BMC Methods

To properly respond to their environment, cells adjust the activity of key regulatory proteins and rates of gene expression. Methods to detect and quantify these forms of regulatory dynamics in living cells are of central importance for understanding cellular signaling events in both physiological and pathological conditions. Current technologies in this field make use of fluorescent probes to track cell signaling dynamics. Although these technologies have been used for decades, challenges remain. In particular, the segmentation, tracking, and interpretation of single cell dynamic data are time-consuming, prone to subjective errors, and often lacking in standardization across experiments. Here, we present SPIFEE, a data pipeline that uses experiment-dependent parameters to smooth noise and quantify key features of fluorescence data from time-lapse imaging studies. Processing data in this manner enhances and accelerates quantification of live-cell gene and protein expression, simplifies data analysis, and facilitates hypothesis generation. Author SummaryCells adjust protein activity and gene expression levels over time to respond to changes in their environment, a process referred to as cell signaling dynamics. Quantifying cell signaling dynamics in living cells often uses fluorescent probes, such as green fluorescent protein (GFP) and its spectral variants, to track changes in gene expression or protein activity over time. Challenges inherent in analyzing fluorescence data from single cells stem from biological and experimental noise, time-consuming quantification, and subjective errors. To address these challenges, we developed a computational tool called Signal Processing and Integrated Feature Extraction (SPIFEE). The pipeline improves the quality of fluorescence data analysis by reducing noise and extracting signal features in a way that is both intuitive and objective. The pipeline provides more accurate, rapid, and unbiased quantification of time-lapse microscopy data.

Stimulated emission depletion (STED) microscopy is a super-resolution fluorescence imaging technique that achieves high spatial and temporal resolution by exploiting stimulated emission to induce fluorescence depletion (FD) and is expected to have substantial utility for imaging applications using fluorescent proteins. However, the compatibility of fluorescent proteins with STED microscopy systems has been understood primarily through empirical observations, and there is no established methodology for the rational selection of fluorescent proteins for STED microscopy. In this study, we systematically evaluated the compatibility of commonly used fluorescent proteins with STED microscopy systems by measuring FD properties using transient absorption spectroscopy and fluorescence dip spectroscopy, both of which are classified as two-color spectroscopy (TCS). Fluorescent proteins identified as compatible with the STED microscopy system based on the TCS measurements were employed for three-dimensional STED imaging of cellular samples expressing each protein. In all samples, three-dimensional spatial resolution was improved relative to confocal laser microscopy, with particularly marked improvements in z-axis resolution. These findings demonstrate that measurements of FD properties via TCS provide a robust approach for evaluating the compatibility of fluorescent proteins with the STED microscopy system and for selecting suitable fluorescent proteins for STED imaging.

Automated analysis of murine bronchoalveolar lavage fluid (BALF) cytology is important for preclinical respiratory research, yet progress has been limited by the lack of publicly available, well-annotated mouse BALF image datasets. We present MurineCyto-Det, a high-resolution murine BALF cytology dataset comprising 333 image tiles of size 1024x1024 pixels, annotated across five cytological categories with both pixel-level segmentation masks and one-to-one matched bounding boxes. The dataset contains 14,551 annotated cell instances and supports two complementary analysis tasks: morphology-oriented cell segmentation and object-level cell detection. To establish reproducible benchmark baselines, we evaluated representative segmentation and detection models. The results demonstrate the practical utility of MurineCyto-Det while highlighting realistic challenges arising from class imbalance, small object size, irregular cell morphology, and ambiguous debris-like structures. MurineCyto-Det provides a standardized resource for developing, evaluating, and comparing automated methods for murine BALF cytology analysis. The dataset is publicly available at https://doi.org/10.5281/zenodo.17608677.

Understanding skeletal muscle metabolism involves real-time monitoring of key cellular parameters, such as calcium ions (Ca2+), adenosine triphosphate (ATP), cyclic adenosine monophosphate (cAMP), and intracellular temperature. Fluorescent protein (FP)-based biosensors are used for live-cell imaging of these signals with high spatiotemporal resolution. Differentiated myotubes are in vitro models used for physiological muscle metabolism research. However, efficient transfection of FP-based biosensors into these cells is challenging. Here, we developed an electroporation-based strategy for delivering recombinant protein biosensors into fully differentiated myotubes. Biosensors for Ca2+, ATP, cAMP, and temperature were recombinantly produced using Escherichia coli and introduced into myotubes using electroporation. Electroporation conditions were optimised to maximise delivery efficiency, preserve cell viability, and minimise cellular damage. We established a robust intracellular delivery system that effectively demonstrated Ca2+, ATP, and temperature dynamics. Furthermore, we achieved the successful co-delivery of two biosensors that enabled dual imaging of Ca2+ and cAMP in response to stimulation.

Altair-dvOPM is an open-access direct-view oblique plane microscope designed for large-field, three-dimensional imaging of cleared and expanded tissue sections. By combining photographic-lens-based detection, externally launched oblique illumination and precision-registered modular baseplates, the system achieves micrometer-scale lateral resolution over a ~5.4 mm field of view without custom objectives or highly specialized alignment procedures. We demonstrate imaging across scales, from subcellular structures in expanded cells to centimeter-scale expanded tissue sections, and provide documentation, CAD files, Zemax models and open-source control software to support replication and extension.

High-resolution microscopy techniques are used across research and industry to analyse biological systems, from biomolecules to subcellular organelles, multicellular models and tissues. As multimodal imaging workflows and quantitative analysis of bioimaging data become increasingly widespread, there is a growing need for materials and methods to calibrate imaging systems and evaluate the fidelity of generated image data. Here, we present three-dimensional microscopy phantoms fabricated using two-photon photolithography from transparent resins that exhibit both broadband visible autofluorescence and Raman scattering across the fingerprint and C-H stretching regions. Suitable for analysis using optical profilometry, the phantoms were dimensionally calibrated with SI traceability using a metrological confocal microscope. Immersible in air and common aqueous imaging media, the phantoms are compatible with a wide variety of optical microscopy techniques, including one and two-photon excited fluorescence and coherent Raman scattering microscopy. We employed a forked wedge design to validate image deconvolution results and a stacked lattice phantom to recover image distortion matrices under realistic biological imaging conditions. We demonstrate the impact of correcting chromatic offsets and axial scaling errors for a representative application: analysis of a cell seeded scaffold using confocal laser scanning fluorescence microscopy. These phantoms provide a versatile platform for calibration, quality control and validation of multimodal imaging pipelines and improved quantitative optical microscopy.

Fresh produce encounters pathogens at various stages of production and supply, with the harvesting process serving as one of these stages. To evaluate contamination associated with harvesting, we systematically swabbed zone 1 harvester surfaces and quantified Bacteroidales as a fecal biomarker using quantitative polymerase chain reaction (qPCR). Baseline contamination was dominated by non-detects, with occasional low-level detections (<25 copies/cm2) near the assay limit of detection (LoD). Detection occurred more frequently post-harvest (overall [~]4% pre-harvest and 10% post-harvest), while microbial loads remained low, indicating that harvesting primarily affected the likelihood of low-level contamination rather than increasing contamination abundance. Additionally, we developed and field-deployed a portable loop- mediated isothermal amplification (LAMP) assay for rapid harvester hygiene assessment and benchmarked its field performance against qPCR. Together, these results support a practical molecular tool for monitoring fecal contamination and informing cleaning and sanitization decisions.

Following ER Ca2+ depletion, Ca2+ release-activated Ca2+ (CRAC) channels are activated by STIM1 at ER-plasma membrane junctions. The restricted localization and low conductance of the CRAC channel (<40 fS) precludes single-channel recordings, limiting studies of CRAC channel gating. Here we describe an optical approach to characterize the gating of HaloTag-fused Orai1 channels labeled with JF646-BAPTA, a Ca2+-sensitive fluorescent dye. While Ca2+ influx through single channels generates fluorescence fluctuations, identifying true gating events is complicated by stochastic transitions of JF646-BAPTA to a non-fluorescent state. To overcome this, we combine TIRF microscopy with whole-cell voltage clamp to control the driving force for Ca2+ entry. We show the open channel intensity at -100 mV reflects Ca2+ saturation of the dyes on each channel, while the closed-channel intensity is defined by the fluorescence at +30 mV, where influx is absent. True gating events can be identified from transitions between the open- and closed-channel levels, distinguishing them from transitions to a non-fluorescent state. We describe the gating behavior of CRAC channels activated by STIM1 after store depletion. Dwell time distributions indicate at least two open and closed states with durations of 0.1 to several seconds, with most channels having an open probability of [&ge;]0.7. We also detect silent channels that colocalize with STIM1 but show no activity over tens of seconds, a population that would be undetectable by whole-cell electrophysiology alone. This method offers an approach to explore CRAC channel gating mechanisms and may be applicable to other Ca2+- permeable channels not amenable to patch-clamp techniques.

Due to recent technological advances, in situ structural cell biology is becoming a high throughput microscopy technique as all the steps of the workflow, from sample preparation to data analysis, are executed faster, more reliable and more reproducible. Sample thinning by cryoFIB-SEM is an essential tool in preparing electron transparent lamellae of biological specimens suitable for further characterization by cryoET. Modern cryoFIB-SEM instruments can be operated remotely and are capable of automated and unsupervised lamellae preparation. To take full advantage of these developments they need a constant supply of LN2 to maintain cryogenic conditions inside the microscope chamber. Here, we introduce a custom automated LN2 refill system that is compatible with gas cooled cryostages, supports long-term cryoFIB-SEM operations and liberates the user from highly repetitive and manual work. We believe this solution can be utilized with other cryoSEM or cryoFIB-SEM devices requiring N2 gas-flow cooling.

Structure elucidation of biological macromolecules by single particle cryogenic electron microscopy (SPA cryo-EM) or cryogenic electron tomography (cryo-ET) relies on low-dose imaging on cryogenic transmission electron microscopes (cryo-TEMs). Routine microscope setup remains technically demanding and can be time-consuming, particularly for inexperienced or infrequent users. We present LowDoseWizard, a guided workflow implemented in SerialEM that enables rapid and standardised setup of cryo-TEM imaging conditions. From minimal user input, the workflow configures microscope optics, camera parameters and image shift settings for all low-dose imaging states, and guides the user through key daily alignment procedures including beam shift offset calibration, objective lens astigmatism correction and coma-free alignment. The workflow is organised into modular routines that can be executed sequentially or independently, while microscope-specific acquisition parameters are defined in editable configuration files, allowing flexible adaptation to different instruments without modification of the core scripts. Across user sessions on three microscopes at EMBL Heidelberg, the complete setup required on average less than 15 minutes. To assess whether predefined imaging conditions generated by the workflow are compatible with high-resolution data collection, we acquired apoferritin data on a 200 kV Glacios and a 300 kV Titan Krios. These datasets yielded reconstructions at 1.62 [A] and 1.09 [A] resolution, respectively, demonstrating that rapid, guided setup can support near-atomic and atomic-resolution single particle cryo-EM. LowDoseWizard lowers the barrier to robust cryo-TEM setup, reduces the time spent on routine parameter selection and alignment, and helps users focus on sample-specific aspects of data acquisition such as target selection. The workflow should be particularly valuable in shared instrumentation environments, where accessibility, reproducibility and efficient microscope use are critical.

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide ("All by All") computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

High-dimensional single-cell technologies, such as flow cytometry and CITE-Seq, typically rely on established lineage markers to define cell identities. Additional markers are commonly analyzed within the context of these predefined cell types. Nonlinear projection methods such as t-SNE and UMAP provide a visual framework for this analysis by enabling the overlay of cell types and marker expression. However, these methods frequently produce projections where distinct cell types substantially overlap, hindering interpretation of marker expression patterns relative to known cell types. In this study, we investigate the underlying causes of this phenomenon and demonstrate that such overlaps often stem from the inherent high-dimensional structure of the data rather than limitations in the dimensionality reduction algorithms themselves. To address this, we introduce Cell Type Weighted Dimensionality Reduction (CWDR), a novel approach that incorporates lineage-based information through a supervised weighting mechanism. By integrating both cell identity and marker expression, CWDR preserves the visual separation between predefined cell types while maintaining the local variance necessary for downstream analysis. We validate our method across multiple high-dimensional flow cytometry and proteogenomic datasets. Our results show that CWDR significantly reduces inter-cluster overlap compared to traditional methods, providing a clearer framework for visualizing marker expression within the context of specific cell lineages.

Archaic introgression has left a significant mark on human genetic diversity, but reliably identifying introgressed segments remains a major challenge, especially with complex demographic histories and limited sample sizes. Existing methods often rely on demographic assumptions or cohort-specific parameter fitting, which compromises robustness and scalability. We introduce ArchaicSeeker 3.0 (AS3), a deep-learning framework designed for haplotype-resolved detection of archaic introgression. AS3 integrates a tract-scale sequence model with an overlap-aware reassembly approach and boundary refinement, enabling accurate, boundary-coherent reconstruction of introgressed segments across diverse genomic contexts. By leveraging a simulation-trained model, AS3 avoids inference-time recalibration, offering stable performance across unrepresented demographic scenarios and small cohorts. In extensive simulations, AS3 outperforms existing methods in precision, recall, and F1 score, while providing more continuous segments with accurate boundary localization. It demonstrates robustness in small-target regimes and varying marker densities. Applied to 3,453 genomes from 209 populations, AS3 shows strong concordance with existing introgression callers and identifies additional introgressed regions, including high-frequency AS3-specific introgressed segments supported by locus-level haplotype and phylogenetic analyses. AS3 provides a scalable, robust solution for detecting archaic introgression from single individuals to large biobank datasets, marking a significant advancement in the field of local ancestry inference and opening new possibilities for the study of human evolutionary genetics. ArchaicSeeker 3.0 is available at https://github.com/Shuhua-Group/ArchaicSeeker3.0.

We present PHYFUM, a novel Bayesian phylogenetic method for methylation data that reconstructs the evolutionary history of stem cells and the glandular structures they reside within in normal tissue. Using simulations, we validated this phylogenetic method and confirmed its accuracy. A re-analysis of 22 patients unveiled early gland divergence in the human gut, in contrast to a much later common ancestor in the endometrium, and yielded strong evidence against gland division by segregation of individual stem cells.

Aims/hypothesisQuantitative nanoscale analysis of insulin secretory granules (ISGs) in human pancreatic tissue has been limited by the lack of imaging methods that combine high resolution with large-scale sampling. We aimed to establish expansion microscopy (ExM) as a platform for in situ, quantitative analysis of ISG organisation in human {beta}-cells and to assess whether type 2 diabetes (T2D) is associated with alterations in granule size, abundance or spatial organisation. MethodsWe applied Magnify ExM to PFA-fixed, paraffin-embedded pancreatic tissue sections from 6 human donors, 3 non-diabetic (ND) and 3 T2D, enabling super-resolution optical imaging of insulin-labelled granules. Insulin-positive structures were segmented and analysed using a morphometric pipeline to quantitatively assess size, shape and spatial features. Granule clustering was quantified based on combined area and roundness criteria. ResultsThe diameter distribution of highly circular granules was similar between ND and T2D samples and estimates of granule number per cell indicated only a modest reduction in T2D ([~]25%). In contrast, mapping insulin-positive structures in a roundness-area space revealed a marked enrichment of large, irregular objects consistent with granule clustering in T2D. The fraction of clustered granules was significantly increased in T2D and strongly inversely correlated with insulin stimulation index (r = -0.85). Conclusions/interpretationThese results establish expansion microscopy as a powerful platform for quantitative nanoscale analysis of human pancreatic tissue and identify altered spatial organisation of insulin granules, rather than marked granule depletion, as a prominent feature associated with {beta}-cell dysfunction in T2D. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LI{beta}-cell dysfunction in type 2 diabetes is often attributed to reduced insulin content or {beta}-cell loss. C_LIO_LIInsulin secretory granules (ISGs) have been characterised ultrastructurally, but quantitative analysis in human tissue remains limited. C_LIO_LISuper-resolution approaches, including expansion microscopy, are emerging tools for nanoscale imaging in biological tissues. C_LI What is the key question?O_LIIs {beta}-cell dysfunction in type 2 diabetes associated with depletion of insulin granules or with altered spatial organisation? C_LI What are the new findings?O_LIInsulin granule size distribution is largely preserved in type 2 diabetes, with only a modest reduction in granule number per cell. C_LIO_LIA significant increase in insulin granule clustering is observed in diabetic {beta}-cells. C_LIO_LIGranule clustering is strongly inversely correlated with insulin secretion in the same donor tissues. C_LI How might this impact on clinical practice in the foreseeable future?O_LIIdentifying altered granule organisation as a feature of {beta}-cell dysfunction may help refine the understanding of disease mechanisms and guide future strategies targeting {beta}-cell function. C_LI

Advances in transcriptome profiling have revealed transcriptomic differences across different cellular states. However, functional interpretation requires precise perturbation tools and experimental frameworks. This study benchmarked two widely used modalities: CRISPR interference (CRISPRi) and Cas13d/CasRx. A standardized workflow was established to generate human pluripotent stem cells (PSCs) with inducible ZIM3-dCas9 or CasRx expression. The cell lines were subjected to flow cytometry, copy number, and immunocytochemical analyses. The knockdown performance was validated via robust OCT4 suppression and the expected downstream effects on pluripotency genes. Time-course measurements indicated that CRISPRi produced faster and stronger repression but slower recovery after inducer withdrawal. In contrast, CasRx yielded slower and typically weaker knockdown with rapid reversibility. Furthermore, a key limitation of CRISPRi was demonstrated using the ATF5-NUP62 locus, wherein CRISPRi could co-repress genes with overlapping promoter regions. In contrast, CasRx avoids these limitations and supports isoform-resolved targeting of circular and alternatively spliced transcripts, albeit with variable efficiency. These results provide practical guidance for selecting complementary knockdown tools to improve the interpretability of transcriptomic function studies. MOTIVATIONAdvances in transcriptome profiling have enabled the detection of subtle cell type-specific differences. However, mechanistic interpretation still depends on perturbation tools that can modulate transcripts with high precision and efficiency. Recent CRISPR-based modalities, CRISPRi and Cas13/CasRx, function as robust and orthogonal methods to achieve the knockdown of specific gene targets. However, a standardized approach for cell line preparation and comparative studies on their relative performances and limitations remains unclear. Consequently, this study presents a standardized workflow for generating cell lines that support high-efficiency knockdown using CRISPRi and CasRx. Moreover, it compares the trade-offs in potency, reversibility, and isoform resolution, along with a practical overview of method-specific pitfalls to guide tool selection and data interpretation in future studies. HIGHLIGHTSO_LIDoxycycline-inducible AAVS1 knock-in human PSC platforms for CRISPRi (ZIM3-dCas9) and CasRx (RfxCas13d) were generated to enable standardized RNA perturbation experiments. C_LIO_LIThe prepared cell lines demonstrated strong OCT4 knockdown, with expected downstream effects on the expression of another pluripotency gene, NANOG. C_LIO_LIA comparison of knockdown characteristics and their reversibility revealed rapid and sustained repression with CRISPRi, whereas slow but rapid recovery was observed with CasRx. C_LIO_LIA CRISPRi-specific off-target effect arising from TSS proximity/overlap (ATF5-NUP62) was identified, whereas CasRx achieved ATF5 knockdown without collateral repression of the neighboring NUP62 gene. C_LIO_LICasRx enables isoform-resolved knockdown of structural isoforms (circHIPK3 vs. linear HIPK3 mRNA) and splice isoforms (RAB6A-iso1 vs. RAB6A-iso2). C_LI

Local ancestry inference (LAI) enables high-resolution characterization of chromosomal segments inherited from distinct ancestral populations, offering unique insights into genetic architecture in admixed cohorts. While LAI is commonly performed with high-coverage whole-genome sequencing (WGS), the ability of other genotyping assays or varying sequencing depths has not been thoroughly benchmarked. In this study, we systematically evaluated the accuracy of LAI across SNP microarrays, whole-exome sequencing (WES), and ultra low-pass WGS (ULP-WGS) using diverse validation samples and state-of-the-art imputation pipelines. We show that ULP-WGS, when paired with GLIMPSE2, achieves robust accuracy at 0.25x coverage with a minimum genome window size of 0.5 centimorgans, with mean accuracy minus one standard deviation exceeding 95%. For WES, using "on-target" reads alone yields suboptimal performance, particularly for European and South Asian ancestries with accuracy less than 79.1% and 70.6%, respectively. However, incorporating "off-target" reads in WES and utilizing GLIMPSE2 substantially improved accuracy [&ge;]95% with a minimum window size of 0.2 centimorgans. We further evaluated formalin-fixed, paraffin-embedded (FFPE) samples and found that LAI could be performed successfully using WES data with accuracies of [&ge;]95% at a minimum window size of 0.5 centimorgans. In contrast, SNP microarrays did not achieve substantial accuracies at any window size ([&le;]95%). Together, these results demonstrate that LAI is achievable without conventional high-coverage WGS and establish optimal parameters for LAI across platforms.

Evidence-based decision making on malaria vector control strategies increasingly rely on triangulation of data which requires informatics systems that can integrate data from complex, multi-stage studies involving mosquitoes. This manuscript describes a performance evaluation of an extended version of the generic schema underpinning the VBDs360 platform, specifically improved to accommodate multiple distinct entomological assays spanning the field, insectary and laboratory. The utility of this extension, with respect to high-fidelity data linkage and robust sample traceability across complex entomological workflows, was evaluated through a case study conducted in southern Tanzania. Wild female mosquitoes were collected from 40 locations across a >4,000 km{superscript 2} area and then reared through multiple generations in an insectary before derived iso-female lineages were tested for phenotypic susceptibility to a pyrethroid insecticide. Such multi-generational lineages (F to F where n [&ge;] 2) were propagated to prevent non-heritable maternal effects on phenotype and produce enough progeny for standard WHO susceptibility assays. All samples were subsequently archived in a molecular laboratory, where all F specimens were tested for sibling species identity. A paper-based implementation of the extended schema enabled successful integration of 77,017 lines of data distributed across 6 different tables that spanned 3 distinct field, insectary, and laboratory workflows, implemented by three different teams working in different locations. At each step, fully independent and redundant primary and secondary keys enabled high fidelity error correction and sample tracing. Consistently perfect linkage between assay design and sample sorting data was achieved for F0 wild-caught adults, with 100% of 66,108 record successfully linked between field capture and morphological categorization. This complete traceability extended to the propagation of derived Fn lineages, with all 100 and 243 records from 9 adult-derived and 13 larval-derived lineages, respectively, correctly linked. Insecticide susceptibility phenotype further confirmed 100% linkage for 5,654 records between exposure history and recorded mortality outcome data in the insectary. Although such cross-cleaned linkages to sample analysis and storage data recorded by the laboratory team were not entirely perfect and could be improved, they were nevertheless of very high fidelity (97.3% (1967/2,022) for F0 samples and 99.3% (437/440) for Fn samples). Overall, this pilot application of the extended generic schema ensured robust data provenance and minimized transcription errors in this complex study distributed across multiple teams and locations. These findings demonstrate how this generic informatics framework may be scaled and adapted to support data integrity across diverse, large-scale, multi-team entomological research workflows.

Chlamydomonas reinhardtii is a model green alga extensively used to study photosynthesis and cilia using molecular biology and genetics. Electroporation is a very common technique to transform DNA into the nuclear genome, which is essential to generate mutant collections and express transgenes. Here, we describe a simple, fast, and efficient protocol to transform strains with an intact cell wall. It achieves a good transformation efficiency without cell wall digestion or use of commercial kits and is compatible with the widely available Gene Pulser electroporation system. Key featuresO_LIHigh transformation efficiency of Chlamydomonas reinhardtii strains with an intact cell wall. C_LIO_LIFaster than currently available electroporation protocols. C_LI

IntroductionReliable generation of hepatocyte-like cells (HLCs) from pluripotent stem cells remains limited by heterogeneity and incomplete maturation of the cells. Derivation of induced pluripotent- and embryonic stem cells into hepatocytes typically relies on complex, and costly reagent-intensive protocols, with inconsistent reporting of differentiation efficiencies and functional maturation criteria. Variability in protocol designs highlights the need for optimisation, particularly in mouse embryonic stem cells (mESCs) systems that can be more comparable with mouse models for underpinning translational and toxicological studies. Here, we developed and evaluated two cytokine-based strategies: an advanced hepatic-inducing cocktail (A-HIC) and a simplified hepatic-inducing cocktail (HIC), both designed to reduce complexity while increasing functional maturation. MethodsHepatic differentiation and maturation were assessed by morphology, immunofluorescence, flow cytometry, and qRT-PCR. Functional competence was evaluated via urea production, glutathione synthesis, indocyanine green handling, cytochrome P450 inducibility, and impedance-based cell layer integrity monitoring. ResultsMorphological, molecular and phenotypic analyses confirmed that both protocols supported hepatic lineage progression, generating heterogeneous populations of hepatoblast-like and more mature HLCs. Gene expression confirmed the loss of pluripotency, transient endoderm induction, and subsequent hepatic specification. Functionally, cells exhibited glycogen storage, inducible urea production, glutathione depletion, and active ICG uptake and clearance, with stable monolayer formation by day 21. A-HIC-derived HLCs demonstrated enhanced maturation, with higher ASGR1 expression and stronger Cyp1a1 induction. DiscussionThese findings suggest that both protocols generate functional HLCs; however, A-HIC yields a higher proportion of functionally mature cells with reduced variability. This approach enables a simple, cost-effective, and time-efficient generation of HLCs, supported by improved functional characterisation with potential applicability to more complex pluripotent systems, including human iPSC-based models for disease modelling and toxicology.