Biology subjects

Shannon, M. J.

Publications and source records attributed to Shannon, M. J..

3 recordsLinked to original sources

bioRxiv2023

Modulation of NK cell migration by IL-15 defined using a new tool for data-driven clustering of heterogeneous cell behaviour trajectories

Advances in imaging, cell segmentation, and cell tracking now routinely produce microscopy datasets of a size and complexity comparable to transcriptomics or proteomics. New tools are required to process this phenomics type data. Cell PLasticity Analysis TOol (cellPLATO) is a Python-based analysis software designed for measurement and classification of diverse cell behaviours based on clustering of parameters of cell morphology and motility. cellPLATO is used after segmentation and tracking of cells from live cell microscopy data. The tool extracts morphological and motility metrics from each cell per timepoint, before being using them to segregate cells into behavioural subtypes with dimensionality reduction. Resultant cell tracks have a behavioural ID for each cell per timepoint corresponding to their changing behaviour over time in a sequence. Similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Trajectories and underlying behaviours generate a phenotypic finger-print for each experimental condition, and representative cells are mathematically identified and graphically displayed for human understanding of each subtype. Here, we use cellPLATO to investigate the role of IL-15 in modulating NK cell migration on ICAM-1 or VCAM-1. We find 8 behavioural subsets of NK cells based on their shape and migration dynamics, and 4 trajectories of behaviour. Therefore, using cellPLATO we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

cell biology↗

bioRxiv2022

Single-cell assessment of trophoblast stem cell-based organoids as human placenta-modeling platforms

The recent discovery of human trophoblast stem cells (hTSC) and techniques allowing for trophoblast organoid (TOrg) culture have established promising approaches for studying human trophoblast development. To validate the accuracy of these models at single-cell resolution, we directly compared in vitro TOrg cultures derived from primary progenitor cytotrophoblasts (CTB) or commercially available hTSC lines to in vivo human trophoblasts using a scRNA-seq approach. While patient-derived (PD)- and hTSC-derived TOrgs overall reflect cell differentiation trajectories with accuracy, specific features related to trophoblast state make-up, distinct sub-paths of differentiation, and predicted transcriptional drivers regulating stem cell maintenance were shown to be misaligned in the in vitro platforms. This is best exemplified by the identification of a distinct progenitor state in hTSC-derived TOrgs that showed characteristics of CTB- and extravillous-like cell states. Together, this work provides a comprehensive resource that identifies underlying strengths and limitations of current TOrg platforms. Summary StatementSingle-cell transcriptomics provides comprehensive comparison between trophoblast organoids derived from commercially available trophoblast stem cells and first-trimester primary human cytotrophoblasts. HIGHLIGHTSO_LIAn integrated single cell transcriptomic atlas of placental and organoid trophoblasts establishes a comprehensive and public web-based resource C_LIO_LIDirect comparison of trophoblasts from placental/decidual tissue to trophoblasts extracted from two distinct organoid platforms highlights both conserved and divergent features C_LIO_LIComputational modeling describes novel trophoblast states and routes of cell differentiation in human trophoblast organoids C_LI IN BRIEFWhile the merits and utility of current trophoblast organoid cultures have been established, high-resolution assessment and comparison of conserved and divergent features of these systems to cell states and differentiation trajectories of trophoblasts in situ or in vitro has not been performed. Here, Shannon et al. generate a single-cell transcriptomic atlas of two trophoblast organoids that comprehensively define the similarities and discrepancies in relation to trophoblasts from the placental-maternal interface.

developmental biology↗

bioRxiv2022

Transcriptomic mapping of the metzincin landscape in human trophoblasts

The metzincin family of metalloproteases coordinates cell and tissue developmental processes through regulation of growth factor availability, receptor signaling, and cell-cell/cell-matrix adhesion. During placental development, while distinct roles for metzincin proteases in controlling specific trophoblast functions have been described, a comprehensive assessment of metzincins during discrete stages of trophoblast differentiation has yet to be performed. Here we provide a comprehensive single cell transcriptomic resource of metzincin protease expression in diverse states of human trophoblasts from first trimester placental and decidual tissues. In the 8 distinct trophoblasts states categorized [four progenitor cytotrophoblast (CTB), one syncytiotrophoblast precursor (SCTp), two column CTB (cCTB), and one extravillous trophoblast (EVT) state], we identified 24 metzincin genes. These included 12 adamalysins, 2 pappalysins, 3 astacins and 7 matrixins. Cell trajectory modeling shows that expression of most (19/24) metzincins increases across CTB to EVT differentiation, though select proteases also increase as CTB fuse into syncytiotrophoblast. Within the CTB niche, single-cell velocity ordering identified 11 metzincins (ADAM10, -17, MMP14, -15, -19, -23B, ADAMTS1, -6, -19, TLL-1, -2) expressed in progenitors proximal to the predicted origin. Analysis of metzincin-substrate interactions within the CTB niche revealed [~]150 substrates and binding partners, including FBN2 as an ADAMTS6-specific substrate preferentially expressed in trophoblast progenitors. Together, this work characterizes the metzincin transcriptomic landscape in human first trimester trophoblasts and establishes insight into the roles specific proteases perform within distinct trophoblast niches and across differentiation. This resource serves as a guide for future investigations into the roles of metzincin proteases in human placental development. Summary StatementSingle cell RNA sequencing characterizes the expression of multiple metzincin proteases within first trimester placental trophoblasts. Examination of protease-substrate interactions within cytotrophoblasts identifies potential interactions between ADAMTS6 and FBN2. HighlightsO_LISingle cell RNA sequencing identifies 24 distinct metzincin proteases expressed in human first trimester trophoblasts C_LIO_LILineage trajectory modelling shows that metzincin genes are dynamic and likely control processes in progenitor, mid-point, and end-point states of trophoblast differentiation. C_LIO_LIADAMTS6, and its putative substrate FBN2, localize specifically to progenitor trophoblasts C_LI

developmental biology↗