Although HLA-II molecules are classically associated with professional antigen-presenting cells, their expression by cancer cells has been recognized for several decades. It has been linked to immune infiltration, responses to immune checkpoint blockade, and clinical outcomes. However, the regulatory mechanisms governing tumor-associated HLA-II expression remain incompletely understood. Genome-wide CRISPR-Cas9 screening was employed to identify candidate regulators of HLA-II expression in human melanoma cells. Key candidates were functionally validated through genetic and pharmacological perturbation approaches. Integrated transcriptomic and epigenomic analyses were conducted to characterize regulatory mechanisms. Retrospective clinical analyses were performed using publicly available The Cancer Genome Atlas (TCGA) datasets to assess associations with immune infiltration, immunotherapy response, and survival. We identified the aryl hydrocarbon receptor (AHR) and its dimerization partner ARNT as critical, FICZ-responsive, positive regulators of HLA-II expression. AHR-ARNT promoted transcription of CIITA through direct binding to its promoter II (pII), in the absence of IFN-γ signaling. Clinically, an AHR-ARNT loss-of-function signature correlated with reduced immune infiltration, poorer response to immunotherapy, and inferior survival across cancer types. These findings reveal a previously unrecognized regulatory axis controlling HLA-II expression on cancer cells, suggesting that targeting the AHR-ARNT pathway may enhance tumor immunogenicity and improve immunotherapy efficacy.

Efficient regeneration of biological energy carriers, such as cofactors of reduced nicotinamide adenine dinucleotide phosphate (NADPH) and adenosine triphosphate, is crucial for driving anabolic processes in artificial photosynthetic systems (APS). However, achieving spatiotemporally regulated cofactor regeneration under physiologically mild conditions remains a fundamental challenge. Here, a nature-inspired, thermoresponsive photo-biocatalytic photosynthetic hydrogel platform that enables dynamic regulation of photosynthetic cofactor regeneration through spatiotemporally tunable photo-biocatalysis is presented. This intelligent system integrates native thylakoid (Tk) membranes as photo-biocatalytic modules within poly(N-isopropylacrylamide) (PNI) (Tk@PNI) hydrogel matrix, constructed via templated, ultraviolet-initiated in situ polymerization process. The integrated thylakoids retain their intrinsic light-harvesting and electron transport capabilities, enabling light-driven NADPH regeneration via photoinduced proton-coupled electron transfer (PCET). Simultaneously, the PNI network functions as a dynamic structural modulator, undergoing reversible volume-phase transitions in response to temperature changes. This triggers reversible change in microenvironment and spatial constraint embedded thylakoid domains, allowing real-time regulation of PCET kinetics and catalytic output. By coupling light-driven energy conversion with thermoresponsive structural reorganization, this biohybrid platform achieves nonlinear, adaptive regulation of photosynthetic performance, sustaining efficient NADPH regeneration over 15-45 degrees C. This work provides a strategy to integrate stimuli-responsive polymers with biological energy modules for programmable energy conversion and sustainable biochemical synthesis.

Correction for 'A biomimetic human disease model of bacterial keratitis using a cornea-on-a-chip system' by Yudan Deng et al., Biomater. Sci., 2024, 12, 5239-5252, https://doi.org/10.1039/D4BM00833B.

Rare cells, despite constituting only a small fraction of the population, play a critical role in health and disease. For instance, a minor subset of cancer cells can drive tumor initiation and progression. However, detecting and analyzing rare cells remain challenging due to their low abundance and the need for high-precision identification methods. Microfluidic impedance-based flow cytometry (μIFC) provides a label-free and highly informative approach for single-cell characterization. In this study, we present a multifrequency μIFC platform enhanced by a support vector machine (SVM) learning strategy to accurately distinguish rare cancer cells from white blood cells (WBCs). Our platform achieves over 99% accuracy in differentiating three cancer cell lines─MDA-MB-231 (breast), A549 (lung), and HeLa (cervical)─from human immortalized T lymphocytes (Jurkat) or peripheral blood mononuclear cells (PBMCs). To further improve detection reliability, we introduce a postprediction correction strategy that reduces false identification rates. Additionally, we demonstrate the platform's capability to detect rare cancer cells within WBC populations at concentrations of 1-10%, with results highly consistent with conventional flow cytometry. This work establishes a robust, label-free, machine learning-enhanced μIFC platform for rare cancer cell analysis, paving the way for broader applications in rare cell characterization.

MHC-II molecules are traditionally restricted to professional antigen-presenting cells (pAPCs), but increasing evidence highlights their expression in cancer cells, where they are associated with enhanced immune infiltration and improved clinical outcomes. However, the mechanisms governing cancer cell-intrinsic MHC-II expression remain poorly understood. Here, through genome-wide CRISPR-Cas9 screening in human melanoma cells, we identify the aryl hydrocarbon receptor (AHR) and its dimerization partner (ARNT) as critical, ligand-responsive regulators of MHC-II expression. Our analyses reveal that AHR–ARNT promotes transcription of the MHC-II transactivator CIITA through direct binding to its promoter II (pII), independently of IFN-γ signaling. Clinically, an AHR–ARNT loss-of-function signature correlates with reduced immune infiltration, poor response to immunotherapy, and inferior survival across cancer types. Together, our findings uncover a previously unrecognized, tumor-intrinsic regulatory axis of MHC-II expression and suggest that targeting the AHR–ARNT pathway may enhance tumor immunogenicity and improve responses to immunotherapy.

Microbial genetic circuits are vital for regulating gene expression and synthesizing bioactive compounds. However, assessing their strength and timing, especially in multicellular fungi, remains challenging. Here, an advanced microfluidic platform is combined with a mathematical model enabling precise characterization of fungal gene regulatory circuits (GRCs) at the single-cell level. Utilizing this platform, the expression intensity and timing of 30 transcription factor-promoter combinations derived from two representative fungal GRCs, using the model fungus Aspergillus nidulans are determined. As a proof of concept, the selected GRC combination is utilized to successfully refactor the biosynthetic pathways of bioactive molecules, precisely control their production, and activate the expression of the silenced biosynthetic gene clusters (BGCs). This study provides insights into microbial gene regulation and highlights the potential of platform in fungal synthetic biology applications and the discovery of novel natural products.

Stem cells are crucial in tissue engineering, and their microenvironment greatly influences their behavior. Among the various dental stem cell types, stem cells from the apical papilla (SCAPs) have shown great potential for regenerating the pulp-dentin complex. Microenvironmental cues that affect SCAPs include physical and biochemical factors. To research optimal pulp-dentin complex regeneration, researchers have developed several models of controlled biomimetic microenvironments, ranging from in vivo animal models to in vitro models, including two-dimensional cultures and three-dimensional devices. Among these models, the most powerful tool is a microfluidic microdevice, a tooth-on-a-chip with high spatial resolution of microstructures and precise microenvironment control. In this review, we start with the SCAP microenvironment in the regeneration of pulp-dentin complexes and discuss research models and studies related to the biological process.

Digital nucleic acid quantification has emerged as an exceptionally valuable technique in molecular diagnosis, capturing significant attention in the biomedical field. This study introduces a novel multi-volume digital loop-mediated isothermal amplification (dLAMP) chip that offers an extensive detection range and user-friendly operation. The chip consists of 1024 large chambers with the volume of 7.2 nL and 6400 small chambers with the volume of 0.064 nL. The ingenious combination of chambers with volume difference beyond a 100-fold on the single chip enables a broad dynamic range exceeding 105 for nucleic acid quantification. Furthermore, this chip incorporates an automated strategy, enabling the rapid loading and partitioning of the reaction mixture into subvolumes within 4 min. In order to evaluate the quantitative capability of the multi-volume dLAMP chip, a 10-fold serial dilution of the beta-actin DNA template is measured. Additionally, the chip is tested for beta-actin DNA concentration in plasma samples from colorectal cancer patients and healthy individuals. By providing enhanced automation, wide dynamic range, and improved accuracy, this chip paves the way for broader applications and the advancement of biomedical research fields.

In the circulatory system, the microenvironment surrounding cancer cells is complex and involves multiple coupled factors. We selected two core physical factors, shear stress and hydraulic resistance, and constructed a microfluidic device with dual negative inputs to study the trade-off movement behavior of cancer cells when facing coupled factors. We detected significant shear stress escape phenomena in the MDA-MB-231 cell line and qualitatively explained this behavior using a cellular force model. Through the dual validation of substrate anti-cell-adhesion modification and employment of the MCF-7 cell line, we further substantiated the predictability and feasibility of our model. This study provides an explanation for the trade-off underlying the direction choosing mechanism of cancer cells when facing environmental selection.

AimThree-dimensional (3D) cell culture systems perform better in resembling tissue or organism structures compared with traditional 2D models. Organs-on-chips (OoCs) are becoming more efficient 3D models. This study aimed to create a novel simplified dentin-on-a-chip using microfluidic chip technology and tissue engineering for screening dental materials.MethodologyA microfluidic device with three channels was designed for creating 3D dental tissue constructs using stem cells from the apical papilla (SCAP) and gelatin methacrylate (GelMA). The study investigated the effect of varying cell densities and GelMA concentrations on the layer features formed within the microfluidic chip. Cell viability and distribution were evaluated through live/dead staining and nuclei/F-actin staining. The osteo/odontogenic potential was assessed through ALP staining and Alizarin red staining. The impact of GelMA concentrations (5%, 10%) on the osteo/odontogenic differentiation trajectory of SCAP was also studied.ResultsThe 3D tissue constructs maintained high viability and favorable spreading within the microfluidic chip for 3-7 days. A cell seeding density of 2×104 cells/μL was found to be the most optimal choice, ensuring favorable cell proliferation and even distribution. GelMA concentrations of 5% and 10% proved to be most effective for promoting cell growth and uniform distribution. Within the 5% GelMA group, SCAP demonstrated higher osteo/odontogenic differentiation than that in the 10% GelMA group.ConclusionIn 3D culture, GelMA concentration was found to regulate the osteo/odontogenic differentiation of SCAP. The study recommends a seeding density of 2×104 cells/μL of SCAP within 5% GelMA for constructing simplified dentin-on-a-chip.Clinical SignificanceThis study built up the 3D culture protocol, and induced odontogenic differentiation of SCAP, thus forming the simplified dentin-on-a-chip and paving the way to be used as a well-defined biological model for regenerative endodontics. It may serve as a potential testing platform for cell differentiation.

The process of biological fate decision regulated by gene regulatory networks involves numerous complex dynamical interactions among many components. Mathematical modeling typically employed ordinary differential equations and steady-state analysis, which has yielded valuable quantitative insights. However, stable states predicted by theoretical models often fail to capture transient or metastable phenomena that occur during most observation periods in experimental or real biological systems. We attribute this discrepancy to the omission of dynamic processes of various complex interactions. Here, we demonstrate the influence of delays in gene regulatory steps and the timescales of the external induction on the dynamic processes of the fate decision in inducible bistable systems. We propose that steady-state parameters determine the landscape of fate decision. However, during the dynamic evolution along the landscape, the unequal delays of biochemical interactions as well as the timescale of external induction cause deviations in the differentiation trajectories, leading to the formation of new transient distributions that persist long term. Our findings emphasize the importance of considering dynamic processes in fate decision instead of relying solely on steady-state analysis. We provide insights into the interpretation of experimental phenomena and offer valuable guidance for future efforts in dynamical modeling and synthetic biology design.

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms. However, it is still unclear how such information is affected by the physically dissipative diffusion process. Here we study one-dimensional patterning systems with analytical derivation and numerical simulations. We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns. Specifically, there exists an optimal diffusion constant that maximizes the positional information. Moreover, we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Bacterial keratitis is a common form of inflammation caused by the bacterial invasion of the corneal stroma after trauma. In extreme cases, it can lead to severe visual impairment or even blindness; therefore, timely medical intervention is imperative. Unfortunately, widespread misuse of antibiotics has led to the development of drug resistance. In recent years, organ-on-chips that integrate multiple cell co-cultures have extensive applications in fundamental research and drug screening. In this study, immortalized human corneal epithelial cells and primary human corneal fibroblasts were co-cultured on a porous polydimethylsiloxane membrane to create a cornea-on-a-chip model. The developed multilayer epithelium closely mimicked clinical conditions, demonstrating high structural resemblance and repeatability. By introducing a consistently defective epithelium and bacterial infection using the space-occupying method, we successfully established an in vitro model of bacterial keratitis using S. aureus. We validate this model by evaluating the efficacy of antibiotics, such as levofloxacin, tobramycin, and chloramphenicol, through simultaneously observing the reactions of bacteria and the two cell types to these antibiotics. Our study has revealed the barrier function of epithelium of the model and differentiated efficacy of three drugs in terms of bactericidal activity, reducing cellular apoptosis, and mitigating scar formation. Altogether, the cornea on chip enables the assessment of ocular antibiotics, distinguishing the impact on corneal cells and structural integrity. This study introduced a biomimetic in vitro disease model to evaluate drug efficacy and provided significant insights into the extensive effects of antibiotics on diverse cell populations within the cornea.

Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2 min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms. Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.

Cells can respond and adapt to complex forms of environmental change. Budding yeast is widely used as a model system for these stress response studies. In these studies, the precise control of the environment with high temporal resolution is most important. However, there is a lack of single-cell research platforms that enable precise control of the temperature and form of cell growth. This has hindered our understanding of cellular coping strategies in the face of diverse forms of temperature change. Here, we developed a novel temperature-controlled microfluidic platform that integrates a microheater (using liquid metal) and a thermocouple (liquid metal vs. conductive PDMS) on a chip. Three forms of temperature changes (step, gradient, and periodical oscillations) were realized by automated equipment. The platform has the advantages of low cost and a simple fabrication process. Moreover, we investigated the nuclear entry and exit behaviors of the transcription factor Msn2 in yeast in response to heat stress (37 degrees C) with different heating modes. The feasibility of this temperature-controlled platform for studying the protein dynamic behavior of yeast cells was demonstrated. Three forms of temperature changes (step, gradient, and oscillations) were realized in a novel microfluidic platform. The feasibility of this temperature-controlled platform for studying the protein dynamic behavior of yeast cells was demonstrated.

Although bacterial chemotaxis behavior in a single gradient has been well studied, chemotaxis of bacterial population in complex environments is not well understood. Here, we discovered four distinct behaviors of populations in microfluidic experiments with different opposing gradients of MeAsp and serine. By using a population chemotaxis model based on the dynamics of intracellular signaling pathways, we found that the nongenetic variability of the relevant chemoreceptors (Tar and Tsr) within the population is responsible for the diverse population behaviors. Through analyses combining the phenotype-to-performance mapping and Tar/Tsr ratio distribution, we predicted the phase diagram of population chemotaxis behaviors under varying chemical gradients and the effect of growth period on population behaviors, which were verified by additional experiments. Our study suggests that phenotypic heterogeneity in chemoreceptors enables diverse chemotactic strategies, which cells may adopt to improve their population fitness in complex environments. Published by the American Physical Society 2024

Signal transduction is crucial for many biological functions. However, it is still unclear how signaling systems function accurately under noisy situations. More specifically, such systems operate in a regime of low response noise, while maintaining high sensitivity to signals. To gain further insight on this regime, here we derive a fundamental trade-off between response sensitivity and precision in biological signaling processes under the static noise condition. We find that the optimal trade-off in signaling networks can be better characterized by a phase diagram structure rather than topological structures. We confirm that the patterning network of early Drosophila embryos agrees with our derived relationship, and apply the optimal phase diagram structure to quantitatively predict the patterning position shifts of the downstream genes, including hunchback , Krüppel , giant , knirps and even-skipped , upon the dosage perturbation of the morphogen Bicoid.

Isolation and characterization of circulating tumor cells (CTCs) provide the possibility for early diagnosis and personalized treatment of cancer. Due to the complexity of blood composition and the rarity of CTCs, existing technologies still have issues in balancing the sample throughput, separate efficiency, and operation convenience. Here, a concept is proposed to improve CTCs capture performance by reforming the separation unit and rearranging functionally independent modules into 3D configuration based on the previous microfluidic chip. In this way, the novel 3D‐CTC chip can significantly decrease to a smaller size with enhanced capture efficiency (>89%) at an ultra‐high throughput (70 mL h−1 with whole blood sample) over a wide range of flow rates (5–70 mL h−1). The capability of the developed chip can be improved manyfold by paralleling single chips whether the samples are injected by pump or manually. The clinical experiments of colorectal cancer (CRC) patients on these chips demonstrate a positive correlation between CTCs counts (5–34 CTCs per 2 mL whole blood) and cancer stages. In general, the proposed compact 3D‐CTC chip provides high performance with low requirements of experiment conditions, which implies an enormous potential for industrial production and handy clinical test.

Super-resolution microscopy is rapidly developed in recent years, allowing biologists to extract more quantitative information on subcellular processes in live cells that is usually not accessible with conventional techniques. However, super-resolution imaging is not fully exploited because of the lack of an appropriate and multifunctional experimental platform. As an important tool in life sciences, microfluidics is capable of cell manipulation and the regulation of the cellular environment because of its superior flexibility and biocompatibility. The combination of microfluidics and super-resolution microscopy revolutionizes the study of complex cellular properties and dynamics, providing valuable insights into cellular structure and biological functions at the single-molecule level. In this perspective, an overview of the main advantages of microfluidic technology that are essential to the performance of super-resolution microscopy are offered. The main benefits of performing super-resolution imaging with microfluidic devices are highlighted and perspectives on the diverse applications that are facilitated by combining these two powerful techniques are provided.