Biology subjects

Inukai, S.

Publications and source records attributed to Inukai, S..

6 recordsLinked to original sources

bioRxiv2024

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors

A DNA sequence pattern, or "motif", is an essential representation of DNA-binding specificity of a transcription factor (TF). Any particular motif model has potential flaws due to shortcomings of the underlying experimental data and computational motif discovery algorithm. As a part of the Codebook/GRECO-BIT initiative, here we evaluated at large scale the cross-platform recognition performance of positional weight matrices (PWMs), which remain popular motif models in many practical applications. We applied ten different DNA motif discovery tools to generate PWMs from the "Codebook" data comprised of 4,237 experiments from five different platforms profiling the DNA-binding specificity of 394 human proteins, focusing on understudied transcription factors of different structural families. For many of the proteins, there was no prior knowledge of a genuine motif. By benchmarking-supported human curation, we constructed an approved subset of experiments comprising about 30% of all experiments and 50% of tested TFs which displayed consistent motifs across platforms and replicates. We present the Codebook Motif Explorer (https://mex.autosome.org), a detailed online catalog of DNA motifs, including the top-ranked PWMs, and the underlying source and benchmarking data. We demonstrate that in the case of high-quality experimental data, most of the popular motif discovery tools detect valid motifs and generate PWMs, which perform well both on genomic and synthetic data. Yet, for each of the algorithms, there were problematic combinations of proteins and platforms, and the basic motif properties such as nucleotide composition and information content offered little help in detecting such pitfalls. By combining multiple PMWs in decision trees, we demonstrate how our setup can be readily adapted to train and test binding specificity models more complex than PWMs. Overall, our study provides a rich motif catalog as a solid baseline for advanced models and highlights the power of the multi-platform multi-tool approach for reliable mapping of DNA binding specificities. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/619379v2_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@79561forg.highwire.dtl.DTLVardef@54c0aorg.highwire.dtl.DTLVardef@1c33f34org.highwire.dtl.DTLVardef@16a93ba_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

bioinformatics↗

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↗

bioRxiv2024

Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors

Gene expression is regulated by transcription factors (TFs), which recognize specific DNA sequence motifs. Several hundred putative human TFs, identified mainly by an apparent DNA-binding domain, lack known binding motifs1, and even for well-characterized TFs, it remains controversial to what degree motifs accurately reflect binding sites in living cells2,3. Here, we describe a systematic effort ("Codebook") to determine the sequence specificity of 332 putative and poorly characterized human TFs. Over 4,000 independent experiments, encompassing multiple in vitro and in vivo assays, produced motifs for just over half (177, or 53%), of which most are unique to a single protein, thereby extending the vocabulary of sequence recognition encoded by human TFs by [~]100 distinct motifs. Moreover, binding motifs identified in vitro are strongly enriched within cellular binding sites. Collectively, the data reveal tens of thousands of previously unknown, conserved, and direct TF binding sites across the human genome. These sites are concentrated in promoter regions, and are predictive of gene expression, illustrating that this new data atlas provides an important step forward in decoding the human genome.

genomics↗

bioRxiv2024

Lipogenic Lung Fibroblast-derived Extracellular Vesicles Mitigate Cigarette Smoke-Induced Chronic Obstructive Pulmonary Disease Pathologies through LAT1-mediated Alveolar Type II Cell Restoration

Emerging research has revealed specific cellular aberrations in Chronic Obstructive Pulmonary Disease (COPD), with a particular focus on alveolar type 2 (AT2) cells, which play a pivotal role in the restoration of damaged lung tissue and promotion of normal cellular differentiation. Lipofibroblasts (LipoFBs), which are stromal fibroblasts that house lipid droplets, have been identified in close proximity to AT2 cells and have been demonstrated to support AT2 function. In this study, we present a comprehensive investigation into the therapeutic potential of extracellular vesicles (EVs) derived from LipoFBs (LipoFB-EVs) in COPD treatment. They effectively mitigate key COPD pathologies such as cellular senescence and inflammatory responses in lung epithelial cells. This is achieved by reducing reactive oxygen species (ROS) levels and modulating DNA damage response pathways. Moreover, LipoFB-EVs demonstrate antifibrotic properties by inhibiting TGF-{beta}-induced myofibroblast differentiation, surpassing conventional antifibrotic drugs. They also aid in restoring impaired AT2 stem cells, which are crucial for lung homeostasis, by enhancing their viability, colony-forming ability, and proliferation. Furthermore, we identify the presence of L-type amino acid transporter 1 (LAT1) within LipoFB-EVs, which mediates amino acid uptake, particularly leucine transport, and contributes to the restoration of AT2 cell dysfunction. Importantly, the administration of LipoFB-EVs in murine models of COPD resulted in significant improvements in airway inflammation, remodeling, obstruction, cellular senescence, and alveolar emphysema induced by both short- and long-term CS exposure. Overall, our findings highlight the therapeutic potential of LipoFB-EVs as a novel regenerative therapy for COPD, offering promising avenues for future clinical interventions.

molecular biology↗

bioRxiv2024

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

systems biology↗

bioRxiv2023

DNA binding analysis of rare variants in homeodomains reveals novel homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and play important roles in regulating development, body patterning, and cellular differentiation. Here, we analyzed 92 human HD mutants, including disease-associated variants and variants of unknown significance (VUSs), for their effects on DNA binding activity. Many of the variants altered DNA binding affinity and/or specificity. Biochemical analysis and structural modeling identified 14 novel specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibited different effects on DNA binding. Variant effect prediction tools perform moderately well in distinguishing variants with altered binding affinity, but poorly in identifying those with altered specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and development of clinical diagnostics and precision therapies.

genetics↗