Insights for disease modeling from single-cell transcriptomics of iPSC-derived Ngn2-induced neurons and astrocytes across differentiation time and co-culture.

BACKGROUND: Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. RESULTS: Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . CONCLUSIONS: While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

An enzyme-distributed system for lidocaine metabolism in the perfused rat liver preparation.

The influence of enzymic distribution on lidocaine metabolism was investigated in the once-through perfused rat liver preparation. Low input concentrations of 14C-lidocaine (1-2 microM) and preformed monoethylglycine xylidide (MEGX; 2.3-2.8 microM) were delivered by normal and retrograde flow directions to the liver preparations at 10 ml/min per liver. Upon reversal of normal to retrograde delivery of lidocaine, the rates at which lidocaine, MEGX, and glycine xylidide (GX) left the liver almost doubled, whereas the rates of appearance of (total) hydroxylated lidocaine and MEGX in bile and perfusate increased to lesser extents. Upon reversal of normal to retrograde delivery of preformed MEGX, the rates of appearance of MEGX and GX were virtually unchanged. Computer simulations on lidocaine and preformed MEGX metabolism were performed on both evenly distributed ("parallel tube" model) and enzyme-distributed systems. An even or parallel distribution of N-deethylation and hydroxylation activities for lidocaine metabolism failed to predict the observed increased hepatic availability of lidocaine. Rather, the distribution of a low-affinity, high-capacity N-deethylation system anterior to a high-affinity, low-capacity hydroxylation system for lidocaine metabolism adequately predicted the increased hepatic availability of lidocaine. Further extension of these consistent enzyme-distributed models on the metabolism of lidocaine metabolites suggests that the N-deethylation and hydroxylation activities for the metabolism of lidocaine, MEGX, 3-hydroxyidocaine, and 3-hydroxy MEGX are not identically distributed. When these enzyme-distributed models were appraised with reference to the "parallel tube" and "well-stirred" models of hepatic drug clearance, predictions from these enzyme-distributed models proved to be superior to the "parallel tube" and "well-stirred" models for the present data on lidocaine metabolites with normal and retrograde perfusions. Previously published data on lidocaine and MEGX metabolism after inputting 4 micrograms/ml (17 microM) lidocaine at flow rates of 10, 12, 14, and 16 ml/min were reexamined with respect to the adequacy of these enzyme-distributed models. They were found to be superior to the evenly-distributed or "parallel tube" model in predicting hepatic availability of lidocaine and the rate of appearance of MEGX. However, the enzyme-distributed systems were not as consistent as the "well-stirred" model in predicting lidocaine hepatic availability in these flow experiments.