative efficiency with which the two algorithms identify clones, as a function of their abundance.</p