Live-seq enables temporal transcriptomic recording of single cells.

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity1. However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy2,3, thus allowing to couple a cell's ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell's trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition.

Single-cell RNA sequencing (scRNA-seq) approaches have transformed our ability to resolve cellular properties across systems, but are currently tailored toward large cell inputs (>1,000 cells). This renders them inefficient and costly when processing small, individual tissue samples, a problem that tends to be resolved by loading bulk samples, yielding confounded mosaic cell population read-outs. Here, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo, aimed at processing low-input samples (<500 cells). We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single-cell suspensions at high capture efficiency (>70%) and at speeds up to 350 cells per hour. To underscore DisCo's unique capabilities, we analyzed 31 individual intestinal organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a+ stem cell population that persists as symmetrical cysts, or spheroids, even under differentiation conditions, and an uncharacterized 'gobloid' subtype consisting predominantly of precursor and mature (Muc2+) goblet cells. To complement this dataset and to demonstrate DisCo's capacity to process low-input, in vivo-derived tissues, we also analyzed individual mouse intestinal crypts. This revealed the existence of crypts with a compositional similarity to spheroids, which consisted predominantly of regenerative stem cells, suggesting the existence of regenerating crypts in the homeostatic intestine. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity in small, individual tissues.

Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing.

High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatments. Focusing on gene expression, the transcriptomic market exploits the benefits of next-generation sequencing (NGS), leveraging RNA sequencing (RNA-seq) as standard for measuring genome-wide gene expression in biological samples. The cumbersome sample preparation, including RNA extraction, conversion to cDNA and amplification, prevents high-throughput translation of RNA-seq technologies. Bulk RNA barcoding and sequencing (BRB-seq) addresses this limitation by enabling sample preparation in multi-well plate format. Sample multiplexing combined with early pooling into a single tube reduces reagents consumption and manual steps. Enabling simultaneous pooling of all samples from the multi-well plate into one tube, our technology relies on smart labware: a pooling lid comprising fluidic features and small pins to transport the liquid, adapted to standard 96-well plates. Operated with standard fluidic tubes and pump, the system enables over 90% recovery of liquid in a single step in less than a minute. Large scale manufacturing of the lid is demonstrated with the transition from a milled polycarbonate/steel prototype into an injection molded polystyrene lid. The pooling lid demonstrated its value in supporting high-throughput barcode-based sequencing by pooling 96 different DNA barcodes directly from a standard 96-well plate, followed by processing within the single sample pool. This new pooling technology shows great potential to address medium throughput needs in the BRB-seq workflow, thereby addressing the challenge of large-scale and cost-efficient sample preparation for RNA-seq.

A parallelized, automated platform enabling individual or sequential ChIP of histone marks and transcription factors.

Despite its popularity, chromatin immunoprecipitation followed by sequencing (ChIP-seq) remains a tedious (>2 d), manually intensive, low-sensitivity and low-throughput approach. Here, we combine principles of microengineering, surface chemistry, and molecular biology to address the major limitations of standard ChIP-seq. The resulting technology, FloChIP, automates and miniaturizes ChIP in a beadless fashion while facilitating the downstream library preparation process through on-chip chromatin tagmentation. FloChIP is fast (<2 h), has a wide dynamic range (from 106 to 500 cells), is scalable and parallelized, and supports antibody- or sample-multiplexed ChIP on both histone marks and transcription factors. In addition, FloChIP's interconnected design allows for straightforward chromatin reimmunoprecipitation, which allows this technology to also act as a microfluidic sequential ChIP-seq system. Finally, we ran FloChIP for the transcription factor MEF2A in 32 distinct human lymphoblastoid cell lines, providing insights into the main factors driving collaborative DNA binding of MEF2A and into its role in B cell-specific gene regulation. Together, our results validate FloChIP as a flexible and reproducible automated solution for individual or sequential ChIP-seq.

SMiLE-seq identifies binding motifs of single and dimeric transcription factors.

Resolving the DNA-binding specificities of transcription factors (TFs) is of critical value for understanding gene regulation. Here, we present a novel, semiautomated protein-DNA interaction characterization technology, selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq). SMiLE-seq is neither limited by DNA bait length nor biased toward strong affinity binders; it probes the DNA-binding properties of TFs over a wide affinity range in a fast and cost-effective fashion. We validated SMiLE-seq by analyzing 58 full-length human, mouse, and Drosophila TFs from distinct structural classes. All tested TFs yielded DNA-binding models with predictive power comparable to or greater than that of other in vitro assays. De novo motif discovery on all JUN-FOS heterodimers and several nuclear receptor-TF complexes provided novel insights into partner-specific heterodimer DNA-binding preferences. We also successfully analyzed the DNA-binding properties of uncharacterized human C2H2 zinc-finger proteins and validated several using ChIP-exo.

Adaptive damage retention mechanism enables healthier yeast population.

During cytokinesis in budding yeast (Saccharomyces cerevisiae) damaged proteins are distributed asymmetrically between the daughter and the mother cell. Retention of damaged proteins is a crucial mechanism ensuring a healthy daughter cell with full replicative potential and an ageing mother cell. However, the protein quality control (PQC) system is tuned for optimal reproduction success which suggests optimal health and size of the population, rather than long-term survival of the mother cell. Modelling retention of damage as an adaptable mechanism, we propose two damage retention strategies to find an optimal way of decreasing damage retention efficiency to maximize population size and minimize the damage in the individual yeast cell. A pedigree model is used to investigate the impact of small variations in the strategies over the whole population. These impacts are based on the altruistic effects of damage retention mechanism and are measured by a cost function whose minimum value provides the optimal health and size of the population. We showed that fluctuations in the cost function allow yeast cell to continuously vary its strategy, suggesting that optimal reproduction success is a local minimum of the cost function. Our results suggest that a rapid decrease in the efficiency of damage retention, at the time when the mother cell is almost exhausted, produces fewer daughters with high levels of damaged proteins. In addition, retaining more damage during the early divisions increases the number of healthy daughters in the population.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation.

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named "variable chromatin modules" (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.

cis-regulatory variation modulates susceptibility to enteric infection in the Drosophila genetic reference panel.

BACKGROUND: Resistance to enteric pathogens is a complex trait at the crossroads of multiple biological processes. We have previously shown in the Drosophila Genetic Reference Panel (DGRP) that resistance to infection is highly heritable, but our understanding of how the effects of genetic variants affect different molecular mechanisms to determine gut immunocompetence is still limited. RESULTS: To address this, we perform a systems genetics analysis of the gut transcriptomes from 38 DGRP lines that were orally infected with Pseudomonas entomophila. We identify a large number of condition-specific, expression quantitative trait loci (local-eQTLs) with infection-specific ones located in regions enriched for FOX transcription factor motifs. By assessing the allelic imbalance in the transcriptomes of 19 F1 hybrid lines from a large round robin design, we independently attribute a robust cis-regulatory effect to only 10% of these detected local-eQTLs. However, additional analyses indicate that many local-eQTLs may act in trans instead. Comparison of the transcriptomes of DGRP lines that were either susceptible or resistant to Pseudomonas entomophila infection reveals nutcracker as the only differentially expressed gene. Interestingly, we find that nutcracker is linked to infection-specific eQTLs that correlate with its expression level and to enteric infection susceptibility. Further regulatory analysis reveals one particular eQTL that significantly decreases the binding affinity for the repressor Broad, driving differential allele-specific nutcracker expression. CONCLUSIONS: Our collective findings point to a large number of infection-specific cis- and trans-acting eQTLs in the DGRP, including one common non-coding variant that lowers enteric infection susceptibility.

Simplified Drop-seq workflow with minimized bead loss using a bead capture and processing microfluidic chip.

Single-cell RNA-sequencing (scRNA-seq) has revolutionized biomedical research by enabling the in-depth analysis of cell-to-cell heterogeneity of tissues with unprecedented resolution. One of the catalyzing technologies is single cell droplet microfluidics, which has massively increased the overall cell throughput, routinely allowing the analysis of thousands of cells per experiment at a relatively low cost. Among several existing droplet-based approaches, the Drop-seq platform has emerged as one of the most widely used systems. Yet, this has surprisingly not incentivized major refinements of the method, thus restricting any lab implementation to the original Drop-seq setup, which is known to suffer from up to 80% bead loss during the process. In this study, we present a systematic re-engineering and optimization of Drop-seq: first, we re-designed the original dropleting device to be compatible with both air-pressure systems and syringe pumps, thus increasing the overall flexibility of the platform. Second, we devised an accompanying chip for post-encapsulation bead processing, which simplifies and massively increases Drop-seq's cell processing efficiency. Taken together, the presented optimization efforts result in a more flexible and efficient Drop-seq version.

A Comprehensive Drosophila melanogaster Transcription Factor Interactome.

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. We further demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

ZFP30 promotes adipogenesis through the KAP1-mediated activation of a retrotransposon-derived Pparg2 enhancer.

Krüppel-associated box zinc finger proteins (KZFPs) constitute the largest family of mammalian transcription factors, but most remain completely uncharacterized. While initially proposed to primarily repress transposable elements, recent reports have revealed that KFZPs contribute to a wide variety of other biological processes. Using murine and human in vitro and in vivo models, we demonstrate here that one poorly studied KZFP, ZFP30, promotes adipogenesis by directly targeting and activating a retrotransposon-derived Pparg2 enhancer. Through mechanistic studies, we further show that ZFP30 recruits the co-regulator KRAB-associated protein 1 (KAP1), which, surprisingly, acts as a ZFP30 co-activator in this adipogenic context. Our findings provide an understanding of both adipogenic and KZFP-KAP1 complex-mediated gene regulation, showing that the KZFP-KAP1 axis can also function in a non-repressive manner.