Monthly Archives: June 2022

CHICAGO, June 21, 2022 /PRNewswire/ --According to the new market research report "Stem Cell Assays Market by Type (Viability, Proliferation, Differentiation, Apoptosis), Cell Type (Mesenchymal, iPSCs, HSCs, hESCs), Product & Service (Instrument), Application (Regenerative Medicine, Clinical Research), End User - Global Forecast to 2027", published by MarketsandMarkets, the global market is projected to reach USD 4.5 billion by 2027 from USD 1.9 billion in 2022, at a CAGR of 17.7 % during the forecast period of 2022 to 2027.

Browse in-depth TOC on "Stem Cell Assays Market"393 Tables 47 Figures 331 Pages

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The stem cell assays market is expected to grow at a CAGR of 17.7% during the forecast period. The growth of the market is projected to be driven by increasing funding for stem cell research, rising demand for cell-based assays in drug discovery, and the rising incidence of cancer across the globe.

The viability/cytotoxicity assays accounted for the largest share of the type segment in the stem cell assays market in 2021.

Cell viability assays help to determine the number of live and dead cells in a culture medium. The viability/cytotoxicity assays includes various types such as tetrazolium reduction assays, resazurin cell viability assays, calcein-AM cell viability assays, and other viability/cytotoxicity assays. The segment accounted for the largest share on 2021. Increase in demand for stem cell assays in drug discovery and development is projected to drive the segment growth.

The adult stem cells segment accounted for the largest share of the cell type segment in the stem cell assays market in 2021.

The adult stem cells accounted for the largest share of the stem cell assay market. The stem cells include mesenchymal stem cells, induced pluripotent stem cells, hematopoietic stem cells, umbilical cord stem cells, and neural stem cells. Increasing demand for mesenchymal stem cells and induced pluripotent stem cells for development of stem cell based therapies and rising R&D spending are various factors projected to drive the segment growth.

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The Asia Pacific region is the fastest-growing region of the stem cell assays market in 2021.

The Asia Pacific is estimated to be the fastest-growing segment of the market. The growth of the stem cell assays markets of China and India is mostly driven by growing public-private funding to support stem cell product development and commercialization and rising prevalence of cancer & other diseases. Furthermore, growing emphasis on strategic initiatives (such as acquisitions, partnerships, and collaborations) by biopharma and biotech companies is expected to support the market growth in the region.

Key players in the stem cell assays market include Thermo Fisher Scientific Inc. (US), Merck KGaA (Germany), Danaher (US), Becton, Dickinson and Company (US), Bio-Rad Laboratories (US), PerkinElmer (US), Agilent Technologies (US), Promega Corporation (US), Cell Biolabs (US), Miltenyi Biotec (Germany), STEMCELL Technologies (Canada), Bio-Techne Corporation (US), FUJIFILM Holdings Corporation (Japan), Charles River Laboratories (US), HemoGenix Inc. (US), Lonza Group (Switzerland), Takara Bio Inc. (Japan), Creative Bioarray (US), AAT Bioquest, Inc. (US), BPS Bioscience, Inc. (US), Enzo Biochem (US), PromoCell GmbH (Germany), Biotium (US), Geno Technology (US), Abcam plc (UK), and ReachBio Research Labs (US).

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Stem Cell Assays Market worth $4.5 billion by 2027 - Exclusive Report by MarketsandMarkets - PR Newswire UK

A new study reveals how photoreceptors grown from stem cells might extend biological wires, known as axons, to contact existing neurons.

The finding has implications for future treatment of retinal diseases that cause blindness, including age-related macular degeneration and rare diseases such as retinitis pigmentosa, Usher syndrome, Stargardt disease and Best disease.

Emily Kumlien (608)516-9154ekumlien@uwhealth.org

People living with these diseases, which are currently uncurable, ultimately lose vision due to destruction of light sensitive cells called rods and cones. Neuroscientists are working on therapies to grow these cells, also known as photoreceptors, from stem cells and transplant them to restore damaged tissue.

However, while the ability to manufacture lab-grown photoreceptors has advanced considerably, it remains challenging to install them. Once transplanted, the photoreceptors must grow axons to connect with existing inner neurons so the light they detect is transmitted via signals to the brain.

The University of Wisconsin School of Medicine and Public Health research team showed that photoreceptors derived from stem cells are initially able to grow axons on their own to connect to other cells but lose that ability within 40 to 80 days. However, they found that mobile helper cells can assist photoreceptors that are no longer able of independently growing axons by pulling and dramatically stretching parts of them.

An image from thestudyis on the cover of the journalCell Reports.

Understanding how photoreceptors reach out to make these connections brings us another step closer to being able to transplant stemcell derived photoreceptors to cure blindness, said Timothy Gomez, professor of neuroscience at the school, and the studys senior author.

Sarah Rempel, a postdoctoral researcher who led the study and works in the Gomez lab, collaborated with the research team led by co-author Dr. David Gamm, professor of ophthalmology and visual science to successfully generate retinal organoids. Retinal organoids are three-dimensional models of the retina derived from human pluripotent stem cells.

As the organoids developed, the human pluripotent stem cell-derived photoreceptors began to produce cone cells, which are critical for human daytime vision. This started around day 30. They also produced rod cells, which allow vision in low-light conditions, which began around day 70.

Photoreceptors undergo axon elongation

Then the team used time-lapse imaging of the living cells to watch as the axons extended from the photoreceptors toward their target cells. While the ends of recently generated cone photoreceptor axons could actively elongate, their window to do so was surprisingly short; by day 80 they lost this ability. Rod photoreceptors, in contrast, completely lacked the ability to extend axons on their own.

The team discovered that older laboratory-grown photoreceptor cells could extend axons to make connections if they were grown along with other, motile retinal cells. Unexpectedly, axons of the photoreceptor cells could attach themselves to these cells and be pulled along for the ride.

The team is also exploring the possibility of encouraging remaining retinal cells targeted by newly transplanted photoreceptors to reach out as well.

The study is an important step in developing stem cell therapies for blindness, said Gamm, who is also director of the McPherson Eye Research Institute and an expert in retinal stem cells and their applications to human disease.

Work here at UWMadison is really converging on this field, he explained. We are beginning to understand core principles of how we might replace photoreceptor cells in people with advanced stages of blinding disease.

Other members of the research team include Madalynn Welch, Allison Ludwig, M. Joseph Phillips and Yochana Kancherla from the UW School of Medicine and Public Health, and Dr. Donald Zack of Johns Hopkins University.

The work was supported by a grant from the National Eye Institute Audacious Goals Initiative, which is aimed at regenerating photoreceptors and other cell types in the human retina.

Additional funding was provided by the National Institute of Neurological Disorders and Stroke (5R01 NS113314-02, 5R01 NS041564, and 1R21 NS113314-01A1), the National Eye Institute (NEI) ( U01 EY027266-01 ), the Retina Research Foundation Emmett Humble Chair, the Sarah E. Slack Prevention of Blindness Fund (a component fund of the Muskingum County Community Foundation), the McPherson Eye Research Institute Sandra Lemke Trout Chair in Eye Research, the Guerrieri Family Foundation, and Research to Prevent Blindness, a core grant to the Waisman Center (NICHHD U54 HD090256), NEI grant T32 EY027721, the UW-Madison School of Veterinary Medicine DVM/PhD Program, NEI grant U24 EY029890, and a Kirschstein NRSA Predoctoral Fellowship ( NEI grant F30 EY031230 ).

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UW eye research uncovers how stem cell photoreceptors reach their targets - University of Wisconsin School of Medicine and Public Health

Scientists have developed a new technique that can repair and even regenerate heart muscle cells after a heart attack (or myocardial infarction).

While it has only been tested on mice so far, if it works the same in humans it could potentially be a life-saving treatment for people who have suffered a heart attack.

The technique uses a synthetic messenger ribonucleic acid (mRNA).mRNA creates a 'blueprint' of DNA sequences that the body then uses to build the proteins that form and regulate our cells.By tweaking the mRNA, scientists can deliver different instructions for different biological processes.

Here, the edited instructions promote the replication of heart muscle cells (cardiomyocytes) via two so-called mutated transcription factors, Stemin and YAP5SA.

Essentially, the idea is to make heart muscle cells, which have very little ability to regenerate, act more like stem cells, which can be turned into various other types of specialized cells by the body.

The difference made by the mRNA treatment after four weeks. (The Journal of Cardiovascular Aging)

"No one has been able to do this to this extent and we think it could become a possible treatment for humans," says biologist Robert Schwartz, from the University of Houston in Texas.

Less than 1 percent of adult cardiac muscle cells can regenerate the cardiomyocytes we have when we die are mostly the same ones we've had since the first month of life and that means heart attacks and heart disease can leave the heart in a permanently fragile state.

In experiments in both tissue culture dishes and in living mice, Stemin was shown to turn on stem cell-like properties in the cardiomyocytes, while YAP5SA promoted organ growth and replication. The process has been described as a "game-changer" by the team.

The in vivostudy involving living mice affected by damaged hearts showed myocyte nuclei replicating by at least 15-fold in the 24 hours after the injections of the mutated transcription factors, Stemin and YAP5SA.

"When both transcription factors were injected into infarcted adult mouse hearts, the results were stunning," says Schwartz.

"The lab found cardiac myocytes multiplied quickly within a day, while hearts over the next month were repaired to near normal cardiac pumping function with little scarring."

The synthetic mRNA added to the cells disappeared in a few days, just as the mRNA produced in our bodies does, the researchers report. This gives the new technique an advantage over gene therapy processes that cannot be easily stopped or removed once they're underway.

It still remains to be seen whether the approach can be translated successfully into humans and many more years of research will be required to get this into a working treatment but the team behind the research is confident.

Work continues to understand more about heart disease and heart injury, andhow the body respondsin its aftermath. Studying cardiovascular health remains a priority for scientists, with heart disease currentlythe leading cause of deathin the US (accounting for around a quarter of all deaths).

"This is a huge study in heart regeneration especially given the smart strategy of using mRNA to deliver Stemin and YAP5SA,"says biologist Siyu Xiao, from the University of Houston.

The research has been published in hereandherein the Journal of Cardiovascular Aging.

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Scientists Have 'Healed' a Heart Attack in Mice by Regenerating Muscle Cells - ScienceAlert

In the current study, Ding and colleagues have identified a drug cocktail that induces an all-powerful stem cell type at will, a cell type that can turn into an entire organism on its own. The researchers are also able to maintain the resulting cells' differentiation potential in the lab, allowing a stable system for later researchers to demystify the creation of life. This alternative path obtaining a clean slate of life's earliest raw materials from more mature cells, instead of new sperms and eggs -- can have a wide range of implications. "Such an alternate to nature's way of creating the beginning of life is a holy grail of biology", Ding says.

The creation of life starts with one cell. Your blood, brain, and liver cells can all be traced back to this one-cell embryo or zygote.

In nature, a zygote is produced as sperm and egg merge together. And the event kicks off an irreversible process where the zygote divides, forms new cells and the new cells continue to divide and become increasingly specialized.

As specialization is gained, something is lost along the way. Once the one-cell embryo divides and hits the two-cell embryo stage, the later cells will quickly lose the differentiation potential to give rise to all cell types for generating an entire organism and its supportive tissues like the yolk sac and placenta, becoming less potent stem cells.

Scientists call these all-powerful cells in the one-cell and two-cell embryo stages totipotent stem cells. And there are pluripotent and multipotent stem cells further down the continuum. "Normally after totipotent cells, none of the other stem cells have the possibility to turn into a life on its own," Ding says.

To better study and control the totipotent stem cells, Ding and his team established a system that achieves the induction and maintenance of these cells, and confirmed their identity with stringent criteria.

With 20 years of work and understanding of cell fate and stem cell regulation by chemical compounds, the team selected and screened thousands of small molecule combinations. Through multiple rounds of analyses, they identified three small molecules that could coax mouse pluripotent stem cells into cells exhibiting totipotent characteristics. The researchers called the molecules TAW cocktail. Each letter in TAW stands for a molecule known to regulate a specific cell fate decision. But their combined effect was not known till the current discovery, Ding explains.

Then the researchers examined cells receiving the TAW cocktail treatment in detail, both their totipotency and none-pluripotency. These cells passed strict molecular testing criteria, at all transcriptome, epigenome, and metabolome levels. For example, the team found that hundreds of critical genes were turned on in the TAW cells. These genes are typically found in totipotent cells and have been indicated by other researchers in the field as the bar to determine totipotency. At the same time, genes associated with pluripotent cells were silenced in the TAW cells.

To further prove that the resulting cells have a true totipotent state, the team tested their differentiation potential in vitro, and also injected them into a mouse early embryo to see the differentiation potential in vivo. They found that not only did the cells behave like true totipotent ones in a petri dish, but they also differentiated into both embryonic and extraembryonic lineages in vivo. This is a typical characteristic of normal totipotent cells, which have the potential to develop into both fetus and the surrounding yolk sac and placenta, whereas pluripotent cells can only develop into a fetus.

In addition, when the researchers used special culture conditions for the TAW cocktail-induced totipotent cells, the subsequent cells also showed similar totipotency traits. This observation suggests that the totipotency of TAW-induced cells can be maintained in a lab environment, and thus a stable system is established.

Such a system is important, as it will enable many scientific investigations concerning the beginning of life. For example, scientists can use this system to manipulate the totipotent cells to better understand the highly orchestrated process at the beginning of life. "Certain cells will have to appear at the right time and the right location for life to occur," Ding says, and one cannot study this without proper tools.

In this sense, "this paper is the first step and opens up tremendous opportunities," he says.

Moreover, having a deeper understanding and thus control over totipotent cells will have a wide range of implications, such as earning a second chance at the creation of individual life and even accelerating the evolution of a species.

Many of the possibilities will spur controversies, Ding acknowledges. It's worth noting that while those possibilities lie in the distant future, he mentions, it's hard to predict what society's ethical concerns will be. After all, the science community hasn't seen any lighter restrictions around human embryo research in the past decade. But last year, people started to seriously consider extending how long a human embryo can be kept in a petri dish from the original 14-days rule.

While the team is highly conscious of ethical considerations, Ding believes that as scientists their main job is to focus on making discoveries in the present, and lay the ground for future generations. Then the latter will have the knowledge and tools to make decisions.

SOURCE School of Pharmaceutical Sciences, Tsinghua University

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Scientists take the first step to master an all-powerful cell type in the beginning of life - PR Newswire

Mapping molecular changes across malignant transformation

We generated single-cell data for 81 samples collected from eight FAP and seven non-FAP donors (Fig. 1a and Supplementary Tables 1 and 2). For each tissue, we performed matched scATAC-seq and snRNA-seq (10x Genomics). We obtained high-quality single-cell chromatin accessibility profiles for 447,829 cells from 80 samples, with a mean transcription start site (TSS) enrichment of ~8 for most samples (Extended Data Fig. 1a). After removing low-quality snRNA-seq cells and samples, we obtained single-cell transcriptomes for 201,884 cells from 70 samples (Extended Data Fig. 1b). Whenever there was sufficient tissue, we generated microscopic pathology data (Extended Data Fig. 2a and Supplementary Table 2) and found the majority of polyps were tubular adenomas, the most common polyp type identified in colonoscopies.

a, Summary of the samples in this study. The bar chart shows the number of normal/unaffected colon tissues (gray), adenomas (purple) and CRCs (red) assayed for each patient. Locations of samples assayed from a single patient are indicated on the colon on the upper right. These data include deep profiling of four patients with FAP from whom we assayed 811 polyps, 01 carcinomas and 45 matched normal (unaffected) tissues. From non-FAP donors, we collected data on normal colon (9 samples from 2 donors), polyps (1 sample from 1 donor) and CRC tissues (4 samples from 4 patients). b,c, UMAP representations of all snRNA-seq (b) and scATAC-seq (c) cells colored by whether the cells were isolated from normal/unaffected colon tissues, adenomas or CRCs. d,g, UMAP representations and annotations of immune (d) and stromal (g) cells. e,h, Fraction of each immune (e) and stromal (h) cell type isolated from normal (green), unaffected (blue), polyp (purple) and CRC (red) samples. The color gradations within each color represent the contributions of each single sample (for example, each shade of red is a single CRC). f, CODEX images of eight polyps and two CRCs where cells are labeled with dark blue, CD3 is labeled in green and PD1 is labeled in light blue. All samples tested are shown in f. CODEX imaging of individual specimens was not reproduced. Representative sections of images of the entire specimen are shown in the figure. DC, dendritic cell; Fib., fibroblast; GC, germinal center; ILC, innate lymphoid cell; Myofib., myofibroblast/smooth muscle; NK, natural killer.

When all snRNA-seq cells (Fig. 1b) and scATAC-seq cells (Fig. 1c) are projected into low-dimensional subspaces, stromal and immune cells generally cluster by cell type whereas epithelial cells largely separate into distinct clusters comprising cells derived from polyps, unaffected tissues or CRCs. As a result, we annotated immune and stromal cells by subclustering cells from all samples, and analyzed epithelial cells separately.

The immune compartment comprised B cells, T cells, monocytes, macrophages, dendritic cells and mast cells (Fig. 1d). We examined expression of known marker genes (Extended Data Fig. 1c) to annotate snRNA-seq data, and examined chromatin activity scoresa measure of accessibility within and around a given gene bodyassociated with marker genes to annotate the scATAC cells (Extended Data Fig. 1d). We identified a cluster of exhausted T cells in the scATAC data that exhibited high gene scores of T cell exhaustion marker genes and accessibility at exhausted T cell motifs, and was labeled as exhausted T cells by a published dataset (Extended Data Fig. 3ag and Methods)15.

The cell types identified were present in nearly all samples, although some cell types were enriched or depleted in specific disease states (Fig. 1e and Extended Data Figs. 2b,c, 3h and 4). Significant differences in cell-type abundance were identified with both Wilcoxon testing and a generalized linear model-based method called Milo16, which produced consistent results. For example, regulatory T cells (Tregs) were enriched in polyps relative to unaffected tissue, while naive B, memory B and germinal center cells were enriched in unaffected tissues relative to polyps (Extended Data Fig. 4a,b). Enrichment of myeloid cells and specific types of T cells and depletion of B cells was recently reported in a group of 22 mismatch repair-proficient and 13 mismatch repair-deficient CRCs17, and we observe similar shifts in the tumor immune composition in precancerous polyps.

The enrichment of (1) Tregs in both polyps and CRC and (2) exhausted T cells in CRC suggests mechanisms of immune evasion in the precancerous and cancerous states18. T cell exhaustion, which occurs in response to chronic antigen stimulation and is characterized by reduced cytokine production and increased expression of inhibitory receptors, is thought to be a primary mechanism of immune evasion by cancers19,20. To further support the observation of T cell exhaustion only occurring in CRC, we performed CODEX imaging of CD3 and PD1 and found low or undetectable PD1 expression in eight polyps but found PD1 expression in both CRC samples tested (Fig. 1f).

Within the stromal compartment, we identified glial cells, adipose cells and multiple types of endothelial cells and fibroblasts (Fig. 1g). Fibroblast subtypes include crypt fibroblasts (WNT2B or RSPO3 high), villus fibroblasts (WNT5B high) and myofibroblasts (ACTA2 and TAGLN high) (Extended Data Figs. 1f,g and 5a)21,22. Consistent with previous results, we observe high expression of BMP signaling genes in villus fibroblasts (Extended Data Fig. 5a). In agreement with recent reports that crypt fibroblasts secrete semaphorins to support epithelial growth, we observe one fibroblast cluster with high expression of semaphorins (Extended Data Fig. 5a)23. This cluster of fibroblasts exhibited the highest expression of RSPO3, a factor that supports the intestinal stem cell niche24. We also observe a cluster of cancer-associated fibroblasts (CAFs) consisting almost exclusively of cells from CRCs, and a scATAC cluster of fibroblasts enriched for cells from polyps and CRCs with accessibility around some of the same genes as CAFs, which we term pre-cancer-associated fibroblasts (preCAFs) (Fig. 1h and Extended Data Figs. 2d,e and 4). These observations suggest that phenotypically distinct fibroblasts exist in polyps and tumors, and thus may play a role in tumorigenesis in precancerous lesions.

We next integrated our scATAC-seq and snRNA-seq datasets to enable analyses of regulatory elements and TFs potentially driving gene expression. We aligned the datasets with canonical correlation analysis (CCA) and assigned RNA-seq profiles to each scATAC-seq cell (integrated expression)25. We then labeled scATAC cells with the nearest snRNA-seq cells, which closely agreed with manual immune (Extended Data Fig. 1i) and stromal (Extended Data Fig. 5b) annotations. Finally, we identified peaks highly correlated to gene expression of proximal genes in our datasets, which resulted in 52,443 stromal peak-to-gene links (Extended Data Fig. 5c,d).

CAFs promote cancer development and progression through diverse mechanisms including matrix remodeling, signaling interactions with cancer cells and perturbation of immune surveillance26,27,28. We observe a CAF cluster with high expression of known CAF marker genes FAP and TWIST1 (Extended Data Fig. 5a)29,30. Among the most significant snRNA-seq markers for CAFs were FAP, VCAN and COL1A2, which are involved in extracellular matrix remodeling and upregulated in multiple cancers30,31,32 (Fig. 2a). Specific expression of these genes by CAFs suggests fibroblasts participate in unique extracellular matrix remodeling in cancerous tissues that does not occur in normal colon or precancerous polyps.

a, Dot plot representation of significant (MAST test) marker genes for CAFs. b, Genomic tracks for accessibility around WNT2 and RUNX1 for different stromal cell types. Peaks called in the scATAC data and peaks-to-gene links are indicated below the tracks. For example, a regulatory element ~50kb away from the WNT2 TSS that is most accessible in CAFs whose accessibility is highly correlated to gene expression of WNT2 is indicated below the tracks. Marker peaks (Wilcoxon FDR0.1 and log2FC1.0) for each fibroblast subtype are indicated below the tracks. c, Marker peaks (Wilcoxon FDR0.1 and log2FC0.5) for each stromal cell type. Significance is determined by comparing each cell type with a background of all other cell types. d, Hypergeometric enrichment of TF motifs in stromal cell marker peaks. e, Plot of maximum difference between chromVAR deviation z-score, depicting TF motif activity, against correlation of chromVAR deviation and corresponding TF expression. TFs with maximum differences in chromVAR deviation z-score in the top quartile of all TFs and a correlation of greater than 0.5 are indicated in red. f, RNA expression (top) and chromVAR deviation z-scores (bottom) for selected TFs. The RNA expression plotted is the expression in the nearest RNA cell following integration of the snRNA-seq and scATAC-seq data. Corresponding violin plots and boxplots quantifying integrated gene expression and chromVar deviation z-scores for cells in each cell type are shown at the right. Boxplots represent the median, 25th percentile and 75th percentile of the data, and whiskers represent the highest and lowest values within 1.5 times the interquartile range of the boxplot. Cell types with significantly higher (Wilcoxon test, FDR0.01 and log2FC1) integrated RNA expression when compared with all other cell types are indicated with an asterisk. Assoc., associated; C. Fib, crypt fibroblast; Endo., endothelial; Norm., normalized.

While CAFs are known to promote CRC progression, we next explored the role of fibroblasts in precancerous lesions. Because the preCAF cluster was enriched for cells from polyps, we examined accessibility around marker genes for CAFs and found many of these genes more accessible in preCAFs than other fibroblast subtypes. For example, CAFs secrete WNT2 to promote cell proliferation and angiogenesis in CRC33,34. CAFs and preCAFs exhibit the greatest accessibility at the WNT2 TSS (Fig. 2b), suggesting that chromatin changes promote expression of WNT2 in CAFs and preCAFs. We also observed that preCAFs demonstrated higher integrated expression of multiple CAF marker genes than other fibroblast subtypes (Extended Data Fig. 5e). We computed global CAF accessibility scores for all fibroblast subtypes (Methods) and found that preCAFs had the highest median CAF scores other than CAFs (Extended Data Fig. 5f). Further, accessibility in CAFs was most correlated with preCAFs; however, the correlation with one crypt fibroblast subtype was only slightly lower (Extended Data Fig. 5g). Together, this highlights the similarities between CAFs and preCAFs and suggests that preCAFs may perform similar functions to CAFs.

We found that CAF marker peaks were enriched for JUN/FOS and CEBP motifs and preCAF marker peaks were enriched for JUN/FOS and FOX motifs (Fig. 2c,d and Methods). To nominate TFs driving changes in chromatin accessibility in different stromal cell types, we identified TFs with the highest correlation between their gene expression and the chromatin accessibility activity level of its DNA motif (Fig. 2e, x axis). Amongst the most correlated TFs were RUNX1, RUNX2 and CEBPB. We next plotted the expression and motif activities of these TFs on the Uniform Manifold Approximation and Projection (UMAP) representation of the stromal cells and in violin plots grouped by each cell type (Fig. 2f), and noted that chromatin activity levels for RUNX1 and RUNX2, which have similar motifs, are highest in CAFs and preCAFs. However, RUNX1 is primarily expressed in CAFs and preCAFs, while RUNX2 has much lower expression in CAFs, suggesting that RUNX1 is a stronger driver of accessibility at RUNX motifs than is RUNX2 in CAFs.

Consistent with the expression of these genes, we observed the greatest accessibility around the RUNX1 TSS in CAFs and preCAFs (Fig. 2b). When comparing gene scores for each stromal cell type with all other stromal cells, preCAFs had significantly higher RUNX1 gene scores (log2 fold-change (log2FC)>1 and false discovery rate (FDR)<0.01), and no other cell types met this significance threshold. When identifying accessibility closest to RUNX1, we found five significant marker peaks for preCAFs and four for CAFs (Fig. 2b).

We examined the epithelial cells that initially clustered by unaffected, polyp or CRC disease state (Fig. 1b,c and Extended Data Fig. 6e). To analyze these data, we first constructed RNA-seq and ATAC-seq references composed of normal epithelial colon cells collected from patients without FAP (Fig. 3a). We annotated cell types in this normal tissue using gene expression and gene activity scores of known marker genes (Extended Data Fig. 6a,b). A stem cell population with high expression and accessibility of LGR5, SMOC2, RGMB, PTPRO, EPHB2 and LRIG1 was evident (Extended Data Fig. 6b), as were goblet cells (MUC2 high) and BEST4+ enterocytes (BEST4 high). Following manual annotation, the snRNA-seq and scATAC-seq datasets were aligned with CCA25,35, and the scATAC cells were labeled based on the nearest snRNA-seq cells, which agreed with the manual annotations for 65% of cells, with mislabeled cells typically being labeled as the nearest cell type in the differentiation trajectory (Extended Data Fig. 6c,d).

a, UMAP projection of snRNA-seq (left) and scATAC-seq (right) epithelial cells isolated from normal colon with cells colored by cell type. Colors for the cell types are defined in c. b, Projection of epithelial snRNA-seq (top) and scATAC-seq (bottom) cells from unaffected (left), polyp (center) and CRC (right) samples into the manifold of normal colon epithelial cells. Projected cells are colored by nearest normal cells in the projection and normal epithelial cells are colored gray. c, Fraction of each epithelial cell type isolated from normal (green), unaffected (blue), polyp (purple) and CRC (red) samples. Cell types are defined based on the identity of the nearest cell types when projecting epithelial cells into normal colon subspace. d, Boxplots depicting the fraction of cells within the epithelial compartment that are stem-like cells, enterocyte progenitors or enterocytes, divided by disease state. Abundances of each cell type in unaffected, polyp and CRC tissues are compared with their abundances in normal tissues with two-sided Wilcoxon testing and Bonferroni correction for multiple comparisons, and the resulting adjusted P values are listed in the plots. The boxplots are constructed with data from 8 normal samples, 18 unaffected samples, 48 polyp samples and 6 CRC samples. Boxplots represent the median, 25th percentile and 75th percentile of the data; whiskers represent the highest and lowest values within 1.5 times the interquartile range of the boxplot; and all points are plotted. e, Distribution of snRNA-seq and scATAC-seq stem scores in all epithelial cells in each sample. The rows represent individual samples and the columns represent 50 bins of stem scores from low to high for RNA (left) and ATAC (right). The heatmap is colored by the percentage of epithelial cells in each sample that are in a given bin of stem scores. A, adenocarcinoma; Ent., enterocyte; N, normal; P, polyp; TA, transit amplifying; U, unaffected FAP.

We then projected the remaining cells into this normal subspace25, and found that epithelial cells from polyps and CRCs tend to project closer to stem cells and other immature cells along the normal differentiation trajectory, whereas cells from unaffected tissues projected relatively evenly throughout the epithelial compartment (Fig. 3b). We classified all epithelial cells based on the nearest normal cells in the projection and found that cells originating from polyps and CRC samples are enriched for stem-like epithelial cells and depleted for mature enterocytes, suggesting that epithelial cells increasingly demonstrate a stem-like phenotype during the transformation from normal to polyp (Fig. 3bd and Extended Data Fig. 4a,b). We speculate that the populations of stem-like cells in the polyps and CRCs likely represent the cancer stem cells in these tissues. Expression of previously described intestinal stem cell and colon cancer stem cell marker genes in these stem-like populations is discussed in detail in a Supplementary Note and Extended Data Fig. 7a.

To quantify the degree of stemness in individual cells within samples, we assigned scores quantifying stemness for each snRNA-seq and scATAC-seq cell and ordered samples by the distribution of stem scores within each sample (Methods and Fig. 3e). As expected, unaffected samples have generally lower stem scores. A number of polyps clustered near the unaffected tissues, suggesting that they are relatively benign. However, cells from most polyps and CRCs typically had higher stem scores, with some demonstrating a larger spread of stemness and others with much tighter distributions of stem scores, indicating that some polyps may be more heterogeneous. Similar results were observed when ordering samples based on the nearest normal cell type in the projection into the normal colon subspace (Methods and Extended Data Fig. 7h).

We next compared the gene expression and chromatin accessibility of polyp and CRC stem-like cells with normal stem cells to identify the aberrant gene expression and regulatory programs in precancerous and cancerous lesions. After computing differential peaks between stem-like cells from each sample and cells from the nearest normal cell type, we computed the principal components of the log2FC for these peaks, then ordered samples by their position along a spline fit in this space (Fig. 4a), where position in ordering can be interpreted as position in a continuum from normal tissue to cancer. We generated a similar RNA trajectory using differential genes rather than differential peaks (Methods). The ordering of samples along the continua defined from the snRNA-seq and scATAC-seq datasets exhibited strong agreement (Extended Data Fig. 6j). This analysis suggests that differences in gene expression and chromatin accessibility between stem cells and these stem-like polyp cells follow a stereotyped progression from early to late polyp to invasive CRC.

a, Malignancy continuum for snRNA-seq (left) and scATAC-seq (right). Principal components were computed on the log2FC values between stem-like cells from each sample and normal colon stem cells for the set of peaks and genes that were significantly differential (Wilcoxon FDR0.05 and |log2FC |1.5 for peaks; MAST test for genes) in at least two samples. A spline was fit to the first two principal components (red) and samples were ordered based on their position along the spline. b, Genomic alterations in common driver genes ordered by the malignancy continuum. c,d, Number of significantly differential genes (MAST test) (c) and peaks (Wilcoxon test) (d) for each sample relative to all unaffected samples. e,f, Heatmap of all genes (e) and peaks (f) that were significantly differentially expressed (MAST test, Padj0.05 and |log2FC|0.75) or accessible (Wilcoxon test, Padj0.05 and |log2FC|1.5) in 2 samples. Samples are ordered along the x axis by the malignancy continuum defined in d. Genes and peaks are k-means clustered into ten groups. g, Hypergeometric enrichment of TF motifs in k-means clusters of peaks defined in e. h, log2FC in expression of ASCL2, HNF4A and GPX2 in stem-like cells from each sample relative to stem-like cells in unaffected samples plotted against the malignancy continuum defined in d. Samples are colored based on if they are derived from polyps or CRCs.

To determine if this continuum is specific to the stem-like cells, which would be consistent with these cells being the only malignant cells in the samples, or if other epithelial cells also exhibit a continuum, which would be consistent with other cell types within the polyp being derived from cancer stem-like cells rather than normal cells, we performed the same analysis with TA2 cells (Extended Data Fig. 6f). We found that TA2 cells exhibit a similar continuum, suggesting that they continue to be derived from stem-like cells. When we perform a control analysis with plasma cells, which are not derived from cancer cells, we do not observe a similar continuum (Extended Data Fig. 6f). Comparison of the continuum with microscopic pathology and genomic alterations (Fig. 4b) is discussed in the Supplementary Information.

After computing the trajectory, we repeated the differential analysis using all unaffected samples rather than normal samples to increase the total number of patients and cells in the background group. We observe that the absolute number of significantly differential peaks and genes gradually increased along the malignancy continuumwith adenocarcinoma samples exhibiting the largest number of differential peaks and genes (Fig. 4c,d).

We examined gene expression changes along this malignancy continuum by selecting genes differentially expressed in at least two samples then clustering these genes into ten k-means clusters (Fig. 4e). These clusters correspond to groups of genes that become differentially expressed at distinct stages of malignant transformation. For example, clusters 14 comprise genes upregulated in stem-like cells in early-stage polyps when compared with unaffected stem cells. Members of cluster 4 include OLFM4, a marker of intestinal stem cells36, indicating that OLMF4 expression increases in stem-like cells from polyps as they approach malignancy. Cluster 4 also includes GPX2, a glutathione peroxidase known to be upregulated in CRC that functions to relieve oxidative stress by reducing hydrogen peroxide, facilitating both tumorigenesis and metastasis37 (Fig. 4h). The upregulation is not donor dependent, and we observe the same trend across all donors in our study (Extended Data Fig. 6g). We observed translation Gene Ontology terms enriched in cluster 4 and splicing and RNA-processing Gene Ontology terms enriched in cluster 2 (Extended Data Fig. 6k). Clusters of genes that gradually reduce expression along the transition from normal colon to cancer (clusters 69) and genes specific to malignant transformation are discussed in a Supplementary Note and Extended Data Fig. 8a.

To identify groups of polyps associated with invasive transformation, we clustered the 36,374 peaks significantly differential compared with the nearest unaffected cell type in at least two samples into ten k-means clusters (Fig. 4f), revealing five clusters that become more accessible and five clusters that become less accessible at different stages of the transition to cancer. To identify TFs driving chromatin accessibility changes in the transition from normal colon to CRC, we computed hypergeometric enrichment of motifs in each cluster of peaks from Fig. 4f (Fig. 4g) and ensured the stability of these results (Extended Data Fig. 7bg).

TCF and LEF family motifs were enriched in all clusters that became more accessible across the malignancy continuum (clusters 15), consistent with the fact that loss of APC leads to -catenin accumulation in the nucleus, which interacts with TCF and LEF TFs to drive WNT signaling38,39,40. This regulatory transformation is gradual across the malignant continuumnew peaks containing TCF and LEF motifs continue to open at all stages of colon cancer development, as does overall accessibility aggregated across TCF and LEF motifs, suggesting that WNT signaling gradually increases throughout this transformation, over and above what is observed in normal stem cell populations.

Cluster 3 peaks, which became more accessible in later-stage polyps and CRC, also exhibited enrichments of ASCL2 motifs (Fig. 4g). ASCL2 is a master regulator of intestinal stem cell fate, and induced deletion of ASCL2 leads to loss of LGR5+ intestinal stem cells in mice41. Consistent with a linkage between a more stem-like state in polyp epithelium and more advanced malignant continuum scores, ASCL2 expression gradually increases as polyps approach malignant transformation (Fig. 4h), again indicative of a super stem-like phenotype, wherein master regulators of stem state are even more active than they are in normal stem cells.

Motifs lost along the malignancy continuum include HOX family motifs, KLF motifs and GATA motifs (Fig. 4g), and specific KLF TFs along the malignancy continuum are discussed in detail in a Supplementary Note and Extended Data Fig. 8d,e. Clusters 4 and 5 exhibit large accessibility increases only in CRC samples, and the greatest enrichment for HNF4A motifs (Fig. 4g). This observation suggests differential usage of HNF4A in polyps, where it decreases to drive WNT signaling, versus in CRC, where it is upregulated to drive cancer-specific accessibility differences (Supplementary Note and Extended Data Fig. 8b,c).

We calculated the fractional contributions of each cell type to each sample as a function of position in the malignancy continuum, and found some cell types were highly correlated with progression along the malignancy continuum. For example, the fraction of stem cells within a sample gradually increases throughout malignant transformation (Fig. 5a,i). Similarly, the number of mature enterocytes decreases as polyps transform to carcinomas (Fig. 5b,i). Milo analysis revealed that neighborhoods of stem-like cells tend to be significantly more abundant at the end of the malignancy continuum (Extended Data Fig. 4b). In the secretory compartment, which primarily consists of immature and mature goblet cells, we observe a fractional increase in immature goblet cells in many polyps. In carcinomas we see a pervasive lack of differentiation into the secretory lineage, effectively eliminating immature and mature goblet cells (Fig. 5c,d,i). This observation is consistent with previous work reporting a depletion of goblet cells in nonmucinous colon adenocarcinomas42. Previous work has also found that knockout of MUC2 leads to the formation of more adenomas and carcinomas in mice43, suggesting that the loss of immature and mature goblet cells may even contribute to tumorigenesis.

ah, Fraction of cell type in each scATAC sample plotted against position of the sample in the malignancy continuum defined in Fig. 4d for stem-like cells (a), enterocytes (b), immature goblet cells (c), goblet cells (d), Tregs (e), exhausted T cells (f), preCAFs (g) and CAFs (h). Samples are colored based on if they are derived from unaffected tissues, polyps or CRCs. Fractions are computed by dividing the number of cells of a given cell type by the total number of cells in the compartment (epithelial versus immune versus stromal). i, Stacked boxplot representation of the fraction of epithelial cells of each cell type for each scATAC sample along the malignancy continuum.

Outside the epithelial compartment, we also observe changes in cellular composition across the transformation from unaffected to polyp to carcinoma. Within the stromal compartment, the fraction of preCAFs gradually increases, while CAFs only appear in CRCs (Fig. 5g,h). Within the immune compartment, Tregs are increased in the more malignant polyps and CRCs, while exhausted T cells only appear in CRCs (Fig. 5e,f and Extended Data Fig. 4b). Tregs are known to suppress the antitumor immune response and are typically present at high levels in the tumor microenvironment44. The gradual increase in Tregs may be a mechanism of immune evasion in precancerous polyps. We discuss possible cellcell interactions between stromal and epithelial cells along the malignant continuum in a Supplementary Note and in Extended Data Fig. 8f,g.

Aberrant DNA methylation is a primary mechanism of tumorigenesis in CRC45,46,47, but the timing and extent to which methylation changes drive changes in chromatin accessibility before and during malignant transformation is not known. We identified differentially methylated probes between normal and CRC samples (Extended Data Fig. 9d) in The Cancer Genome Atlas (TCGA) DNA methylation data (Illumina 450K array)48. For the ~89,000 chromatin accessibility peaks from epithelial cells that overlap at least one 450K array probe, we determined how many overlapped at least one hypermethylated site, at least one hypomethylated site or no differentially methylated sites. We then divided the peaks into groups based on whether they were members of significantly upregulated or significantly downregulated clusters identified in Fig. 4h.

For peaks overlapping hypomethylated probes, approximately one-third (534) belonged to clusters that became significantly more accessible along the continuum, while <0.5% (5) became significantly less accessible (Fig. 6a). We saw similar correspondence for peaks overlapping hypermethylated probes, with approximately one-quarter (754) becoming less accessible, and <0.5% (9) becoming more accessible. Therefore, hypermethylation and hypomethylation in CRC nearly perfectly predict that accessibility at that site will either decrease or increase (respectively), or remain unchanged. In peaks not meeting the significance threshold, we still observe less aggregate accessibility within peaks overlapping hypermethylated probes and more accessibility when they overlap hypomethylated probes (Fig. 6b). However, we also observe that 79.4% (2,096) of significantly more accessible and 76.3% (2,440) of less accessible peaks overlap nondifferential probes, implying that a majority of chromatin accessibility changes are likely not driven by methylation.

a, Table relating the change in accessibility for peaks to the methylation status of Illumina 450K methylation probes they overlap. In total, ~89,000 peaks overlapped 180,000 450K probes. Peaks classified as up were members of clusters 15 in Fig. 4f and peaks classified as down were members of clusters 610 in Fig. 4f. b, Heatmaps of peaks overlapping hypomethylated (top) and hypermethylated (bottom) 450K probes in CRC. The heatmaps are split into peaks from more accessible and less accessible groups defined in Fig. 4h and peaks not included in Fig. 4h. For nondifferential (nondiff) peaks overlapping hypermethylated probes, ({{{P}}}left( {overline {{mathrm{log}}_{2}{rm{FC}}} < 0} right) = 0.81) and sign test P<1050. For nondifferential peaks overlapping hypomethylated peaks, ({{{P}}}left( {overline {{mathrm{log}}_{2}{rm{FC}}} > 0} right) = 0.73) and sign test P<1050. c, Number of significantly differential peaks overlapping hypomethylated or hypermethylated 450K probes for each sample. The total number of peaks overlapping hypermethylated and hypomethylated probes is listed in each plot. d, Accessibility tracks around ITGA4 and NR5A2, which are hypermethylated in CRC. Tracks are ordered by position of the corresponding sample in the malignancy continuum defined in Fig. 4. DMR, differentially methylated region.

We next plotted the number of differential peaks overlapping hypermethylated and hypomethylated probes across the malignancy continuum (Fig. 6c), and found that changes in chromatin accessibility that occur in regions that are ultimately differentially methylated in CRC accumulate along the transition from normal to cancer, with the greatest number observed in late-stage polyps and CRC.

Among regions that overlap hypermethylated probes in CRC that become less accessible in polyps are several previously reported cancer-specific hypermethylated loci49. For example, the promoter region and multiple distal regulatory elements near the ITGA4 gene are accessible in normal colon, unaffected FAP colon and very early-stage polyps, but become closed early in the progression to CRC and remain closed even in low-grade polyps (Fig. 6d). The gene with the most nearby differential peaks overlapping hypermethylated probes in our dataset was NR5A2. Multiple peaks near this gene become less accessible along the malignancy continuum (Fig. 6d) and expression of NR5A2 also gradually decreases along the malignancy continuum (Extended Data Fig. 6h). NR5A2 is a nuclear receptor that has been linked to a wide range of functions including inflammation and cell proliferation50. The hypermethylation, decrease in accessibility, and decrease in gene expression of NR5A2 suggests that the pro-inflammatory state that may be triggered by the loss of NR5A2 might have a role in tumorigenesis.

Hypermethylated DNA regions in CRC have also been incorporated into CRC screening tests, including hypermethylation of the promoter regions of BMP3 and NDRG4 (ref. 51). We observe multiple distal elements around BMP3 that become inaccessible in the middle of the malignancy continuum (Extended Data Fig. 9a). We observe many regions with a similar behavior: sharp increases or decreases in accessibility at a specific point along the malignancy continuum. We speculate that testing for accessibility, or methylation, at these loci may enable staging of polyps along the malignancy continuum. This approach also identifies methylation markers/loci (for example, GRASP, CIDEB) specific for malignant transformation in CRC (Extended Data Fig. 9b,c), and differential genes whose promoters overlap CRC methylation changes (Extended Data Fig. 9e).

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Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer -...

Extraction method for miRNA from culture supernatants

We hypothesised that measuring miRNAs in the culture supernatant would enable the development of a highly sensitive and non-disruptive quality testing method (Fig.1). First, we optimised an extraction method for miRNAs specifically from the culture supernatants. Using phosphate-buffered saline (PBS) spiked with a known amount of synthesised cel-miR-54 as a sample, a commercially available small RNA extraction column could be used to extract approximately 20% of spiked miRNA (Fig.2a). On the contrary, we developed an miRNA extraction method specialised for culture supernatants that could recover approximately 60% of the spiked miRNA (Fig.2a).

Schematic representation of the concept of our novel method for detecting residual undifferentiated cells using miRNAs in culture supernatants.

Highly efficient method to extract and detect miRNAs in culture supernatants was developed. (a) The recovery rate of spiked cel-miR-54 in PBS using our method and a commercially available kit, which is used to extract miRNAs using columns. (b) The recovery rate of spiked cel-miR-54 in various culture media using our method. (cg) Calibration curves for each miRNA, plotted using the measured Ct values from 100 copies or 50 copies to 107 copies, and the theoretical copy number (log). The slope and R2 value for each calibration curve are presented within the graph. (h) Level of each miRNA detected in the culture supernatant of iPSCs and RPE cells. UD: no miRNA detected; error bar=+3SD.

We confirmed the miRNA extraction efficiency in different types of media: STEM-Fit and mTeSR, which are generally used as an iPSC culture medium; Dulbeccos modified Eagle medium (DMEM), Roswell Park Memorial Institute medium (RPMI), and Leibovits medium (L-15 medium), which are commonly used for other cell cultures; Yssel's serum-free T cell medium, which is a medium for T cells; and RtEBM, which is a medium for retinal pigment epithelium (RPE) cells. Each medium was spiked with synthetic cel-miR-54 to determine miRNA recovery rate. The results confirmed that our method extracted miRNA with a high recovery rate of more than approximately 70% from these seven media (Fig.2b).

The miR-302 family members and miR-367 (miR-302/367), which have been reported to be expressed abundantly in undifferentiated cells, such as iPSCs and ESCs15, were examined as potential markers for detecting undifferentiated cells. miR-371, miR-372, and miR-373 are also known as iPSC and ESC markers; however, their expression was lower than miR-302/367 expression (Supplementary Fig.1). The sequences of miR-302/367 are shown in Table 1. We constructed quantitative reverse-transcription PCR (qRT-PCR) assay systems for these miRNAs and confirmed by following the MIQE guidelines19. The linear dynamic ranges were from 50 to 107 copies for miR-302b and from 100 to 107 copies for the other four miRNAs (Fig.2cg). The PCR efficiency ranged from 97.5 to 112.7%. These trials were performed three times for each miRNA, and we confirmed that the lowest concentrations were detected at 100%. By comparing the expression of miR-302/367 in culture supernatants of iPSCs and RPE cells, miR-302b, miR-302c, and miR-367 were detected specifically in the iPSC supernatant (Fig.2h). miR-302b was not detected in RPE cells but was the most abundant in iPSCs. As miR-302b was the best marker for undifferentiated cells, we decided to carry out all further experiments using it.

Next, we confirmed the extent of release of the undifferentiated cell-specific miRNAs in the culture supernatant. Using iPSCs and RPE cells, we compared the expression levels of LIN28 and Oct4 (also known as Pou5f1), which are well-known undifferentiated cell markers, and miR-302b in cells and the culture supernatant. We compared the amount of nucleic acids in 105 iPSCs or RPE cells, and in 2mL of their culture supernatants. Approximately 1.4108 copies of miR-302b were expressed in 105 iPSCs (Fig.3a). The LIN28 and Oct4 levels in iPSCs were approximately 8,000 times higher than those in RPE cells (Fig.3b,c). In iPSCs, the LIN28 and Oct4 levels detected in the supernatant were 0.3% and 5.7% of intracellular expression, respectively. In contrast, approximately 6.0107 copies of miR-302b were released into the iPSC supernatant (Fig.3a), which was half of the intracellular expression level. LIN28 and Oct4 were also detected at negligible levels in RPE cells and their culture supernatant, but miR-302b was not detected in them (Fig.3ac).

miRNA was abundantly secreted into the culture supernatant. The expression level of (a) miR-302b, (b) LIN28, and (c) Oct4 in 105 iPSCs and 105 RPE cells and in 2mL of their culture supernatants. For LIN28 and Oct4, the vertical axis is the relative expression level as the expression level in RPE cells was 1. The level of miRNAs in the supernatant was corrected by multiplying the detected value with 20, because only 100L in 2mL of the culture supernatants was used as a sample. As the cells were extracted from whole cells, such a correction was not performed. UD: no miRNA detected; error bar=+3SD.

To use miRNAs in culture supernatants as targets for quality testing, properties such as stability during storage are important. We quantified the change in miRNA levels in the culture supernatant after changing the medium to determine the optimal timing for collecting the culture supernatant. The level of miR-302b in the culture supernatant reached saturation between 7 and 24h after changing the medium (Fig.4a). Next, to determine the storage conditions for the culture supernatant, the collected media were stored at various temperatures, and the changes in the level of miRNA in the medium were noted. At 25C or higher, the levels of miRNAs decreased to less than 10% of the original level within 3days (Fig.4b). At 4C, 70% of miRNAs were detected after 1week and 30% after 2weeks (Fig.4c). At 30C, the miRNA levels of more than 80% of the level on the day of collection could be detected after 2weeks (Fig.4b). Furthermore, at 80C, miRNA in the medium was stably detected even after 3months (Fig.4c). Therefore, we decided to collect the culture media 24h after the medium change and store them at 80C.

miRNAs in the culture supernatant were found to be stable. (a) Changes in the level of miR-302b in the culture supernatant observed up to 24h after changing the medium. The graph shows data from three independent experiments. (b) The collected culture medium was stored at various temperatures for 2weeks, and the change in the level of miR-302b was noted. Day 0 is the day of collection of the culture medium. (c) When the collected medium was stored at 80C, the level of miR-302b detected before and that after 3months of storage were comparable. Hence, 80C was used in all further experiments. Error bar=+3SD.

We examined whether the level of miR-302b in the culture supernatant reflects a change in the cell state. We checked the behaviour of miR-302b in the culture supernatant during the differentiation of iPSCs to NPCs. The neural marker TUJ1 (also known as TUBB3) was expressed on day 15 after the induction of differentiation, confirming that iPSCs were induced to differentiate into NPCs (Fig.5a,b). During this process, miR-302b in the culture supernatant continually decreased, reaching 1/100 of the pre-differentiation level on day 15 and 1/1000 on day 20 (Fig.5c).

miR-302b expression level in the culture supernatant decreased as iPSCs were induced to differentiate to NPCs. The images of cells (a) before inducing differentiation, that is, iPSCs, and (b) on day 15 of the iPSC-derived NPC-induction process. Blue channel represents the nuclei and green is TUJ1. Scale bar is 50m. (c) The level of miR-302b in the culture supernatant continually decreased during the induction of iPSCs to NPC differentiation. Error bar=3SD.

To quantify the efficiency of detecting undifferentiated cells by miR-302b in culture supernatants, we established a residual undifferentiated cell model in which 106 RPE cells were spiked with an arbitrary amount of iPSCs. To determine the accuracy of the model, we constructed a model using only iPSCs that maintain an undifferentiated state. Because iPSCs are prone to differentiate at the colony margin during culture20, it is possible that undifferentiated iPSCs are contaminated with iPSCs that have lost their undifferentiated state. Therefore, we confirmed the expression of Oct4 in each cell using an imaging flow cytometer, and found that the proportion of Oct4-positive cells was 98.2% (Fig.6a). We then constructed our accurate residual undifferentiated cell model by measuring miR-302b in the supernatant, 0.001%, that is, 10 iPSCs could be detected in the RPE cell background (Fig.6b). In contrast, the measurement of LIN28 in the cells could only detect iPSCs up to 0.01% of RPE cells (Fig.6c). A non-disruptive undifferentiated cell detection method for detecting H-type3 (Fuca1-2Gal1-3GaINAc), a mucin-like o-glycan on the surface of iPSCs, with rBC2LCN lectin, has been reported21. We further measured H-type3 in the culture supernatant using the same samples, and achieved a performance of 0.1% (Fig.6d). Furthermore, we checked the detection sensitivity of miR-302b in the supernatant in Clonetics human hepatocyte cell system (liver cell), human umbilical vein endothelial cell (HUVEC), and mesenchymal stem cell (MSC) backgrounds using mixed supernatants. Specifically, the culture supernatants of iPSCs and differentiated cells were mixed at an arbitrary ratio according to the number of each cells. In these mixed supernatants, the miR-302b level was below the detection limit in 0% and 0.001% iPSC samples, and the detection performance was 0.01% in all three backgrounds (Fig.6e).

Sensitivity of detecting undifferentiated cells by measuring miR-302b in culture supernatant was 0.001%. (a) Oct4-positive rate of iPSCs used to develop the residual undifferentiated cell model was found to be 98.2%. (b) The detection sensitivity of miR-302b in the culture supernatant, (c) LIN28 in the cells, and (d) Fuca1-2Gal1-3GaINAc in the culture supernatant was compared in the same residual undifferentiated cell model in which 106 RPE cells were spiked with the appropriate number of iPSCs. (e) Detection sensitivity of undifferentiated cells measured by detecting miR-302b in the culture supernatant of liver cells, HUVECs, and MSCs. Error bar=+3SD. UD: no miRNA detected. *p value<0.01, compared with 0%, Students t-test.

A large number of cells is required for the transplantation of heart or liver cells generated from iPSCs, which are currently under clinical research. Nucleic acid extraction and PCR are inhibited when a target gene is detected in many cells. Therefore, we investigated the possibility of detecting miRNAs in the culture supernatant under scaled-up conditions. HCT116 cells (107) spiked with 1% (105 cells) or 10% (106 cells) of iPSCs were seeded in a 10-cm dish, and miR-302b was extracted and measured from the cells and supernatant, respectively. All detached cells and 100L of the supernatant from 10mL of the medium were used as samples. The positive control sample (PC) consisted of 106 iPSCs, and miR-302b was detected in both cells and supernatant (Fig.7). In the sample consisting of 0% iPSC sample, that is, only 107 HCT116 cells, miR-302b was not detected in the cells or supernatant (Fig.7). However, in the samples with HCT116 cells spiked with iPSCs, miR-302b was detected in the culture supernatant but not in the cells (Fig.7).

Measuring miR-302b in the culture supernatant allows the detection of iPSCs in a large number of cells. (a) 107 HCT116 cells were spiked with iPSCs, and miR-302b was measured in the culture supernatant. (b) 107 HCT116 cells were spiked with iPSCs and miR-302b was measured in the cells. PC: positive control, which is the culture condition of only 106 iPS cells. UD: no miRNA detected. Error bar=+3SD.

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Highly sensitive and non-disruptive detection of residual undifferentiated cells by measuring miRNAs in culture supernatant | Scientific Reports -...

Parkinson's patients could be getting benefits from research conducted on the International Space Station that has connections to Louisville. Paula Grisanti, Chief Executive Officer for the National Stem Cell Foundation Headquarters in Louisville, spoke with WLKY about a groundbreaking new study.Organoids will be launched into space and will spend six weeks on the ISS before splashing back down.These organoids, which Grisanti described as "mini-brains," are composed of cells from people suffering from MS and Parkinson's Disease. After they return, the data they produce will be collected, prepared and refined for another mission in 2023. Grisanti said that sending the organoids to space allows them to communicate with each other in a zero-gravity environment. This activates them much like a spinner would on Earth but without "confusing" the organoids and preventing them from communicating at their best with each other. The hope is that the research will help scientists accelerate the discovery of Parkinson's before it onsets.

Parkinson's patients could be getting benefits from research conducted on the International Space Station that has connections to Louisville.

Paula Grisanti, Chief Executive Officer for the National Stem Cell Foundation Headquarters in Louisville, spoke with WLKY about a groundbreaking new study.

Organoids will be launched into space and will spend six weeks on the ISS before splashing back down.

These organoids, which Grisanti described as "mini-brains," are composed of cells from people suffering from MS and Parkinson's Disease.

After they return, the data they produce will be collected, prepared and refined for another mission in 2023.

Grisanti said that sending the organoids to space allows them to communicate with each other in a zero-gravity environment.

This activates them much like a spinner would on Earth but without "confusing" the organoids and preventing them from communicating at their best with each other.

The hope is that the research will help scientists accelerate the discovery of Parkinson's before it onsets.

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Research conducted in space to fight Parkinson's has Louisville connection - WLKY Louisville