A comprehensive library of human transcription factors for cell fate engineering

Uncovering the dynamics and consequences of RNA isoform changes during neuronal differentiation

Static gene expression programs have been extensively characterized in stem cells and mature human cells. However, the dynamics of RNA isoform changes upon cell-state-transitions during cell differentiation, the determinants and functional consequences have largely remained unclear. Here, we established an improved model for human neurogenesis in vitro that is amenable for systems-wide analyses of gene expression. Our multi-omics analysis reveals that the pronounced alterations in cell morphology correlate strongly with widespread changes in RNA isoform expression. Our approach identifies thousands of new RNA isoforms that are expressed at distinct differentiation stages. RNA isoforms mainly arise from exon skipping and the alternative usage of transcription start and polyadenylation sites during human neurogenesis. The transcript isoform changes can remodel the identity and functions of protein isoforms. Finally, our study identifies a set of RNA binding proteins as a potential determinant of differentiation stage-specific global isoform changes. This work supports the view of regulated isoform changes that underlie state-transitions during neurogenesis.

Models of Herpes Simplex Virus Latency

Our current understanding of HSV latency is based on a variety of clinical observations, and in vivo, ex vivo, and in vitro model systems, each with unique advantages and drawbacks. The criteria for authentically modeling HSV latency include the ability to easily manipulate host genetics and biological pathways, as well as mimicking the immune response and viral pathogenesis in human infections. Although realistically modeling HSV latency is necessary when choosing a model, the cost, time requirement, ethical constraints, and reagent availability are also equally important. Presently, there remains a pressing need for in vivo models that more closely recapitulate human HSV infection. While the current in vivo, ex vivo, and in vitro models used to study HSV latency have limitations, they provide further insights that add to our understanding of latency. In vivo models have shed light on natural infection routes and the interplay between the host immune response and the virus during latency, while in vitro models have been invaluable in elucidating molecular pathways involved in latency. Below, we review the relative advantages and disadvantages of current HSV models and highlight insights gained through each.

Systematic mapping of TF-mediated cell fate changes by a pooled induction coupled with scRNA-seq and multi-omics approaches

Transcriptional regulation controls cellular functions through interactions between transcription factors (TFs) and their chromosomal targets. However, understanding the fate conversion potential of multiple TFs in an inducible manner remains limited. Here, we introduce iTF-seq as a method for identifying individual TFs that can alter cell fate toward specific lineages at a single-cell level. iTF-seq enables time course monitoring of transcriptome changes, and with biotinylated individual TFs, it provides a multi-omics approach to understanding the mechanisms behind TF-mediated cell fate changes. Our iTF-seq study in mouse embryonic stem cells identified multiple TFs that trigger rapid transcriptome changes indicative of differentiation within a day of induction. Moreover, cells expressing these potent TFs often show a slower cell cycle and increased cell death. Further analysis using bioChIP-seq revealed that GCM1 and OTX2 act as pioneer factors and activators by increasing gene accessibility and activating the expression of lineage specification genes during cell fate conversion. iTF-seq has utility in both mapping cell fate conversion and understanding cell fate conversion mechanisms.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

Discovering mechanisms of human genetic variation and controlling cell states at scale

Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Rapid Generation of hPSC-Derived High Endothelial Venule Organoids with In Vivo Ectopic Lymphoid Tissue Capabilities

Bioengineering strategies for the fabrication of implantable lymphoid structures mimicking lymph nodes (LNs) and tertiary lymphoid structures (TLS) could amplify the adaptive immune response for therapeutic applications such as cancer immunotherapy. No method to date has resulted in the consistent formation of high endothelial venules (HEVs), which is the specialized vasculature responsible for naïve T cell recruitment and education in both LNs and TLS. Here orthogonal induced differentiation of human pluripotent stem cells carrying a regulatable ETV2 allele is used to rapidly and efficiently induce endothelial differentiation. Assembly of embryoid bodies combining primitive inducible endothelial cells and primary human LN fibroblastic reticular cells results in the formation of HEV-like structures that can aggregate into 3D organoids (HEVOs). Upon transplantation into immunodeficient mice, HEVOs successfully engraft and form lymphatic structures that recruit both antigen-presenting cells and adoptively-transferred lymphocytes, therefore displaying basic TLS capabilities. The results further show that functionally, HEVOs can organize an immune response and promote anti-tumor activity by adoptively-transferred T lymphocytes. Collectively, the experimental approaches represent an innovative and scalable proof-of-concept strategy for the fabrication of bioengineered TLS that can be deployed in vivo to enhance adaptive immune responses.

Sp1 facilitates continued HSV-1 gene expression in the absence of key viral transactivators

Productive replication of herpes simplex virus (HSV) relies upon a well-ordered transcriptional cascade flowing from immediate-early (IE) to early (E) to late (L) gene products. While several virus-encoded transcriptional activators are involved in this process, IE and E gene promoters also contain multiple binding sites for the ubiquitously expressed cellular transcription factor Sp1. Sp1 has been previously implicated in activating HSV-1 gene transcription downstream of these sites, but why Sp1-binding sites are maintained in the promoters of genes activated by virus-encoded activators remains unclear. We hypothesized that Sp1 enables continued HSV-1 transcription and replication when viral transactivators are limited. We used a depletion-based approach in human foreskin fibroblasts to investigate the specific contribution of Sp1 to the initiation and progression of the HSV-1 lytic gene cascade. We found that Sp1 increased viral transcript levels, protein expression, and replication following infection with VP16- or ICP0-deficient viruses but had little to no effect on rescued viruses or during wild-type (WT) HSV-1 infection. Moreover, Sp1 promoted WT virus transcription and replication following interferon treatment of fibroblasts and thus may contribute to viral immune evasion. Interestingly, we observed reduced expression of Sp1 and Sp1-family transcription factors in differentiated sensory neurons compared to undifferentiated cells, suggesting that reduced Sp1 levels may also contribute to HSV-1 latent infection. Overall, these findings indicate that Sp1 can promote HSV-1 gene expression in the absence of key viral transactivators; thus, HSV-1 may use Sp1 to maintain its gene expression and replication under adverse conditions.IMPORTANCEHerpes simplex virus (HSV) is a common human pathogen that actively replicates in the epithelia but can persist for the lifetime of the infected host via a stable, latent infection in neurons. A key feature of the HSV replication cycle is a complex transcriptional program in which virus and host-cell factors coordinate to regulate expression of the viral gene products necessary for continued viral replication. Multiple binding sites for the cellular transcription factor Sp1 are located in the promoters of HSV-1 genes, but how Sp1 binding contributes to transcription and replication of wild-type virus is not fully understood. In this study, we identified a specific role for Sp1 in maintaining HSV-1 gene transcription under adverse conditions, as when virus-encoded transcriptional activators were absent or limited. Preservation of Sp1-binding sites in HSV-1 gene promoters may thus benefit the virus as it navigates diverse cell types and host-cell conditions during infection.

Neuronal miR-9 promotes HSV-1 epigenetic silencing and latency by repressing Oct-1 and Onecut family genes

Herpes simplex virus 1 (HSV-1) latent infection entails repression of viral lytic genes in neurons. By functional screening using luciferase-expressing HSV-1, we identify ten neuron-specific microRNAs potentially repressing HSV-1 neuronal replication. Transfection of miR-9, the most active candidate from the screen, decreases HSV-1 replication and gene expression in Neuro-2a cells. Ectopic expression of miR-9 from lentivirus or recombinant HSV-1 suppresses HSV-1 replication in male primary mouse neurons in culture and mouse trigeminal ganglia in vivo, and reactivation from latency in the primary neurons. Target prediction and validation identify transcription factors Oct-1, a known co-activator of HSV transcription, and all three Onecut family members as miR-9 targets. Knockdown of ONECUT2 decreases HSV-1 yields in Neuro-2a cells. Overexpression of each ONECUT protein increases HSV-1 replication in Neuro-2a cells, human induced pluripotent stem cell-derived neurons, and primary mouse neurons, and accelerates reactivation from latency in the mouse neurons. Mutagenesis, ChIP-seq, RNA-seq, ChIP-qPCR and ATAC-seq results suggest that ONECUT2 can nonspecifically bind to viral genes via its CUT domain, globally stimulate viral gene transcription, reduce viral heterochromatin and enhance the accessibility of viral chromatin. Thus, neuronal miR-9 promotes viral epigenetic silencing and latency by targeting multiple host transcription factors important for lytic gene activation.

Canalizing cell fate by transcriptional repression

Precision in the establishment and maintenance of cellular identities is crucial for the development of multicellular organisms and requires tight regulation of gene expression. While extensive research has focused on understanding cell type-specific gene activation, the complex mechanisms underlying the transcriptional repression of alternative fates are not fully understood. Here, we provide an overview of the repressive mechanisms involved in cell fate regulation. We discuss the molecular machinery responsible for suppressing alternative fates and highlight the crucial role of sequence-specific transcription factors (TFs) in this process. Depletion of these TFs can result in unwanted gene expression and increased cellular plasticity. We suggest that these TFs recruit cell type-specific repressive complexes to their cis-regulatory elements, enabling them to modulate chromatin accessibility in a context-dependent manner. This modulation effectively suppresses master regulators of alternative fate programs and their downstream targets. The modularity and dynamic behavior of these repressive complexes enables a limited number of repressors to canalize and maintain major and minor cell fate decisions at different stages of development.

Rapid and high-purity differentiation of human medium spiny neurons reveals LMNB1 hypofunction and subtype necessity in modeling Huntington's disease

BACKGROUND

Different neural subtypes are selectively lost in diverse neurodegenerative diseases. Huntington's disease (HD) is an inherited neurodegenerative disease characterized by motor abnormalities that primarily affect the striatum. The Huntingtin (HTT) mutation involves an expanded CAG repeat, leading to insoluble polyQ, which renders GABA+ medium spiny neurons (MSN) more venerable to cell death. Human pluripotent stem cells (hPSCs) technology allows for the construction of disease-specific models, providing valuable cellular models for studying pathogenesis, drug screening, and high-throughput analysis.

METHODS

In this study, we established a method that allows for rapid and efficient generation of MSNs (> 90%) within 21 days from hPSC-derived neural progenitor cells, by introducing a specific combination of transcription factors.

RESULTS

We efficiently induced several neural subtypes, in parallel, based on the same cell source, and revealed that, compared to other neural subtypes, MSNs exhibited higher polyQ aggregation propensity and overexpression toxicity, more severe dysfunction in BDNF/TrkB signaling, greater susceptibility to BDNF withdrawal, and more severe disturbances in nucleocytoplasmic transport (NCT). We further found that the nuclear lamina protein LMNB1 was greatly reduced in HD neurons and mislocalized to the cytoplasm and axons. Knockdown of HTT or treatment with KPT335, an orally selective inhibitor of nuclear export (SINE), effectively attenuated the pathological phenotypes and alleviated neuronal death caused by BDNF withdrawal.

CONCLUSIONS

This study thus establishes an effective method for obtaining MSNs and underscores the necessity of using high-purity MSNs to study HD pathogenesis, especially the MSN-selective vulnerability.

Enhancing regenerative medicine: the crucial role of stem cell therapy

Stem cells offer new therapeutic avenues for the repair and replacement of damaged tissues and organs owing to their self-renewal and multipotent differentiation capabilities. In this paper, we conduct a systematic review of the characteristics of various types of stem cells and offer insights into their potential applications in both cellular and cell-free therapies. In addition, we provide a comprehensive summary of the technical routes of stem cell therapy and discuss in detail current challenges, including safety issues and differentiation control. Although some issues remain, stem cell therapy demonstrates excellent potential in the field of regenerative medicine and provides novel tactics and methodologies for managing a wider spectrum of illnesses and traumas.

Engineered stem cells by emerging biomedical stratagems

Stem cell therapy holds immense potential as a viable treatment for a widespread range of intractable disorders. As the safety of stem cell transplantation having been demonstrated in numerous clinical trials, various kinds of stem cells are currently utilized in medical applications. Despite the achievements, the therapeutic benefits of stem cells for diseases are limited, and the data of clinical researches are unstable. To optimize tthe effectiveness of stem cells, engineering approaches have been developed to enhance their inherent abilities and impart them with new functionalities, paving the way for the next generation of stem cell therapies. This review offers a detailed analysis of engineered stem cells, including their clinical applications and potential for future development. We begin by briefly introducing the recent advances in the production of stem cells (induced pluripotent stem cells (iPSCs), embryonic stem cells (ESCs), mesenchymal stem cells (MSCs) and hematopoietic stem cells (HSCs)). Furthermore, we present the latest developments of engineered strategies in stem cells, including engineered methods in molecular biology and biomaterial fields, and their application in biomedical research. Finally, we summarize the current obstacles and suggest future prospects for engineered stem cells in clinical translations and biomedical applications.

The Current Situation and Development Prospect of Whole-Genome Screening

High-throughput genetic screening is useful for discovering critical genes or gene sequences that trigger specific cell functions and/or phenotypes. Loss-of-function genetic screening is mainly achieved through RNA interference (RNAi), CRISPR knock-out (CRISPRko), and CRISPR interference (CRISPRi) technologies. Gain-of-function genetic screening mainly depends on the overexpression of a cDNA library and CRISPR activation (CRISPRa). Base editing can perform both gain- and loss-of-function genetic screening. This review discusses genetic screening techniques based on Cas9 nuclease, including Cas9-mediated genome knock-out and dCas9-based gene activation and interference. We compare these methods with previous genetic screening techniques based on RNAi and cDNA library overexpression and propose future prospects and applications for CRISPR screening.

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Single-cell technologies enable the dynamic analyses of cell fate mapping. However, capturing the gene regulatory relationships and identifying the driver factors that control cell fate decisions are still challenging. We present CEFCON, a network-based framework that first uses a graph neural network with attention mechanism to infer a cell-lineage-specific gene regulatory network (GRN) from single-cell RNA-sequencing data, and then models cell fate dynamics through network control theory to identify driver regulators and the associated gene modules, revealing their critical biological processes related to cell states. Extensive benchmarking tests consistently demonstrated the superiority of CEFCON in GRN construction, driver regulator identification, and gene module identification over baseline methods. When applied to the mouse hematopoietic stem cell differentiation data, CEFCON successfully identified driver regulators for three developmental lineages, which offered useful insights into their differentiation from a network control perspective. Overall, CEFCON provides a valuable tool for studying the underlying mechanisms of cell fate decisions from single-cell RNA-seq data.

Mechanisms and biotechnological applications of transcription factors

Transcription factors play an indispensable role in maintaining cellular viability and finely regulating complex internal metabolic networks. These crucial bioactive functions rely on their ability to respond to effectors and concurrently interact with binding sites. Recent advancements have brought innovative insights into the understanding of transcription factors. In this review, we comprehensively summarize the mechanisms by which transcription factors carry out their functions, along with calculation and experimental-based methods employed in their identification. Additionally, we highlight recent achievements in the application of transcription factors in various biotechnological fields, including cell engineering, human health, and biomanufacturing. Finally, the current limitations of research and provide prospects for future investigations are discussed. This review will provide enlightening theoretical guidance for transcription factors engineering.

Can we stop one heart from breaking: triumphs and challenges in cardiac reprogramming

Ischemic cardiac injury causes irreversible muscle loss and scarring, but recent years have seen dramatic advances in cardiac reprogramming, the field focused on regenerating cardiac muscle. With SARS-CoV2 increasing the age-adjusted cardiovascular disease mortality rate, it is worth evaluating the state of this field. Here, we summarize novel innovations in reprogramming strategies, insights into their mechanisms, and technologies for factor delivery. We also propose a broad model of reprogramming to suggest directions for future research. Poet Emily Dickinson wrote, "If I can stop one heart from breaking, I shall not live in vain." Today, researchers studying cardiac reprogramming view this line as a call to action to translate this revolutionary approach into life-saving treatments for patients with cardiovascular diseases.

Gene regulatory network inference in the era of single-cell multi-omics

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

Unbiased transcription factor CRISPR screen identifies ZNF800 as master repressor of enteroendocrine differentiation

Enteroendocrine cells (EECs) are hormone-producing cells residing in the epithelium of stomach, small intestine (SI), and colon. EECs regulate aspects of metabolic activity, including insulin levels, satiety, gastrointestinal secretion, and motility. The generation of different EEC lineages is not completely understood. In this work, we report a CRISPR knockout screen of the entire repertoire of transcription factors (TFs) in adult human SI organoids to identify dominant TFs controlling EEC differentiation. We discovered ZNF800 as a master repressor for endocrine lineage commitment, which particularly restricts enterochromaffin cell differentiation by directly controlling an endocrine TF network centered on PAX4. Thus, organoid models allow unbiased functional CRISPR screens for genes that program cell fate.

Human retinal ganglion cell neurons generated by synchronous BMP inhibition and transcription factor mediated reprogramming

In optic neuropathies, including glaucoma, retinal ganglion cells (RGCs) die. Cell transplantation and endogenous regeneration offer strategies for retinal repair, however, developmental programs required for this to succeed are incompletely understood. To address this, we explored cellular reprogramming with transcription factor (TF) regulators of RGC development which were integrated into human pluripotent stem cells (PSCs) as inducible gene cassettes. When the pioneer factor NEUROG2 was combined with RGC-expressed TFs (ATOH7, ISL1, and POU4F2) some conversion was observed and when pre-patterned by BMP inhibition, RGC-like induced neurons (RGC-iNs) were generated with high efficiency in just under a week. These exhibited transcriptional profiles that were reminiscent of RGCs and exhibited electrophysiological properties, including AMPA-mediated synaptic transmission. Additionally, we demonstrated that small molecule inhibitors of DLK/LZK and GCK-IV can block neuronal death in two pharmacological axon injury models. Combining developmental patterning with RGC-specific TFs thus provided valuable insight into strategies for cell replacement and neuroprotection.

Single-cell epigenome analysis identifies molecular events controlling direct conversion of human fibroblasts to pancreatic ductal-like cells

Cell fate can be reprogrammed by ectopic expression of lineage-specific transcription factors (TFs). However, the exact cell state transitions during transdifferentiation are still poorly understood. Here, we have generated pancreatic exocrine cells of ductal epithelial identity from human fibroblasts using a set of six TFs. We mapped the molecular determinants of lineage dynamics using a factor-indexing method based on single-nuclei multiome sequencing (FI-snMultiome-seq) that enables dissecting the role of each individual TF and pool of TFs in cell fate conversion. We show that transition from mesenchymal fibroblast identity to epithelial pancreatic exocrine fate involves two deterministic steps: an endodermal progenitor state defined by activation of HHEX with FOXA2 and SOX17 and a temporal GATA4 activation essential for the maintenance of pancreatic cell fate program. Collectively, our data suggest that transdifferentiation-although being considered a direct cell fate conversion method-occurs through transient progenitor states orchestrated by stepwise activation of distinct TFs.

Proteogenomics of different urothelial bladder cancer stages reveals distinct molecular features for papillary cancer and carcinoma in situ

The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.

Somatic mutation effects diffused over microRNA dysregulation

MOTIVATION

As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest disease and dictate prognosis. Previous studies that tried to correlate mutation with gene expression dysregulation neglected to adjust for the disparate multitudes of false positives associated with unequal sample sizes and uneven class balancing scenarios.

RESULTS

To properly address this issue, we developed a statistical framework to rigorously assess the extent of mutation impact on microRNAs in relation to a permutation-based null distribution of a matching sample structure. Carrying out the framework in a pan-cancer study, we ascertained 9008 protein-coding genes with statistically significant mutation impacts on miRNAs. Of these, the collective miRNA expression for 83 genes showed significant prognostic power in nine cancer types. For example, in lower-grade glioma, 10 genes' mutations broadly impacted miRNAs, all of which showed prognostic value with the corresponding miRNA expression. Our framework was further validated with functional analysis and augmented with rich features including the ability to analyze miRNA isoforms; aggregative prognostic analysis; advanced annotations such as mutation type, regulator alteration, somatic motif, and disease association; and instructive visualization such as mutation OncoPrint, Ideogram, and interactive mRNA-miRNA network.

AVAILABILITY AND IMPLEMENTATION

The data underlying this article are available in MutMix, at http://innovebioinfo.com/Database/TmiEx/MutMix.php.

Manipulating and studying gene function in human pluripotent stem cell models

Human pluripotent stem cells (hPSCs) are uniquely suited to study human development and disease and promise to revolutionize regenerative medicine. These applications rely on robust methods to manipulate gene function in hPSC models. This comprehensive review aims to both empower scientists approaching the field and update experienced stem cell biologists. We begin by highlighting challenges with manipulating gene expression in hPSCs and their differentiated derivatives, and relevant solutions (transfection, transduction, transposition, and genomic safe harbor editing). We then outline how to perform robust constitutive or inducible loss-, gain-, and change-of-function experiments in hPSCs models, both using historical methods (RNA interference, transgenesis, and homologous recombination) and modern programmable nucleases (particularly CRISPR/Cas9 and its derivatives, i.e., CRISPR interference, activation, base editing, and prime editing). We further describe extension of these approaches for arrayed or pooled functional studies, including emerging single-cell genomic methods, and the related design and analytical bioinformatic tools. Finally, we suggest some directions for future advancements in all of these areas. Mastering the combination of these transformative technologies will empower unprecedented advances in human biology and medicine.

Predicting transcriptional outcomes of novel multigene perturbations with GEARS

Understanding cellular responses to genetic perturbation is central to numerous biomedical applications, from identifying genetic interactions involved in cancer to developing methods for regenerative medicine. However, the combinatorial explosion in the number of possible multigene perturbations severely limits experimental interrogation. Here, we present graph-enhanced gene activation and repression simulator (GEARS), a method that integrates deep learning with a knowledge graph of gene-gene relationships to predict transcriptional responses to both single and multigene perturbations using single-cell RNA-sequencing data from perturbational screens. GEARS is able to predict outcomes of perturbing combinations consisting of genes that were never experimentally perturbed. GEARS exhibited 40% higher precision than existing approaches in predicting four distinct genetic interaction subtypes in a combinatorial perturbation screen and identified the strongest interactions twice as well as prior approaches. Overall, GEARS can predict phenotypically distinct effects of multigene perturbations and thus guide the design of perturbational experiments.

Transcriptomic reprogramming for neuronal age reversal

Aging is a progressive multifaceted functional decline of a biological system. Chronic age-related conditions such as neurodegenerative diseases are leading causes of death worldwide, and they are becoming a pressing problem for our society. To address this global challenge, there is a need for novel, safe, and effective rejuvenation therapies aimed at reversing age-related phenotypes and improving human health. With gene expression being a key determinant of cell identity and function, and in light of recent studies reporting rejuvenation effects through genetic perturbations, we propose an age reversal strategy focused on reprogramming the cell transcriptome to a youthful state. To this end, we suggest using transcriptomic data from primary human cells to predict rejuvenation targets and develop high-throughput aging assays, which can be used in large perturbation screens. We propose neural cells as particularly relevant targets for rejuvenation due to substantial impact of neurodegeneration on human frailty. Of all cell types in the brain, we argue that glutamatergic neurons, neuronal stem cells, and oligodendrocytes represent the most impactful and tractable targets. Lastly, we provide experimental designs for anti-aging reprogramming screens that will likely enable the development of neuronal age reversal therapies, which hold promise for dramatically improving human health.

Generating human neural diversity with a multiplexed morphogen screen in organoids

Morphogens choreograph the generation of remarkable cellular diversity in the developing nervous system. Differentiation of stem cells toward particular neural cell fates in vitro often relies upon combinatorial modulation of these signaling pathways. However, the lack of a systematic approach to understand morphogen-directed differentiation has precluded the generation of many neural cell populations, and knowledge of the general principles of regional specification remain in-complete. Here, we developed an arrayed screen of 14 morphogen modulators in human neural organoids cultured for over 70 days. Leveraging advances in multiplexed RNA sequencing technology and annotated single cell references of the human fetal brain we discovered that this screening approach generated considerable regional and cell type diversity across the neural axis. By deconvoluting morphogen-cell type relationships, we extracted design principles of brain region specification, including critical morphogen timing windows and combinatorics yielding an array of neurons with distinct neuro-transmitter identities. Tuning GABAergic neural subtype diversity unexpectedly led to the derivation of primate-specific interneurons. Taken together, this serves as a platform towards an in vitro morphogen atlas of human neural cell differentiation that will bring insights into human development, evolution, and disease.

Spinal Cord Organoids to Study Motor Neuron Development and Disease

Motor neuron diseases (MNDs) are a heterogeneous group of disorders that affect the cranial and/or spinal motor neurons (spMNs), spinal sensory neurons and the muscular system. Although they have been investigated for decades, we still lack a comprehensive understanding of the underlying molecular mechanisms; and therefore, efficacious therapies are scarce. Model organisms and relatively simple two-dimensional cell culture systems have been instrumental in our current knowledge of neuromuscular disease pathology; however, in the recent years, human 3D in vitro models have transformed the disease-modeling landscape. While cerebral organoids have been pursued the most, interest in spinal cord organoids (SCOs) is now also increasing. Pluripotent stem cell (PSC)-based protocols to generate SpC-like structures, sometimes including the adjacent mesoderm and derived skeletal muscle, are constantly being refined and applied to study early human neuromuscular development and disease. In this review, we outline the evolution of human PSC-derived models for generating spMN and recapitulating SpC development. We also discuss how these models have been applied to exploring the basis of human neurodevelopmental and neurodegenerative diseases. Finally, we provide an overview of the main challenges to overcome in order to generate more physiologically relevant human SpC models and propose some exciting new perspectives.

Transcription factor-mediated programming of stem cell fate

Direct activation of transcription factors (TFs) in human pluripotent stem cells (hPSCs) allows more rapid and efficient conversion of cell fates compared with classical approaches. Here, we summarize recent TF screening studies and established forward programming methods for different cell types, and highlight their current limitations and future perspectives.

Comparative single-cell analyses identify shared and divergent features of human and mouse kidney development

Mammalian kidneys maintain fluid homeostasis through the cellular activity of nephrons and the conjoined collecting system. Each epithelial network originates from distinct progenitor cell populations that reciprocally interact during development. To extend our understanding of human and mouse kidney development, we profiled chromatin organization (ATAC-seq) and gene expression (RNA-seq) in developing human and mouse kidneys. Data were analyzed at a species level and then integrated into a common, cross-species multimodal data set. Comparative analysis of cell types and developmental trajectories identified conserved and divergent features of chromatin organization and linked gene activity, revealing species- and cell-type specific regulatory programs. Identification of human-specific enhancer regions linked through GWAS studies to kidney disease highlights the potential of developmental modeling to provide clinical insight.

GATA3 mediates doxorubicin resistance by inhibiting CYB5R2-catalyzed iron reduction in breast cancer cells

AIMS

Neoadjuvant chemotherapy (NAC) is the primary preoperative therapy for breast cancer. The luminal subtype of breast cancer shows less NAC response than the basal subtype, with an inefficient NAC treatment effect. Understanding of the molecular and cellular mechanisms responsible for this chemoresistance is an important issue when determining optimal treatment.

METHODS

Doxorubicin-induced apoptosis and ferroptosis was investigated using cytotoxicity, western blotting, and flow cytometry assays. The role of GATA3 in modulating doxorubicin-induced cell death was investigated both in vitro and in vivo. RNA-seq, qPCR, ChIP, and luciferase assay and association analyses were performed to investigate the regulation of CYB5R2 by GATA3. The function of GATA3 and CYB5R2 in regulating doxorubicin-induced ferroptosis was evaluated with iron, ROS, and lipid peroxidation detection assays. Immunohistochemistry was performed for results validation.

RESULTS

Doxorubicin-induced basal breast cancer cell death is dependent on iron-mediated ferroptosis. Overexpression of the luminal signature transcriptional factor GATA3 mediates doxorubicin resistance. GATA3 promotes cell viability by decreasing ferroptosis-related gene CYB5R2 expression and by maintaining iron homeostasis. Analyzing data from the public and our cohorts demonstrates that GATA3 and CYB5R2 are associated with NAC response.

CONCLUSIONS

GATA3 promotes doxorubicin resistance by inhibiting CYB5R2-mediated iron metabolism and ferroptosis. Therefore, patients with breast cancer who display high GATA3 expression do not benefit from doxorubicin-based NAC regimens.

scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons

CRISPR activation (CRISPRa) is an important tool to perturb transcription, but its effectiveness varies between target genes. We employ human pluripotent stem cells with thousands of randomly integrated barcoded reporters to assess epigenetic features that influence CRISPRa efficacy. Basal expression levels are influenced by genomic context and dramatically change during differentiation to neurons. Gene activation by dCas9-VPR is successful in most genomic contexts, including developmentally repressed regions, and activation level is anti-correlated with basal gene expression, whereas dCas9-p300 is ineffective in stem cells. Certain chromatin states, such as bivalent chromatin, are particularly sensitive to dCas9-VPR, whereas constitutive heterochromatin is less responsive. We validate these rules at endogenous genes and show that activation of certain genes elicits a change in the stem cell transcriptome, sometimes showing features of differentiated cells. Our data provide rules to predict CRISPRa outcome and highlight its utility to screen for factors driving stem cell differentiation.

Microfat exerts an anti-fibrotic effect on human hypertrophic scar via fetuin-A/ETV4 axis

BACKGROUND

Hypertrophic scar is a fibrotic disease following wound healing and is characterized by excessive extracellular matrix deposition. Autologous microfat grafting proves an effective strategy for the treatment thereof as it could improve the texture of scars and relieve relevant symptoms. This study aims to explore the potential mechanisms underlying the anti-fibrotic effect of microfat on hypertrophic scars.

METHODS

In this study, we injected microfat into transplanted hypertrophic scars in mouse models and investigated the subsequent histological changes and differential expression of mRNAs therein. As for in vitro studies, we co-cultured microfat and hypertrophic scar fibroblasts (HSFs) and analyzed molecular profile changes in HSFs co-cultured with microfat by RNA sequencing. Moreover, to identify the key transcription factors (TFs) which might be responsible for the anti-fibrotic function of microfat, we screened the differentially expressed TFs and transfected HSFs with lentivirus to overexpress or knockdown certain differentially expressed TFs. Furthermore, comparative secretome analyses were conducted to investigate the proteins secreted by co-cultured microfat; changes in gene expression of HSFs were examined after the administration of the potential anti-fibrotic protein. Finally, the relationship between the key TF in HSFs and the microfat-secreted anti-fibrotic adipokine was analyzed.

RESULTS

The anti-fibrotic effect of microfat was confirmed by in vivo transplanted hypertrophic scar models, as the number of α-SMA-positive myofibroblasts was decreased and the expression of fibrosis-related genes downregulated. Co-cultured microfat suppressed the extracellular matrix production of HSFs in in vitro experiment, and the transcription factor ETV4 was primarily differentially expressed in HSFs when compared with normal skin fibroblasts. Overexpression of ETV4 significantly decreased the expression of fibrosis-related genes in HSFs at both mRNA and protein levels. Fetuin-A secreted by microfat could also downregulate the expression of fibrosis-related genes in HSFs, partially through upregulating ETV4 expression.

CONCLUSIONS

Our results demonstrated that transcription factor ETV4 is essential for the anti-fibrotic effect of microfat on hypertrophic scars, and that fetuin-A secreted by microfat could suppress the fibrotic characteristic of HSFs through upregulating ETV4 expression. Microfat wields an alleviative influence over hypertrophic scars via fetuin-A/ETV4 axis.

Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease

A major fraction of loci identified by genome-wide association studies (GWASs) lead to alterations in alternative splicing, but interpretation of how such alterations impact proteins is hindered by the technical limitations of short-read RNA-seq, which cannot directly link splicing events to full-length transcript or protein isoforms. Long-read RNA-seq represents a powerful tool to define and quantify transcript isoforms, and recently, infer protein isoform existence. Here we present a novel approach that integrates information from GWAS, splicing QTL (sQTL), and PacBio long-read RNA-seq in a disease-relevant model to infer the effects of sQTLs on the ultimate protein isoform products they encode. We demonstrate the utility of our approach using bone mineral density (BMD) GWAS data. We identified 1,863 sQTLs from the Genotype-Tissue Expression (GTEx) project in 732 protein-coding genes which colocalized with BMD associations (H 4 PP ≥ 0.75). We generated deep coverage PacBio long-read RNA-seq data (N=∼22 million full-length reads) on human osteoblasts, identifying 68,326 protein-coding isoforms, of which 17,375 (25%) were novel. By casting the colocalized sQTLs directly onto protein isoforms, we connected 809 sQTLs to 2,029 protein isoforms from 441 genes expressed in osteoblasts. Using these data, we created one of the first proteome-scale resources defining full-length isoforms impacted by colocalized sQTLs. Overall, we found that 74 sQTLs influenced isoforms likely impacted by nonsense mediated decay (NMD) and 190 that potentially resulted in the expression of new protein isoforms. Finally, we identified colocalizing sQTLs in TPM2 for splice junctions between two mutually exclusive exons, and two different transcript termination sites, making it impossible to interpret without long-read RNA-seq data. siRNA mediated knockdown in osteoblasts showed two TPM2 isoforms with opposing effects on mineralization. We expect our approach to be widely generalizable across diverse clinical traits and accelerate system-scale analyses of protein isoform activities modulated by GWAS loci.

Directed differentiation of human iPSCs to functional ovarian granulosa-like cells via transcription factor overexpression

An in vitro model of human ovarian follicles would greatly benefit the study of female reproduction. Ovarian development requires the combination of germ cells and several types of somatic cells. Among these, granulosa cells play a key role in follicle formation and support for oogenesis. Whereas efficient protocols exist for generating human primordial germ cell-like cells (hPGCLCs) from human induced pluripotent stem cells (hiPSCs), a method of generating granulosa cells has been elusive. Here, we report that simultaneous overexpression of two transcription factors (TFs) can direct the differentiation of hiPSCs to granulosa-like cells. We elucidate the regulatory effects of several granulosa-related TFs and establish that overexpression of NR5A1 and either RUNX1 or RUNX2 is sufficient to generate granulosa-like cells. Our granulosa-like cells have transcriptomes similar to human fetal ovarian cells and recapitulate key ovarian phenotypes including follicle formation and steroidogenesis. When aggregated with hPGCLCs, our cells form ovary-like organoids (ovaroids) and support hPGCLC development from the premigratory to the gonadal stage as measured by induction of DAZL expression. This model system will provide unique opportunities for studying human ovarian biology and may enable the development of therapies for female reproductive health.

Myelinating Glia: Potential Therapeutic Targets in Polyglutamine Spinocerebellar Ataxias

Human studies, in combination with animal and cellular models, support glial cells as both major contributors to neurodegenerative diseases and promising therapeutic targets. Among glial cells, oligodendrocytes and Schwann cells are the myelinating glial cells of the central and peripheral nervous system, respectively. In this review, we discuss the contributions of these central and peripheral myelinating glia to the pathomechanisms of polyglutamine (polyQ) spinocerebellar ataxia (SCA) types 1, 2, 3, 6, 7, and 17. First, we highlight the function of oligodendrocytes in healthy conditions and how they are disrupted in polyQ SCA patients and diseased model systems. We then cover the role of Schwann cells in peripheral nerve function and repair as well as their possible role in peripheral neuropathy in polyQ SCAs. Finally, we discuss potential polyQ SCA therapeutic interventions in myelinating glial.

Modeling Nonalcoholic Fatty Liver Disease in the Dish Using Human-Specific Platforms: Strategies and Limitations

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease affecting multiple cell types of the human liver. The high prevalence of NAFLD and the lack of approved therapies increase the demand for reliable models for the preclinical discovery of drug targets. In the last decade, multiple proof-of-principle studies have demonstrated human-specific NAFLD modeling in the dish. These systems have included technologies based on human induced pluripotent stem cell derivatives, liver tissue section cultures, intrahepatic cholangiocyte organoids, and liver-on-a-chip. These platforms differ in functional maturity, multicellularity, scalability, and spatial organization. Identifying an appropriate model for a specific NAFLD-related research question is challenging. Therefore, we review different platforms for their strengths and limitations in modeling NAFLD. To define the fidelity of the current human in vitro NAFLD models in depth, we define disease hallmarks within the NAFLD spectrum that range from steatosis to severe fibroinflammatory tissue injury. We discuss how the most common methods are efficacious in modeling genetic contributions and aspects of the early NAFLD-related tissue response. We also highlight the shortcoming of current models to recapitulate the complexity of inter-organ crosstalk and the chronic process of liver fibrosis-to-cirrhosis that usually takes decades in patients. Importantly, we provide methodological overviews and discuss implementation hurdles (eg, reproducibility or costs) to help choose the most appropriate NAFLD model for the individual research focus: hepatocyte injury, ductular reaction, cellular crosstalk, or other applications. In sum, we highlight current strategies and deficiencies to model NAFLD in the dish and propose a framework for the next generation of human-specific investigations.

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making

The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.

A transcription factor atlas of directed differentiation

Transcription factors (TFs) regulate gene programs, thereby controlling diverse cellular processes and cell states. To comprehensively understand TFs and the programs they control, we created a barcoded library of all annotated human TF splice isoforms (>3,500) and applied it to build a TF Atlas charting expression profiles of human embryonic stem cells (hESCs) overexpressing each TF at single-cell resolution. We mapped TF-induced expression profiles to reference cell types and validated candidate TFs for generation of diverse cell types, spanning all three germ layers and trophoblasts. Targeted screens with subsets of the library allowed us to create a tailored cellular disease model and integrate mRNA expression and chromatin accessibility data to identify downstream regulators. Finally, we characterized the effects of combinatorial TF overexpression by developing and validating a strategy for predicting combinations of TFs that produce target expression profiles matching reference cell types to accelerate cellular engineering efforts.

A Survey of Transcription Factors in Cell Fate Control

Transcription factors (TFs) play a cardinal role in the development and maintenance of human physiology by acting as mediators of gene expression and cell state control. Recent advancements have broadened our knowledge on the potency of TFs in governing cell physiology and have deepened our understanding of the mechanisms through which they exert this control. The ability of TFs to program cell fates has gathered significant interest in recent decades, and high-throughput technologies now allow for the systematic discovery of forward programming factors to convert pluripotent stem cells into numerous differentiated cell types. The next generation of these technologies has the potential to improve our understanding and control of cell fates and states and provide advanced therapeutic modalities to address many medical conditions.

Inducing Neural Regeneration from Glia Using Proneural bHLH Transcription Factors

Endogenous regeneration strategies to replace lost neurons hold great promise for treating neurodegenerative disorders. In the majority of cases, neural regeneration is induced by converting resident glial cells into neurogenic precursors. This review will outline how proneural bHLH transcription factors can be used to reprogram glia in the brain and retina into a source for new neurons.

Towards AI-driven longevity research: An overview

While in the past technology has mostly been utilized to store information about the structural configuration of proteins and molecules for research and medical purposes, Artificial Intelligence is nowadays able to learn from the existing data how to predict and model properties and interactions, revealing important knowledge about complex biological processes, such as aging. Modern technologies, moreover, can rely on a broader set of information, including those derived from the next-generation sequencing (e.g., proteomics, lipidomics, and other omics), to understand the interactions between human body and the external environment. This is especially relevant as external factors have been shown to have a key role in aging. As the field of computational systems biology keeps improving and new biomarkers of aging are being developed, artificial intelligence promises to become a major ally of aging research.

Deciphering Transcriptional Networks during Human Cardiac Development

Human heart development is governed by transcription factor (TF) networks controlling dynamic and temporal gene expression alterations. Therefore, to comprehensively characterize these transcriptional regulations, day-to-day transcriptomic profiles were generated throughout the directed cardiac differentiation, starting from three distinct human- induced pluripotent stem cell lines from healthy donors (32 days). We applied an expression-based correlation score to the chronological expression profiles of the TF genes, and clustered them into 12 sequential gene expression waves. We then identified a regulatory network of more than 23,000 activation and inhibition links between 216 TFs. Within this network, we observed previously unknown inferred transcriptional activations linking IRX3 and IRX5 TFs to three master cardiac TFs: GATA4, NKX2-5 and TBX5. Luciferase and co-immunoprecipitation assays demonstrated that these five TFs could (1) activate each other's expression; (2) interact physically as multiprotein complexes; and (3) together, finely regulate the expression of SCN5A, encoding the major cardiac sodium channel. Altogether, these results unveiled thousands of interactions between TFs, generating multiple robust hypotheses governing human cardiac development.

Reprogramming cell fates towards novel cancer immunotherapies

Recent advances in our understanding of host immune and cancer cells interactions have made immunotherapy a prominent choice in cancer treatment. Despite such promise, cell-based immunotherapies remain inapplicable to many patients due to severe limitations in the availability and quality of immune cells isolated from donors. Reprogramming technologies that facilitate the engineering of cell types of interest, are emerging as a putative solution to such challenges. Here we focus on the recent progress being made in reprogramming technologies with respect to the immune system and their potential for clinical applications.

SOX9 maintains human foetal lung tip progenitor state by enhancing WNT and RTK signalling

The balance between self-renewal and differentiation in human foetal lung epithelial progenitors controls the size and function of the adult organ. Moreover, progenitor cell gene regulation networks are employed by both regenerating and malignant lung cells, where modulators of their effects could potentially be of therapeutic value. Details of the molecular networks controlling human lung progenitor self-renewal remain unknown. We performed the first CRISPRi screen in primary human lung organoids to identify transcription factors controlling progenitor self-renewal. We show that SOX9 promotes proliferation of lung progenitors and inhibits precocious airway differentiation. Moreover, by identifying direct transcriptional targets using Targeted DamID, we place SOX9 at the centre of a transcriptional network, which amplifies WNT and RTK signalling to stabilise the progenitor cell state. In addition, the proof-of-principle CRISPRi screen and Targeted DamID tools establish a new workflow for using primary human organoids to elucidate detailed functional mechanisms underlying normal development and disease.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.