Additional file 2: of The CXCR4 antagonist plerixafor (AMD3100) promotes proliferation of Ewing sarcoma cell lines in vitro and activates receptor tyrosine kinase signaling

Table S1. Plerixafor treatment changes receptor tyrosine kinase phosphorylation patterns in CXCR4-high and -low Ewing sarcoma cell lines. (PDF 1503 kb

Additional file 1: of The CXCR4 antagonist plerixafor (AMD3100) promotes proliferation of Ewing sarcoma cell lines in vitro and activates receptor tyrosine kinase signaling

Figure S1. Granulocyte-colony stimulating factor and DMSO vehicle do not induce proliferation of Ewing sarcoma cell lines in vitro. Figure S2. Serum-deprivation does not alter cell line groups of CXCR4-high and -low surface expressions. (PDF 625 kb

Target discovery screens using pooled shRNA libraries and next-generation sequencing: A model workflow and analytical algorithm

<div><p>In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing on this assay development process, we here describe a target discovery screen using pooled shRNA libraries and next-generation sequencing (NGS) deconvolution in a cell line model of Ewing sarcoma. In a strategy designed for comparative and synthetic lethal studies, we screened for targets specific to the A673 Ewing sarcoma cell line. Methods, results and pitfalls are described for the entire multi-step screening procedure, from lentiviral shRNA delivery to bioinformatics analysis, illustrating a complete model workflow. We demonstrate that successful studies are feasible from the first assay performance and independent of specialized screening units. Furthermore, we show that a resource-saving screen depth of 100-fold average shRNA representation can suffice to generate reproducible target hits despite heterogeneity in the derived datasets. Because statistical analysis methods are debatable for such datasets, we created ProFED, an analysis package designed to facilitate descriptive data analysis and hit calling using an aim-oriented profile filtering approach. In its versatile design, this open-source online tool provides fast and easy analysis of shRNA and other count-based datasets to complement other analytical algorithms.</p></div

Sequencing data analysis and screen performance.

<p>(A) Representative read length histogram of a test sample (exp_A673) in technical replicates of Ion Proton NGS library preparations incorporating adapters via ligation (top panel) or PCR (middle panel), and of its replicate 1 counterpart (bottom panel). (B) Boxplot representation of shRNA read count distribution of raw data (left panel) and of TMM normalized data filtered for shRNAs with ≥ 50 alignments in ctrl_<i>a</i>/<i>b</i> (right panel). Numbers indicate screen replicates. (C) Biological reproducibility of the relative changes in shRNA abundance. Scatter plots show the correlation of log2 fold changes (FC) of experimental (exp_) relative to control samples (ctrl_) for screen replicates 1 and 2, based on TMM normalized and filtered datasets.</p

General design and workflow of the pooled shRNA screen.

<p>Collected samples of representative cell populations are depicted in blue: ctrl_<i>a</i>/<i>b</i> = unselected control populations; exp_<i>a</i>/<i>b</i> = experimental populations selected for phenotype of interest, here cell survival; Decode ctrl = virus particle control.</p

Enriched gene ontologies of A673 (condition <i>a</i>)-specific hits.

<p>Enriched gene ontologies of A673 (condition <i>a</i>)-specific hits.</p

Profile filtering approach for the identification of screen hits.

<p>(A) Illustration of sample annotation and basic profile filter parameters. Shading indicates that additional replicates are optional. FC = fold change. (B) Screen-shot from the ProFED online tool showing the “slider” panel used to set fold change thresholds and limits of desired hit profiles. The depicted setting filters for targets specific to condition <i>a</i>. (C) Exemplary read count profiles of hits specific to condition <i>a</i> (A673; top panel) and <i>b</i> (HEK293; bottom panel) as generated by ProFED. (D) STRING analysis of reported and predicted protein-protein interactions among condition <i>a</i> (A673)-specific hits. 13 hits filtered with a stringent ProFED profile (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191570#pone.0191570.t001" target="_blank">Table 1A</a>) were analyzed in comparison to 28 hits based on a more open hit profile (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191570#pone.0191570.t001" target="_blank">Table 1A</a> plus <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191570#pone.0191570.t001" target="_blank">1B</a>). Line thickness indicates the strength of data support.</p

Screen hits specific to the A673 cell line (condition <i>a</i>) as filtered using ProFED.

<p>Screen hits specific to the A673 cell line (condition <i>a</i>) as filtered using ProFED.</p

Lentivirus titration and MOI-directed shRNA transduction.

<p>(A) Titration curves of non-silencing and LaminA/C shRNA viruses. A673 cells were transduced with serial dilutions of generated lentivirus and GFP expression was analyzed after 72 h by flow cytometry. Functional titers were calculated based on non-shaded dilutions. (B) Titration curves of purchased non-silencing shRNA particles, generated as in (A). (C) Overview of determined functional virus titers [TU / ml] and deduced values. (D) Transduced cell fractions generated with a calculated MOI of 0.3. Left panel: A673 cells were transduced with indicated lentiviruses and GFP expression was analyzed after 72 h. Right panel: Representative flow cytometry plot; shaded graph: transduced cell population; open graph: non-treated control cells. (E) Time-course of puromycin selection. A673 cells transduced with purchased non-silencing shRNA particles in (D) were exposed to puromycin 72 h after transduction. Left panel: GFP-positive cell fractions were determined at time points indicated. Right panel: Representative flow cytometry plot corresponding to that in (D) after 72 h puromycin selection. (F) Western blot of LaminA/C protein expression. A673 cells were transduced as indicated and selected with 1 μg / ml puromycin after 72 h for additional 72 h. Arrows indicate 74 and 65 kDa double-band of LaminA/C. Actin was loading control. All graphs of this figure represent mean ±SD of three independent experiments.</p

Sequencing data analysis and screen performance.

<p>(A) Representative read length histogram of a test sample (exp_A673) in technical replicates of Ion Proton NGS library preparations incorporating adapters via ligation (top panel) or PCR (middle panel), and of its replicate 1 counterpart (bottom panel). (B) Boxplot representation of shRNA read count distribution of raw data (left panel) and of TMM normalized data filtered for shRNAs with ≥ 50 alignments in ctrl_<i>a</i>/<i>b</i> (right panel). Numbers indicate screen replicates. (C) Biological reproducibility of the relative changes in shRNA abundance. Scatter plots show the correlation of log2 fold changes (FC) of experimental (exp_) relative to control samples (ctrl_) for screen replicates 1 and 2, based on TMM normalized and filtered datasets.</p