Retrospective identification of intrinsic factors that mark pluripotency potential in rare somatic cells

Abstract

Pluripotency can be induced in somatic cells by the expression of the four Yamanaka factors OCT4, KLF4, SOX2, and MYC. However, even in homogeneous conditions, usually only a rare subset of cells admit reprogramming, and the molecular characteristics of this subset remain unknown. Here, we apply retrospective clone tracing to identify and characterize the individual human fibroblast cells that are primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis led to increased reprogramming efficiency, identifying it as a barrier to reprogramming. Changing the frequency of reprogramming by inhibiting the activity of LSD1 led to an enlarging of the pool of cells that were primed for reprogramming. Our results show that even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

Piscis: a novel loss estimator of the F1 score enables accurate spot detection in fluorescence microscopy images via deep learning

“…For the experimental data, we performed either standard single-molecule RNA FISH or HCR RNA FISH and imaged cells using fluorescence widefield microscopy. We collected six datasets representing multiple cellular systems, including WM989 human melanoma cells 28,29 grown in vitro and in NOD SCID mice 31 , human inducible fibroblast-like (hiF-T) cells 26,27 , Calu-3 human lung adenocarcinoma cells 30 , and primary human monocyte-derived macrophages (hMDMs). All images were acquired at 60x magnification and 1.4 numerical aperture using a Nikon Ti-E microscope.…”

“…Figure 2: Piscis is trained on a diverse dataset using the SmoothF1 loss function. a, The dataset used to train and test Piscis included experimental RNA FISH images of human inducible fibroblast-like (hiF-T) cells26,27 , WM989 human melanoma cells28,29 , Calu-3 human lung adenocarcinoma cells30 , and primary human monocyte-derived macrophages (hMDMs). Images are shown with DAPI-stained nuclei (blue), spots of single mRNA molecules (red), and the corresponding manual ground truth annotations (white).…”

Proliferation history and transcription factor levels drive direct conversion

“…Extrinsic variation including variability across batches of cells, complex cocktails of transcription factors, and expression of those factors, as well as intrinsic cellular variation have obscured how the levels of individual transcription factors promote or impede reprogramming (Jain et al, 2023; Wang et al, 2020). Process variability combined with low rates of reprogramming constrain our ability to resolve the distinct molecular states and processes that cells adopt during successful reprogramming (Ilia et al, 2023).…”

“…While transcriptional profiling identifies expression trajectories, transcription factors exert their influence as proteins, which cannot be directly imputed from mRNA expression (Hafner et al, 2017; Ideker et al, 2001; Lundberg et al, 2010). Moreover, global processes such as transcription, replication, and proliferation strongly influence reprogramming events and may amplify or dampen the expression and activity of transcription factors (Babos et al, 2019; Hu et al, 2020; Jain et al, 2023; Kueh et al, 2013; Palozola et al, 2017; Percharde et al, 2017; Stadhouders et al, 2018). Thus, transcription factors are a powerful driver of cellular reprogramming but how they combine with other global processes to guide cell-fate transitions remains unclear.…”

“…In direct conversion, cells do not necessarily transit through a defined progenitor state (Son et al, 2011) and proliferation is not required for reprogramming (Di Tullio and Graf, 2012; Fishman et al, 2015; Heinrich et al, 2010). However, highly proliferative cells reprogram at higher rates to both induced pluripotent stem cells (iPSCs) and to post-mitotic neurons, suggesting that proliferation may serve a conserved role in facilitating cell-fate transitions (Babos et al, 2019; Guo et al, 2014; Jain et al, 2023). Curiously, we and others have observed that the rate of proliferation can substantially impact the expression of transcription factors in both native and synthetic systems (Babos et al, 2019; Kueh et al, 2013).…”