Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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In vitro growth signature identification from SmartSeq3 sequencing of 5 human cancer cell lines and 1 mouse cancer cell line

ABSTRACT: Cell lines used to determine the growth of cell lines over time were used for transcriptomic profiling to build a model that predicts growth rate from transcriptome of cells. To establish robust transcriptional signatures of dying cells, we performed single-well cell sorting followed by Smart-seq3xpress. 4T1, A549, MDA-MB-231 clone A, L and S were grown in cell culture medium. Adherent MDA-MB-231 clone L were grown with 1uM of Paclitaxel, a concentration we have previously shown to slow proliferation while retaining a viability compatible with the experiment27. The cells in culture were detached with Trypsin treatment for 3-5 minutes at 37 degrees C and the reaction was quenched by adding back the cells supernatant to conserve dead cells. The suspension was washed twice in PBS, 4 minutes at 400g. The cells were then labelled using the live/dead stain BOBO3 and apoptosis marker AnnexinV-APC following manufacturer's instruction. We isolated 3 cell populations on the basis of the BOBO3 and Annexin-V flow cytometry markers using an Aria3 flow cytometry with a 100um nozzle and low pressure settings. Live cells were gated as BOBO3- AnnexinV-, dying (early apoptotic) cells as BOBO3- AnexinV+ and dead cells (necrosis or late apoptosis) as BOBO3+ AnexinV+ (Fig. S2a-b). Individual cells were isolated in 384 well pcr-plates. After 10s centrifugation at 1000g the plates were sealed and stored at -80*C until processed using Smart-seq3xpress protocol30. All the reagents and bioinformatic pipeline related to Smart-seq3xpress are available online31.

INSTRUMENT(S): Illumina NovaSeq X

ORGANISM(S): Homo sapiens

SUBMITTER: Alper Eroglu

PROVIDER: E-MTAB-16354 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:In vertebrates, all cells except circulating blood cells must adhere to support their normal growth and functions. The adherence to extracellular matrix and/or other cells is critical and adherent cells placed in non-adherent conditions either die or form multicellular spheroids. Placing cells in non-adherent conditions has been used to induce differentiation in teratocarcinoma cells and more recently to form organoids . Because of such important consequences induced by cell adhesion on cell growth and function, the transition between adherent and non-adherent states is rather rare. There are however physiological situations, such as blood cells diapedesis, during which cells that circulate into the blood stream must adhere to the endothelial cells and cross the endothelial barrier to reach target tissues. Another example of transition, from an adherent to a non-adherent state, is observed in the metastasic process, where cells detach from the tumor mass and circulate in the blood and lymphatic vasculature prior to reattaching and extravasating to colonize distant organs. The comparative analysis of the only effects of adherence on cellular functions is complicated by the fact that in many study models the acquisition or loss of adherence induces major alterations in cell physiology that would obscure the effects of the adherence itself. For example, P19 teratocarcinoma cells differentiate in suspension spheroids while they do not in adhering conditions. In this context, the comparison between spheroids and adherent cells would not be a comparison between adherent and non-adherent cells, but between differentiated cells adhering between them and undifferentiated cells adhering on plastic. Mouse macrophage cell lines represent one of the rare experimental models that may be suitable to compare the adherent and non-adherent states. Indeed, they grow equally well under adherent and non-adherent conditions and keep their differentiated functions under both conditions. We therefore decided to use this model to analyze the changes between the adherent and the non-adherent state using a broad approach, based on proteomics.

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In vitro growth signature identification from SmartSeq3 sequencing of 5 human cancer cell lines and 1 mouse cancer cell line

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