Spliceosome-targeted therapies trigger an antiviral immune response in triple-negative breast cancer.

Many oncogenic insults deregulate RNA splicing, often leading to hypersensitivity of tumors to spliceosome-targeted therapies (STTs). However, the mechanisms by which STTs selectively kill cancers remain largely unknown. Herein, we discover that mis-spliced RNA itself is a molecular trigger for tumor killing through viral mimicry. In MYC-driven triple-negative breast cancer, STTs cause widespread cytoplasmic accumulation of mis-spliced mRNAs, many of which form double-stranded structures. Double-stranded RNA (dsRNA)-binding proteins recognize these endogenous dsRNAs, triggering antiviral signaling and extrinsic apoptosis. In immune-competent models of breast cancer, STTs cause tumor cell-intrinsic antiviral signaling, downstream adaptive immune signaling, and tumor cell death. Furthermore, RNA mis-splicing in human breast cancers correlates with innate and adaptive immune signatures, especially in MYC-amplified tumors that are typically immune cold. These findings indicate that dsRNA-sensing pathways respond to global aberrations of RNA splicing in cancer and provoke the hypothesis that STTs may provide unexplored strategies to activate anti-tumor immune pathways.

Enhancer RNA m6A methylation facilitates transcriptional condensate formation and gene activation.

The mechanistic understanding of nascent RNAs in transcriptional control remains limited. Here, by a high sensitivity method methylation-inscribed nascent transcripts sequencing (MINT-seq), we characterized the landscapes of N6-methyladenosine (m6A) on nascent RNAs. We uncover heavy but selective m6A deposition on nascent RNAs produced by transcription regulatory elements, including promoter upstream antisense RNAs and enhancer RNAs (eRNAs), which positively correlates with their length, inclusion of m6A motif, and RNA abundances. m6A-eRNAs mark highly active enhancers, where they recruit nuclear m6A reader YTHDC1 to phase separate into liquid-like condensates, in a manner dependent on its C terminus intrinsically disordered region and arginine residues. The m6A-eRNA/YTHDC1 condensate co-mixes with and facilitates the formation of BRD4 coactivator condensate. Consequently, YTHDC1 depletion diminished BRD4 condensate and its recruitment to enhancers, resulting in inhibited enhancer and gene activation. We propose that chemical modifications of eRNAs together with reader proteins play broad roles in enhancer activation and gene transcriptional control.

Retraction Note: A homing system targets therapeutic T cells to brain cancer.

This Article has been retracted; see accompanying Retraction.

Transcriptional coactivation of NRF2 signaling in cardiac fibroblasts promotes resistance to oxidative stress.

We recently discovered that steroid receptor coactivators (SRCs) SRCs-1, 2 and 3, are abundantly expressed in cardiac fibroblasts (CFs) and their activation with the SRC small molecule stimulator MCB-613 improves cardiac function and dramatically lowers pro-fibrotic signaling in CFs post-myocardial infarction. These findings suggest that CF-derived SRC activation could be beneficial in the mitigation of chronic heart failure after ischemic insult. However, the cardioprotective mechanisms by which CFs contribute to cardiac pathological remodeling are unclear. Here we present studies designed to identify the molecular and cellular circuitry that governs the anti-fibrotic effects of an MCB-613 derivative, MCB-613-10-1, in CFs. We performed cytokine profiling and whole transcriptome and proteome analyses of CF-derived signals in response to MCB-613-10-1. We identified the NRF2 pathway as a direct MCB-613-10-1 therapeutic target for promoting resistance to oxidative stress in CFs. We show that MCB-613-10-1 promotes cell survival of anti-fibrotic CFs exposed to oxidative stress by suppressing apoptosis. We demonstrate that an increase in HMOX1 expression contributes to CF resistance to oxidative stress-mediated apoptosis via a mechanism involving SRC co-activation of NRF2, hence reducing inflammation and fibrosis. We provide evidence that MCB-613-10-1 acts as a protectant against oxidative stress-induced mitochondrial damage. Our data reveal that SRC stimulation of the NRF2 transcriptional network promotes resistance to oxidative stress and highlights a mechanistic approach toward addressing pathologic cardiac remodeling.

A homing system targets therapeutic T cells to brain cancer.

Successful T cell immunotherapy for brain cancer requires that the T cells can access tumour tissues, but this has been difficult to achieve. Here we show that, in contrast to inflammatory brain diseases such as multiple sclerosis, where endothelial cells upregulate ICAM1 and VCAM1 to guide the extravasation of pro-inflammatory cells, cancer endothelium downregulates these molecules to evade immune recognition. By contrast, we found that cancer endothelium upregulates activated leukocyte cell adhesion molecule (ALCAM), which allowed us to overcome this immune-evasion mechanism by creating an ALCAM-restricted homing system (HS). We re-engineered the natural ligand of ALCAM, CD6, in a manner that triggers initial anchorage of T cells to ALCAM and conditionally mediates a secondary wave of adhesion by sensitizing T cells to low-level ICAM1 on the cancer endothelium, thereby creating the adhesion forces necessary to capture T cells from the bloodstream. Cytotoxic HS T cells robustly infiltrated brain cancers after intravenous injection and exhibited potent antitumour activity. We have therefore developed a molecule that targets the delivery of T cells to brain cancer.

Multiple Respiratory Syncytial Virus (RSV) Strains Infecting HEp-2 and A549 Cells Reveal Cell Line-Dependent Differences in Resistance to RSV Infection.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here, we reported a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with one of four strains of RSV representing both major subgroups as well as historic and more contemporary genotypes (RSV/A/Tracy [GA1], RSV/A/Ontario [ON], RSV/B/18537 [GB1], and RSV/B/Buenos Aires [BA]) via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response, including transcriptional changes and levels of secreted cytokines and growth factors. IMPORTANCE Infection with the respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. Most RSV studies have involved either of two historic RSV/A strains infecting one of two cell lines, HEp-2 or A549 cells. However, RSV contains ample variation within two evolving subgroups (A and B), and HEp-2 and A549 cell lines are genetically distinct. Here, we measured viral action and host response in both HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporary strains. We discovered a subgroup-dependent difference in viral gene expression and found A549 cells were more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings revealed important differences between RSV subgroups and two widely used cell lines and provided baseline data for experiments with model systems better representative of natural RSV infection.

Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming.

Blockade of angiogenesis can retard tumour growth, but may also paradoxically increase metastasis. This paradox may be resolved by vessel normalization, which involves increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability, and consequently mitigated hypoxia. Although these processes alter tumour progression, their regulation is poorly understood. Here we show that type 1 T helper (TH1) cells play a crucial role in vessel normalization. Bioinformatic analyses revealed that gene expression features related to vessel normalization correlate with immunostimulatory pathways, especially T lymphocyte infiltration or activity. To delineate the causal relationship, we used various mouse models with vessel normalization or T lymphocyte deficiencies. Although disruption of vessel normalization reduced T lymphocyte infiltration as expected, reciprocal depletion or inactivation of CD4+ T lymphocytes decreased vessel normalization, indicating a mutually regulatory loop. In addition, activation of CD4+ T lymphocytes by immune checkpoint blockade increased vessel normalization. TH1 cells that secrete interferon-γ are a major population of cells associated with vessel normalization. Patient-derived xenograft tumours growing in immunodeficient mice exhibited enhanced hypoxia compared to the original tumours in immunocompetent humans, and hypoxia was reduced by adoptive TH1 transfer. Our findings elucidate an unexpected role of TH1 cells in vasculature and immune reprogramming. TH1 cells may be a marker and a determinant of both immune checkpoint blockade and anti-angiogenesis efficacy.

Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data.

Humans are continuously exposed to a variety of toxicants and chemicals which is exacerbated during and after environmental catastrophes such as floods, earthquakes, and hurricanes. The hazardous chemical mixtures generated during these events threaten the health and safety of humans and other living organisms. This necessitates the development of rapid decision-making tools to facilitate mitigating the adverse effects of exposure on the key modulators of the endocrine system, such as the estrogen receptor alpha (ERα), for example. The mechanistic stages of the estrogenic transcriptional activity can be measured with high content/high throughput microscopy-based biosensor assays at the single-cell level, which generates millions of object-based minable data points. By combining computational modeling and experimental analysis, we built a highly accurate data-driven classification framework to assess the endocrine disrupting potential of environmental compounds. The effects of these compounds on the ERα pathway are predicted as being receptor agonists or antagonists using the principal component analysis (PCA) projections of high throughput, high content image analysis descriptors. The framework also combines rigorous preprocessing steps and nonlinear machine learning algorithms, such as the Support Vector Machines and Random Forest classifiers, to develop highly accurate mathematical representations of the separation between ERα agonists and antagonists. The results show that Support Vector Machines classify the unseen chemicals correctly with more than 96% accuracy using the proposed framework, where the preprocessing and the PCA steps play a key role in suppressing experimental noise and unraveling hidden patterns in the dataset.

Estrogen-induced transcription at individual alleles is independent of receptor level and active conformation but can be modulated by coactivators activity.

Steroid hormones are pivotal modulators of pathophysiological processes in many organs, where they interact with nuclear receptors to regulate gene transcription. However, our understanding of hormone action at the single cell level remains incomplete. Here, we focused on estrogen stimulation of the well-characterized GREB1 and MYC target genes that revealed large differences in cell-by-cell responses, and, more interestingly, between alleles within the same cell, both over time and hormone concentration. We specifically analyzed the role of receptor level and activity state during allele-by-allele regulation and found that neither receptor level nor activation status are the determinant of maximal hormonal response, indicating that additional pathways are potentially in place to modulate cell- and allele-specific responses. Interestingly, we found that a small molecule inhibitor of the arginine methyltransferases CARM1 and PRMT6 was able to increase, in a gene specific manner, the number of active alleles/cell before and after hormonal stimulation, suggesting that mechanisms do indeed exist to modulate hormone receptor responses at the single cell and allele level.

The SINEB1 element in the long non-coding RNA Malat1 is necessary for TDP-43 proteostasis.

Transposable elements (TEs) comprise a large proportion of long non-coding RNAs (lncRNAs). Here, we employed CRISPR to delete a short interspersed nuclear element (SINE) in Malat1, a cancer-associated lncRNA, to investigate its significance in cellular physiology. We show that Malat1 with a SINE deletion forms diffuse nuclear speckles and is frequently translocated to the cytoplasm. SINE-deleted cells exhibit an activated unfolded protein response and PKR and markedly increased DNA damage and apoptosis caused by dysregulation of TDP-43 localization and formation of cytotoxic inclusions. TDP-43 binds stronger to Malat1 without the SINE and is likely 'hijacked' by cytoplasmic Malat1 to the cytoplasm, resulting in the depletion of nuclear TDP-43 and redistribution of TDP-43 binding to repetitive element transcripts and mRNAs encoding mitotic and nuclear-cytoplasmic regulators. The SINE promotes Malat1 nuclear retention by facilitating Malat1 binding to HNRNPK, a protein that drives RNA nuclear retention, potentially through direct interactions of the SINE with KHDRBS1 and TRA2A, which bind to HNRNPK. Losing these RNA-protein interactions due to the SINE deletion likely creates more available TDP-43 binding sites on Malat1 and subsequent TDP-43 aggregation. These results highlight the significance of lncRNA TEs in TDP-43 proteostasis with potential implications in both cancer and neurodegenerative diseases.

Phenotypic and protein localization heterogeneity associated with AHDC1 pathogenic protein-truncating alleles in Xia-Gibbs syndrome.

Xia-Gibbs syndrome (XGS) is a rare Mendelian disease typically caused by de novo stop-gain or frameshift mutations in the AT-hook DNA binding motif containing 1 (AHDC1) gene. Patients usually present in early infancy with hypotonia and developmental delay and later exhibit intellectual disability (ID). The overall presentation is variable, however, and the emerging clinical picture is still evolving. A detailed phenotypic analysis of 34 XGS individuals revealed five core phenotypes (delayed motor milestones, speech delay, low muscle tone, ID, and hypotonia) in more than 80% of individuals and an additional 12 features that occurred more variably. Seizures and scoliosis were more frequently associated with truncations that arise before the midpoint of the protein although the occurrence of most features could not be predicted by the mutation position. Transient expression of wild type and different patient truncated AHDC1 protein forms in human cell lines revealed abnormal patterns of nuclear localization including a diffuse distribution of a short truncated form and nucleolar aggregation in mid-protein truncated forms. Overall, both the occurrence of variable phenotypes and the different distribution of the expressed protein reflect the heterogeneity of this syndrome.

A Genetically Engineered Rotavirus NSP2 Phosphorylation Mutant Impaired in Viroplasm Formation and Replication Shows an Early Interaction between vNSP2 and Cellular Lipid Droplets.

Many RNA viruses replicate in cytoplasmic compartments (virus factories or viroplasms) composed of viral and cellular proteins, but the mechanisms required for their formation remain largely unknown. Rotavirus (RV) replication in viroplasms requires interactions between virus nonstructural proteins NSP2 and NSP5, which are associated with components of lipid droplets (LDs). We previously identified two forms of NSP2 in RV-infected cells, a cytoplasmically dispersed form (dNSP2) and a viroplasm-specific form (vNSP2), which interact with hypophosphorylated and hyperphosphorylated NSP5, respectively, indicating that a coordinated phosphorylation cascade controls viroplasm assembly. The cellular kinase CK1α phosphorylates NSP2 on serine 313, triggering the localization of vNSP2 to sites of viroplasm assembly and its association with hyperphosphorylated NSP5. Using reverse genetics, we generated a rotavirus with a phosphomimetic NSP2 (S313D) mutation to directly evaluate the role of CK1α NSP2 phosphorylation in viroplasm formation. Recombinant rotavirus NSP2 S313D (rRV NSP2 S313D) is significantly delayed in viroplasm formation and in virus replication and interferes with wild-type RV replication in coinfection. Taking advantage of the delay in viroplasm formation, the NSP2 phosphomimetic mutant was used as a tool to observe very early events in viroplasm assembly. We show that (i) viroplasm assembly correlates with NSP5 hyperphosphorylation and (ii) vNSP2 S313D colocalizes with RV-induced LDs without NSP5, suggesting that vNSP2 phospho-S313 is sufficient for interacting with LDs and may be the virus factor required for RV-induced LD formation. Further studies with the rRV NSP2 S313D virus are expected to reveal new aspects of viroplasm and LD initiation and assembly.IMPORTANCE Reverse genetics was used to generate a recombinant rotavirus with a single phosphomimetic mutation in nonstructural protein 2 (NSP2 S313D) that exhibits delayed viroplasm formation, delayed replication, and an interfering phenotype during coinfection with wild-type rotavirus, indicating the importance of this amino acid during virus replication. Exploiting the delay in viroplasm assembly, we found that viroplasm-associated NSP2 colocalizes with rotavirus-induced lipid droplets prior to the accumulation of other rotavirus proteins that are required for viroplasm formation and that NSP5 hyperphosphorylation is required for viroplasm assembly. These data suggest that NSP2 phospho-S313 is sufficient for interaction with lipid droplets and may be the virus factor that induces lipid droplet biogenesis in rotavirus-infected cells. Lipid droplets are cellular organelles critical for the replication of many viral and bacterial pathogens, and thus, understanding the mechanism of NSP2-mediated viroplasm/lipid droplet initiation and interaction will lead to new insights into this important host-pathogen interaction.

Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.

Environmental toxicants affect human health in various ways. Of the thousands of chemicals present in the environment, those with adverse effects on the endocrine system are referred to as endocrine-disrupting chemicals (EDCs). Here, we focused on a subclass of EDCs that impacts the estrogen receptor (ER), a pivotal transcriptional regulator in health and disease. Estrogenic activity of compounds can be measured by many in vitro or cell-based high throughput assays that record various endpoints from large pools of cells, and increasingly at the single-cell level. To simultaneously capture multiple mechanistic ER endpoints in individual cells that are affected by EDCs, we previously developed a sensitive high throughput/high content imaging assay that is based upon a stable cell line harboring a visible multicopy ER responsive transcription unit and expressing a green fluorescent protein (GFP) fusion of ER. High content analysis generates voluminous multiplex data comprised of minable features that describe numerous mechanistic endpoints. In this study, we present a machine learning pipeline for rapid, accurate, and sensitive assessment of the endocrine-disrupting potential of benchmark chemicals based on data generated from high content analysis. The multidimensional imaging data was used to train a classification model to ultimately predict the impact of unknown compounds on the ER, either as agonists or antagonists. To this end, both linear logistic regression and nonlinear Random Forest classifiers were benchmarked and evaluated for predicting the estrogenic activity of unknown compounds. Furthermore, through feature selection, data visualization, and model discrimination, the most informative features were identified for the classification of ER agonists/antagonists. The results of this data-driven study showed that highly accurate and generalized classification models with a minimum number of features can be constructed without loss of generality, where these machine learning models serve as a means for rapid mechanistic/phenotypic evaluation of the estrogenic potential of many chemicals.

Coactivators enable glucocorticoid receptor recruitment to fine-tune estrogen receptor transcriptional responses.

Nuclear receptors (NRs) are central regulators of pathophysiological processes; however, how their responses intertwine is still not fully understood. The aim of this study was to determine whether and how steroid NRs can influence each other's activity under co-agonist treatment. We used a unique system consisting of a multicopy integration of an estrogen receptor responsive unit that allows direct visualization and quantification of estrogen receptor alpha (ERα) DNA binding, co-regulator recruitment and transcriptional readout. We find that ERα DNA loading is required for other type I nuclear receptors to be co-recruited after dual agonist treatment. We focused on ERα/glucocorticoid receptor interplay and demonstrated that it requires steroid receptor coactivators (SRC-2, SRC-3) and the mediator component MED14. We then validated this cooperative interplay on endogenous target genes in breast cancer cells. Taken together, this work highlights another layer of mechanistic complexity through which NRs cross-talk with each other on chromatin under multiple hormonal stimuli.

VEGF signalling controls GnRH neuron survival via NRP1 independently of KDR and blood vessels.

Gonadotropin-releasing hormone (GnRH) neurons are neuroendocrine cells that are born in the nasal placode during embryonic development and migrate through the nose and forebrain to the hypothalamus, where they regulate reproduction. Many molecular pathways that guide their migration have been identified, but little is known about the factors that control the survival of the migrating GnRH neurons as they negotiate different environments. We previously reported that the class 3 semaphorin SEMA3A signals through its neuropilin receptors, NRP1 and NRP2, to organise the axons that guide migrating GnRH neurons from their birthplace into the brain. By combining analysis of genetically altered mice with in vitro models, we show here that the alternative neuropilin ligand VEGF164 promotes the survival of migrating GnRH neurons by co-activating the ERK and AKT signalling pathways through NRP1. We also demonstrate that survival signalling relies on neuronal, but not endothelial, NRP1 expression and that it occurs independently of KDR, the main VEGF receptor in blood vessels. Therefore, VEGF164 provides survival signals directly to developing GnRH neurons, independently of its role in blood vessels. Finally, we show that the VEGF164-mediated neuronal survival and SEMA3A-mediated axon guidance cooperate to ensure that migrating GnRH neurons reach the brain. Thus, the loss of both neuropilin ligands leads to an almost complete failure to establish the GnRH neuron system.

A novel ERß high throughput microscopy platform for testing endocrine disrupting chemicals.

In this study we present an inducible biosensor model for the Estrogen Receptor Beta (ERß), GFP-ERß:PRL-HeLa, a single-cell-based high throughput (HT) in vitro assay that allows direct visualization and measurement of GFP-tagged ERß binding to ER-specific DNA response elements (EREs), ERß-induced chromatin remodeling, and monitor transcriptional alterations via mRNA fluorescence in situ hybridization for a prolactin (PRL)-dsRED2 reporter gene. The model was used to accurately (Z' = 0.58-0.8) differentiate ERß-selective ligands from ERα ligands when treated with a panel of selective agonists and antagonists. Next, we tested an Environmental Protection Agency (EPA)-provided set of 45 estrogenic reference chemicals with known ERα in vivo activity and identified several that activated ERß as well, with varying sensitivity, including a subset that is completely novel. We then used an orthogonal ERE-containing transgenic zebrafish (ZF) model to cross validate ERß and ERα selective activities at the organism level. Using this environmentally relevant ZF assay, some compounds were confirmed to have ERß activity, validating the GFP-ERß:PRL-HeLa assay as a screening tool for potential ERß active endocrine disruptors (EDCs). These data demonstrate the value of sensitive multiplex mechanistic data gathered by the GFP-ERß:PRL-HeLa assay coupled with an orthogonal zebrafish model to rapidly identify environmentally relevant ERß EDCs and improve upon currently available screening tools for this understudied nuclear receptor.

Characterization of flavonoids with potent and subtype-selective actions on estrogen receptors alpha and beta.

The initial step in estrogen-regulated transcription is the binding of a ligand to its cognate receptors, named estrogen receptors (ERα and ERß). Phytochemicals present in foods and environment can compete with endogenous hormones to alter physiological responses. We screened 224 flavonoids in our engineered biosensor ERα and ERß PRL-array cell lines to characterize their activity on several steps of the estrogen signaling pathway. We identified 83 and 96 flavonoids that can activate ERα or ERß, respectively. While most act on both receptors, many appear to be subtype-selective, including potent flavonoids that activate ER at sub-micromolar concentrations. We employed an orthogonal assay using a transgenic zebrafish in vivo model that validated the estrogenic potential of these compounds. To our knowledge, this is the largest study thus far on flavonoids and the ER pathway, facilitating the identification of a new set of potential endocrine disruptors acting on both ERα and ERß.

SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data.

Phenotypic profiling by high throughput microscopy has become one of the leading tools for screening large sets of perturbations in cellular models. Of the numerous methods used over the years, the flexible and economical Cell Painting (CP) assay has been central in the field, allowing for large screening campaigns leading to a vast number of data-rich images. Currently, to analyze data of this scale, available open-source software ( i.e. , CellProfiler) requires computational resources that are not available to most laboratories worldwide. In addition, the image-embedded cell-to-cell variation of responses within a population, while collected and analyzed, is usually averaged and unused. Here we introduce SPACe ( S wift P henotypic A nalysis of Ce lls), an open source, Python-based platform for the analysis of single cell image-based morphological profiles produced by CP experiments. SPACe can process a typical dataset approximately ten times faster than CellProfiler on common desktop computers without loss in mechanism of action (MOA) recognition accuracy. It also computes directional distribution-based distances (Earth Mover's Distance - EMD) of morphological features for quality control and hit calling. We highlight several advantages of SPACe analysis on CP assays, including reproducibility across multiple biological replicates, easy applicability to multiple (∼20) cell lines, sensitivity to variable cell-to-cell responses, and biological interpretability to explain image-based features. We ultimately illustrate the advantages of SPACe in a screening campaign of cell metabolism small molecule inhibitors which we performed in seven cell lines to highlight the importance of testing perturbations across models.

Infant and Adult Human Intestinal Enteroids are Morphologically and Functionally Distinct.

Background & Aims: Human intestinal enteroids (HIEs) are gaining recognition as physiologically relevant models of the intestinal epithelium. While HIEs from adults are used extensively in biomedical research, few studies have used HIEs from infants. Considering the dramatic developmental changes that occur during infancy, it is important to establish models that represent infant intestinal characteristics and physiological responses. Methods: We established jejunal HIEs from infant surgical samples and performed comparisons to jejunal HIEs from adults using RNA sequencing (RNA-Seq) and morphologic analyses. We validated differences in key pathways through functional studies and determined if these cultures recapitulate known features of the infant intestinal epithelium. Results: RNA-Seq analysis showed significant differences in the transcriptome of infant and adult HIEs, including differences in genes and pathways associated with cell differentiation and proliferation, tissue development, lipid metabolism, innate immunity, and biological adhesion. Validating these results, we observed a higher abundance of cells expressing specific enterocyte, goblet cell and enteroendocrine cell markers in differentiated infant HIE monolayers, and greater numbers of proliferative cells in undifferentiated 3D cultures. Compared to adult HIEs, infant HIEs portray characteristics of an immature gastrointestinal epithelium including significantly shorter cell height, lower epithelial barrier integrity, and lower innate immune responses to infection with an oral poliovirus vaccine. Conclusions: HIEs established from infant intestinal tissues reflect characteristics of the infant gut and are distinct from adult cultures. Our data support the use of infant HIEs as an ex-vivo model to advance studies of infant-specific diseases and drug discovery for this population.

Infant and adult human intestinal enteroids are morphologically and functionally distinct.

Human intestinal enteroids (HIEs) are gaining recognition as physiologically relevant models of the intestinal epithelium. While HIEs from adults are used extensively in biomedical research, few studies have used HIEs from infants. Considering the dramatic developmental changes that occur during infancy, it is important to establish models that represent infant intestinal characteristics and physiological responses. We established jejunal HIEs from infant surgical samples and performed comparisons to jejunal HIEs from adults using RNA sequencing (RNA-Seq) and morphologic analyses. We then validated differences in key pathways through functional studies and determined whether these cultures recapitulate known features of the infant intestinal epithelium. RNA-Seq analysis showed significant differences in the transcriptome of infant and adult HIEs, including differences in genes and pathways associated with cell differentiation and proliferation, tissue development, lipid metabolism, innate immunity, and biological adhesion. Validating these results, we observed a higher abundance of cells expressing specific enterocyte, goblet cell, and enteroendocrine cell markers in differentiated infant HIE monolayers, and greater numbers of proliferative cells in undifferentiated 3D cultures. Compared to adult HIEs, infant HIEs portray characteristics of an immature gastrointestinal epithelium including significantly shorter cell height, lower epithelial barrier integrity, and lower innate immune responses to infection with an oral poliovirus vaccine. HIEs established from infant intestinal tissues reflect characteristics of the infant gut and are distinct from adult cultures. Our data support the use of infant HIEs as an ex vivo model to advance studies of infant-specific diseases and drug discovery for this population. IMPORTANCE: Tissue or biopsy stem cell-derived human intestinal enteroids are increasingly recognized as physiologically relevant models of the human gastrointestinal epithelium. While enteroids from adults and fetal tissues have been extensively used for studying many infectious and non-infectious diseases, there are few reports on enteroids from infants. We show that infant enteroids exhibit both transcriptomic and morphological differences compared to adult cultures. They also differ in functional responses to barrier disruption and innate immune responses to infection, suggesting that infant and adult enteroids are distinct model systems. Considering the dramatic changes in body composition and physiology that begin during infancy, tools that appropriately reflect intestinal development and diseases are critical. Infant enteroids exhibit key features of the infant gastrointestinal epithelium. This study is significant in establishing infant enteroids as age-appropriate models for infant intestinal physiology, infant-specific diseases, and responses to pathogens.