bims-gerecp 2026-06-07 papers

bims-gerecp

Biomed News

on Gene regulatory networks of epithelial cell plasticity

Issue of 2026–06–07
seventeen papers selected by
Xiao Qin, University of Oxford

Plasticity in Cancer Cells: The Master Engine of Therapeutic Resistance and Tumor Evolution.
Widespread transcriptional memory shapes heritable states and functional heterogeneity in cancer and stem cells.
Combinatorial transcription factor interactions drive modular gene regulatory networks.
Single-cell multi-omic atlas and morphogen screening informs midbrain and hindbrain organoid engineering.
Identifying fate-determining transcription factors with single-cell omics.
Single-cell mapping of regulatory DNA-protein interactions.
Clonal lineage tracing of innate immune cells in human cancer.
Echo characterizes the desynchronization of gene expression and chromatin accessibility during cell-state transitions.
PerturbPlan: An analytical framework for designing Perturb-seq experiments.
Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data.
Inflammatory Stromal Aging in Ulcerative Colitis and Colitis-Associated Cancer.
Massively parallel reporter assay-informed modeling improves prediction of context-specific enhancer-gene regulatory interactions.
'Virtual cells' aim to turn raw data into predictive models of biology.
Early-onset colorectal cancer: epidemiology, risk factors, and implications for clinical practice.
The Rising Burden of Early-Onset Cancer: Challenges and Opportunities.
Spatial omics of immunity: Mapping cellular landscapes in tissue microenvironments.
Discovering what is possible: How synthetic biology illuminates development.

Curr Mol Med. 2026 May 25.

Plasticity in Cancer Cells: The Master Engine of Therapeutic Resistance and Tumor Evolution.

Afza Ahmad.

  Cancer cell plasticity refers to the ability of cancer cells to change their phenotype and is one of the primary requirements for metastasis. It is considered one of the main contributors to intratumoral heterogeneity, a key factor in the development of cancer, and is known to alter responses and resistance to different forms of therapy. However, tumour cells are impaired in various cellular signalling pathways, such as mitogen-activated protein kinases, phosphoinositide-3-kinases, Wnt, Hedgehog, and Notch, as well as in epithelial-mesenchymal transition (EMT) and phenotypic plasticity. Cancer stem cells (CSCs) are considered an integral part of tumour plasticity, as they have the capacity to proliferate, differentiate, and initiate the growth of tumours. Recent studies suggest that targeting signals from the tumor microenvironment, plasticity-related pathways, and epigenetic regulators may offer promising therapeutic options to improve long-term response and reduce phenotypic dysregulation. This approach, which emphasizes plasticity as a primary biological driving force rather than a secondary one, allows cancer cells to change from an epithelial, mesenchymal, stem cell, or dormant state to a drug-resistant state in response to environmental stimuli. Taken together, these results suggest that cellular plasticity is important in tumour development and treatment failure. Therefore, targeting pathways associated with plasticity, modifying the tumour microenvironment, and using adaptive therapies may improve long-term tumour control.

Keywords:  Plasticity; cancer stem cells; signalling pathways; stemness; tumor evolution

DOI:  https://doi.org/10.2174/0115665240472692260521045539
Cell Syst. 2026 Jun 04. pii: S2405-4712(26)00103-1. [Epub ahead of print] 101621

Widespread transcriptional memory shapes heritable states and functional heterogeneity in cancer and stem cells.

Yongjie Lin, Xiangru Chen, Long Wu, Yutong Zhou, Yihan Lin.

  Recent studies show that non-genetic heterogeneity, particularly through heritable cell states, shapes cancer evolution and developmental trajectories. However, single-cell snapshots lack temporal information to identify these states. We employ lineage-resolved single-cell transcriptomics to map heritable cell states that persist across divisions, distinguishing them from transient fluctuations. We reveal that heritable states are underpinned by widespread transcriptional memory, whereby heritable gene expression defines two classes of states: clustered states, characterized by clustered gene expression, and latent states, marked by non-clustered gene expression. This memory shows partial conservation across cell types and conditions and appears to be maintained by robust epigenetic mechanisms that are resistant to environmental perturbations. Functionally, memory genes predict critical behaviors, including metastatic potential and lineage commitment, with latent-state genes often outperforming clustered-state genes. Our findings establish transcriptional memory as a potential basis for heritable cellular heterogeneity, providing a framework for understanding functional cellular variation across biological systems.

Keywords:  CORAL; cancer; cellular heterogeneity; heritable cell state; lineage tracing; memory genes; single-cell transcriptomics; stem cells; transcriptional memory

DOI:  https://doi.org/10.1016/j.cels.2026.101621
bioRxiv. 2026 May 21. pii: 2026.05.20.726505. [Epub ahead of print]

Combinatorial transcription factor interactions drive modular gene regulatory networks.

Jialei Duan, Boxun Li, Kartik Kulkarni, Gabriela Orquera-Tornakian, Daryl Barth, Lei Wang, Vrushali Pandit, Joel Liou, Nikhil V Munshi, Gary C Hon.

Transcription factors ( TFs ) cooperatively drive gene regulatory networks ( GRNs ) to establish transcriptional states. Forced induction of TFs in combination can reprogram cell state by supplanting existing GRNs. Thus, TFs and GRNs are the building blocks to engineering transcriptional state. However, one key challenge is that the relationship between TF combinations and GRNs remains largely uncharacterized and difficult to accurately predict. Here, we apply single-cell overexpression screens to map the combinatorial activities of ∼100 TFs to gene expression states. Our analysis identifies diverse TF combinations driving cell-type specific regulatory programs. Notably, different TF combinations induce shared gene sets with cell-type specific functions, suggesting a modular regulatory architecture of the transcriptome. Furthermore, we define pairwise TF interactions and show that cooperative interactions improve transcriptional reprogramming. Finally, we developed tools to predict combinatorial TF phenotypes. These findings improve our understanding of cell state and how to manipulate it for biomedical applications.
HIGHLIGHTS: Combinatorial over-expression screens for ∼100 transcription factors (TFs).Diverse TF combinations drive cell-type specific regulatory programs.TF regulatory networks reveal a modular regulatory architecture of the transcriptome.TF-TF interactions and predictive models enhance reprogramming cocktails.

DOI: https://doi.org/10.64898/2026.05.20.726505
Nat Neurosci. 2026 Jun 03.

Single-cell multi-omic atlas and morphogen screening informs midbrain and hindbrain organoid engineering.

Nadezhda Azbukina, Zhisong He, Hsiu-Chuan Lin, Malgorzata Santel, Bijan Kashanian, Ashley Maynard, Tivadar Török, Ryoko Okamoto, Marina T Nikolova, Makiko Seimiya, Sabina Kanton, Valentin Brösamle, Rene Holtackers, J Gray Camp, Barbara Treutlein.

Patterning of the neural tube establishes midbrain and hindbrain structures that coordinate motor movement, process sensory input and integrate cognitive functions. Cellular impairment within these structures underlies diverse neurological disorders, and in vitro organoid models promise inroads to understanding development and modeling disease. Here, we use paired single-cell transcriptome and accessible chromatin sequencing to map cell composition and regulatory mechanisms in organoid models of midbrain and hindbrain. We find that existing midbrain organoid protocols generate ventral and dorsal cell types, covering regions including floor plate, dorsal and ventral midbrain and adjacent hindbrain regions. Gene regulatory network inference and transcription factor perturbation resolve mechanisms underlying neuronal differentiation. A single-cell multiplexed patterning screen identifies morphogen concentrations that expand existing organoid models, including conditions generating medulla glycinergic neurons and cerebellum glutamatergic subtypes. Together, the multi-omic atlas and morphogen screen reveal morphogen-regulon relationships guiding region-specific progenitor differentiation towards diverse neuron types of the posterior brain.

DOI: https://doi.org/10.1038/s41593-026-02316-x
Trends Genet. 2026 Jun 04. pii: S0168-9525(26)00116-2. [Epub ahead of print]

Identifying fate-determining transcription factors with single-cell omics.

Xi Xi, Chen Li, Lei Wei, Xuegong Zhang.

  Single-cell sequencing enables the systematic discovery of cell fate-determining transcription factors (TFs), or key TFs, that define cellular identity or drive cell state transitions. A wide range of computational methods have been developed for this goal, but they differ substantially in the input data and the biological questions they address. In this article, we systematically review computational approaches for key TF identification and organize them from three perspectives: whether they identify TFs defining cell state identity or driving state transitions, whether transitions are modeled as discrete or continuous processes, and whether TFs act individually or combinatorially. We summarize key features and application scenarios of relevant methods to guide tool selection and discuss emerging trends in this field toward programmable and active control of cell fate.

Keywords:  cell identity; cell state transition; single-cell; transcription factors

DOI:  https://doi.org/10.1016/j.tig.2026.05.005
Cell. 2026 Jun 04. pii: S0092-8674(26)00573-8. [Epub ahead of print]

Single-cell mapping of regulatory DNA-protein interactions.

Wei-Yu Chi, Sang-Ho Yoon, Evrim Goksel, Levan Mekerishvili, Joe Pelt, Yiyun Lin, Tamara Prieto, John Zinno, Saravanan Ganesan, Catherine Potenski, Franco Izzo, Dan A Landau, Ivan Raimondi.

  Gene expression is controlled by transcription factors (TFs), whose genome binding is shaped by chromatin accessibility and histone modifications, yet mapping these interactions, particularly those with weak affinity or a transient nature, in single cells remains technically challenging. To address this gap, we developed docking and deamination followed by sequencing (D&D-seq), a single-cell immuno-tethering technology for profiling DNA-protein interactions. D&D-seq couples an antibody-binding nanobody to a cytosine base editor, a combination that enables detection of weak or transient factor binding through targeted cytosine-to-uracil editing at protein-bound genomic sites. This approach is compatible with standard single-cell multi-omic workflows and therefore allows integrated analyses of gene regulation. Using assay for transposase-accessible chromatin using sequencing (ATAC-seq) and single-cell ATAC-seq (scATAC-seq), we assessed chromatin accessibility as a functional readout of TF activity, and by coupling D&D-seq with whole-genome sequencing, we captured CTCF binding in both active and inactive chromatin compartments.

Keywords:  clonal hematopoiesis; epigenomics; gene regulation; single-cell; transcription factors

DOI:  https://doi.org/10.1016/j.cell.2026.05.014
Cancer Cell. 2026 Jun 04. pii: S1535-6108(26)00251-5. [Epub ahead of print]

Clonal lineage tracing of innate immune cells in human cancer.

Vincent Liu, Katalin Sandor, Patrick K Yan, Zhuang Miao, Yajie Yin, Robert R Stickels, Andy Y Chen, Kamir Hiam-Galvez, Jacob Gutierrez, Wenxi Zhang, Sairaj M Sajjath, Raeline Valbuena, Steven Wang, Bence Daniel, Leif S Ludwig, Brooke E Howitt, Caleb A Lareau, Ansuman T Satpathy.

  Innate immune cells constitute the majority of the tumor microenvironment (TME) and mediate anti-tumor immunity and immunotherapy responses. While single-cell T and B cell receptor sequencing have revealed insights into the clonal dynamics of adaptive immunity, the lack of analogous tools has precluded similar analysis of innate immune cells. Here, we describe a method leveraging somatic mitochondrial DNA (mtDNA) mutations to reconstruct clonal lineage relationships between cells in native human tissues. By jointly profiling single-cell chromatin accessibility and mtDNA variants, we resolve clonal dynamics of 218,715 cells from matched tumors, tissues, and blood from patients with lung and ovarian cancers. Clonal tracing reveals that TME-resident myeloid subsets, including macrophages and type 3 dendritic cells (DC3), are clonally related to circulating and tissue-infiltrating monocytes. We further identify distinct DC-biased and macrophage-biased clones, whose circulating monocyte precursors exhibit distinct epigenetic profiles, suggesting intratumoral myeloid differentiation fate may be peripherally programmed before TME infiltration.

Keywords:  fate bias; innate immunity; lineage tracing; single-cell multi-omics; tumor microenvironment

DOI:  https://doi.org/10.1016/j.ccell.2026.05.006
bioRxiv. 2026 May 22. pii: 2026.05.20.726634. [Epub ahead of print]

Echo characterizes the desynchronization of gene expression and chromatin accessibility during cell-state transitions.

Connor Finkbeiner, Dominik Otto, Manu Setty.

Cell-state transitions during differentiation and disease involve coordinated changes across gene expression and chromatin accessibility, but these modalities do not change in lockstep. For example, regulatory elements can be primed before their target genes are expressed or remain accessible after expression ceases. This desynchronization between changes in gene expression and chromatin accessibility can manifest at the level of cell states. Understanding the drivers of this desynchronization can give insights into the molecular mechanisms underlying cell-state progression. Here we introduce Echo, a statistical framework that identifies desynchronized cell states and the associated genes and regulatory elements from paired single-cell RNA and ATAC data. Echo States estimates cell-state density independently for each modality and compares them to determine which states are better resolved in RNA or ATAC. Echo Features then predicts feature values over each state space to identify the genes, regulatory loci, and transcription-factor motifs driving this desynchronization. Applying Echo to the developing human fetal retina, we find that desynchronization is pervasive across every major cell population. Expression of cell-cycle genes resolves multipotent progenitors in gene expression but not chromatin accessibility, while fate priming resolves cycling neurogenic precursors in chromatin accessibility before gene expression. By combining desynchronized states and features along the cone trajectory, we reconstructed the regulatory logic of cone fate specification from multipotent progenitors, revealing a tight coupling between multipotency exit, cell cycle and lineage specification. Applying Echo to human hematopoiesis, we identified that the balance between stem-cell quiescence and differentiation is resolved more strongly in chromatin accessibility than in gene expression. Our results establish desynchronization as a pervasive, structured feature of differentiating systems, and Echo as a framework for characterizing the interplay between gene expression and chromatin accessibility during cell-state transitions.

DOI: https://doi.org/10.64898/2026.05.20.726634
bioRxiv. 2026 May 23. pii: 2026.05.22.727199. [Epub ahead of print]

PerturbPlan: An analytical framework for designing Perturb-seq experiments.

Ziang Niu, Yihui He, James Galante, Andreas R Gschwind, Judhajeet Ray, Lars M Steinmetz, Jesse M Engreitz, Eugene Katsevich.

CRISPR screens with single-cell RNA-seq readouts provide a powerful tool for characterizing the functions of noncoding elements and genes. However, designing these experiments to balance statistical power and cost is challenging, given the large number of design parameters. The only available tool for this purpose is a simulation-based power calculator, but it is computationally costly and requires high-performance computing to run. We derive a novel analytical formula for the power to detect perturbation-expression associations, recapitulating power estimates from the simulation-based tool while reducing runtime by up to seven orders of magnitude. This acceleration unlocks the possibility of interactive single-cell CRISPR screen design. Accordingly, we develop PerturbPlan, an interactive web application built on the analytical power formula. PerturbPlan helps users address 11 design questions for two types of single-cell CRISPR screens, Perturb-seq and targeted Perturb-seq (TAP-seq). We apply PerturbPlan to carry out a comparative analysis of three recent Perturb-seq designs, demonstrating how optimal design varies across experiments of different scales. We also use PerturbPlan to quantify the cost savings of a recent TAP-seq study relative to a hypothetical Perturb-seq study assaying the same perturbations, illustrating how the tool can inform decisions about targeted versus whole-transcriptome readouts. In sum, PerturbPlan is the first tool to facilitate flexible and interactive design of well-powered single-cell CRISPR screen experiments.

DOI: https://doi.org/10.64898/2026.05.22.727199
Nat Commun. 2026 Jun 04.

Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data.

Ishita Debnath, Zhana Duren.

Integrating spatial transcriptomics, which maps gene expression location within tissues, with single-cell multi-omics data, profiling gene expression and chromatin accessibility (or other epigenomic data) for the same cell, offers powerful insights into gene regulation. However, commercially available kits for simultaneous spatial multi-omics profiling are currently unavailable, hindering widespread data generation. Here, we present ISON (Integrated Spatial Omics Network), a unified computational method for integrative spatial multi-omics analysis from single cell multiome data and spatial transcriptomics data. ISON accurately predicts chromatin accessibility profiles for spatial spots and reconstructs spatially resolved gene regulatory networks, demonstrating scalability in both time and memory. Importantly, ISON's chromatin accessibility prediction captures patterns consistent with cis- and trans- regulatory information and enables estimation of transcription factor (TF) activity at the spot level, distinguishing between TFs even within the same family, which is unique and is not present in approaches relying solely on chromatin accessibility data. The application of ISON to Alzheimer's disease data reveals disease- and age-specific spatially variable gene regulatory modules, highlighting its potential to uncover spatially organized mechanisms driving complex biological processes.

DOI: https://doi.org/10.1038/s41467-026-73948-7
bioRxiv. 2026 May 20. pii: 2026.05.18.725891. [Epub ahead of print]

Inflammatory Stromal Aging in Ulcerative Colitis and Colitis-Associated Cancer.

Khalil Almotah, Uyen Tran, Haylee Gilbert, R Allen Schweickart, Robert C Fisher, Yaroslav Bisikalo, Manal Ali, Munir Buhaya, Mingyuan Cheng, Michael Cruise, Zhikai Chi, Samaneh Kamali Sarvestani, Emina H Huang, Oliver Wessely.

Ulcerative colitis is a chronic inflammatory bowel disease that can progress from dysplasia to cancer. Inflammatory responses are critical drivers in this process, typically triggered by epithelial lesions and the ensuing infiltration of microbiota into the interstitial layer. Here, we focus on the pro-inflammatory state of the interstitial fibroblasts, which promotes immune infiltration and augments disease progression. The study aims to provide a mechanistic link how fibroblasts of the colitis-associated microenvironment integrate inflammatory signals, microbial infiltration and cellular memory. To this end, we investigated a large number of primary colon fibroblasts obtained from normal, colitis and colon cancer samples using a range of in vitro approaches and an in vivo co-inoculation cancer model. mRNA sequencing analysis identified that the disease-associated fibroblasts are exhibit a cellular inflammatory status, which involves the injury-induced senescence pathway. Using CXCL8, a potent chemokine upregulated in colitis and cancer colon fibroblasts, as a paradigm, this inflammatory status is triggered by the activation of the NFκB signaling via immune-derived cytokines (TNFα, IL-1β), bacterial signals (LPS) and the microbiome itself using mycoplasma as a paradigm. Finally, iPSC reprogramming studies indicate that fibroblasts from ulcerative colitis retain an epigenetic memory that sustains elevated CXCL8 expression. Together, our findings demonstrate that the senescence associated secretory phenotype of colon fibroblasts is a robust indicator for inflammation-driven colon tumorigenesis.

DOI: https://doi.org/10.64898/2026.05.18.725891
Nucleic Acids Res. 2026 May 20. pii: gkag554. [Epub ahead of print]54(10):

Massively parallel reporter assay-informed modeling improves prediction of context-specific enhancer-gene regulatory interactions.

William DeGroat, Anat Kreimer.

Enhancers are cis-regulatory elements that drive context-specific gene expression, yet their target genes and modes of action remain largely unresolved. Because most disease-associated variants lie in non-coding regulatory DNA, accurate, cell type-specific enhancer-gene (E-G) mapping is essential for understanding genetic risk. However, current E-G prediction frameworks lack the resolution to capture such context-specific interactions. Massively parallel reporter assays (MPRAs) provide measurements of cis-regulatory activity, but their integration into genome-scale E-G models has been limited. Here, we introduce MPRabc, an MPRA-informed model that improves E-G interaction prediction. MPRabc integrates predicted MPRA activity, sequence-derived regulatory features, epigenomic signals, and three-dimensional chromatin contact maps with clustered regularly interspaced short palindromic repeats-based perturbation training data. Benchmarking against validated regulatory interactions shows that MPRabc outperforms state-of-the-art models. We generated high-resolution E-G networks for K562, HepG2, and human induced pluripotent stem cell (hiPSC) cell lines and applied a graph-based framework to identify regulatory architecture, map trait-associated variants and expression quantitative trait loci, and resolve transcription factor drivers of enhancer activity. Across contexts, we accurately recovered lineage-defining regulatory programs, including GATA1::TAL1 in K562, HNF1A/B in HepG2, and POU factor circuits in hiPSCs. Together, these results establish MPRA-informed modeling as a scalable strategy for decoding enhancer function and linking non-coding variants to gene regulatory mechanisms across cellular contexts.

DOI: https://doi.org/10.1093/nar/gkag554
Nature. 2026 Jun;654(8117): 286-288

'Virtual cells' aim to turn raw data into predictive models of biology.

Michael Eisenstein.



Keywords:  Machine learning; Systems biology; Technology; Transcriptomics

DOI:  https://doi.org/10.1038/d41586-026-01731-1
Clin Transl Oncol. 2026 Jun 04.

Early-onset colorectal cancer: epidemiology, risk factors, and implications for clinical practice.

Antonio Vitiello, Andrea Zovi.

  The incidence of colorectal cancer (CRC) in individuals under 50 years of age has increased steadily over the past two decades in several high-income countries, contrasting with declining rates in older populations following the implementation of screening programmes. This epidemiological shift represents an emerging challenge for clinical practice and public health systems. This clinical review aims to summarise current epidemiological evidence, risk factors, and biological characteristics of early-onset colorectal cancer, and to examine its implications for screening strategies and health policy. Although hereditary cancer syndromes account for a minority of cases, most earlyonset CRCs occur in individuals without a recognised genetic predisposition. Identified risk factors include obesity, unhealthy dietary patterns, physical inactivity, microbiome alterations, and early-life environmental exposures. Diagnostic delays are common, as symptoms such as rectal bleeding or changes in bowel habits are frequently attributed to benign conditions in younger adults, leading to presentation at more advanced stages. Growing epidemiological data and modelling studies support lowering the age of average-risk screening initiation to 45 years, a strategy already adopted in several countries. However, implementation requires careful consideration of healthcare capacity, cost-effectiveness, and equitable access. Early-onset colorectal cancer represents a significant and evolving public health concern. Enhanced clinical vigilance in symptomatic young adults, together with evidence-based adjustments to screening policies, will be essential to mitigate the increasing burden of disease in this population.

Keywords:  Cancer; Epidemiology; Mortality; Risk factors

DOI:  https://doi.org/10.1007/s12094-026-04382-w
Cancer Discov. 2026 Jun 01. 16(6): 1050-1054

The Rising Burden of Early-Onset Cancer: Challenges and Opportunities.

Andrea Cercek, Daniel J Zabransky, Gianluca Mauri, Elizabeth M Jaffee, Alberto Bardelli, Timothy R Rebbeck.

Early-onset cancers are increasing globally, yet traditional research frameworks have yet to inform the epidemiologic and biological underpinnings of this trend. This perspective summarizes the current state of knowledge and prospects for a research agenda spanning epidemiology, exposure science, mechanistic studies, and federated infrastructures to address this emerging challenge.

DOI: https://doi.org/10.1158/2159-8290.CD-26-0328
Curr Opin Immunol. 2026 Jun 02. pii: S0952-7915(26)00067-1. [Epub ahead of print]101 102790

Spatial omics of immunity: Mapping cellular landscapes in tissue microenvironments.

Ji-Eun See, Yuitian Liu, Jasmine Plummer.

The tumor microenvironment (TME) is composed of diverse heterogeneous components and plays a crucial role in immune cell infiltration, immune evasion, and dynamic interactions between tumor cells and the immune system. A precise understanding of the TME is essential for tissue immunology research and the development of effective immunotherapies. Technologies that spatially dissect the TME and analyze it at the molecular level are increasingly important. Recently, cutting-edge, high-resolution, high-multiplex molecular profiling technologies capable of high-throughput RNA and protein profiling while incorporating spatial information have been rapidly developing. This review describes a variety of cutting-edge spatial transcriptomics and proteomics technologies, including sequencing-based spatial transcriptomics, multiplex in situ hybridization imaging-based spatial proteomics, and multiomics, which are particularly useful for tissue immunology research. Technological advances in computational tools are discussed, as well as how researchers have interpreted visualized data using our own results as examples. These technologies enable simultaneous analysis of the diverse types and functional states of immune cells in cancer tissues within the tissue architecture, providing a crucial foundation for understanding immune cell organization, function, and cell-to-cell interactions of tissue immune responses. Current spatial molecular profiling technologies still face technological limitations in resolution and analytical complexity. The lack of data standardization across diverse platforms and experimental conditions remains a significant issue, hindering the reproducibility and comparability of research results. To overcome these limitations, multiomics integrated research combining spatial transcriptomics, proteomics, and genomics data is expected to become more active in the future, which will enable a more multidimensional understanding of the TME and tissue immune environment. The introduction of artificial intelligence and machine learning technologies is expected to enable more precise interpretation of the functional status and interactions of immune cells within organizations, ultimately contributing to the development of next-generation immunotherapies.

DOI: https://doi.org/10.1016/j.coi.2026.102790
Cell Syst. 2026 Jun 04. pii: S2405-4712(26)00101-8. [Epub ahead of print] 101619

Discovering what is possible: How synthetic biology illuminates development.

Nicholas T Hutchins, Alexandra Cao, Pulin Li.

  Developmental biology seeks to understand how multicellular organization emerges from cell-cell interactions. Advances in stem cell and synthetic biology now enable researchers to rebuild developmental processes outside the embryo, with varying degrees of resemblance to natural systems. While some reconstituted systems reveal how development occurs, others uncover what is possible. This perspective examines how such bottom-up approaches have elucidated general principles and causal mechanisms of multicellular organization. We argue that synthetic systems, though simplified, provide powerful platforms to test the limits of developmental potential, disentangle causal relationships, and inform predictive models. With rapid advances in genomic engineering, imaging, and computational modeling, leveraging these engineered systems to discover what is possible holds transformative promise for understanding what is happening in nature.

Keywords:  bottom-up reconstitution; cell sorting; morphogen gradient; synthetic cell state; synthetic development

DOI:  https://doi.org/10.1016/j.cels.2026.101619