Signs of Susy

After a brief introduction to 21st century fundamental physics suitable for the layman with a reasonable level of mathematical competence, I introduce the concept of unnaturalness in Standard Model electroweak symmetry breaking and Supersymmetry (Susy) as a potential solution. The optimally natural situation in Susy in light of the 2012 discovery of a Higgs boson is derived, namely that of almost maximal mixing, with the scalar top partners almost as light as can be. The discovery is also interpreted numerically in terms of the Next-to-Minimal Supersymmetric Standard Model, with greater emphasis placed on the visibility of the Higgs boson at the observed mass, i.e. on signal strengths. I introduce simple models of gauge-mediated Susy breaking (GMSB), and how their generalisation leads to a richer parameter space. I then investigate the role played by the mediation scale of GMSB: this is found to be as a control of the extent to which Yukawa couplings de-tune flavour-blind relations set by gauge couplings. Finally, issues relating to the discovery or exclusion of Susy at colliders are discussed. Bounds are derived for the masses of new particles from Large Hadron Collider searches for excesses of jets and missing energy without leptons, and compared to constraints arising from Higgs boson searches, for models of GMSB and the Constrained Minimal Supersymmetric Standard Model. I present a novel search strategy for new physics signatures with two neutral, stable particles, when such particles are produced by boosted decays. (Susy examples include models with light gravitinos, pseudo-goldstinos, singlinos or new photinos.) The method is shown to produce sharp mass peaks that enhance the visibility of the signal

Novel cis-selective and non-epimerisable C3 hydroxy azapodophyllotoxins targeting microtubules in cancer cells

Podophyllotoxin (PT) and its clinically used analogues are known to be powerful antitumour agents. These compounds contain a trans fused strained γ-lactone system, a feature that correlates to the process of epimerisation, whereby the trans γ-lactone system of ring D opens and converts to the more thermodynamically stable cis epimer. Since these cis epimers are known to be either less active or lacking antitumour activity, epimerisation is an undesirable feature from a chemotherapeutic point of view. To circumvent this problem, considerable efforts have been reported, amongst which is the synthesis of azapodophyllotoxins where the stereocentres at C2 and C3 are removed in order to preclude epimerisation. Herein we report the identification of a novel C3 hydroxy, cis-selective γ-lactone configuration of ring C in the azapodophyllotoxin scaffold, through an efficient stereoselective multicomponent reaction (MCR) involving fluorinated and non-fluorinated aldehydes. This configuration releases the highly strained trans γ-lactone system in podophyllotoxin analogues into the more thermodynamically stable cis γ-lactone motif and yet retains significantly potent activity. These compounds were evaluated against the human cancer lines MCF-7 and 22Rv1 in vitro. Fourteen out of the seventeen tested compounds exhibited sub-micromolar activity with IC50 values in the range of 0.11–0.91 μM, which is comparable and in some cases better than the activity profile of etoposide in this assay. Interestingly, we obtained strong evidence from spectroscopic and X-ray data analyses that the previously reported structure of similar analogues is not accurate. Molecular modelling performed using the podophyllotoxin binding site on β tubulin revealed a novel binding mode of these analogues. Furthermore, sub-cellular study of our compounds using immunolabelling and confocal microscopy analyses showed strong microtubule disruptive activity, particularly in dividing cells

Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell-cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing "arms race." Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic's effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell-cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated

Identifying the necessary conditions for constitutive competence to be effective in inhibiting MGE transmission.

<p>(<b>A</b>) Heatmap showing the outcome of simulations in which MGEs infect cells competent for transformation at rate τ = 10⁻⁴. The colour of the heatmap represents the proportion of the population infected by MGEs over the course of each simulation. Each cell represents a specific MGE transmissibility (β) and transformation asymmetry (φ); the “MH” and “MV” components show simulations with MGEs having relatively greater propensities for horizontal and vertical transmission, respectively. (<b>B</b>) Heatmap, displayed as in panel A, but this time comparing the effects of varying β against changing the rate of transformation (τ) with a fixed value of φ = 0.1. (<b>C</b>) Conditions necessary for transformation to provide a fitness advantage to the population. This heatmap shows the ratio of the total number of cells in two independent sets of simulations: one in which cells were nontransformable, and another in which the cells were transformable and suffered an associated cost (<i>c</i>_C). In both sets of simulations, either the MH or MV MGEs were present in the populations, each of which was associated with a varying cost to the host (<i>c</i>_M); transformation was only effective at inhibiting the transmission of MV. The higher the value of the ratio, indicated by the heatmap colour, the relatively greater the size of the bacterial population when cells were transformable. Raw data are tabulated in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s001" target="_blank">S1 Data</a>.</p

Evidence for coexistence of susceptible and infected BC1-19F cells within individual carriage episodes.

<p>The displayed phylogeny was generated based on point mutations, excluding base substitutions likely to have been introduced by recombination (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s005" target="_blank">S4 Fig</a>). Leaf nodes are annotated to indicate whether the <i>comYC</i> gene, required for efficient transformation, is intact (green dash) or disrupted by a prophage insertion (orange dash; see key in Figs <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.g008" target="_blank">8</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s006" target="_blank">S5</a>). Specific cases of changes in prophage content within what are likely to represent individual carriage episodes are highlighted. Each box displays the annotation of a specific prophage (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s018" target="_blank">S2 Table</a>), along with sequence read mapping heatmaps beneath showing the depth of coverage across the viral sequence for individual isolates from a single host: blue for low levels of mapping, indicating the sequence is absent, and red for high levels of mapping, indicating it is present (see scale in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.g008" target="_blank">Fig 8</a>). The isolates are ordered by the date of isolation. Epidemiological data are summarised in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s019" target="_blank">S3 Table</a>.</p

The effect of different patterns of competence expression on the transmission of MGEs that benefit their host.

<p>(<b>A</b>) Heatmap summarising the outcome of simulations in which MV-type MGEs infected cells that entered the C state in a cell-density-dependent manner (<i>r</i>_C = 0). Each cell represents a specific transformation rate τ_C and “cost” of the MGE (<i>c</i>_M); negative costs imply the MGE benefits the cell. Each cell is split into two components, representing an MV MGE with high (β = 10⁻¹) or low (10⁻³) transmissibility. (<b>B</b>,<b>C</b>) Heatmaps, displayed as in panel A, but comparing cells transiently entering the C state with <i>k</i>_C = 10⁻⁶ (panel B) or <i>k</i>_C = 10⁻³ (panel C; <i>r</i>_C = 0.9 and φ = 0.5 in both cases). Compared to cell-density-dependent C state, these patterns of C state expression were still effective at inhibiting the spread of MV that were detrimental to the cell, but were a relatively lower impediment to the spread of MV that benefitted the cell. Raw data are tabulated in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s001" target="_blank">S1 Data</a>.</p

Variation in the effectiveness of transformation when importing DNA from a different strain.

<p>(<b>A</b>) Heatmap showing the outcome of simulated competitions between two strains, of which only one is transformable. Each cell in the grid represents a specific transformation rate (τ) and relative fitness of the allele at an exchangeable locus within the transformable strain, displayed at the top of each column. Relative fitnesses greater than one indicate the transformable strain has an initial advantage over the nontransformable strain; relative fitnesses below one indicate the nontransformable strain has the initial fitness advantage. Each cell is split in two: the “S” component shows the outcome of simulations in which transformation is symmetrical, and the “A” component shows the outcome of simulations in which transformation is asymmetrical, with the lower fitness allele acquired at a rate 10-fold lower than that of the higher fitness allele. (<b>B</b>) Heatmap showing the outcome of simulated competitions between two strains, of which only one is transformable, when there is a cost associated with the expression of the competence machinery. This figure shows the outcome of simulations analogous to those displayed in panel A, except that the transformable strain has a growth rate, γ, 5% lower than the nontransformable strain to represent the cost of the competence machinery. This cost was constant across simulations and independent of the relative fitness difference between the alleles of the exchangeable locus. Raw data are tabulated in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s001" target="_blank">S1 Data</a>.</p

The effectiveness of MGE strategies for reducing elimination by transformation.

<p>(<b>A</b>) Heatmap summarising the outcomes of simulations comparing the patterns of cellular competence shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.g004" target="_blank">Fig 4C</a> in the presence of the MGE MI (top row), which has properties intermediate between those of MH and MV. The colour of each cell represents the proportion of the population infected by the MGE over the course of the simulations. In the second row, the same simulations are performed, but in this case the MGE MI_NT inhibits transformation in the host cell. The bottom two rows show the outcome of simulations in which both MI and MI_NT infect the same population. (<b>B</b>) Heatmap summarising the outcomes of simulations comparing cell growth patterns with different MI activation patterns: <i>f</i>, the normal rate of activation, is either low (0.005) or high (0.5), as is <i>f</i>_C, the rate of activation in C state. (<b>C</b>) Heatmap summarising the same simulations shown in panel B, but for MI_NT. (<b>D</b>) Competition between MI_NT operating with its optimal strategy (<i>f</i> and <i>f</i>_C low) and MI operating with its optimal strategy (<i>f</i> low, <i>f</i>_C high). Both MGEs were allowed to infect the same population in these simulations. The heatmap shows the ratio of strains infected with MI_NT to those infected with MI when cells grew and expressed competence for transformation under different strategies. Raw data are tabulated in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s001" target="_blank">S1 Data</a>.</p

Selected examples of MGE insertions disrupting chromosomal protein coding sequences.

<p>(<b>A</b>) Comparison between <i>Lactococcus lactis</i> isolates IL1403 and KLDS 4.0325, the latter of which has a prophage inserted into the <i>comYC</i> gene, encoding the major structural component of the competence pilus. The sequences’ accession codes are given in brackets underneath the isolate names. Blue and orange boxes represent CDSs, with the direction of their transcription indicated by their vertical position relative to the horizontal line; pink boxes indicate putative MGE CDSs in the same way. Brown boxes linked by dashed lines mark the fragments of a pseudogene disrupted by MGE insertion. The red bands link regions of similar sequence in the two loci, as identified by BLAST-like alignment tool (BLAT); the intensity of the colour indicates the strength of the match. The prophage integrase has ~51% identity with the protein that drives integration into the orthologous gene in <i>S</i>. <i>pneumoniae</i> 670-6B (SP670_2190). (<b>B</b>) Comparison between <i>Streptococcus agalactiae</i> isolates COH1 and FSL S3-277, the latter of which has a prophage inserted into the <i>cas3</i> gene of the <i>S</i>. <i>agalactiae</i> CRISPR2 locus. This prophage integrase is ~76% identical with that of the prophage disrupting the <i>comYC</i> gene of <i>S</i>. <i>pneumoniae</i> 670-6B. (<b>C</b>) Comparison of <i>Streptococcus suis</i> isolates P1/7 and 89–590, the latter of which has a prophage inserted into the 3’ half of the <i>comFA</i> competence gene. This prophage integrase is ~46% identical with that of the prophage inserted into the orthologous gene in <i>Streptococcus equi</i> (SEQ_1765). (<b>D</b>) Comparison between <i>Bacillus cereus</i> isolates MHI 226 and VD214, the latter of which has a prophage inserted into the 5’ half of the <i>comFA</i> competence gene. The prophage’s integrase is ~44% identical with that of the prophage inserted into the <i>comK</i> competence gene in <i>Listeria monocytogenes</i> (LMRG_01511).</p

Inhibition of MGE transmission by transient competence.

<p>(<b>A</b>) Model of a transient competent (“C”) state and cell–cell killing of non-C-state cells. (<b>B</b>) Graph showing the original cell growth curve (no C state), cells entering the C state in a cell-density-dependent manner, then never leaving (<i>k</i>_C = 0 and <i>r</i>_C = 0); a “bet hedging” strategy (<i>k</i>_C = 0, <i>g</i>_C = 0.1, <i>r</i>_C = 0.5) in which only a fraction of the population is competent for transformation at any one time; cells undergoing small population oscillations (<i>k</i>_C = 10⁻⁶) and cells undergoing large population oscillations (<i>k</i>_C = 10⁻³) at frequencies determined by <i>r</i>_C. (<b>C</b>) Heatmap summarising the outcomes of simulations comparing patterns of growth and competence expression in panel B with different MGEs. Colours are scaled as in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.g003" target="_blank">Fig 3</a>. Results for two representatives of MH and MV are shown, each associated with different rates of HDT. Transformation at the specified τ_C rate occurred in the C state, such that the cells that never entered the C state were never competent for transformation. Raw data are tabulated in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002394#pbio.1002394.s001" target="_blank">S1 Data</a>.</p