Dataset Information

Implantation-on-a-chip cellular proteome

ABSTRACT: We have designed an implantation-on-a-chip device to model the invasion of specialized fetal extravillous trophoblasts (EVTs) from an implanting embryo into the maternal decidua. We profiled the cellular proteome of sorted EVTs or endothelial cells from devices containing different cell compositions: 1) EVTs monoculture, 2) Endothelial cells monoculture, and 3) EVTs and endothelial cells co-cultured. The proteins were extracted using the MPLEx extraction method (Nakayasu et. al. PMCID: PMC5069757), digested with 1:50 (trypsin:protein, w:w) for 3 hr at 37 C. Solid phase extraction (SPE) was performed on the samples using 1 mL/50 mg columns from Phenomenex as previously described (PMCID: PMC7192326). Peptidic concentration was assayed using a BCA assay and 5 ul at 0.1 ug/ul were injected on the LC-MS/MS system. Data was searched with MaxQuant.

INSTRUMENT(S): Q Exactive HF-X

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Geremy Clair

PROVIDER: MSV000088677 | MassIVE | Wed Jan 12 16:10:00 GMT 2022

REPOSITORIES: MassIVE

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Publications

A microphysiological model of human trophoblast invasion during implantation.

Park Ju Young JY Mani Sneha S Clair Geremy G Olson Heather M HM Paurus Vanessa L VL Ansong Charles K CK Blundell Cassidy C Young Rachel R Kanter Jessica J Gordon Scott S Yi Alex Y AY Mainigi Monica M Huh Dan Dongeun DD

Nature communications 20220315 1

Successful establishment of pregnancy requires adhesion of an embryo to the endometrium and subsequent invasion into the maternal tissue. Abnormalities in this critical process of implantation and placentation lead to many pregnancy complications. Here we present a microenigneered system to model a complex sequence of orchestrated multicellular events that plays an essential role in early pregnancy. Our implantation-on-a-chip is capable of reconstructing the three-dimensional structural organiza ...[more]

PMID: 35292627

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Project description:Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data. We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.. Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples. We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Dataset Information

Implantation-on-a-chip cellular proteome

Publications

A microphysiological model of human trophoblast invasion during implantation.

Similar Datasets

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