Biology subjects

Niakan, K. K.

Publications and source records attributed to Niakan, K. K..

3 recordsLinked to original sources

bioRxiv2021

Direct reprogramming of human embryonic to trophoblast stem cells

During the first week of development, human embryos form a blastocyst comprised of an inner cell mass and trophectoderm (TE) cells, the latter of which are progenitors of placental trophoblast. Here we investigated the expression of transcripts in the human TE from early to late blastocyst stages. We identified enrichment of transcription factors GATA2, GATA3, TFAP2C and KLF5 and characterised their protein expression dynamics across TE development. By inducible overexpression and mRNA transfection we determined that these factors, together with MYC, are sufficient to establish induced trophoblast stem cells (iTSCs) from primed human embryonic stem cells. These iTSCs self-renew and recapitulate morphological characteristics, gene expression profiles, and directed differentiation potential similar to existing human TSCs. Systematic omission of each, or combinations of factors, revealed the critical importance of GATA2 and GATA3 for iTSC transdifferentiation. Altogether, these findings provide insights into the transcription factor network that may be operational in the human TE and broaden the methods for establishing cellular models of early human placental progenitor cells, which may be useful in the future to model placental-associated diseases. Summary statementTranscriptional analysis of human blastocysts reveals transcription factors sufficient to derive induced trophoblast stem cells from primed human embryonic stem cells.

developmental biology↗

bioRxiv2020

KLF17 promotes human naïve pluripotency but is not required for its establishment

Current knowledge of the transcriptional regulation of human pluripotency is incomplete, with lack of inter-species conservation observed. Single-cell transcriptomics of human embryos previously enabled us to identify transcription factors, including the zinc-finger protein KLF17, that are enriched in the human epiblast and naive hESCs. Here we show that KLF17 is expressed coincident with the known pluripotency factors NANOG and SOX2 across human blastocyst development. We investigate the function of KLF17 in pluripotency using primed and naive hESCs for gain- and loss-of-function analyses. We find that ectopic expression of KLF17 in primed hESCs is sufficient to induce a naive-like transcriptome and that KLF17 can drive transgene-mediated resetting to naive pluripotency. This implies a role for KLF17 in establishing naive pluripotency. However, CRISPR-Cas9-mediated knockout studies reveal that KLF17 is not required for naive pluripotency acquisition in vitro. Transcriptome analysis of naive hESCs identifies subtle effects on metabolism and signalling following KLF17 loss of function, and possible redundancy with the related factor, KLF5. Overall, we show that KLF17 is sufficient, but not necessary, for naive pluripotency under the given in vitro conditions. Summary statementInvestigating KLF17 in human pluripotency reveals that it is sufficient, but not necessary, to establish naive hESCs. We posit that KLF17 is a peripheral regulator, like KLF2 in the mouse.

developmental biology↗

bioRxiv2020

GIANI: open-source software for automated analysis of 3D microscopy images

The study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. Here we describe GIANI (djpbarry.github.io/Giani), new software for the analysis of 3D images, implemented as a plugin for the popular FIJI platform. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images and also comes with scripting and command line tools, allowing users to incorporate its functionality into their own scripts and also run GIANI on a high-performance computing cluster. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light sheet microscopy images of the flour beetle embryo. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.

bioinformatics↗