Biology subjects

Soumillon, M.

Publications and source records attributed to Soumillon, M..

3 recordsLinked to original sources

bioRxiv2019

Spatio-temporal analysis of human preimplantation development reveals dynamics of epiblast and trophectoderm

Recent technological advances such as single-cell RNAseq1-3 and CRISPR-CAS9-mediated knock-out4 have allowed an unprecedented access into processes orchestrating human preimplantation development5. However, the sequence of events which occur during human preimplantation development are still unknown. In particular, timing of first human lineage specification, the process by which the morula cells acquire a specific fate, remains elusive. Here, we present a human preimplantation development model based on transcriptomic pseudotime modelling of scRNAseq biologically validated by spatial information and precise time-lapse staging. In contrast to mouse, we show that trophectoderm (TE) / inner cell mass (ICM) lineage specification in human is only detectable at the transcriptomic level at the blastocyst stage, just prior to expansion. We validated the expression profile of novel markers enabling precise staging of human preimplantation embryos, such as IFI16 which highlights establishment of epiblast (EPI) and NR2F2 which appears at the transition from specified to mature TE. Strikingly, mature TE cells arise from the polar side, just after specification, supporting a model of polar TE cells driving TE maturation. Altogether, our study unravels the first lineage specification event in the human embryo and provides a browsable resource for mapping spatio-temporal events underlying human lineage specification.

cell biology↗

bioRxiv2017

Light-Activated Cell Identification and Sorting (LACIS): A New Method to Identify and Select Edited Clones on a Microfluidic Device

CRISPR-Cas9 gene editing has revolutionized cell engineering and promises to open new doors in gene and cell therapies. Despite improvements in the CRISPR-editing molecular toolbox in cell lines and primary cells, identifying and purifying properly edited clones remains slow, laborious and low-yield. Here, we establish a new method that uses cell manipulation on a chip with Opto-Electronic Positioning (OEP) technology to enable clonal isolation and selection of edited cells. We focused on editing CXCR4 in primary human T cells, a gene that encodes a co-receptor for HIV entry. T cells hold significant potential for cell-based therapy, but the gene-editing efficiency and expansion potential of these cells is limited. We describe here a method to obviate these limitations. Briefly, after electroporation of cells with CXCR4-targeting Cas9 ribonucleoproteins (RNPs), single T cells were isolated on a chip, where they proliferated over time into well-resolved colonies. Phenotypic consequences of genome editing could be rapidly assessed on-chip with cell-surface staining for CXCR4. Furthermore, independent of phenotype, individual colonies could be identified based on their specific genotype at the 5-10 cell stage. Each colony was split and sequentially exported for immediate on-target sequencing and validation, and further off-chip clonal expansion of the validated clones. We were able to assess single-clone editing efficiencies, including the rate of monoallelic and biallelic indels or precise nucleotide replacements. This new method will enable identification and selection of perfectly edited clones within 10 days from Cas9-RNP introduction in cells based on the phenotype and/or genotype.

bioengineering↗

bioRxiv2017

A Comparison of mRNA Sequencing with Random Primed and 3’-Directed Libraries

Deep mRNA sequencing (mRNAseq) is the state-of-the-art for whole transcriptome measurements. A key step is creating a library of cDNA sequencing fragments from RNA. This is generally done by random priming, creating multiple sequencing fragments along the length of each transcript. A 3 end-focused library approach cannot detect differential splicing, but has potentially higher throughput at lower cost (~10-fold lower), along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) to correct for PCR bias. Here, we compare implementation of such a 3-digital gene expression (3-DGE) approach with \"conventional\" random primed mRNAseq, which has not yet been done. We find that while conventional mRNAseq detects ~15% more genes, the resulting lists of differentially expressed genes and therefore biological conclusions and gene signatures are highly concordant between the two techniques. We also find good quantitative agreement on the level of individual genes between the two techniques in terms of both read counts and fold change between two conditions. We conclude that for high-throughput applications, the potential cost savings associated with the 3-DGE approach are a very reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable much larger scale studies focused on not only differential expression analysis, but also quantitative transcriptome profiling. The computational scripts and programs, along with experimental standard operating procedures used in our pipeline presented here, are freely available on our website (www.dtoxs.org).

genomics↗