Biology subjects

Lipecki, J.

Publications and source records attributed to Lipecki, J..

3 recordsLinked to original sources

bioRxiv2018

Discordant perturbations of transcriptome and epigenome landscapes highlight dual roles of proinflammatory players in normal and IL1B-compromised OPC maturation trajectory in a prenatal model of diffuse white matter injury

Inflammatory insults accompanying prematurity provokes diffuse white matter injury (DWMI) which is associated with increased risk of neurodevelopmental disorders: pre-term infants have a 10 to 18-fold increased risk of developing autism spectrum disorders, compared to term infants. DWMI is due to maturation arrest in oligodendrocyte precursor cells (OPCs). Using integrated genome-wide approaches in a validated mouse perinatal model of DWMI, induced by systemic- and neuro-inflammation based on repeated interleukin-1B administrations, we show that neuroinflammation induces limited epigenomic disturbances in OPCs. In contrast, we unravel marked transcriptomic alterations of genes of the immune/inflammatory pathways, which are expressed in unstressed OPCs and physiologically downregulated along OPC maturation. Consistently, we observe that transcription factors of the inflammatory pathways occupy DNA both in unstressed and inflamed OPCs. Thus, rather than altering genome-wide chromatin accessibility, neuroinflammation takes advantage of open chromatin regions and deeply counteracts the stage-dependent downregulation of these active transcriptional programs. Therefore, our study opens new avenues for the future development of targeted approaches to protect preterm brains. Highlights{circ} Limited epigenomic impact of inflammation on OPC maturation blockade {circ}Major transcriptomic disturbances take advantage of a primed epigenetic landscape {circ}Proinflammatory genes are active in OPCs and downregulated upon maturation {circ}Neuroinflammation counteracts both this downregulation and maturation in OPCs

developmental biology↗

bioRxiv2018

Reconstruction of the Decidual Pathways in Human Endometrial Cells Using Single-Cell RNA-Seq

Breakdown of the feto-maternal interface in early pregnancy causes miscarriage. The cycling endometrium becomes poised to transition to a pregnant state during the midluteal implantation window, coinciding with differentiation of stromal cells into decidual cells (DC) and emergence of senescent decidual cells (snDC). Emerging evidence suggests that DC engage uterine natural killer cells to eliminate their senescent counterparts, thus enabling formation of a robust decidual matrix in pregnancy. To examine if failure to constrain snDC during the peri-implantation window increases the risk of miscarriage, we reconstructed the decidual pathway at single-cell level in vitro and demonstrated that, without immune surveillance, secondary senescence rapidly transforms DC into progesterone-resistant cells that abundantly express extracellular matrix remodelling factors. Additional single-cell analysis of midluteal endometrium identified DIO2 and SCARA5 as marker genes of a diverging decidual response in vivo. Finally, we report a conspicuous link between a pro-senescent decidual response in luteal phase endometrium and recurrent pregnancy loss, suggesting that pre-pregnancy screening and intervention may reduce the burden of miscarriage.

systems biology↗

bioRxiv2018

The contribution of mitochondrial metagenomics to largescale data mining and phylogenetic analysis of Coleoptera

A phylogenetic tree at the species level is still far off for highly diverse insect orders, including the Coleoptera, but the taxonomic breadth of public sequence databases is growing. In addition, new types of data may contribute to increasing taxon coverage, such as metagenomic shotgun sequencing for assembly of mitogenomes from bulk specimen samples. The current study explores the application of these techniques for large-scale efforts to build the tree of Coleoptera. We used shotgun data from 17 different ecological and taxonomic datasets (5 unpublished) to assemble a total of 1942 mitogenome contigs of >3000 bp. These sequences were combined into a single dataset together with all mitochondrial data available at GenBank, in addition to nuclear markers widely used in molecular phylogenetics. The resulting matrix of nearly 16000 species with two or more loci produced trees (RAxML) showing overall congruence with the Linnaean taxonomy at hierarchical levels from suborders to genera. We tested the role of full-length mitogenomes in stabilizing the tree from GenBank data, as mitogenomes might link terminals with non-overlapping gene representation. However, the mitogenome data were only partly useful in this respect, presumably because of the purely automated approach to assembly and gene delimitation, but improvements in future may be possible by using multiple assemblers and manual curation. In conclusion, the combination of data mining and metagenomic sequencing of bulk samples provided the largest phylogenetic tree of Coleoptera to date, which represents a summary of existing phylogenetic knowledge and a defensible tree of great utility, in particular for studies at the intra-familial level, despite some shortcomings for resolving basal nodes.

evolutionary biology↗