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adecuado para predecir estructuras secundaria y tercearia

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UCL Computer Science Department Bioinformatics Group

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The following is intended as documentation on how to submit jobs to the RaptorX servers, and retrieve and interpret results. For detailed explanation of the algorithms deployed please see relevant papers listed at http://raptorx.uchicago.edu/about/#cite .

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Lo encontre, este es el enlace de la base de datos de las modificaciones posttraduccionales. Super recomendado

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dbPTM is an integrated resource for protein post-translational modifications (PTMs). Due to the importance of protein post-translational modifications (PTMs) in regulating biological processes, the dbPTM was developed as a comprehensive database by integrating experimentally verified PTMs from several databases and annotating the potential PTMs for all UniProtKB protein entries. The dbPTM has been maintained for over ten years with an attempt to provide comprehensively functional and structural analyses for post-translational modifications (PTMs). In this update, dbPTM not only integrate more experimentally validated PTMs from available databases and manual curation of literature, but also provide disease association based on non-synonymous single nucleotide polymorphisms (nsSNPs). - [Data Statistics Page]

The high-throughput deep sequencing technology has leaded the analysis of association between SNPs and diseases into a data surge in both growth and scope. This update thus integrated disease-associated nsSNPs from dbSNP based on Genome-Wide Association Studies (GWAS). The PTM substrate sites locating in a specified distance of the amino acids encoded from nsSNPs were referred to having an association with its involving diseases (Figure 1). In recent years, an increasing evidence for crosstalk between PTMs has been reported.

Although mass spectrometry (MS)-based proteomics has substantially improved our knowledge about substrate site specificity of single PTM, this neglects the fact that the crosstalk of combinatorial PTMs may act in concert in the regulation of protein function. Due to the relatively limited information about the frequency and functional relevance of PTM crosstalk, in this update, the PTM sites neighbouring with other PTM sites in a specified window length were subjected to motif discovery and functional enrichment analysis. This update confronts the current state of PTM crosstalk research and breaks the bottleneck of how proteomics may contribute to understanding PTM codes, revealing the next level of data complexity and proteomic limitation in prospective PTM research.

# data[].attributes.attachment_link.description
dbPTM is an integrated resource for protein post-translational modifications (PTMs). Due to the importance of protein post-translational modifications (PTMs) in regulating biological processes, the dbPTM was developed as a comprehensive database by integrating experimentally verified PTMs from several databases and annotating the potential PTMs for all UniProtKB protein entries.

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RaptorX - Property: a protein structure property prediction server

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RaptorX Property is a web server predicting structure property of a protein sequence without using any template information. It outperforms other servers especially for proteins without close homologs in the Protein Data Bank (PDB) or with very sparse sequence profile. This server employs an emergin…

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Analysis of nucleotide and protein sequence data was initially restricted to those with access to complicated mainframe or expensive desktop computer programs (for example PC/GENE, Lasergene, MacVector, Accelrys etc.). The availability of online tools permits even the novice molecular biologist the opportunity to derive a considerable amount of useful nformation from nucleotide or protein sequence data. For those with no experience I have provided three sequences: (a) a DNA sequence, (b) a protein sequence, and (c) four protein sequences presented in
FASTA format. Prior to trying out a Web Site select the sequence and copy to clipboard. Each of the items in blue text is hyperlinked to a site on the Web. Each of these Web Sites has a box into which you can "Paste" your sequence. Click on the button labeled "Search," "Run" or "Submit." If in doubt use the default setting that the sites provide, but for the more adventuresome some of the sites offer the chance of modifying the search strategy.

ONLINE RESOURCES (tutorials and glossaries) - Needs work

TERTIARY STRUCTURE PREDICTIONS OF SACCHARIDES

ALIGNMENTS
CONVERT SEQUENCE (upper to low case, complement, reverse, RNA to DNA)
COMPOSITION
DNA MOTIFS
HOMOLOGY SEARCHES
MELTING TEMPERATURE (Tm)
PCR PRIMER DESIGN
PHYLOGENY
PROMOTERS
REPEATS & SECONDARY STRUCTURE
RESTRICTION ENDONUCLEASE SITES
TRANSLATION (GENERAL)
TRANSLATION (EUKARYOTIC GENES) (identification of introns and exons)
TRANSCRIPTION FACTORS

TOOLS FOR WHOLE GENOME ANALYSIS

TOOLS FOR METABOLOMIC RESEARCH

ALIGNMENTS
COMPOSITION & CHEMISTRY
HOMOLOGY SEARCHES
MOTIFS
PHYLOGENY
QUATERNARY STRUCTURE PREDICTIONS
SECONDARY STRUCTURE PREDICTIONS
TERTIARY STRUCTURE PREDICTIONS

RNA ANALYSIS
PROMOTERS & TERMINATORS
TRANSCRIPTION FACTORS

TOOLS FOR TRANSCRIPTOME RESEARCH

BUFFERS
CENTRIFUGATION CALCULATIONS
GENERAL MOLECULAR BIOLOGY CALCULATIONS
META SITES FOR DNA & PROTEIN ANALYSIS
SEQUENCE CLEANUP & CONVERSION
ONLINE GRAPHICS

WINDOWS- & JAVA or PERL-BASED PROGRAMS - free molecular biology programs

DOWNLOADING SEQUENCES FROM GENBANK & MANIPULATING THEM IN BIOEDIT

The Bio-Web: Resources for Molecular and Cell Biologists is a non-commercial, educational site with the only purpose of facilitating access to biology-related information over the internet.

Problems and suggestions: Contact - Andrew M. Kropinski (Email: Phage.Canada (at) gmail.com)

# data[].attributes.attachment_link.description
Analysis of nucleotide and protein sequence data was initially restricted to those with access to complicated mainframe or expensive desktop computer programs (for example PC/GENE, Lasergene, MacVector, Accelrys etc.). The availability of online tools permits even the novice molecular biologist the opportunity to derive a considerable amount of useful nformation from nucleotide or protein sequence data.

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Articulo semana 2

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Art. semana 3

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Articulo 5 semana

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Differentiation media induces CHGA expression in human duodenal enteroids

To optimize human EE cell differentiation, we developed a DM (Supplementary Table 1) by combining specific components from published protocols used to induce EE cells, including Wnt3a and two additional small molecules associated with endocrine cell differentiation: (1) betacellulin, a ligand of both EGFR and the ErbB4 receptors and (2) PF06260933 (PF), a small molecule inhibitor of MAP4K4. Human enteroids were first cultured in growth media (GM, Supplementary Table 1) for two days, allowing for ISC expansion, followed by DM for 12 days (G2D12). Enteroids maintained for 14 days in GM (G14) were used as controls to assess for changes in gene expression. In contrast to previous strategies aimed at generating EE cells over a five-day period, exposure to DM for 12 days was compatible with maintenance of enteroid structural integrity (Fig. 1a), possibly due to the continued presence of WNT3a.

To quantify the effectiveness of DM to induce EE cell differentiation, we profiled the gene expression of CHGA and other lineage markers, including atonal BHLH transcription factor 1 ( ATOH1, secretory progenitor cells), mucin 2 ( MUC2, goblet cells), lysozyme ( LYZ, Paneth cells), intestinal alkaline phosphatase ( ALPI, enterocytes), and leucine-rich repeat-containing G-protein coupled receptor 5 ( LGR5, ISCs). In addition, we assessed the expression of transcription factors required for duodenal EE differentiation and function ( PDX1, PAX4, NEUROG3, and NEUROD1), as well as hormones secreted from the duodenum ( CCK, SST, and GIP). To allow for relative comparison to native tissue expression levels, total RNA from whole duodenal mucosal biopsies was included in each qPCR analysis. Exposure of enteroids to G2D12 induced consistent expression of CHGA, PAX4, SST, and GIP, with significantly higher levels of ALPI and significantly lower expression of LGR5 when compared to G14 (Fig. 1b and Supplementary Fig 1a). Despite G2D12's ability to induce EE and enterocyte markers when compared to G14, their overall expression levels remained considerably lower than whole duodenal mucosa. Levels of PDX1, NEUROD1, NEUROG3, CCK, ATOH1, and LYZ were unchanged compared to G14, with MUC2 showing a trend towards higher expression in G2D12 enteroids (Fig. 1b and Supplementary Fig 1a). Finally, despite induction in CHGA mRNA levels in response to G2D12, analysis of CHGA protein using immunofluorescence staining and flow cytometric analysis revealed fewer than 0.1% of all cells to be CHGA + , showing a trend toward higher expression compared to G14 (Fig. 1b-e).

Removal of WNT3a has been shown to aid EE differentiation. Analysis of enteroids cultured in DM without WNT3a (G2D12-Wnt) revealed undetectable expression levels of CHGA and SST, reduced MUC2 expression, and increased ALPI expression when compared with enteroids differentiated with WNT3a (G2D12 + Wnt) (Fig. 1f). To determine whether CHGA expression was increased at an earlier time-point during the 14-day differentiation protocol, we performed time-course studies and found that CHGA expression was undetectable in enteroids cultured in G2D12-Wnt, while those exposed to G2D12 + Wnt showed expression after six days of starting DM (Supplementary Fig 1b). Furthermore, two of the three enteroid lines exposed to G2D12-Wnt showed low total RNA levels around the eighth day of differentiation, consistent with failure to maintain these lines (Supplementary Fig 1c). Therefore, we concluded that the presence of WNT3a in DM is beneficial to sustain enteroids in long-term culture (14 days) and is not detrimental to EE differentiation. We also evaluated the impact of including betacellulin and PF in our DM and found that both factors led to increased expression of EE cell markers when compared with G14 and G2D12 without betacellulin or PF, as well as maintaining ALPI levels when compared to G2D12 (Supplementary Fig 1d, e). Together, these data indicate that our differentiation protocol markedly induced expression of some EE cell marker genes (e.g., CHGA and PAX4), but is not sufficient to induce a significant increase in the number of CHGA + EE cells compared to undifferentiated controls.

Treatment with rimonabant and SP600125 induces duodenal EE lineage differentiation

To identify additional strategies that might further induce EE cell differentiation, we focused on small molecules shown to target endocannabinoid signaling and PDX1 activity. First, we utilized Rim, a highly selective CB1 inverse agonist. In parallel, we used the small molecule SP to inhibit JNK signaling, which has been shown to suppress PDX1 activity.

Separately, both Rim and SP induced expression of multiple EE lineage markers ( CHGA, NEUROG3, SST, and GIP) when added to DM, with Rim having a much larger effect (Supplementary Fig 2a). Together, RSP yielded even further increases in SST and GIP expression compared to Rim or SP alone. PDX1 expression was unchanged under all experimental conditions (Supplementary Fig 2a). Based on these results, Rim and SP were used in combination for all subsequent experiments. The addition of RSP to DM maintained overall enteroid structural integrity during the 14-day differentiation protocol (Fig. 2a and Supplementary Fig 2b). Moreover, compared to enteroids grown in G14 and G2D12, treatment with RSP led to the upregulation of multiple EE markers ( CHGA, PAX4, NEUROD1, NEUROG3, CCK, SST, and GIP) to levels approximating whole duodenal mucosa (Fig. 2b). Other lineage markers were also increased with RSP exposure, including ATOH1, MUC2, LYZ, ALPI, and LGR5 when compared to G14 and ATOH1, MUC2, and LGR5 when compared to G2D12 (Supplementary Fig 2c). Immunofluorescence staining for CHGA showed multiple positive cells within individual enteroids (Fig. 2c), with a large majority of enteroids (83%) containing CHGA + cells (Fig. 2d). By comparison, only 1.0% of enteroids grown in G2D12 were CHGA+ (Fig. 2d). Quantitative flow cytometric analysis revealed 1.4% of all cells treated with RSP were CHGA+, almost seven times the number seen with G2D12 alone (Fig. 2e).

Treatment with AS1842856 induces duodenal EE lineage differentiation

Next, we assessed the impact of adding AS, a well-described FOXO1 inhibitor, to our differentiation protocol. Addition of AS led to the formation of small, spherical enteroids (Fig. 3a and Supplementary Fig 3a). Compared to enteroids grown in G14 and G2D12, AS treatment led to the upregulation of multiple EE markers ( CHGA, PAX4, PDX1, NEUROD1, NEUROG3, SST, and GIP), many to levels approximating whole duodenal mucosa. The only exception to this was CCK, which was significantly lower in AS when compared to G14 (Fig. 3b). In addition, AS increased expression of other secretory and ISC markers, including ATOH1, MUC2, and LGR5, when compared to G14 and G2D12 (Supplementary Fig 3b). Interestingly, the use of AS reduced expression of the enterocyte marker ALPI when compared to G14 and G2D12, suggesting a possible role for FOXO1 inhibition in the induction of the secretory lineage (Supplementary Fig 3b). Immunofluorescence staining revealed CHGA + cells within a large majority of individual enteroids (85%) (Fig. 3c, d). By comparison, only 3.5% of enteroids grown in G2D12 had CHGA + cells (Fig. 3d). Quantitative flow cytometric analysis revealed 5.2% of all cells exposed to AS to be CHGA + , almost 50 times the number seen with G2D12 alone (Fig. 3e).

Treatment with rimonabant/SP600125 or AS1842856 promote distinct enteroid differentiation trajectories

To better assess the transcriptomic distinctions between cells from the various culture conditions, we utilized single-cell RNA sequencing (scRNA-seq) on the 10X platform combined with sample hashing, allowing us to assess the reproducibility of our findings from distinct donors. Enteroids from three individuals were grown in G2D12, RSP or AS, for a total of nine samples. After the 14-day protocol, enteroids were isolated and processed into a single-cell suspension and their condition and patient source were marked using Hashtag antibodies prior to pooling the samples together. After labeling, cells were processed, and single-cell transcriptomes were generated.

By using hashtag labeling, we were able to categorize cells into singlets (significant detection of one antibody), doublets (significant detection of more than one antibody) or negative droplets (no significant detection of any antibodies). Negative droplets were found to have a reduced number of both detected genes and unique genes or unique molecular identifiers (UMIs), supporting the idea that the majority of these datapoints do not correspond to an individual cell (Supplementary Fig 4a). In contrast, both singlets and doublets had appreciable numbers of both genes and UMIs detected. In addition, we found that they had similar UMIs, percentage of mitochondrial RNA, which aids in identification of low-quality cells, and detected gene distributions (Supplementary Fig 4a). However, upon dimensional reduction, we found that singlets and doublets formed distinct groupings in both t-distributed stochastic neighbor embedding visualization (Supplementary Fig 4b), as well as uniform manifold approximation and projection (UMAP) visualization and clustering (Supplementary Fig 4b, c), indicating that although they had similar RNA content, singlets likely correspond to true singlets, whereas doublets correspond to multiple cell types analyzed together in a single droplet.

After removal of doublets, negative droplets, and low-quality cells (gene count <200, percentage of mitochondrial RNA > 25%), the resulting dataset consisted of 14,767 cells spread across the three different culture conditions. UMAP visualization revealed distinct cell separation between G2D12 and AS treatment with minimal overlap between the two populations (Fig. 4a). In contrast, enteroid treatment with RSP generated populations that overlapped with the two other culture conditions (Fig. 4a). To further characterize the developing populations within each treatment, we performed Louvain clustering and identified 15 clusters within the combined dataset (Supplementary Fig 4d). Of these 15 clusters, some were composed of cells sourced from all three culture conditions, such as clusters 2, 4, 7, and 9, whereas other clusters were primarily formed by cells from one treatment group, such as cluster 8 (AS) and cluster 3 (G2D12). To assist with manual annotation of each cluster, we calculated the top markers of each Louvain cluster (Supplementary Fig 4e; Wilcoxon rank-sum test, p adj < 1.38 × 10 −21 for displayed markers). By using these markers, as well as classical markers of various epithelial populations, we broadly classified the data into six populations of epithelial cells, including stem cells, proliferating progenitor cells, progenitor cells, enterocytes, goblet cells, and enteroendocrine cells (Fig. 4b). ISCs were identified by expression of LGR5, AXIN2 and ASCL2. Enterocytes were identified by the expression of KRT20, FABP2, and FABP1, goblet cells by the expression of MUC2, FCGBP, and GFI1, and EE cells by expression of CHGA, NEUROG3, NEUROD1, and PAX4 (Fig. 4c). Finally, progenitor cells were identified as having a mixture of stem cell markers, albeit at a lower level than the ISCs, while also expressing mature enterocyte markers. We were able to distinguish proliferating cycling progenitors from other progenitor cells by expression of the proliferation marker MKI67 (Fig. 4b, c); however, some progenitor markers were also lowly expressed in secretory cell populations, suggesting that these groups likely also contain secretory progenitors.

a Uniform manifold approximation and projection (UMAP) visualization of 14,767 cells summarizing enteroid differentiation from all samples, color labeled by culture condition. b UMAP visualization from a, color labeled by broad annotated cell identity, following Louvain clustering. c Dot plot of the average scaled expression (measured by average Pearson residual) of canonical markers of various intestinal epithelial cell types, plotted against cluster identity. d Proportional abundance of epithelial cell subsets by enteroid culture protocol. Each culture condition consists of three different enteroid lines from distinct human donors, as denoted by data point shape. Bars show mean ± SEM; Kruskal-Wallis test with Dunn's post-hoc analysis displayed. P values were adjusted using Bonferroni correction for multiple comparisons. * p = 0.0219 (Intestinal Stem Cells and Enteroendocrine Cells), 0.0338 (Enterocytes). e UMAP visualization of 14,767 cells divided by culture condition and colored by cell identity. Trajectory analysis of each protocol was calculated using scVelo and the vector field was overlaid on top of each UMAP. Arrows represent smoothed averages of the estimated cellular differentiation trajectory, with arrow thickness corresponding to the "speed" of differentiation. f UMAP visualization from a, with individual cells colored by their EE cell module score. Each score was scaled on a range from 0 to 1. g Violin plots of the module score described in f split across culture condition. The effect size between culture conditions was calculated as Cohen's d; $$0.8 <  d < 1.2. Source data are provided as a Source Data file.

To understand how different culture conditions impacted enteroid development and differentiation, we first compared the proportions of the various cell types across each condition (Fig. 4d). We found that treatment with G2D12 primarily gave rise to cells of the absorptive lineage, with 58% identified as enterocytes. The remaining cells exposed to G2D12 consisted of stem cells (5.7%), proliferating progenitor cells (5.4%) and progenitor cells (30%). G2D12 did not give rise to secretory cells, with almost no detection of goblet cells (0.6%) or EE cells (0.2%). In contrast to G2D12, treatment with either RSP or AS led to a decrease in the proportion of enterocytes (RSP: 17%, AS: 2.5%) and an increase in stem cells (RSP: 22%, AS: 42%), goblet cells (RSP: 4.6%, AS: 1.5%), and EE cells (RSP: 4.3%, AS: 18%), with significant differences noted between G2D12 and AS conditions for stem cells, enterocytes, and EE cells.

To further characterize the differentiation path of each culture condition, we used scVelo to model the RNA velocity and differentiation trajectory of each cell type. Briefly, RNA velocity analysis pipelines, such as scVelo, leverage the fact that scRNA-seq can distinguish between un-spliced and spliced variants of each gene. Since recently transcribed RNA is present as an un-spliced variant which is then spliced into its mature form before eventually being degraded, it is possible to calculate the dynamic kinetics of each individual gene's expression across all cells within the dataset based on the ratio of un-spliced to spliced RNA. scVelo uses the collection of gene kinetics to infer the direction and speed of cell state changes on a population level. We applied this method to each culture condition and generated vector estimates of cellular transition overlaid on each UMAP (Fig. 4e). In all three conditions, the majority of vector arrows initiate from a stem cell cluster in the lower half of the UMAP. In the G2D12 culture condition, cells primarily move towards proliferating progenitors and progenitor cells, before moving toward the enterocyte cluster. In contrast, in AS treated cells, the vector arrows proceed through a completely different trajectory, with the majority of vectors moving towards the goblet cell cluster and then into the EE cluster. Cells treated with RSP revealed vector arrows in patterns that resembled both G2D12 and AS treated cells, suggesting it may promote early differentiation of both secretory and absorptive cell types. Finally, a small proportion of vector arrows suggested a "backwards" trajectory, with movement from a differentiated enterocyte into a progenitor population. This behavior may be indicative of de-differentiation or possibly movement towards cell death, as the cells lose features associated with mature cell types. Overall, these results indicate that all three culture conditions have distinct differentiation potentials, with AS and RSP giving rise to an increased proportion of EE cells compared to G2D12.

To verify that the EE cells identified in our enteroid system resemble those found in situ, we compared our dataset with a reference gene set from isolated mouse EE cells. This list encompasses 77 genes, including conventional markers such as CHGA, NEUROG3, and the enzyme TPH1 (Supplementary Fig. 4f). An EE cell gene module score was calculated for each cell in our scRNA dataset based on the number of shared features with the reference EE gene set, which revealed exclusive marking of cells within our EE cell cluster (Fig. 4f). In addition, when looking across culture conditions, RSP and AS showed an increased effect size in relation to G2D12, with AS having a larger effect size than RSP (Fig. 4g). These results underscore differences observed between the three culture conditions described in previous results and further demonstrate that EE cells generated using these protocols resemble those found within native tissue.

To understand the effect of each culture condition on the differentiation of individual enteroendocrine subsets, we further clustered the EE cells previously identified in our scRNA-seq dataset. Following sub-clustering, we identified a total of 471 EE cells, which consisted of enteroendocrine progenitor cells, enterochromaffin cells and various hormone-producing cells (Supplementary Fig. 5a, b). We defined enteroendocrine progenitor cells by the expression of DLL1 and NEUROG3, and the absence of expression of differentiated markers NEUROD1, CHGA, and ARX, the last of which specifically marks non-enterochromaffin EE cells (Supplementary Fig. 5c). We found that RSP treatment gave rise to a greater proportion of enteroendocrine progenitor cells compared to AS (RSP 50% vs AS 13%) (Supplementary Fig. 5d). In contrast, AS treatment led to an increased frequency of mature EE cells compared to RSP (RSP 50% vs AS 87%), with the majority consisting of enterochromaffin cells (RSP 40% vs AS 62% of all cells) (Supplementary Fig. 5d). To investigate the population of peptide hormone-producing cells, we leveraged our scRNA-seq dataset to determine the expression of hormones and related genes that have previously been attributed to various EE subsets. Notably, we found expression of both TPH1, associated with enterochromaffin cells, and GHRL, associated with X cells, across both AS and RSP. SST was not differentially expressed between AS and RSP, while MLN, associated with M cells, was identified predominantly in RSP-treated cells, although these markers, along with GAST, associated with G cells, GIP, and CCK, were expressed in only a small number of cells (Supplementary Fig. 5e).

Treatment with AS1842856 followed by rimonabant and SP600215 increases GIP expression in human duodenal enteroids

Compared to RSP treated enteroids, AS treatment led to more robust EE differentiation, based on overall induction of multiple EE cell markers and the larger fraction of CHGA + cells (Figs. 2- 4). Direct comparison of the two protocols revealed that AS exposure led to higher expression of CHGA, NEUROD1, NEUROG3, and SST (Supplementary Fig. 6a), consistent with the higher percentage of CHGA + cells (Figs. 2 and 3). In contrast, we noted that RSP induced higher expression of GIP compared to AS (Supplementary Fig. 6a). Given these results, we next hypothesized that the combination of Rim, AS, and SP (RASP) would further increase expression of both CHGA and GIP. Exposure of enteroids to RASP for the full duration of the differentiation protocol, however, was not compatible with viable enteroids, as evidenced by their irregular morphology and extremely low RNA content (Supplementary Fig. 6b, c).

We next tested the impact of adding RSP after exposure to AS, reasoning that AS treatment would shunt a larger proportion of cells into the EE lineage, as indicated by the scRNA-seq data (Fig. 4d, g), with the later addition of RSP inducing GIP expression in more cells than RSP alone. To identify the appropriate time for the addition of RSP, we performed a time-course analysis of AS-treated enteroids and found that multiple transcription factors required for EE differentiation, including NEUROD1 and NEUROG3, showed increased expression around the fourth day of differentiation. Following this, both CHGA and SST had detectable transcript levels by the sixth day of differentiation (Supplementary Fig. 7a). Given these data, we next hypothesized that AS treatment for six days followed by subsequent exposure to RSP would lead to increased GIP expression compared to RSP alone. To test this, we utilized two differentiation strategies: (1) switching from AS to RSP at day six of differentiation (AS→RSP) or (2) adding RSP to AS at day six of differentiation (AS→RASP). Morphologically, AS→RASP produced smaller enteroids compared to other conditions (Supplementary Fig. 7b); however, RNA concentrations were consistently above the minimum threshold of 10 ng/μL, suggesting improved viability over exposure to RASP for the full duration of the differentiation protocol (Supplementary Fig. 7c). Enteroids treated with AS→RSP showed gene expression changes that were similar to RSP alone, aside from CHGA and SST (Fig. 5a). Enteroids treated with AS→RASP showed 2-3-fold higher gene expression levels of most EE cell markers when compared to AS, with the exception of PDX1 and CCK (Fig. 5a).

a qPCR analysis of enteroendocrine markers of enteroids grown in AS, AS for 6 days, followed by RSP only for 6 days (AS→RSP) and AS for 6 days, followed by AS and RSP for 6 days (AS→RASP) compared to enteroids grown in RSP and normalized to 18S. Representative experiment showing n = 3 wells from each condition from a single enteroid line. CHGA = chromogranin A, PAX4 = paired box 4, PDX1 = pancreatic and duodenal homeobox 1, NEUROD1 = neuronal differentiation 1, NEUROG3 = neurogenin 3, CCK = cholecystokinin, SST = somatostatin, GIP = glucose-dependent insulinotropic peptide. * p = 0.0424 ( PAX4), 0.0123 ( SST); ** p = 0.039 ( CHGA, RSP to AS→RSP), 0.0059 ( CHGA, AS to AS→RSP), 0.0064 ( CHGA, AS to AS→RASP), 0.0019 ( SST), 0.0010 ( GIP); *** p = 0.0006 ( NEUROD1), 0.0004 ( NEUROG3), 0.0003 ( CCK), 0.0001 ( GIP); **** p < 0.0001. b Representative immunofluorescence staining of CHGA (magenta) in enteroids (whole well) treated with G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. DNA (4′,6-diamidino-2-phenylindole (DAPI), blue). Scale bar = 1 mm. c Percentage of enteroids with positive CHGA staining in G14, G2D12, AS, RSP, AS→RSP, and AS→RASP treatments. Table above graph shows the total number of enteroids examined per condition. Average results are from three separate experiments from three different enteroid lines or passages. **** p < 0.0001. d Left six panels: Representative flow cytometry plots of CHGA + cells from enteroids grown in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. Right panel: Percentage of CHGA + cells per well. Representative experiment showing n = 3 wells from each condition from a single enteroid line. ** p = 0.0041 (G14 to RSP), 0.0045 (G2D12 to RSP), 0.0020 (AS to AS→RASP); ****p < 0.0001. Bars show mean ± SEM; two-way ANOVA with Tukey correction for multiple comparisons ( a); one-way ANOVA with Tukey correction for multiple comparisons ( c, d). Each experiment repeated with at least three different enteroid lines. Source data are provided as a Source Data file.

Furthermore, exposure to AS for the entire differentiation protocol, i.e., AS and AS→RASP, decreased expression of MUC2 and ALPI and increased expression of LGR5 compared to those that received RSP alone, for any amount of time (Supplementary Fig. 8a). In terms of other lineages, immunofluorescence staining showed that the enterocyte marker cytokeratin 20 (CK20) was expressed in all differentiation conditions, but with very little stain noted in AS→RASP (Supplementary Fig. 8b). MUC2 staining was only noted in RSP, AS, and AS→RSP enteroids while LYZ, similar to CK20, was present in all differentiation conditions except AS→RASP (Supplementary Fig. 8c, d).

We also evaluated the effect of our differentiation protocols on proliferation and apoptosis after seven and 14 days of culture. As expected, at seven days GM supported cell proliferation, as evidenced by a significantly higher fraction of EdU-positive (EdU+) cells (2.7%) after a 2-h pulse, compared to all other conditions. There were no significant differences between DM only, RSP and AS, which ranged from 0.1 to 0.5% EdU+ cells. At day 14 of culture, no differences in the percentage of EdU+ cells were detected between any groups (which ranged from 0.1 to 0.6%), suggesting that GM conditions are not able to sustain ongoing proliferation indefinitely (Supplementary Fig. 8e). Analysis of apoptosis at seven days showed GM had the lowest percentage of Annexin V-positive cells (13%) compared to each differentiation condition, with RSP showing the highest fraction at 29%. At day 14, despite modest differences between groups, levels of apoptosis were fairly consistent ranging from 19 to 29% (Supplementary Fig. 8f). Further, enteroids exposed to RSP (including RSP, AS→RSP, and AS→RASP) appeared to have more apoptotic cells compared to DM alone and AS.

All four differentiation strategies induced a high fraction of CHGA + enteroids, ranging from 79% to 88% (RSP, 79%; AS, 82%; AS→RSP, 81%; AS→RASP, 88%), as assessed by immunostaining (Fig. 5b, c). Quantitative flow cytometric analysis revealed 3.7% of all cells exposed to AS→RSP to be CHGA+, which was between the 1.0% seen in RSP alone and the 6.1% seen in AS alone. AS→RASP had the highest percentage of CHGA+ cells at 7.1%, more than 100 times the number seen with G2D12 alone (Fig. 5d). Taken together, these data reveal that exposure of human enteroids to AS→RASP is the most effective way to induce EE cell differentiation, in terms of expression of CHGA, PAX4, NEUROD1, and NEUROG3, as well as overall number of CHGA + cells.

Hormone production and secretion mirror gene expression changes in duodenal enteroids

To assess hormone production and secretion during EE cell differentiation, we next assayed for duodenal-associated hormones in response to the various differentiation conditions. Immunofluorescence staining showed that SST was expressed similarly in all differentiation conditions, aside from G2D12, with 42-53% of enteroids containing SST-positive cells (RSP, 45%; AS, 42%; AS→RSP, 53%; AS→RASP, 51%) (Fig. 6a, b). 5HT was expressed in a higher percentage of enteroids treated with AS throughout the entire differentiation period than those that only received RSP (RSP, 44%; AS, 75%; AS→RSP, 59%; AS→RASP, 76%) (Fig. 6c, d). An induction in GIP-positive enteroids was detected in response to all differentiation conditions, with the exceptions of G2D12 and AS→RASP (RSP, 66%; AS, 53%; AS→RSP, 56%; AS→RASP, 8.6%) (Fig. 6e, f). Further, CCK-positive enteroids were predominantly detected in response to RSP (29%) and AS→RSP (30%) compared to all other treatment groups (AS, 4.5%; AS→RASP, 2.6%) (Fig. 6g, h).

a Representative immunofluorescence staining of somatostatin (SST, green) and chromogranin A (CHGA, magenta) in enteroids treated with G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. DNA (4′,6-diamidino-2-phenylindole (DAPI), blue). Scale bar = 50 µm. b Percentage of enteroids with SST staining in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP treatments. Average results are from three different enteroid lines or passages. ** p = 0.0017 (G14 to RSP, G2D12 to RSP), 0.0029 (G14 to AS, G2D12 to AS); *** p = 0.0004 (G14 to AS→RSP, G2D12 to AS→RSP), 0.0006 (G14 to AS→RASP, G2D12 to AS→RASP). c Representative immunofluorescence staining of serotonin (5HT, green) and CHGA (magenta) in enteroids treated with G14, G2D12, RSP, AS, AS→RSP and AS→RASP. DNA (DAPI, blue). Scale bar = 50 µm. d Percentage of enteroids with 5HT staining in G14, G2D12, RSP, AS, AS→RSP and AS→RASP treatments. Average results are from three different enteroid lines or passages. * p = 0.0183 (RSP to AS), 0.0134 (RSP to AS→RASP); ** p = 0.0014; *** p = 0.0009; **** p < 0.0001. e Representative immunofluorescence staining of glucose-dependent insulinotropic peptide (GIP, green) and CHGA (magenta) in enteroids treated with G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. DNA (DAPI, blue). Scale bar = 50 µm. f Percentage of enteroids with GIP staining in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP treatments. Average results are from three different enteroid lines or passages. *** p = 0.0001; **** p < 0.0001. g Representative immunofluorescence staining of cholecystokinin (CCK, green) and CHGA (magenta) in enteroids treated with G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. DNA (DAPI, blue). Scale bar = 50 µm. h Percentage of enteroids with CCK staining in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP treatments. Average results are from three different enteroid lines or passages. *** p = 0.0002 (RSP to AS), 0.0001 (AS to AS→RSP); **** p < 0.0001. Bars show mean ± SEM; one-way ANOVA with Tukey correction for multiple comparisons ( b, d, f, h). Tables above graphs show the total number of enteroids examined per condition. Each experiment repeated with at least three different enteroid lines. Source data are provided as a Source Data file.

Finally, to assess hormone secretion, we assayed conditioned media from each differentiation condition. Exposure to AS alone induced higher levels of 5HT secretion than all other conditions, with AS→RSP conditioned media showing higher levels of 5HT when compared to RSP and AS→RASP (Fig. 7a). These patterns persisted when controlled for total DNA content, with the exception of a modest difference between AS→RSP and AS→RASP (Supplementary Fig. 9a). Importantly, secretion of 5HT was significantly increased when differentiated enteroids were exposed to the adenylate cyclase activator forskolin (Fsk) (Fig. 7b and Supplementary Fig. 9b). Secretion of GIP was highest following exposure to AS→RSP, compared to RSP alone, while AS and AS→RASP treated enteroids revealed no secretion of GIP (Fig. 7c and Supplementary Fig. 9c). Secretion of GIP from enteroids exposed to AS→RSP was also significantly increased after exposure to Fsk (Fig. 7d and Supplementary Fig. 9d). Overall, these data show that RSP and AS, either alone or in combination, can induce protein expression and secretion of multiple duodenal hormones (5HT, GIP, SST, and CCK) from human enteroids, with specific differences depending on exposure and/or timing of RSP and AS treatment.

a Serotonin (5HT) ELISA of conditioned media from the last two days of differentiation of enteroids grown in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. Representative experiment showing n = 3 wells from each condition from a single enteroid line. * p = 0.049; ** p = 0.0049 (RSP to AS→RSP), 0.0011 (AS to AS→RSP); *** p = 0.0005 (G14 to AS→RSP and G2D12 to AS→RSP); **** p < 0.0001. b 5HT ELISA of AS conditioned media collected after 24 h on day 13 (solid bar) and after 24 h with forskolin (Fsk) on day 14 (striped bar). Representative experiment showing n = 3 wells from each condition from a single enteroid line. ** p = 0.0015. c Glucose-dependent insulinotropic peptide (GIP) ELISA of conditioned media from the last two days of differentiation of enteroids grown in G14, G2D12, RSP, AS, AS→RSP, and AS→RASP. Representative experiment showing n = 3 wells from each condition from a single enteroid line. ** p = 0.0013 (RSP to AS), 0.0031 (RSP to AS→RSP); *** p = 0.0009 (G14 to RSP, G2D12 to RSP, and RSP to AS→RASP); **** p < 0.0001. d GIP ELISA of AS→RSP conditioned media collected after 24 h on day 13 (solid bar) and after 24 h with Fsk on day 14 (striped bar). Representative experiment showing n = 3 wells from each condition from a single enteroid line. ** p = 0.0025. Bars show mean ± SEM; one-way ANOVA with Tukey correction for multiple comparisons ( a, c); two-tailed unpaired t test ( b, d). Dotted line at 2.6 ng/mL represents the lower limit of detection for the 5HT ELISA ( a, b). Dotted line at 4.2 pg/mL represents the lower limit of detection for the GIP ELISA ( c, d). Each experiment repeated with at least three different enteroid lines. Source data are provided as a Source Data file.

Differentiation media induces EE cell differentiation in human rectoids

To evaluate the ability of our DM to induce EE cell differentiation outside of the duodenum, we exposed organoids derived from rectal ISCs (rectoids) to the G14 and G2D12 protocols (Supplementary Table 1). Rectoids treated with G14 maintained spherical structures, while those exposed to G2D12 had a mixture of spherical and budding structures (Fig. 8a). In contrast to enteroids, rectoids exposed to G2D12 had significantly increased expression of the majority of EE markers, included CHGA, PAX4, NEUROD1, NEUROG3, SST, GCG, and PYY, many of which were at or above the expression level observed in whole rectal mucosa (Fig. 8b). Notably, rectoids exposed to G2D12 also had significantly higher expression of ATOH1 and MUC2, decreased expression of LGR5, and no change in CAII expression, a marker for absorptive cells of the rectum, when compared to G14 (Supplementary Fig. 10).

Immunofluorescence staining revealed CHGA + cells within a majority of G2D12 rectoids (72%) (Fig. 8c, d) and quantitative flow cytometric analysis revealed 4.7% of all cells exposed to G2D12 to be CHGA + (Fig. 8e). Additional immunofluorescence staining revealed that both GLP-1 and PYY were expressed in a large number of G2D12 rectoids (GLP-1, 61%; PYY, 40%) (Fig. 9a-d). We next assayed conditioned media from G14 and G2D12 rectoids to evaluate for hormone secretion and found significant levels of both GLP-1 and PYY in G2D12 rectoids compared to G14, which was increased by stimulation with Fsk (Fig. 9e-h, Supplementary Fig 11a-d). Overall, these data indicate that G2D12 is sufficient to induce EE cell differentiation of rectal ISCs.

a Representative immunofluorescence staining of glucagon-like peptide-1 (GLP-1, green) and CHGA (magenta) in rectoids treated with G14 and G2D12. DNA (4′,6-diamidino-2-phenylindole (DAPI), blue). Scale bar = 50 µm. b Percentage of rectoids with GLP-1 staining in G14 and G2D12. Average results are from three different rectoid lines or passages. **** p < 0.0001. c Representative immunofluorescence staining of peptide YY (PYY, green) and CHGA (magenta) in rectoids treated with G14 and G2D12. DNA (DAPI, blue). Scale bar = 50 µm. d Percentage of rectoids with PYY staining in G14 and G2D12. Average results are from three different rectoid lines or passages. * p = 0.0118. e GLP-1 ELISA of conditioned media from the last two days of differentiation of rectoids grown in G14 and G2D12. Representative experiment showing n = 3 wells from each condition from a single rectoid line. * p = 0.0229. f GLP-1 ELISA of G2D12 conditioned media collected after 24 h on day 13 (solid bar) and after 24 hours with forskolin (Fsk) on day 14 (striped bar). Representative experiment showing n = 3 wells from each condition from a single rectoid line. ** p = 0.0061. g PYY ELISA of conditioned media from the last two days of differentiation of rectoids grown in G14 and G2D12. Representative experiment showing n = 3 wells from each condition from a single rectoid line. ** p = 0.0056. h PYY ELISA of G2D12 conditioned media collected after 24 h on day 13 (solid bar) and after 24 hours with forskolin (Fsk) on day 14 (striped bar). Representative experiment showing n = 3 wells from each condition from a single rectoid line. *** p = 0.0006. Bars show mean ± SEM; two-tailed unpaired t test ( b, d, e, f, g, h). Dotted line at 25 pg/mL represents the lower limit of detection for the GLP-1 ELISA ( e, f). Dotted line at 7.3 pg/mL represents the lower limit of detection for the PYY ELISA ( g, h). Each experiment repeated with at least three different rectoid lines. Tables above graphs show the total number of rectoids examined per condition. Source data are provided as a Source Data file.

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Robust differentiation of human enteroendocrine cells from intestinal stem cells - Nature Communications

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Hormone-producing enteroendocrine cells (EEC) regulate of energy homeostasis and gastrointestinal function. Here the authors report protocols to induce human intestinal stem cells into EECs producing multiple gut hormones, including SST, 5-HT, CCK and GIP, using directed differentiation with small molecules targeting FOXO1, JNK and CB1 signalling.

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ADAR2 Is Involved in Self and Nonself Recognition