High-throughput Titration of Luciferase-expressing Recombinant Viruses

Standard plaque assays to determine infectious viral titers can be time consuming, are not amenable to a high volume of samples, and cannot be done with ...

Ottawa Hospital Research Institute

University of Ottawa

High-throughput genomics has enabled the global mapping of genetic interactions based on the phenotypic impact of combinatorial genetic perturbations. An important next step is to understand how these networks are dynamically remodelled in response to environmental stimuli. Here, we report on the development and testing of a method to identify such interactions. The method was developed from first principles by treating the impact on cellular growth of environmental perturbations equivalently to that of gene deletions. This allowed us to establish a novel neutrality function marking the absence of epistasis in terms of sensitivity phenotypes rather than fitness. We tested the method by identifying fitness- and sensitivity-based interactions involved in the response to drug-induced DNA-damage of budding yeast Saccharomyces cerevisiae using two mutant libraries - one containing transcription factor deletions, and the other containing deletions of DNA repair genes.

Identification of response-modulated genetic interactions by sensitivity-based epistatic analysis.

Gen Ausdruck L&auml;rm mit genomische Position variiert und ist eine treibende Kraft in der Entwicklung der Chromosom-Organisation. Trotzdem bleiben Positionseffekte schlecht charakterisiert. Hier pr&auml;sentieren wir eine systematische Analyse der chromosomalen Positionseffekte durch einzellige Genexpression von Histons Positionen &uuml;ber die L&auml;nge eines eukaryotischen Chromosoms charakterisieren. Wir zeigen, dass die Position Genexpression beeinflusst durch die Gr&ouml;&szlig;e des transkriptionelle platzt, anstatt ihre Frequenz Modulation und die Histon-Deacetylase Sir2 spielt eine Rolle in diesem Prozess auf dem Chromosom.

Chromosomale Positionseffekte sind verbunden mit sir2-vermittelte Variation in transkriptionelle Burst-Gr&ouml;&szlig;e.

Rumore di espressione del gene &egrave; una forza trainante nell&#39;evoluzione dell&#39;organizzazione del cromosoma e varia con la posizione di genomic. Effetti di posizione restano tuttavia scarsamente caratterizzati. Presentiamo qui, un&#39;analisi sistematica degli effetti posizione cromosomici di caratterizzare l&#39;espressione genica di cella singola da eucromatina posizioni che abbracciano la lunghezza di un cromosoma eucariotico. Dimostriamo che posizione influisce sull&#39;espressione genica modulando la dimensione di transcriptional scoppia, piuttosto che la loro frequenza, e che l&#39;istone deacetylase Sir2 gioca un ruolo in questo processo attraverso il cromosoma.

Effetti posizione cromosomici sono collegati alla variazione di sir2-mediata nella dimensione di transcriptional burst.

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&#x57FA;&#x56E0;&#x8868;&#x8FBE;&#x566A;&#x97F3;&#x57FA;&#x56E0;&#x7EC4;&#x7684;&#x4F4D;&#x7F6E;&#x800C;&#x5F02;&#xFF0C;&#x67D3;&#x8272;&#x4F53;&#x7EC4;&#x7EC7;&#x6F14;&#x53D8;&#x7684;&#x9A71;&#x52A8;&#x529B;&#x3002;&#x7136;&#x800C;&#xFF0C;&#x4F4D;&#x7F6E;&#x5F71;&#x54CD;&#x4ECD;&#x7136;&#x5F88;&#x5DEE;&#x7684;&#x7279;&#x70B9;&#x3002;&#x5728;&#x8FD9;&#x91CC;&#xFF0C;&#x6211;&#x4EEC;&#x63D0;&#x51FA;&#x67D3;&#x8272;&#x4F53;&#x4F4D;&#x7F6E;&#x5F71;&#x54CD;&#x7CFB;&#x7EDF;&#x7684;&#x5206;&#x6790;&#x7684;&#x7279;&#x70B9;&#x4ECE; euchromatic &#x9635;&#x5730;&#x8DE8;&#x8D8A;&#x7684;&#x771F;&#x6838;&#x67D3;&#x8272;&#x4F53;&#x957F;&#x5EA6;&#x5355;&#x7EC6;&#x80DE;&#x57FA;&#x56E0;&#x8868;&#x8FBE;&#x3002;&#x6211;&#x4EEC;&#x8BC1;&#x660E;&#x4F4D;&#x7F6E;&#x901A;&#x8FC7;&#x8C03;&#x8282;&#x8F6C;&#x5F55;&#x7684;&#x7206;&#x53D1;&#xFF0C;&#x800C;&#x4E0D;&#x662F;&#x5176;&#x9891;&#x7387;&#x7684;&#x5927;&#x5C0F;&#x4F1A;&#x5F71;&#x54CD;&#x57FA;&#x56E0;&#x7684;&#x8868;&#x8FBE;&#x548C;&#x7EC4;&#x86CB;&#x767D;&#x53BB;&#x4E59;&#x9170;&#x5316;&#x9176; 2 &#x8DE8;&#x67D3;&#x8272;&#x4F53;&#x53D1;&#x6325;&#x5728;&#x8FD9;&#x4E00;&#x8FDB;&#x7A0B;&#x4E2D;&#x7684;&#x4F5C;&#x7528;&#x3002;

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Gene expression noise varies with genomic position and is a driving force in the evolution of chromosome organization. Nevertheless, position effects remain poorly characterized. Here, we present a systematic analysis of chromosomal position effects by characterizing single-cell gene expression from euchromatic positions spanning the length of a eukaryotic chromosome. We demonstrate that position affects gene expression by modulating the size of transcriptional bursts, rather than their frequency, and that the histone deacetylase Sir2 plays a role in this process across the chromosome.

Chromosomal position effects are linked to sir2-mediated variation in transcriptional burst size.

L&#x26;#39;expression des g&#xE8;nes du bruit varie avec la position de la g&#xE9;nomique et est une force motrice dans l&#x26;#39;&#xE9;volution de l&#x26;#39;organisation des chromosomes. N&#xE9;anmoins, les effets de position restent mal caract&#xE9;ris&#xE9;s. Ici, nous pr&#xE9;sentons une analyse syst&#xE9;matique des effets de position chromosomiques par la caract&#xE9;risation de l&#x26;#39;expression du g&#xE8;ne &#xE0; une cellule &#xE0; partir de positions euchromatiques couvrant la longueur d&#x26;#39;un chromosome eucaryote. Nous d&#xE9;montrons que la position affecte l&#x26;#39;expression des g&#xE8;nes en modulant la taille des rafales de transcription, plut&#xF4;t que de leur fr&#xE9;quence, et que le histone d&#xE9;ac&#xE9;tylase Sir2 joue un r&#xF4;le dans ce processus &#xE0; travers le chromosome.

Effets position chromosomique sont li&#xE9;es &#xE0; Sir2 m&#xE9;di&#xE9;e par variation de la taille d&#x26;#39;&#xE9;clatement de la transcription

&#xC9C4; &#xC2DD; &#xC18C;&#xC74C; &#xAC8C;&#xB188; &#xC704;&#xCE58;&#xC5D0; &#xB530;&#xB77C; &#xB2EC;&#xB77C;&#xC9C4; &#xB2E4; &#xACE0; &#xC5FC;&#xC0C9;&#xCCB4; &#xC870;&#xC9C1; &#xC9C4;&#xD654;&#xC758; &#xC6D0;&#xB3D9;&#xB825;&#xC740;. &#xADF8;&#xB7FC;&#xC5D0;&#xB3C4; &#xBD88;&#xAD6C; &#xD558; &#xACE0;, &#xC704;&#xCE58; &#xD6A8;&#xACFC; &#xC81C;&#xB300;&#xB85C; &#xD2B9;&#xC9D5;&#xC774; &#xB0A8;&#xC544; &#xC788;&#xC2B5;&#xB2C8;&#xB2E4;. &#xC5EC;&#xAE30;, &#xC6B0;&#xB9AC; &#xC9C4; &#xD575; &#xC5FC;&#xC0C9;&#xCCB4;&#xC758; &#xAE38;&#xC774; &#xAC78;&#xCE5C; euchromatic &#xC704;&#xCE58;&#xC5D0;&#xC11C; &#xB2E8;&#xC77C; &#xC140; &#xC720;&#xC804;&#xC790; &#xBC1C;&#xD604;&#xC744; &#xD2B9;&#xC131;&#xD654; &#xD558; &#xC5EC; &#xC5FC;&#xC0C9;&#xCCB4; &#xC704;&#xCE58; &#xD6A8;&#xACFC;&#xC758; &#xCCB4;&#xACC4;&#xC801;&#xC778; &#xBD84;&#xC11D;&#xC744; &#xC81C;&#xC2DC;. &#xC6B0;&#xB9AC;&#xB294; &#xC704;&#xCE58; transcriptional &#xBC84;&#xC2A4;&#xD2B8; &#xBCF4;&#xB2E4;&#xB294; &#xADF8;&#xB4E4;&#xC758; &#xC8FC;&#xD30C;&#xC218;&#xC758; &#xD06C;&#xAE30;&#xB97C; &#xBCC0;&#xC870; &#xD558; &#xC5EC; &#xC720;&#xC804;&#xC790; &#xBC1C;&#xD604;&#xC5D0; &#xC601;&#xD5A5;&#xC744; &#xBBF8;&#xCE58;&#xB294; &#xD788;&#xC2A4;&#xD1A4; deacetylase sir2&#xB294; &#xC5FC;&#xC0C9;&#xCCB4;&#xC5D0; &#xAC78;&#xCCD0;&#xC774; &#xACFC;&#xC815;&#xC5D0;&#xC11C; &#xC5ED;&#xD560;&#xC744; &#xD55C;&#xB2E4;&#xB294; &#xBCF4;&#xC5EC; &#xC90D;&#xB2C8;&#xB2E4;.

&#xC5FC;&#xC0C9;&#xCCB4; &#xC704;&#xCE58; &#xD6A8;&#xACFC; transcriptional &#xBC84;&#xC2A4;&#xD2B8; &#xD06C;&#xAE30;&#xC5D0;&#xC11C; &#xD3B8;&#xCC28; sir2 &#xC911;&#xC7AC;&#xC5D0; &#xC5F0;&#xACB0; &#xB429;&#xB2C8;&#xB2E4;.

Ruido de la expresi&#xF3;n de genes var&#xED;a con la posici&#xF3;n gen&#xF3;mica y es una fuerza impulsora en la evoluci&#xF3;n de la organizaci&#xF3;n de los cromosomas. Sin embargo, los efectos de posici&#xF3;n siguen siendo mal caracterizado. A continuaci&#xF3;n, presentamos un an&#xE1;lisis sistem&#xE1;tico de los efectos de posici&#xF3;n cromosomales mediante la caracterizaci&#xF3;n de una sola c&#xE9;lula la expresi&#xF3;n g&#xE9;nica de las posiciones eucrom&#xE1;ticas extienda a lo largo de un cromosoma eucariota. Se demuestra que la posici&#xF3;n afecta la expresi&#xF3;n de genes mediante la modulaci&#xF3;n del tama&#xF1;o de las r&#xE1;fagas de la transcripci&#xF3;n, en lugar de su frecuencia, y que la histona deacetilasa Sir2 desempe&#xF1;a un papel en este proceso a trav&#xE9;s del cromosoma.

Efectos cromos&#xF3;micos de posici&#xF3;n se relaciona con Sir2 mediada por variaci&#xF3;n en el tama&#xF1;o de r&#xE1;faga de la transcripci&#xF3;n

Inferring regulatory and metabolic network models from quantitative genetic interaction data remains a major challenge in systems biology. Here, we present a novel quantitative model for interpreting epistasis within pathways responding to an external signal. The model provides the basis of an experimental method to determine the architecture of such pathways, and establishes a new set of rules to infer the order of genes within them. The method also allows the extraction of quantitative parameters enabling a new level of information to be added to genetic network models. It is applicable to any system where the impact of combinatorial loss-of-function mutations can be quantified with sufficient accuracy. We test the method by conducting a systematic analysis of a thoroughly characterized eukaryotic gene network, the galactose utilization pathway in Saccharomyces cerevisiae. For this purpose, we quantify the effects of single and double gene deletions on two phenotypic traits, fitness and reporter gene expression. We show that applying our method to fitness traits reveals the order of metabolic enzymes and the effects of accumulating metabolic intermediates. Conversely, the analysis of expression traits reveals the order of transcriptional regulatory genes, secondary regulatory signals and their relative strength. Strikingly, when the analyses of the two traits are combined, the method correctly infers ~80% of the known relationships without any false positives.

Quantitative epistasis analysis and pathway inference from genetic interaction data.

Oncolytic viruses are complex biological agents that interact at multiple levels with both tumour and normal tissues. Antiviral pathways induced by interferon are known to have a critical role in determining tumour cell sensitivity and normal cell resistance to infection with oncolytic viruses. Here we pursue a synthetic biology approach to identify methods that enhance antitumour activity of oncolytic viruses through suppression of interferon signalling. On the basis of the mathematical analysis of multiple strategies, we hypothesize that a positive feedback loop, established by virus-mediated expression of a soluble interferon-binding decoy receptor, increases tumour cytotoxicity without compromising normal cells. Oncolytic rhabdoviruses engineered to express a secreted interferon antagonist have improved oncolytic potential in cellular cancer models, and display improved therapeutic potential in tumour-bearing mice. Our results demonstrate the potential of this methodology in evaluating potential caveats of viral immune-evasion strategies and improving the design oncolytic viruses.

Cory Batenchuk

Center for Innovative Cancer Research

Ottawa Hospital Research Institute

High-throughput Titration of Luciferase-expressing Recombinant Viruses

Cory Batenchuk

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Center for Innovative Cancer Research

Ottawa Hospital Research Institute

High-throughput Titration of Luciferase-expressing Recombinant Viruses

Center for Innovative Cancer Research