Preconception opioids interact with mouse strain to alter morphine withdrawal in the next generation.

RATIONALE: Transgenerational effects of preconception morphine exposure in female rats have been reported which suggest that epigenetic modifications triggered by female opioid exposure, even when that exposure ends several weeks prior to pregnancy, has significant ramifications for their future offspring. OBJECTIVE: The current study compares two mouse strains with well-established genetic variation in their response to mu opioid receptor agonists, C57BL/6J (BL6) and 129S1/svlmJ (129) to determine whether genetic background modifies the impact of preconception opioid exposure. METHODS: Adolescent females from both strains were injected daily with morphine for a total of 10 days using an increasing dosing regimen with controls receiving saline. Several weeks after their final injection, aged-matched BL6 and 129 morphine (Mor-F0) or saline (Sal-F0) females were mated with drug naïve males to generate Mor-F1 and Sal-F1 offspring, respectively. As adults, F1 mice were made morphine dependent using thrice daily morphine injections for 4 days. On day 5, mice were administered either saline or morphine followed 3 h later by naloxone. Behavioral and physiological signs of withdrawal were then measured. RESULTS: Regardless of strain or sex, morphine-dependent Mor-F1 mice had significantly lower levels of withdrawal-induced corticosterone but significantly higher glucose levels when compared to Sal-F1 controls. In contrast, both strain- and preconception opioid exposure effects on physical signs of morphine dependence were observed.

Hepatic organoids move from adolescence to maturity.

Since organoids were developed 15 years ago, they are now in their adolescence as a research tool. The ability to generate 'tissue in a dish' has created enormous opportunities for biomedical research. We examine the contributions that hepatic organoids have made to three areas of liver research: as a source of cells and tissue for basic research, for drug discovery and drug safety testing, and for understanding disease pathobiology. We discuss the features that enable hepatic organoids to provide useful models for human liver diseases and identify four types of advances that will enable them to become a mature (i.e., adult) research tool over the next 5 years. During this period, advances in single-cell RNA sequencing and CRISPR technologies coupled with improved hepatic organoid methodology, which enables them to have a wider range of cell types that are present in liver and to be grown in microwells, will generate discoveries that will dramatically advance our understanding of liver development and the pathogenesis of liver diseases. It will generate also new approaches for treating liver fibrosis, which remains a major public health problem with few treatment options.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Genetic Discovery Enabled by A Large Language Model.

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.

Neuron Navigator 1 (Nav1) regulates the response to cocaine in mice.

Genetic variation accounts for much of the risk for developing a substance use disorder, but the underlying genetic factors and their genetic effector mechanisms are mostly unknown. Inbred mouse strains exhibit substantial and heritable differences in the extent of voluntary cocaine self-administration. Computational genetic analysis of cocaine self-administration data obtained from twenty-one inbred strains identified Nav1, a member of the neuron navigator family that regulates dendrite formation and axonal guidance, as a candidate gene. To test this genetic hypothesis, we generated and characterized Nav1 knockout mice. Consistent with the genetic prediction, Nav1 knockout mice exhibited increased voluntary cocaine intake and had increased motivation for cocaine consumption. Immunohistochemistry, electrophysiology, and transcriptomic studies were performed as a starting point for investigating the mechanism for the Nav1 knockout effect. Nav1 knockout mice had a reduced inhibitory synapse density in their cortex, increased excitatory synaptic transmission in their cortex and hippocampus, and increased excitatory neurons in a deep cortical layer. Collectively, our results indicate that Nav1 regulates the response to cocaine, and we identified Nav1 knockout induced changes in the excitatory and inhibitory synaptic balance in the cortex and hippocampus that could contribute to this effect.

GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses.

Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter ( https://muster.jax.org ), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Analysis of structural variation among inbred mouse strains.

BACKGROUND: 'Long read' sequencing methods have been used to identify previously uncharacterized structural variants that cause human genetic diseases. Therefore, we investigated whether long read sequencing could facilitate genetic analysis of murine models for human diseases. RESULTS: The genomes of six inbred strains (BTBR T + Itpr3tf/J, 129Sv1/J, C57BL/6/J, Balb/c/J, A/J, SJL/J) were analyzed using long read sequencing. Our results revealed that (i) Structural variants are very abundant within the genome of inbred strains (4.8 per gene) and (ii) that we cannot accurately infer whether structural variants are present using conventional short read genomic sequence data, even when nearby SNP alleles are known. The advantage of having a more complete map was demonstrated by analyzing the genomic sequence of BTBR mice. Based upon this analysis, knockin mice were generated and used to characterize a BTBR-unique 8-bp deletion within Draxin that contributes to the BTBR neuroanatomic abnormalities, which resemble human autism spectrum disorder. CONCLUSION: A more complete map of the pattern of genetic variation among inbred strains, which is produced by long read genomic sequencing of the genomes of additional inbred strains, could facilitate genetic discovery when murine models of human diseases are analyzed.

GSEApy: a comprehensive package for performing gene set enrichment analysis in Python.

MOTIVATION: Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes. However, the currently available tools used to perform GSEA have a limited ability to analyze large datasets, which is particularly problematic for the analysis of single-cell data. To overcome this limitation, we developed a GSEA package in Python (GSEApy), which could efficiently analyze large single-cell datasets. RESULTS: We present a package (GSEApy) that performs GSEA in either the command line or Python environment. GSEApy uses a Rust implementation to enable it to calculate the same enrichment statistic as GSEA for a collection of pathways. The Rust implementation of GSEApy is 3-fold faster than the Numpy version of GSEApy (v0.10.8) and uses >4-fold less memory. GSEApy also provides an interface between Python and Enrichr web services, as well as for BioMart. The Enrichr application programming interface enables GSEApy to perform over-representation analysis for an input gene list. Furthermore, GSEApy consists of several tools, each designed to facilitate a particular type of enrichment analysis. AVAILABILITY AND IMPLEMENTATION: The new GSEApy with Rust extension is deposited in PyPI: https://pypi.org/project/gseapy/. The GSEApy source code is freely available at https://github.com/zqfang/GSEApy. Also, the documentation website is available at https://gseapy.rtfd.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dysregulated Lipid Synthesis by Oncogenic IDH1 Mutation Is a Targetable Synthetic Lethal Vulnerability.

Isocitrate dehydrogenase 1 and 2 (IDH) are mutated in multiple cancers and drive production of (R)-2-hydroxyglutarate (2HG). We identified a lipid synthesis enzyme [acetyl CoA carboxylase 1 (ACC1)] as a synthetic lethal target in mutant IDH1 (mIDH1), but not mIDH2, cancers. Here, we analyzed the metabolome of primary acute myeloid leukemia (AML) blasts and identified an mIDH1-specific reduction in fatty acids. mIDH1 also induced a switch to b-oxidation indicating reprogramming of metabolism toward a reliance on fatty acids. Compared with mIDH2, mIDH1 AML displayed depletion of NADPH with defective reductive carboxylation that was not rescued by the mIDH1-specific inhibitor ivosidenib. In xenograft models, a lipid-free diet markedly slowed the growth of mIDH1 AML, but not healthy CD34+ hematopoietic stem/progenitor cells or mIDH2 AML. Genetic and pharmacologic targeting of ACC1 resulted in the growth inhibition of mIDH1 cancers not reversible by ivosidenib. Critically, the pharmacologic targeting of ACC1 improved the sensitivity of mIDH1 AML to venetoclax. SIGNIFICANCE: Oncogenic mutations in both IDH1 and IDH2 produce 2-hydroxyglutarate and are generally considered equivalent in terms of pathogenesis and targeting. Using comprehensive metabolomic analysis, we demonstrate unexpected metabolic differences in fatty acid metabolism between mutant IDH1 and IDH2 in patient samples with targetable metabolic interventions. See related commentary by Robinson and Levine, p. 266. This article is highlighted in the In This Issue feature, p. 247.

Optimizing a therapy for opiate use disorders: Characterizing ondansetron pharmacokinetics in blood and brain.

Administration of a widely used 5-hydroxytryptamine receptor (5HT3A R) antagonist (ondansetron) potently inhibited the development of experimentally induced opioid dependence and withdrawal responses in mice and humans. However, in several studies examining withdrawal symptoms in subjects with chronic opioid use disorders (OUDs), ondansetron exhibited reduced or absent efficacy. Because attenuation of opioid withdrawal symptomatology is mediated within the brain, this study examined single-dose ondansetron pharmacokinetics in the blood and brain of mice. We demonstrate that ondansetron concentrations in the brain (Cbrain ng/mg) are 1000-fold lower than the blood concentrations (Cblood ng/ml) and decrease rapidly after ondansetron administration; and that a large percentage of brain ondansetron remains in the ventricular fluid. These results indicate that the ondansetron dose, and the time window between ondansetron and opioid administration, and when withdrawal is assessed are critical considerations for clinical studies involving subjects with chronic OUD. The pharmacokinetic results and the dosing considerations discussed here can be used to improve the design of subsequent clinical trials, which will test whether a more prolonged period of ondansetron administration can provide a desperately needed therapy that can prevent the development of neonatal opioid withdrawal syndrome in babies born to mothers with chronic OUD.

Ondansetron to reduce neonatal opioid withdrawal severity a randomized clinical trial.

OBJECTIVE: To determine if treatment with a 5-HT3 antagonist (ondansetron) reduces need for opioid therapy in infants at risk for neonatal opioid withdrawal syndrome (NOWS). STUDY DESIGN: A multicenter, randomized, placebo controlled, double blind clinical trial of ninety (90) infants. The intervention arms were intravenous ondansetron or placebo during labor followed by a daily dose of ondansetron or placebo in infants for five days. RESULTS: Twenty-two (49%) ondansetron-treated and 26 (63%) placebo-treated infants required pharmacologic treatment (p > 0.05). The Finnegan score was lower in the ondansetron-treated group (4.6 vs. 5.6, p = 0.02). A non-significant trend was noted for the duration of hospitalization. There was no difference in need for phenobarbital or clonidine therapy, or total dose of morphine in the first 15 days of NOWS treatment. CONCLUSIONS: Ondansetron treatment reduced the severity of NOWS symptoms; and there was an indication that it could reduce the length of stay. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov NCT01965704.

Clinical Application of Induced Hepatocyte-like Cells Produced from Mesenchymal Stromal Cells: A Literature Review.

Liver disease is a leading cause of mortality worldwide, resulting in 1.3 million deaths annually. The vast majority of liver disease is caused by metabolic disease (i.e., NASH) and alcohol-induced hepatitis, and to a lesser extent by acute and chronic viral infection. Furthermore, multiple insults to the liver is becoming common due to the prevalence of metabolic and alcohol-related liver diseases. Despite this rising prevalence of liver disease, there are few treatment options: there are treatments for viral hepatitis C and there is vaccination for hepatitis B. Aside from the management of metabolic syndrome, no direct liver therapy has shown clinical efficacy for metabolic liver disease, there is very little for acute alcohol-induced liver disease, and liver transplantation remains the only effective treatment for late-stage liver disease. Traditional pharmacologic interventions have failed to appreciably impact the pathophysiology of alcohol-related liver disease or end-stage liver disease. The difficulties associated with developing liver-specific therapies result from three factors that are common to late-stage liver disease arising from any cause: hepatocyte injury, inflammation, and aberrant tissue healing. Hepatocyte injury results in tissue damage with inflammation, which sensitizes the liver to additional hepatocyte injury and stimulates hepatic stellate cells and aberrant tissue healing responses. In the setting of chronic liver insults, there is progressive scarring, the loss of hepatocyte function, and hemodynamic dysregulation. Regenerative strategies using hepatocyte-like cells that are manufactured from mesenchymal stromal cells may be able to correct this pathophysiology through multiple mechanisms of action. Preclinical studies support their effectiveness and recent clinical studies suggest that cell replacement therapy can be safe and effective in patients with liver disease for whom there is no other option.

Zhx2 Is a Candidate Gene Underlying Oxymorphone Metabolite Brain Concentration Associated with State-Dependent Oxycodone Reward.

Understanding the pharmacogenomics of opioid metabolism and behavior is vital to therapeutic success, as mutations can dramatically alter therapeutic efficacy and addiction liability. We found robust, sex-dependent BALB/c substrain differences in oxycodone behaviors and whole brain concentration of oxycodone metabolites. BALB/cJ females showed robust state-dependent oxycodone reward learning as measured via conditioned place preference when compared with the closely related BALB/cByJ substrain. Accordingly, BALB/cJ females also showed a robust increase in brain concentration of the inactive metabolite noroxycodone and the active metabolite oxymorphone compared with BALB/cByJ mice. Oxymorphone is a highly potent, full agonist at the mu opioid receptor that could enhance drug-induced interoception and state-dependent oxycodone reward learning. Quantitative trait locus (QTL) mapping in a BALB/c F2 reduced complexity cross revealed one major QTL on chromosome 15 underlying brain oxymorphone concentration that explained 32% of the female variance. BALB/cJ and BALB/cByJ differ by fewer than 10,000 variants, which can greatly facilitate candidate gene/variant identification. Hippocampal and striatal cis-expression QTL (eQTL) and exon-level eQTL analysis identified Zhx2, a candidate gene coding for a transcriptional repressor with a private BALB/cJ retroviral insertion that reduces Zhx2 expression and sex-dependent dysregulation of cytochrome P450 enzymes. Whole brain proteomics corroborated the Zhx2 eQTL and identified upregulated CYP2D11 that could increase brain oxymorphone in BALB/cJ females. To summarize, Zhx2 is a highly promising candidate gene underlying brain oxycodone metabolite levels. Future studies will validate Zhx2 and its site of action using reciprocal gene editing and tissue-specific viral manipulations in BALB/c substrains. SIGNIFICANCE STATEMENT: Our findings show that genetic variation can result in sex-specific alterations in whole brain concentration of a bioactive opioid metabolite after oxycodone administration, reinforcing the need for sex as a biological factor in pharmacogenomic studies. The cooccurrence of female-specific increased oxymorphone and state-dependent reward learning suggests that this minor yet potent and efficacious metabolite of oxycodone could increase opioid interoception and drug-cue associative learning of opioid reward, which has implications for cue-induced relapse of drug-seeking behavior and for precision pharmacogenetics.

An automated multi-modal graph-based pipeline for mouse genetic discovery.

MOTIVATION: Our ability to identify causative genetic factors for mouse genetic models of human diseases and biomedical traits has been limited by the difficulties associated with identifying true causative factors, which are often obscured by the many false positive genetic associations produced by a GWAS. RESULTS: To accelerate the pace of genetic discovery, we developed a graph neural network (GNN)-based automated pipeline (GNNHap) that could rapidly analyze mouse genetic model data and identify high probability causal genetic factors for analyzed traits. After assessing the strength of allelic associations with the strain response pattern; this pipeline analyzes 29M published papers to assess candidate gene-phenotype relationships; and incorporates the information obtained from a protein-protein interaction network and protein sequence features into the analysis. The GNN model produces markedly improved results relative to that of a simple linear neural network. We demonstrate that GNNHap can identify novel causative genetic factors for murine models of diabetes/obesity and for cataract formation, which were validated by the phenotypes appearing in previously analyzed gene knockout mice. The diabetes/obesity results indicate how characterization of the underlying genetic architecture enables new therapies to be discovered and tested by applying 'precision medicine' principles to murine models. AVAILABILITY AND IMPLEMENTATION: The GNNHap source code is freely available at https://github.com/zqfang/gnnhap, and the new version of the HBCGM program is available at https://github.com/zqfang/haplomap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic basis of thermal nociceptive sensitivity and brain weight in a BALB/c reduced complexity cross.

Thermal nociception involves the transmission of temperature-related noxious information from the periphery to the CNS and is a heritable trait that could predict transition to persistent pain. Rodent forward genetics complement human studies by controlling genetic complexity and environmental factors, analysis of end point tissue, and validation of variants on appropriate genetic backgrounds. Reduced complexity crosses between nearly identical inbred substrains with robust trait differences can greatly facilitate unbiased discovery of novel genes and variants. We found BALB/cByJ mice showed enhanced sensitivity on the 53.5°C hot plate and mechanical stimulation in the von Frey test compared to BALB/cJ mice and replicated decreased gross brain weight in BALB/cByJ versus BALB/cJ. We then identified a quantitative trait locus (QTL) on chromosome 13 for hot plate sensitivity (LOD = 10.7; p < 0.001; peak = 56 Mb) and a QTL for brain weight on chromosome 5 (LOD = 8.7; p < 0.001). Expression QTL mapping of brain tissues identified H2afy (56.07 Mb) as the top transcript with the strongest association at the hot plate locus (FDR = 0.0002) and spliceome analysis identified differential exon usage within H2afy associated with the same locus. Whole brain proteomics further supported decreased H2AFY expression could underlie enhanced hot plate sensitivity, and identified ACADS as a candidate for reduced brain weight. To summarize, a BALB/c reduced complexity cross combined with multiple-omics approaches facilitated identification of candidate genes underlying thermal nociception and brain weight. These substrains provide a powerful, reciprocal platform for future validation of candidate variants.

Genetic Differences in Dorsal Hippocampus Acetylcholinesterase Activity Predict Contextual Fear Learning Across Inbred Mouse Strains.

Learning is a critical behavioral process that is influenced by many neurobiological systems. We and others have reported that acetylcholinergic signaling plays a vital role in learning capabilities, and it is especially important for contextual fear learning. Since cholinergic signaling is affected by genetic background, we examined the genetic relationship between activity levels of acetylcholinesterase (AChE), the primary enzyme involved in the acetylcholine metabolism, and learning using a panel of 20 inbred mouse strains. We measured conditioned fear behavior and AChE activity in the dorsal hippocampus, ventral hippocampus, and cerebellum. Acetylcholinesterase activity varied among inbred mouse strains in all three brain regions, and there were significant inter-strain differences in contextual and cued fear conditioning. There was an inverse correlation between fear conditioning outcomes and AChE levels in the dorsal hippocampus. In contrast, the ventral hippocampus and cerebellum AChE levels were not correlated with fear conditioning outcomes. These findings strengthen the link between acetylcholine activity in the dorsal hippocampus and learning, and they also support the premise that the dorsal hippocampus and ventral hippocampus are functionally discrete.

A human multi-lineage hepatic organoid model for liver fibrosis.

To investigate the pathogenesis of a congenital form of hepatic fibrosis, human hepatic organoids were engineered to express the most common causative mutation for Autosomal Recessive Polycystic Kidney Disease (ARPKD). Here we show that these hepatic organoids develop the key features of ARPKD liver pathology (abnormal bile ducts and fibrosis) in only 21 days. The ARPKD mutation increases collagen abundance and thick collagen fiber production in hepatic organoids, which mirrors ARPKD liver tissue pathology. Transcriptomic and other analyses indicate that the ARPKD mutation generates cholangiocytes with increased TGFß pathway activation, which are actively involved stimulating myofibroblasts to form collagen fibers. There is also an expansion of collagen-producing myofibroblasts with markedly increased PDGFRB protein expression and an activated STAT3 signaling pathway. Moreover, the transcriptome of ARPKD organoid myofibroblasts resemble those present in commonly occurring forms of liver fibrosis. PDGFRB pathway involvement was confirmed by the anti-fibrotic effect observed when ARPKD organoids were treated with PDGFRB inhibitors. Besides providing insight into the pathogenesis of congenital (and possibly acquired) forms of liver fibrosis, ARPKD organoids could also be used to test the anti-fibrotic efficacy of potential anti-fibrotic therapies.

The Effect of Population Structure on Murine Genome-Wide Association Studies.

The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 - 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated.

Engineered Matrices Enable the Culture of Human Patient-Derived Intestinal Organoids.

Human intestinal organoids from primary human tissues have the potential to revolutionize personalized medicine and preclinical gastrointestinal disease models. A tunable, fully defined, designer matrix, termed hyaluronan elastin-like protein (HELP) is reported, which enables the formation, differentiation, and passaging of adult primary tissue-derived, epithelial-only intestinal organoids. HELP enables the encapsulation of dissociated patient-derived cells, which then undergo proliferation and formation of enteroids, spherical structures with polarized internal lumens. After 12 rounds of passaging, enteroid growth in HELP materials is found to be statistically similar to that in animal-derived matrices. HELP materials also support the differentiation of human enteroids into mature intestinal cell subtypes. HELP matrices allow stiffness, stress relaxation rate, and integrin-ligand concentration to be independently and quantitatively specified, enabling fundamental studies of organoid-matrix interactions and potential patient-specific optimization. Organoid formation in HELP materials is most robust in gels with stiffer moduli (G' ≈ 1 kPa), slower stress relaxation rate (t1/2 ≈ 18 h), and higher integrin ligand concentration (0.5 × 10-3-1 × 10-3 m RGD peptide). This material provides a promising in vitro model for further understanding intestinal development and disease in humans and a reproducible, biodegradable, minimal matrix with no animal-derived products or synthetic polyethylene glycol for potential clinical translation.