Biology subjects

Nam, J.-W.

Publications and source records attributed to Nam, J.-W..

10 recordsLinked to original sources

bioRxiv2026

Mitochondrial metabolic remodeling drives innate immune activation in Drosophila hemocytes

Innate immune cells rapidly reprogram their metabolism upon activation, yet the metabolic basis of this flexibility in invertebrate systems remains largely unexplored. Here, we investigate the metabolic landscape of Drosophila larval hemocytes, functional analogs of vertebrate myeloid cells, across developmental stages, genotypes, and immune activation states, by combining metabolic flux measurements with single-cell transcriptomics. Under homeostatic conditions, hemocytes rely predominantly on mitochondrial oxidative phosphorylation for ATP production, with minimal glycolytic contribution. Immune activation, particularly lamellocyte differentiation, drives enhanced mitochondrial respiration and metabolic flexibility, accompanied by structural remodeling of the mitochondrial network. Mechanistically, functional lamellocytes require Drp1-mediated mitochondrial fission and utilize glucose and trehalose as primary carbon sources to sustain mitochondrial respiration, which is essential for effective immune responses. Overall, these findings establish that mitochondrial metabolic reprogramming is a conserved feature of innate immune activation in myeloid-like immune cells and reveal an evolutionarily ancient link between mitochondrial dynamics and immune cell activation, with implications for understanding metabolic regulation of innate immunity in invertebrate models and beyond.

developmental biology↗

bioRxiv2024

shRNAI: a deep neural network for the design of highly potent shRNAs

miRNA-mimicking short hairpin RNA (shRNAmir), which depends on whole miRNA biogenesis, has been used to elucidate the function of target genes and to develop therapeutic approaches due to its stable, robust downregulation. Despite efforts to design potent shRNAmir guide RNAs (gRNAs), biological features other than the sequence have not been fully considered. Here, we developed shRNAI, a convolutional neural network model for the prediction of highly potent shRNAmir gRNAs. The shRNAI model trained with gRNA sequences alone predicted more potent shRNAmir gRNAs than the existing algorithms. The shRNAI+ model, trained with the additional features of shRNAmir processibility and target site context, was further improved on both public and our experimental test datasets. Although the shRNAI models were trained on datasets generated with the CNNC motif-free shRNAmir backbone, they also exhibited better performance for the CNNC motif. Our study provides not only a rational framework for designing shRNAmir gRNAs for targets but also a means of designing optimal RNA interference drugs necessary for RNA therapeutics.

bioinformatics↗

bioRxiv2023

Comparative Interactome Analysis of α-arrestin Families in Human and Drosophila

The -arrestins form a large family of evolutionally conserved modulators that control diverse signaling pathways, including both G-protein-coupled receptor-(GPCR-) mediated and non-GPCR mediated pathways, across eukaryotes. However, unlike {beta}-arrestins, only a few -arrestin targets and functions have been characterized. Here, using affinity purification and mass spectrometry, we constructed interactomes for six human and twelve Drosophila -arrestins. The resulting high-confidence interactomes comprised 307 and 467 prey proteins in human and Drosophila, respectively. A comparative analysis of these interactomes predicted not only conserved binding partners, such as motor proteins, proteases, ubiquitin ligases, RNA splicing factors, and GTPase-activating proteins, but also those specific to mammals, such as histone modifiers and the subunits of V-type ATPase. Given the manifestation of the interaction between the human -arrestin, TXNIP, and the histone-modifying enzymes, including HDAC2, we undertook a global analysis of transcription signals and chromatin structures that were affected by TXNIP knockdown. We found that TXNIP activated targets by blocking HDAC2 recruitment to targets, a result that was validated by chromatin immunoprecipitation assays. Additionally, the interactome for an uncharacterized human -arrestin ARRDC5 uncovered multiple components in the V-type ATPase, which plays a key role in bone resorption by osteoclasts. Our study presents conserved and species-specific protein-protein interaction maps for -arrestins, which provide a valuable resource for interrogating their cellular functions for both basic and clinical research.

cell biology↗

bioRxiv2020

Ultra-fast Prediction of Somatic Structural Variations by Reduced Read Mapping via Pan-Genome k-mer Sets

Genome rearrangements often result in copy number alterations of cancer-related genes and cause the formation of cancer-related fusion genes. Current structural variation (SV) callers, however, still produce massive numbers of false positives (FPs) and require high computational costs. Here, we introduce an ultra-fast and high-performing somatic SV detector, called ETCHING, that significantly reduces the mapping cost by filtering reads matched to pan-genome and normal k-mer sets. To reduce the number of FPs, ETCHING takes advantage of a Random Forest classifier that utilizes six breakend-related features. We systematically benchmarked ETCHING with other SV callers on reference SV materials, validated SV biomarkers, tumor and matched-normal whole genomes, and tumor-only targeted sequencing datasets. For all datasets, our SV caller was much faster ([≥]15X) than other tools without compromising performance or memory use. Our approach would provide not only the fastest method for largescale genome projects but also an accurate clinically practical means for real-time precision medicine.

bioinformatics↗

bioRxiv2020

Single-cell transcriptome maps of myeloid blood cell lineages in Drosophila

Drosophila lymph gland, the larval hematopoietic organ comprised of prohemocytes and hemocytes, has been a valuable model for understanding mechanisms underlying hematopoiesis and immunity. Three types of mature hemocytes have been characterized in the lymph gland: plasmatocytes, lamellocytes, and crystal cells, which are analogous to vertebrate myeloid cells. Here, we used single-cell RNA sequencing to comprehensively analyze heterogeneity of developing hemocytes in the lymph gland, and discovered novel hemocyte types, stem-like prohemocytes, and intermediate prohemocytes. Additionally, we identified the emergence of the lamellocyte lineage following active cellular immunity caused by wasp infestation. We unraveled similarities and differences between embryonically derived- and larval lymph gland hemocytes. Finally, the comparison of Drosophila lymph gland hemocytes and human immune cells highlights similarities between prohemocytes and hematopoietic stem cell, and between mature hemocytes and myeloid cells across species. Altogether, our study provides detailed insights on the development and evolution of hematopoiesis at single-cell resolution.

developmental biology↗

bioRxiv2019

A single-cell survey of Drosophila blood

Drosophila blood cells, called hemocytes, are classified into plasmatocytes, crystal cells, and lamellocytes based on the expression of a few marker genes and cell morphologies, which are inadequate to classify the complete hemocyte repertoire. Here, we used single-cell RNA sequencing (scRNA-seq) to map hemocytes across different inflammatory conditions in larvae. We resolved plasmatocytes into different states based on the expression of genes involved in cell cycle, antimicrobial response, and metabolism together with the identification of intermediate states. Further, we discovered rare subsets within crystal cells and lamellocytes that express fibroblast growth factor (FGF) ligand branchless and receptor breathless, respectively. We demonstrate that these FGF components are required for mediating effective immune responses against parasitoid wasp eggs, highlighting a novel role for FGF signaling in inter-hemocyte crosstalk. Our scRNA-seq analysis reveals the diversity of hemocytes and provides a rich resource of gene expression profiles for a systems-level understanding of their functions. HighlightsO_LIscRNA-seq of Drosophila blood recovers plasmatocytes, crystal cells, and lamellocytes C_LIO_LIscRNA-seq identifies different plasmatocyte states based on the expression of genes involved in cell cycle regulation, antimicrobial response, and metabolism C_LIO_LIPseudotemporal ordering of single cells identifies crystal cell and lamellocyte intermediate states C_LIO_LIscRNA-seq uncovers a novel role for FGF signaling in inter-hemocyte crosstalk C_LI

immunology↗

bioRxiv2019

Quantification and Discovery of Acyl-ACPs by LC-MS/MS

Acyl carrier proteins (ACPs) are the scaffolds for fatty acid biosynthesis in living systems, rendering them essential to a comprehensive understanding of lipid metabolism; however, accurate quantitative methods to assess individual acyl-ACPs do not exist. A robust method was developed to quantify acyl-ACPs at picogram levels. Acyl-ACP elongation intermediates (3-hydroxyacyl-ACPs and 2, 3-trans-enoyl-ACPs), and unexpected medium chain (C10:1, C14:1) and polyunsaturated long chain acyl-ACPs (C16:3) were also identified, indicating the sensitivity of the method and that descriptions of lipid metabolism and ACP function are incomplete. Such ACPs are likely important to medium chain lipid production for fuels and highlight poorly understood lipid remodeling events in the chloroplast. The approach is broadly applicable to Type II FAS systems found in plants, bacteria, and mitochondria of animal and fungal systems because it uses a strategy that capitalizes on a highly conserved Asp-Ser-Leu-Asp (DSLD) amino acid sequence in ACPs to which acyl groups are attached. This allows for sensitive quantification using LC-MS/MS with de novo generated standards and an isotopic dilution strategy and will fill a gap in understanding, providing insights through quantitative exploration of fatty acid biosynthesis processes for optimal biofuels, renewable feed stocks, and medical studies in health and disease.

biochemistry↗

bioRxiv2017

Whole genome hybrid assembly and protein-coding gene annotation of the entirely black native Korean chicken breed Yeonsan Ogye

Yeonsan Ogye (YO), an indigenous Korean chicken breed (gallus gallus domesticus), has entirely black external features and internal organs. In this study, the draft genome of YO was assembled using a hybrid de novo assembly method that takes advantage of high-depth Illumina short-reads (232.2X) and low-depth PacBio long-reads (11.5X). Although the contig and scaffold N50s (defined as the shortest contig or scaffold length at 50% of the entire assembly) of the initial de novo assembly were 53.6Kbp and 10.7Mbp, respectively, additional and pseudo-reference-assisted assemblies extended the assembly to 504.8Kbp for contig N50 (pseudo-contig) and 21.2Mbp for scaffold N50, which included 551 structural variations including the Fibromelanosis (FM) locus duplication, compared to galGal4 and 5. The completeness (97.6%) of the draft genome (Ogye_1) was evaluated with single copy orthologous genes using BUSCO, and found to be comparable to the current chicken reference genome (galGal5; 97.4%), which was assembled with a long read-only method, and superior to other avian genomes (92~93%), assembled with short read-only and hybrid methods. To comprehensively reconstruct transcriptome maps, RNA sequencing (RNA-seq) and representation bisulfite sequencing (RRBS) data were analyzed from twenty different tissues, including black tissues. The maps included 15,766 protein-coding and 6,900 long non-coding RNA genes, many of which were expressed in the tissue-specific manner, closely related with the DNA methylation pattern in the promoter regions.

genomics↗

bioRxiv2017

Non-coding Transcriptome Maps Across Twenty Tissues of the Korean Black Chicken, Yeonsan Ogye

The Yeonsan Ogye (Ogye) is a rare Korean domestic chicken breed, the entire body of which, including its feathers and skin, has a unique black coloring. Although some protein-coding genes related to this unique feature have been examined, non-coding elements have not been globally investigated. In this study, high-throughput RNA sequencing and DNA methylation sequencing were performed to dissect the expression landscape of 14,264 Ogye protein-coding and 6900 long non-coding RNA (lncRNA) genes along with DNA methylation landscape in twenty different Ogye tissues. About 75% of Ogye lncRNAs showed tissue-specific expression whereas about 45% of protein-coding genes did. For some genes, the tissue-specific expression levels were inversely correlated with DNA methylation levels in their promoters. About 39% of the tissue-specific lncRNAs displayed functional association with proximal or distal protein-coding genes. In particular, heat shock transcription factor 2 (HSF2)-associated lncRNAs were discovered to be functionally linked to protein-coding genes that are specifically expressed in black skin tissues, tended to be more syntenically conserved in mammals, and were differentially expressed in black tissues relative to white tissues. Our results not only facilitate understanding how the non-coding genome regulates unique phenotypes but also should be of use for future genomic breeding of chickens.

bioinformatics↗

bioRxiv2017

High-confidence Coding and Noncoding Transcriptome Maps

The advent of high-throughput RNA-sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising ninety-nine billion RNAs-seq reads from the ENCODE, human BodyMap projects, The Cancer Genome Atlas, and GTEx, CAFE enabled us to predict the directions of about eighty-nine billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalogue that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes.

bioinformatics↗