Biology subjects

Dainese, R.

Publications and source records attributed to Dainese, R..

4 recordsLinked to original sources

bioRxiv2024

Identification of methylation-sensitive human transcription factors using meSMiLE-seq

Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown. Here, we assayed 284 mostly poorly characterized, putative human TFs using selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq), revealing 72 new DNA binding motifs. To investigate whether some of the 158 TFs for which we did not find motifs preferably bind epigenetically modified DNA (i.e. methylated CG dinucleotides), we developed methylation-sensitive SMiLE-seq (meSMiLE-seq). This microfluidic assay simultaneously probes the affinity of a protein to methylated and unmethylated DNA, augmenting the capabilities of the original method to infer methylation-aware binding sites. We assayed 114 TFs with meSMiLE-seq and identified DNA-binding models for 48 proteins, including the known methylation-sensitive binding modes for POU5F1 and RFX5. For 11 TFs, binding to methylated DNA was preferred or resulted in the discovery of alternative, methylation-dependent motifs (e.g. PRDM13), while aversion towards methylated sequences was found for 13 TFs (e.g. USF3). Finally, we uncovered a potential role for ZHX2 as a putative binder of Z-DNA, a left-handed helical DNA structure which is adopted more frequently upon CpG methylation. Altogether, our study significantly expands the human TF codebook by identifying DNA binding motifs for 98 TFs, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.

genomics↗

bioRxiv2021

Genome-wide molecular recording using Live-seq

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity in health and disease. However, scRNA-seq requires lysing cells, which makes it impossible to link the individual cells to downstream molecular and phenotypic states. Here, we established Live-seq, an approach for single-cell transcriptome profiling that preserves cell viability during RNA extraction using fluidic force microscopy. Based on cell division, functional responses and whole-cell transcriptome read-outs, we show that Live-seq does not induce major cellular perturbations and therefore can function as a transcriptomic recorder. We demonstrate this recording capacity by preregistering the transcriptomes of individual macrophage-like RAW 264.7 cells that were subsequently subjected to time-lapse imaging after lipopolysaccharide (LPS) exposure. This enabled the unsupervised, genome-wide ranking of genes based on their ability to impact macrophage LPS response heterogeneity, revealing basal NFKBIA expression level and cell cycle state as major phenotypic determinants. Furthermore, we show that Live-seq can be used to sequentially profile the transcriptomes of individual macrophages before and after stimulation with LPS, thus enabling the direct mapping of a cells trajectory. Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

molecular biology↗

bioRxiv2020

Deterministic scRNA-seq of individual intestinal organoids reveals new subtypes and coexisting distinct stem cell pools

Single-cell RNA-sequencing (scRNA-seq) has transformed our ability to resolve cellular properties across systems. However, current scRNA-seq platforms are one-size-fits-all approaches that are tailored toward large cell inputs (> 1,000 cells), rendering them inefficient and costly when processing small, individual tissue samples. This important drawback tends to be resolved by loading bulk samples, but this yields confounded mosaic cell population read-outs. To overcome these technological limitations, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo. We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics. In comparison to other microfluidics systems, the active flow control driving DisCo, enables continuous operation and processing of low-input samples (< 100 cells) at high capture efficiency (> 70%). To underscore the unique capabilities of our approach, we analyzed intestinal organoid development by "DisCo-ing" 31 individual organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a+ stem cell population which persists as symmetrical cysts even under differentiation conditions. Furthermore, we uncovered a so far uncharacterized "gobloid" subtype consisting predominantly of precursor and mature (Muc2+) goblet cells. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity among small, individual tissues.

bioengineering↗

bioRxiv2019

A highly parallel, 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 (>2d), 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 approach, FloChIP, automates and miniaturizes ChIP in a beadless fashion while facilitating the downstream library preparation process through on-chip chromatin tagmentation. FloChIP is fast (<2h), has a wide dynamic range (from 106 to 500 cells), is high-throughput (up to 64 parallel, antibody- or sample-multiplexed experiments) and is compatible with both histone mark and transcription factor ChIP. In addition, FloChIPs interconnected design allows for straightforward chromatin re-immunoprecipitation, thus constituting the first example of a microfluidic sequential ChIP-seq system. Finally, we demonstrate FloChIPs high-throughput capacity by performing ChIP-seq of the transcription factor MEF2A in 32 distinct human lymphoblastoid cell lines, providing novel 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.

bioengineering↗