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Microfluidic chips have emerged as significant tools in cell culture due to their capacity for supporting cells to adopt more physiologically relevant morphologies in 3D compared with traditional cell culture in 2D. Currently, irreversible bonding methods, where chips cannot be detached from their substrates without destroying the structure, are commonly used in fabrication, making it challenging to conduct further analysis on cells that have been cultured on-chip. Although some reversible bonding techniques have been developed, they are either restricted to certain materials such as glass, or require complex processing procedures. Here, we demonstrate a simple and reversible polydimethylsiloxane (PDMS)–polystyrene (PS) bonding technique that allows devices to withstand extended operations while pressurized, and supports long-term stable cell cultures. More importantly, it allows rapid and gentle live cell extraction for downstream manipulation and characterization after long-term on-chip culturing, and even further subculturing. Our new approach could greatly facilitate microfluidic chip-based cell and tissue cultures, overcoming current analytical limitations and opening up new avenues for downstream uses of on-chip cultures, including 3D-engineered tissue structures for biomedical applications.

Spider silk is recognized for its exceptional mechanical properties and biocompatibility, making it a versatile platform for developing functional materials. In this study, a modular functionalization strategy for recombinant spider silk is presented using SpyTag/SpyCatcher chemistry, a prototype of genetically encoded click chemistry. The approach involves AlphaFold2-aided design of SpyTagged spider silk coupled with bacterial expression and biomimetic spinning, enabling the decoration of silk with various SpyCatcher-fusion motifs, such as fluorescent proteins, enzymes, and cell-binding ligands. The silk threads can be coated with a silica layer using silicatein, an enzyme for silicification, resulting in a hybrid inorganic–organic 1D material. The threads installed with RGD or laminin cell-binding ligands lead to enhanced endothelial cell attachment and proliferation. These findings demonstrate a straightforward yet powerful approach to 1D protein materials., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., ImPhys/Maresca group

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

Single-cell multi-omics technologies can provide a unique perspective on tumor cellular heterogeneity. We have developed a versatile method for simultaneous transcriptome and genome profiling of single cells or single nuclei in one tube reaction, named scONE-seq. It is conveniently compatible with frozen tissue from biobanks, which are a major source of patient samples for research. Here, we describe the detailed procedures to profile single-cell/nucleus transcriptome and genome. The sequencing library is compatible with both Illumina and MGI sequencers; it is also compatible with frozen tissue from biobanks, which are a major source of patient samples for research and drug discovery.

Spider silk is recognized for its exceptional mechanical properties and biocompatibility, making it a versatile platform for developing functional materials. In this study, a modular functionalization strategy for recombinant spider silk is presented using SpyTag/SpyCatcher chemistry, a prototype of genetically encoded click chemistry. The approach involves AlphaFold2-aided design of SpyTagged spider silk coupled with bacterial expression and biomimetic spinning, enabling the decoration of silk with various SpyCatcher-fusion motifs, such as fluorescent proteins, enzymes, and cell-binding ligands. The silk threads can be coated with a silica layer using silicatein, an enzyme for silicification, resulting in a hybrid inorganic–organic 1D material. The threads installed with RGD or laminin cell-binding ligands lead to enhanced endothelial cell attachment and proliferation. These findings demonstrate a straightforward yet powerful approach to 1D protein materials.

Modelling the human brain in vitro has been extremely challenging due to the brain's intricate cellular composition and specific structural architecture. The recent emergence of brain organoids that recapitulate many key features of human brain development has thus piqued the interest of many to further develop and apply this in vitro model for various physiological and pathological investigations. Despite ongoing efforts, the existing brain organoids demonstrate several limitations, such as the lack of a functional human vasculature with perfusion capability. Microfluidics is suited to enhance such brain organoid models by enabling vascular perfusion and a curated blood-brain barrier microenvironment. In this review, we first provide an introduction to in vivo human brain development and present the state-of-the-art in vitro human brain models. We further elaborate on different strategies to improve the vascularized human brain organoid microenvironment using microfluidic devices, while discussing the current obstacles and future directions in this field.

Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.

Cytokine monitoring has attracted great attention due to its significance in the diagnosis and treatment of many diseases, such as tumors, microbial infections, and immunological diseases. Enzyme-linked immunosorbent assay (ELISA) is one of the most popular methods in cytokine detection, ascribing to the lavish signal amplification methods in the ELISA platform. In addition to classical enzymes, other signal amplifiers such as fluorescent probes, artificial nano-enzymes, and photothermal reagents have been applied to reduce the detection limit and produce more sensitive ELISA kits. Due to the accumulative effect of heat, photothermal reagents are promising materials in the signal amplification of ELISA. However, the lack of efficient photothermal generation material at an aggregate scale may delay the further development of this area. In this contribution, based on an efficient organic photothermal aggregate material, an enzyme-free photothermally amplified fluorescent immunosorbent assay system consisting of an assay microfluidic chip and detecting platform was developed. The photothermal nanoparticles with highly efficient photothermal conversion by harvesting energy via excited-state intramolecular motions and enlarging molar absorptivity were successfully prepared. The detection concentration at 50 pg/mL of interleukin-2 was achieved, realizing a signal improvement of detection limits by 20-fold compared to that of previously reported photothermal ELISA. The microscopic imaging integrated with plane sweeping technology provided high spatial resolution and precision, indicating the potential of achieving high throughput profiling at the microscale. Moreover, as an alternative excitation source, light-emitting diode not only provided a more affordable and miniaturized detection system but also revealed the great feasibility of intramolecular motion-induced photothermy nanoparticles for biological analyses. © 2023 The Authors. Aggregate published by SCUT, AIEI, and

Spontaneous mutations introduce uncertainty into coronavirus disease 2019 (COVID-19) control procedures and vaccine development. Here, we perform a spatiotemporal analysis on intra-host single-nucleotide variants (iSNVs) in 402 clinical samples from 170 affected individuals, which reveals an increase in genetic diversity over time after symptom onset in individuals. Nonsynonymous mutations are overrepresented in the pool of iSNVs but underrepresented at the single-nucleotide polymorphism (SNP) level, suggesting a two-step fitness selection process: a large number of nonsynonymous substitutions are generated in the host (positive selection), and these substitutions tend to be unfixed as SNPs in the population (negative selection). Dynamic iSNV changes in subpopulations with different gender, age, illness severity, and viral shedding time displayed a varied fitness selection process among populations. Our study highlights that iSNVs provide a mutational pool shaping the rapid global evolution of the virus. © 2021 The Authors

Currently, most advances in site-specific epigenetic editing for human use are concentrated in basic research, yet, there is considerable interest to translate this technology beyond the bench. This review highlights recent developments with epigenetic editing technology in comparison with the canonical CRISPR-Cas genome editing, as well as the epistemic and ethical considerations with preemptive translation of epigenetic editing into clinical or commercial use in humans. Key considerations in safety, equity, and access to epigenetic editing are highlighted, with a spotlight on the ethical, legal, and social issues of this technology in the context of global health equity.

Human body encompasses a huge number of microorganisms, which constitute the human microbiome. These microbes are in active interactions with immune system and play important role in maintaining health. Traditional studies of human microbes mainly focused on infection-causing single pathogens and ignored impact from the whole microbial community. Metagenomic and metatranscriptomic next-generation sequencing (mNGS) has emerged as a promising technology that can not only be used for pan-pathogen detection but has also enabled the illustration of whole microbial composition and function. Here, I will demonstrate two applications of mNGS in monitoring human diseases: 1) In the first study, we have explored multiple components of blood cell-free DNA (cfDNA) from ICU patients using metagenomic sequencing. Both the human and microbial cfDNA fragments contain information about the disease condition. After integrating these multifaceted cfDNA information, we can achieve very good performance for diagnosis of sepsis and moderate results for prediction of clinical outcome at an early stage; 2) In the second project, we have revealed altered microbial composition and function, as well as high risk of secondary infections caused by pathogens other than SARS-CoV-2 in COVID-19 patients. By comparing the microbial features in different body sites, gut microbiome seems to be more directly affected by SARS-CoV-2 abundance as compared to that in the respiratory tract. Moreover, we didn’t observe restoration of microbial composition during the study period. The results suggest that SARS-CoV-2 infection could have a long-time effect on human microbiome, which deserves more attention for the management of COVID-19 patients.

In vitro models of vasculature are of great importance for modelling vascular physiology and pathology. However, there is usually a lack of proper spatial patterning of interacting heterotypic cells in conventional vasculature dish models, which might confound results between contact and non-contact interactions. We use a microfluidic platform with structurally defined separation between human microvasculature and fibroblasts to probe their dynamic, paracrine interactions. We also develop a novel, versatile technique to retrieve cells embedded in extracellular matrix from the microfluidic device for downstream transcriptomic analysis, and uncover growth factor and cytokine expression profiles associated with improved vasculature growth. Paired receptor-ligand analysis further reveals paracrine signaling molecules that could be supplemented into the medium for vasculatures models where fibroblast coculture is undesirable or infeasible. These findings also provide deeper insights into the molecular cues for more physiologically relevant vascular mimicry and vascularized organoid model for clinical applications such as drug screening and disease modeling.

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues and other batch effects make scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. We present FIRM, a re-scaling algorithm which accounts for the effects of cell type compositions, and achieve accurate integration of scRNA-seq datasets across multiple tissue types, platforms and experimental batches. Compared with existing state-of-the-art integration methods, FIRM provides accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. FIRM is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

The rapid emergence of large-scale atlas-level single-cell RNA-seq datasets presents remarkable opportunities for broad and deep biological investigations through integrative analyses. However, harmonizing such datasets requires integration approaches to be not only computationally scalable, but also capable of preserving a wide range of fine-grained cell populations. We created Portal, a unified framework of adversarial domain translation to learn harmonized representations of datasets. With innovation in model and algorithm designs, Portal achieves superior performance in preserving biological variation during integration, while achieving integration of millions of cells in minutes with low memory consumption. We show that Portal is widely applicable to integrating datasets across samples, platforms and data types (including scRNA-seq, snRNA-seq and scATAC-seq). Finally, we demonstrate the power of Portal by applying it to the integration of cross-species datasets with limited shared information among them, elucidating biological insights into the similarities and divergences in the spermatogenesis process among mouse, macaque and human.

The extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach, to detect cell-type-specific splicing in >110K cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type-specifically spliced, including ubiquitously expressed genes MYL6 and RPS24. These results are validated with RNA FISH, single-cell PCR, and Smart-seq2. SpliZ analysis reveals 170 genes with regulated splicing during human spermatogenesis, including examples conserved in mouse and mouse lemur. The SpliZ allows model-based identification of subpopulations indistinguishable based on gene expression, illustrated by subpopulation-specific splicing of classical monocytes involving an ultraconserved exon in SAT1. Together, this analysis of differential splicing across multiple organs establishes that splicing is regulated cell-type-specifically. © 2021, eLife Sciences Publications Ltd. All rights reserved.

A decade since its invention, single-cell RNA sequencing (scRNA-seq) has become a mainstay technology for profiling transcriptional heterogeneity in individual cells. Yet, most existing scRNA-seq methods capture only polyadenylated mRNA to avoid the cost of sequencing non-messenger transcripts, such as ribosomal RNA (rRNA), that are usually not of-interest. Hence, there are not very many protocols that enable single-cell analysis of total RNA. We adapted a method called DASH (Depletion of Abundant Sequences by Hybridisation) to make it suitable for depleting rRNA sequences from single-cell total RNA-seq libraries. Our analyses show that our single-cell DASH (scDASH) method can effectively deplete rRNAs from sequencing libraries with minimal off-target non-specificity. Importantly, as a result of depleting the rRNA, the rest of the transcriptome is significantly enriched for detection. © 2021 PeerJ Inc.. All rights reserved.

Emulsion polymerase chain reaction (ePCR) enables parallel amplification of millions of different DNA molecules while avoiding bias and chimeric byproducts, essential criteria for applications including next generation sequencing, aptamer selection, and protein-DNA interaction studies. Despite these advantages, ePCR remains underused due to the lack of optimal starting conditions, straightforward methods to evaluate success, and guidelines for tuning the reaction. This knowledge has been elusive for bulk emulsion generation methods, such as stirring and vortexing, the only methods that can emulsify libraries of ≥108 sequences within minutes, because these emulsions have not been characterized in ways that preserve the heterogeneity that defines successful ePCR. Our study quantifies the outcome of ePCR from conditions specified in the literature using single particle analysis, which preserves this heterogeneity. We combine ePCR with magnetic microbeads and quantify the amplification yield via qPCR and the proportion of clonal and saturated beads via flow cytometry. Our single particle level analysis of thousands of beads resolves two key criteria that define the success of ePCR: 1) whether the target fraction of 20% clonal beads predicted by the Poisson distribution is achieved, and 2) whether those beads are partially or maximally covered by amplified DNA. We found that among the two concentrations of polymerase tested, only the higher one, which is 20-fold more than the concentration recommended for conventional PCR, could yield sufficient PCR products. Dramatic increases in the concentrations of reverse primer and nucleotides recommended in literature gave no measurable change in outcome. We thus provide evidence-based starting conditions for effective and economical ePCR for real DNA libraries and a straightforward workflow for evaluating the success of tuning ePCR prior to downstream applications. © 2020 The Author(s)