A computer-guided design tool to increase the efficiency of cellular conversions

Machine-guided cell-fate engineering

The creation of induced pluripotent stem cells (iPSCs) has enabled scientists to explore the function, mechanisms, and differentiation processes of many types of cells. One of the fastest and most efficient approaches is transcription factor (TF) over-expression. However, finding the right combination of TFs to over-express to differentiate iPSCs directly into other cell types is a difficult task. Here, we describe a machine-learning (ML) pipeline, called CellCartographer, that uses chromatin accessibility and transcriptomics data to design multiplex TF pooled-screening experiments for cell-type conversions that then may be iteratively refined. We validate this method by differentiating iPSCs into twelve cell types at low efficiency in preliminary screens and iteratively refine our TF combinations to achieve high-efficiency differentiation for six of these cell types in <6 days. Finally, we functionally characterize iPSC-derived cytotoxic T cells (iCytoTs), regulatory T cells (iTregs), type II astrocytes (iAstIIs), and hepatocytes (iHeps) to validate functionally accurate differentiation.

Computational methods for biofabrication in tissue engineering and regenerative medicine - a literature review

This literature review rigorously examines the growing scientific interest in computational methods for Tissue Engineering and Regenerative Medicine biofabrication, a leading-edge area in biomedical innovation, emphasizing the need for accurate, multi-stage, and multi-component biofabrication process models. The paper presents a comprehensive bibliometric and contextual analysis, followed by a literature review, to shed light on the vast potential of computational methods in this domain. It reveals that most existing methods focus on single biofabrication process stages and components, and there is a significant gap in approaches that utilize accurate models encompassing both biological and technological aspects. This analysis underscores the indispensable role of these methods in understanding and effectively manipulating complex biological systems and the necessity for developing computational methods that span multiple stages and components. The review concludes that such comprehensive computational methods are essential for developing innovative and efficient Tissue Engineering and Regenerative Medicine biofabrication solutions, driving forward advancements in this dynamic and evolving field.

HMGA1 stimulates cancer stem-like features and sensitivity to monensin in gastric cancer

Gastric cancer represents a serious health problem worldwide, with insufficient molecular biomarkers and therapeutic options. Consequently, several efforts have been directed towards finding specific disease markers in order to develop new therapies capable of defeating gastric cancer. Attention has been pointed to cancer stem cells (CSCs) as they are primarily responsible for tumor initiation and recurrence, making them essential therapeutic targets. Using the SORE6-GFP reporter system, based on the expression of SOX2 and/or OCT4 to drive GFP expression, we isolated gastric cancer stem-like cells (SORE6+ cells) enriched in several molecules, including SOX2, C-MYC, KLF4, HIF-1α, NOTCH1 and HMGA1. Here, we explored the previously undisclosed link of HMGA1 with gastric CSCs. Our results indicated that HMGA1 can activate a transcriptional program that includes SOX2, C-MYC, and KLF4 and endows cells with CSC features. We further showed that chemical induction of gastric CSCs using ciclopirox (CPX) can be mediated by HMGA1. Finally, we showed that HMGA1 GFP+ cells were sensitive to monensin confirming the selective activity of this drug over CSCs. Thus, HMGA1 is a key player in the cellular reprogramming of gastric non-CSCs to cancer stem-like cells.

Algorithms for Autonomous Formation of Multicellular Shapes from Single Cells

Multicellular organisms originate from a single cell, ultimately giving rise to mature organisms of heterogeneous cell type composition in complex structures. Recent work in the areas of stem cell biology and tissue engineering has laid major groundwork in the ability to convert certain types of cells into other types, but there has been limited progress in the ability to control the morphology of cellular masses as they grow. Contemporary approaches to this problem have included the use of artificial scaffolds, 3D bioprinting, and complex media formulations; however, there are no existing approaches to controlling this process purely through genetics and from a single-cell starting point. Here we describe a computer-aided design approach, called CellArchitect, for designing recombinase-based genetic circuits for controlling the formation of multicellular masses into arbitrary shapes in human cells.

Epigenome editing technologies for discovery and medicine

Epigenome editing has rapidly evolved in recent years, with diverse applications that include elucidating gene regulation mechanisms, annotating coding and noncoding genome functions and programming cell state and lineage specification. Importantly, given the ubiquitous role of epigenetics in complex phenotypes, epigenome editing has unique potential to impact a broad spectrum of diseases. By leveraging powerful DNA-targeting technologies, such as CRISPR, epigenome editing exploits the heritable and reversible mechanisms of epigenetics to alter gene expression without introducing DNA breaks, inducing DNA damage or relying on DNA repair pathways.

Human Blood Serum Counteracts EGFR/HER2-Targeted Drug Lapatinib Impact on Squamous Carcinoma SK-BR-3 Cell Growth and Gene Expression

Lapatinib is a targeted therapeutic inhibiting HER2 and EGFR proteins. It is used for the therapy of HER2-positive breast cancer, although not all the patients respond to it. Using human blood serum samples from 14 female donors (separately taken or combined), we found that human blood serum dramatically abolishes the lapatinib-mediated inhibition of growth of the human breast squamous carcinoma SK-BR-3 cell line. This antagonism between lapatinib and human serum was associated with cancelation of the drug induced G1/S cell cycle transition arrest. RNA sequencing revealed 308 differentially expressed genes in the presence of lapatinib. Remarkably, when combined with lapatinib, human blood serum showed the capacity of restoring both the rate of cell growth, and the expression of 96.1% of the genes expression of which were altered by the lapatinib treatment alone. Co-administration of EGF with lapatinib also restores the cell growth and cancels alteration of expression of 95.8% of the genes specific to lapatinib treatment of SK-BR-3 cells. Differential gene expression analysis also showed that in the presence of human serum or EGF, lapatinib was unable to inhibit the Toll-Like Receptor signaling pathway and alter expression of genes linked to the Gene Ontology term of Focal adhesion.

Logical design of synthetic cis-regulatory DNA for genetic tracing of cell identities and state changes

Descriptive data are rapidly expanding in biomedical research. Instead, functional validation methods with sufficient complexity remain underdeveloped. Transcriptional reporters allow experimental characterization and manipulation of developmental and disease cell states, but their design lacks flexibility. Here, we report logical design of synthetic cis-regulatory DNA (LSD), a computational framework leveraging phenotypic biomarkers and trans-regulatory networks as input to design reporters marking the activity of selected cellular states and pathways. LSD uses bulk or single-cell biomarkers and a reference genome or custom cis-regulatory DNA datasets with user-defined boundary regions. By benchmarking validated reporters, we integrate LSD with a computational ranking of phenotypic specificity of putative cis-regulatory DNA. Experimentally, LSD-designed reporters targeting a wide range of cell states are functional without minimal promoters. Applied to broadly expressed genes from human and mouse tissues, LSD generates functional housekeeper-like sLCRs compatible with size constraints of AAV vectors for gene therapy applications. A mesenchymal glioblastoma reporter designed by LSD outperforms previously validated ones and canonical cell surface markers. In genome-scale CRISPRa screens, LSD facilitates the discovery of known and novel bona fide cell-state drivers. Thus, LSD captures core principles of cis-regulation and is broadly applicable to studying complex cell states and mechanisms of transcriptional regulation.

DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion

MOTIVATION

Direct reprogramming (DR) is a process that directly converts somatic cells to target cells. Although DR via small molecules is safer than using transcription factors (TFs) in terms of avoidance of tumorigenic risk, the determination of DR-inducing small molecules is challenging.

RESULTS

Here we present a novel in silico method, DIRECTEUR, to predict small molecules that replace TFs for DR. We extracted DR-characteristic genes using transcriptome profiles of cells in which DR was induced by TFs, and performed a variant of simulated annealing to explore small molecule combinations with similar gene expression patterns with DR-inducing TFs. We applied DIRECTEUR to predicting combinations of small molecules that convert fibroblasts into neurons or cardiomyocytes, and were able to reproduce experimentally verified and functionally related molecules inducing the corresponding conversions. The proposed method is expected to be useful for practical applications in regenerative medicine.

AVAILABILITY AND IMPLEMENTATION

The code and data are available at the following link: https://github.com/HamanoLaboratory/DIRECTEUR.git.

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.

Programming human cell fate: overcoming challenges and unlocking potential through technological breakthroughs

In recent years, there have been notable advancements in the ability to programme human cell identity, enabling us to design and manipulate cell function in a Petri dish. However, current protocols for generating target cell types often lack efficiency and precision, resulting in engineered cells that do not fully replicate the desired identity or functional output. This applies to different methods of cell programming, which face similar challenges that hinder progress and delay the achievement of a more favourable outcome. However, recent technological and analytical breakthroughs have provided us with unprecedented opportunities to advance the way we programme cell fate. The Company of Biologists' 2023 workshop on 'Novel Technologies for Programming Human Cell Fate' brought together experts in human cell fate engineering and experts in single-cell genomics, manipulation and characterisation of cells on a single (sub)cellular level. Here, we summarise the main points that emerged during the workshop's themed discussions. Furthermore, we provide specific examples highlighting the current state of the field as well as its trajectory, offering insights into the potential outcomes resulting from the application of these breakthrough technologies in precisely engineering the identity and function of clinically valuable human cells.

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.

Stem cell-like memory T cells: Role in viral infections and autoimmunity

Stem cell-like memory T (T_SCM) cells possess stem cell properties including multipotency and self-renewal and are being recognized as emerging players in various human diseases. Advanced technologies such as multiparametric flowcytometry and single cell sequencing have enabled their identification and molecular characterization. In case of chronic viral diseases such as human immunodeficiency virus-1, CD4+ T_SCM cells, serve as major reservoirs of the latent virus. However, during immune activation and functional exhaustion of effector T cells, these cells also possess the potential to replenish the pool of functional effector cells to curtail the infection. More recently, these cells are speculated to play important role in protective immunity following acute viral infections such as coronavirus disease 2019 and might be amenable for therapeutics by ex vivo expansion. Similarly, studies are also investigating their pathological role in driving autoimmune responses. However, there are several gaps in the understanding of the role of T_SCM cells in viral and autoimmune diseases to make them potential therapeutic targets. In this minireview, we have attempted an updated compilation of the dyadic role of these complex T_SCM cells during such human diseases along with their biology and transcriptional programs.

Human Blood Serum Can Diminish EGFR-Targeted Inhibition of Squamous Carcinoma Cell Growth through Reactivation of MAPK and EGFR Pathways

Regardless of the presence or absence of specific diagnostic mutations, many cancer patients fail to respond to EGFR-targeted therapeutics, and a personalized approach is needed to identify putative (non)responders. We found previously that human peripheral blood and EGF can modulate the activities of EGFR-specific drugs on inhibiting clonogenity in model EGFR-positive A431 squamous carcinoma cells. Here, we report that human serum can dramatically abolish the cell growth rate inhibition by EGFR-specific drugs cetuximab and erlotinib. We show that this phenomenon is linked with derepression of drug-induced G1S cell cycle transition arrest. Furthermore, A431 cell growth inhibition by cetuximab, erlotinib, and EGF correlates with a decreased activity of ERK1/2 proteins. In turn, the EGF- and human serum-mediated rescue of drug-treated A431 cells restores ERK1/2 activity in functional tests. RNA sequencing revealed 1271 and 1566 differentially expressed genes (DEGs) in the presence of cetuximab and erlotinib, respectively. Erlotinib- and cetuximab-specific DEGs significantly overlapped. Interestingly, the expression of 100% and 75% of these DEGs restores to the no-drug level when EGF or a mixed human serum sample, respectively, is added along with cetuximab. In the case of erlotinib, EGF and human serum restore the expression of 39% and 83% of DEGs, respectively. We further assessed differential molecular pathway activation levels and propose that EGF/human serum-mediated A431 resistance to EGFR drugs can be largely explained by reactivation of the MAPK signaling cascade.

An Optogenetic-Controlled Cell Reprogramming System for Driving Cell Fate and Light-Responsive Chimeric Mice

Pluripotent stem cells (PSCs) hold great promise for cell-based therapies, disease modeling, and drug discovery. Classic somatic cell reprogramming to generate induced pluripotent stem cells (iPSCs) is often achieved based on overexpression of transcription factors (TFs). However, this process is limited by side effect of overexpressed TFs and unpredicted targeting of TFs. Pinpoint control over endogenous TFs expression can provide the ability to reprogram cell fate and tissue function. Here, a light-inducible cell reprogramming (LIRE) system is developed based on a photoreceptor protein cryptochrome system and clustered regularly interspaced short palindromic repeats/nuclease-deficient CRISPR-associated protein 9 for induced PSCs reprogramming. This system enables remote, non-invasive optogenetical regulation of endogenous Sox2 and Oct4 loci to reprogram mouse embryonic fibroblasts into iPSCs (iPSCLIRE ) under light-emitting diode-based illumination. iPSCLIRE cells can be efficiently differentiated into different cells by upregulating a corresponding TF. iPSCLIRE cells are used for blastocyst injection and optogenetic chimeric mice are successfully generated, which enables non-invasive control of user-defined endogenous genes in vivo, providing a valuable tool for facile and traceless controlled gene expression studies and genetic screens in mice. This LIRE system offers a remote, traceless, and non-invasive approach for cellular reprogramming and modeling of complex human diseases in basic biological research and regenerative medicine applications.

Human Blood Serum Inhibits Ductal Carcinoma Cells BT474 Growth and Modulates Effect of HER2 Inhibition

Trastuzumab, a HER2-targeted antibody, is widely used for targeted therapy of HER2-positive breast cancer (BC) patients; yet, not all of them respond to this treatment. We investigated here whether trastuzumab activity on the growth of HER2-overexpressing BT474 cells may interfere with human peripheral blood endogenous factors. Among 33 individual BC patient blood samples supplemented to the media, BT474 sensitivity to trastuzumab varied up to 14 times. In the absence of trastuzumab, human peripheral blood serum samples could inhibit growth of BT474, and this effect varied ~10 times for 50 individual samples. In turn, the epidermal growth factor (EGF) suppressed the trastuzumab effect on BT474 cell growth. Trastuzumab treatment increased the proportion of BT474 cells in the G0/G1 phases of cell cycle, while simultaneous addition of EGF decreased it, yet not to the control level. We used RNA sequencing profiling of gene expression to elucidate the molecular mechanisms involved in EGF- and human-sera-mediated attenuation of the trastuzumab effect on BT474 cell growth. Bioinformatic analysis of the molecular profiles suggested that trastuzumab acts similarly to the inhibition of PI3K/Akt/mTOR signaling axis, and the mechanism of EGF suppression of trastuzumab activity may be associated with parallel activation of PKC and transcriptional factors ETV1-ETV5.

Narrative engineering of the liver

Liver organoids are primary or pluripotent stem cell-derived three-dimensional structures that recapitulate regenerative or ontogenetic processes in vitro towards biomedical applications including disease modelling and diagnostics, drug safety and efficacy prediction, and therapeutic use. The cellular composition and structural organization of liver organoids may vary depending on the goal at hand, and the key challenge in general is to direct their development in a rational and controlled fashion for gaining targeted maturity, reproducibility, and scalability. Such endeavor begins with a detailed understanding of the biological processes in space and time behind hepatogenesis, followed by precise translation of these narrative processes through a bioengineering approach. Here, we discuss advancements in liver organoid technology through the lens of 'narrative engineering' in an attempt to synergize evolving understanding around molecular and cellular landscape governing hepatogenesis with engineering-inspired approaches for organoidgenesis.

Benchmarking of ATAC Sequencing Data From BGI's Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions

Background: Chromatin falls into one of two major subtypes: closed heterochromatin and euchromatin which is accessible, transcriptionally active, and occupied by transcription factors (TFs). The most widely used approach to interrogate differences in the chromatin state landscape is the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). While library generation is relatively inexpensive, sequencing depth requirements can make this assay cost-prohibitive for some laboratories. Findings: Here, we benchmark data from Beijing Genomics Institute's (BGI) DNBSEQ-G400 low-cost sequencer against data from a standard Illumina instrument (HiSeqX10). For comparisons, the same bulk ATAC-seq libraries generated from pluripotent stem cells (PSCs) and fibroblasts were sequenced on both platforms. Both instruments generate sequencing reads with comparable mapping rates and genomic context. However, DNBSEQ-G400 data contained a significantly higher number of small, sub-nucleosomal reads (>30% increase) and a reduced number of bi-nucleosomal reads (>75% decrease), which resulted in narrower peak bases and improved peak calling, enabling the identification of 4% more differentially accessible regions between PSCs and fibroblasts. The ability to identify master TFs that underpin the PSC state relative to fibroblasts (via HOMER, HINT-ATAC, TOBIAS), namely, foot-printing capacity, were highly similar between data generated on both platforms. Integrative analysis with transcriptional data equally enabled direct recovery of three published 3-factor combinations that have been shown to induce pluripotency. Conclusion: Other than a small increase in peak calling sensitivity for DNBSEQ-G400 data (BGI), both platforms enable comparable levels of open chromatin identification for ATAC-seq library sequencing, yielding similar analytical outcomes, albeit at low-data generation costs in the case of the BGI instrument.

Ranking reprogramming factors for cell differentiation

Transcription factor over-expression is a proven method for reprogramming cells to a desired cell type for regenerative medicine and therapeutic discovery. However, a general method for the identification of reprogramming factors to create an arbitrary cell type is an open problem. Here we examine the success rate of methods and data for differentiation by testing the ability of nine computational methods (CellNet, GarNet, EBseq, AME, DREME, HOMER, KMAC, diffTF and DeepAccess) to discover and rank candidate factors for eight target cell types with known reprogramming solutions. We compare methods that use gene expression, biological networks and chromatin accessibility data, and comprehensively test parameter and preprocessing of input data to optimize performance. We find the best factor identification methods can identify an average of 50-60% of reprogramming factors within the top ten candidates, and methods that use chromatin accessibility perform the best. Among the chromatin accessibility methods, complex methods DeepAccess and diffTF have higher correlation with the ranked significance of transcription factor candidates within reprogramming protocols for differentiation. We provide evidence that AME and diffTF are optimal methods for transcription factor recovery that will allow for systematic prioritization of transcription factor candidates to aid in the design of new reprogramming protocols.

NETISCE: a network-based tool for cell fate reprogramming

The search for effective therapeutic targets in fields like regenerative medicine and cancer research has generated interest in cell fate reprogramming. This cellular reprogramming paradigm can drive cells to a desired target state from any initial state. However, methods for identifying reprogramming targets remain limited for biological systems that lack large sets of experimental data or a dynamical characterization. We present NETISCE, a novel computational tool for identifying cell fate reprogramming targets in static networks. In combination with machine learning algorithms, NETISCE estimates the attractor landscape and predicts reprogramming targets using signal flow analysis and feedback vertex set control, respectively. Through validations in studies of cell fate reprogramming from developmental, stem cell, and cancer biology, we show that NETISCE can predict previously identified cell fate reprogramming targets and identify potentially novel combinations of targets. NETISCE extends cell fate reprogramming studies to larger-scale biological networks without the need for full model parameterization and can be implemented by experimental and computational biologists to identify parts of a biological system relevant to the desired reprogramming task.

An integrated pipeline for mammalian genetic screening

With the recent advancements in genome editing, next-generation sequencing (NGS), and scalable cloning techniques, scientists can now conduct genetic screens at unprecedented levels of scale and precision. With such a multitude of technologies, there is a need for a simple yet comprehensive pipeline to enable systematic mammalian genetic screening. In this study, we develop unique algorithms for target identification and a toxin-less Gateway cloning tool, termed MegaGate, for library cloning which, when combined with existing genetic perturbation methods and NGS-coupled readouts, enable versatile engineering of relevant mammalian cell lines. Our integrated pipeline for sequencing-based target ascertainment and modular perturbation screening (STAMPScreen) can thus be utilized for a host of cell state engineering applications.

Single-Cell Genomics: Catalyst for Cell Fate Engineering

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.

Direct reprogramming of somatic cells into induced hepatocytes: Cracking the Enigma code

There is an unmet need for functional primary human hepatocytes to support the pharmaceutical and (bio)medical demand. The unique discovery, a decade ago, that somatic cells can be drawn out of their apparent biological lockdown to reacquire a pluripotent state has revealed a completely new avenue of possibilities for generating surrogate human hepatocytes. Since then, the number of papers reporting the direct conversion of somatic cells into induced hepatocytes (iHeps) has burgeoned. A hepatic cell fate can be established via the ectopic expression of native liver-enriched transcription factors in somatic cells, thereby bypassing the need for an intermediate (pluripotent) stem cell state. That said, understanding and eventually controlling the processes that give rise to functional iHeps remains challenging. In this review, we provide an overview of the state-of-the-art reprogramming cocktails and techniques, as well as their corresponding conversion efficiencies. Special attention is paid to the role of liver-enriched transcription factors as hepatogenic reprogramming tools and small molecules as facilitators of hepatic transdifferentiation. To conclude, we formulate recommendations to optimise, standardise and enrich the in vitro production of iHeps to reach clinical standards, and propose minimal criteria for their characterisation.

Transcription Factor-Based Strategies to Generate Neural Cell Types from Human Pluripotent Stem Cells

In the last years, the use of pluripotent stem cells in studies of human biology has grown exponentially. These cells represent an infinite source for differentiation into several human cell types facilitating the investigation on biological processes, functionality of cells, or diseases mechanisms in relevant human models. In the neurobiology field, pluripotent stem cells have been extensively used to generate the main neuronal and glial cells of the brain. Traditionally, protocols following developmental cues have been applied to pluripotent stem cells to drive differentiation toward different cell lineages; however, these protocols give rise to populations with mixed identities. Interestingly, new protocols applying overexpression of lineage-specific transcription factors (TFs) have emerged and facilitated the generation of highly pure populations of specific subtypes of neurons and glial cells in an easy, reproducible, and rapid manner. In this study, we review protocols based on this strategy to generate excitatory, inhibitory, dopaminergic, and motor neurons as well as astrocytes, oligodendrocytes, and microglia. In addition, we will discuss the main applications for cells generated with these protocols, including disease modeling, drug screening, and mechanistic studies. Finally, we will discuss the advantages and disadvantages of TF-based protocols and present our view of the future in this field.