Biology subjects

Kim, D.-K.

Publications and source records attributed to Kim, D.-K..

27 records · Page 2Linked to original sources

bioRxiv2020

A SARS-CoV-2 - host proximity interactome

Viral replication is dependent on interactions between viral polypeptides and host proteins. Identifying virus-host protein interactions can thus uncover unique opportunities for interfering with the virus life cycle via novel drug compounds or drug repurposing. Importantly, many viral-host protein interactions take place at intracellular membranes and poorly soluble organelles, which are difficult to profile using classical biochemical purification approaches. Applying proximity-dependent biotinylation (BioID) with the fast-acting miniTurbo enzyme to 27 SARS-CoV-2 proteins in a lung adenocarcinoma cell line (A549), we detected 7810 proximity interactions (7382 of which are new for SARS-CoV-2) with 2242 host proteins (results available at covid19interactome.org). These results complement and dramatically expand upon recent affinity purification-based studies identifying stable host-virus protein complexes, and offer an unparalleled view of membrane-associated processes critical for viral production. Host cell organellar markers were also subjected to BioID in parallel, allowing us to propose modes of action for several viral proteins in the context of host proteome remodelling. In summary, our dataset identifies numerous high confidence proximity partners for SARS-CoV-2 viral proteins, and describes potential mechanisms for their effects on specific host cell functions.

systems biology↗

bioRxiv2020

Exostosin-1 Glycosyltransferase Regulates Endoplasmic Reticulum Architecture and Dynamics

The endoplasmic reticulum (ER) is a central eukaryotic organelle with a tubular network made of hairpin proteins linked by hydrolysis of GTP nucleotides. Among post-translational modifications initiated at the ER level, glycosylation is the most common reaction. However, our understanding of the impact of glycosylation on ER structure remains unclear. Here, we show that Exostosin-1 (EXT1) glycosyltransferase, an enzyme involved in N-glycosylation, is a key regulator of ER morphology and dynamics. We have integrated multi-omics data and super-resolution imaging to characterize the broad effect of EXT1 inactivation, including ER shape-dynamics-function relationships in mammalian cells. We have observed that, inactivating EXT1 induces cell enlargement and enhances metabolic switches such as protein secretion. In particular, suppressing EXT1 in mouse thymocytes causes developmental dysfunctions associated to ER network extension. Our findings suggest that EXT1 drives glycosylation reactions involving ER structural proteins and high-energy nucleotide sugars, which might also apply to other organelles.

cell biology↗

bioRxiv2020

Global BioID-based SARS-CoV-2 proteins proximal interactome unveils novel ties between viral polypeptides and host factors involved in multiple COVID19-associated mechanisms

The worldwide SARS-CoV-2 outbreak poses a serious challenge to human societies and economies. SARS-CoV-2 proteins orchestrate complex pathogenic mechanisms that underlie COVID-19 disease. Thus, understanding how viral polypeptides rewire host protein networks enables better-founded therapeutic research. In complement to existing proteomic studies, in this study we define the first proximal interaction network of SARS-CoV-2 proteins, at the whole proteome level in human cells. Applying a proximity-dependent biotinylation (BioID)-based approach greatly expanded the current knowledge by detecting interactions within poorly soluble compartments, transient, and/or of weak affinity in living cells. Our BioID study was complemented by a stringent filtering and uncovered 2,128 unique cellular targets (1,717 not previously associated with SARS-CoV-1 or 2 proteins) connected to the N- and C-ter BioID-tagged 28 SARS-CoV-2 proteins by a total of 5,415 (5,236 new) proximal interactions. In order to facilitate data exploitation, an innovative interactive 3D web interface was developed to allow customized analysis and exploration of the landscape of interactions (accessible at http://www.sars-cov-2-interactome.org/). Interestingly, 342 membrane proteins including interferon and interleukin pathways factors, were associated with specific viral proteins. We uncovered ORF7a and ORF7b protein proximal partners that could be related to anosmia and ageusia symptoms. Moreover, comparing proximal interactomes in basal and infection-mimicking conditions (poly(I:C) treatment) allowed us to detect novel links with major antiviral response pathway components, such as ORF9b with MAVS and ISG20; N with PKR and TARB2; NSP2 with RIG-I and STAT1; NSP16 with PARP9-DTX3L. Altogether, our study provides an unprecedented comprehensive resource for understanding how SARS-CoV-2 proteins orchestrate host proteome remodeling and innate immune response evasion, which can inform development of targeted therapeutic strategies.

systems biology↗

bioRxiv2020

A SARS-CoV-2 BioID-based virus-host membrane protein interactome and virus peptide compendium: new proteomics resources for COVID-19 research

Key steps of viral replication take place at host cell membranes, but the detection of membrane-associated protein-protein interactions using standard affinity-based approaches (e.g. immunoprecipitation coupled with mass spectrometry, IP-MS) is challenging. To learn more about SARS-CoV-2 - host protein interactions that take place at membranes, we utilized a complementary technique, proximity-dependent biotin labeling (BioID). This approach uncovered a virus-host topology network comprising 3566 proximity interactions amongst 1010 host proteins, highlighting extensive virus protein crosstalk with: (i) host protein folding and modification machinery; (ii) membrane-bound vesicles and organelles, and; (iii) lipid trafficking pathways and ER-organelle membrane contact sites. The design and implementation of sensitive mass spectrometric approaches for the analysis of complex biological samples is also important for both clinical and basic research proteomics focused on the study of COVID-19. To this end, we conducted a mass spectrometry-based characterization of the SARS-CoV-2 virion and infected cell lysates, identifying 189 unique high-confidence virus tryptic peptides derived from 17 different virus proteins, to create a high quality resource for use in targeted proteomics approaches. Together, these datasets comprise a valuable resource for MS-based SARS-CoV-2 research, and identify novel virus-host protein interactions that could be targeted in COVID-19 therapeutics.

cell biology↗

bioRxiv2019

The first finding of lichen Solorina saccata at an algific talus slope in Korea

An algific talus slope is composed of broken rocks with vents connected to an ice cave, releasing cool air in summer and relatively warmer air in winter to maintain a more stable microclimate all year round. Such geological features create a very unusual and delicate ecosystem. Although there are around 25 algific talus slopes in Korea, lichen ecology of these areas had not been investigated to date. In this study, we report the first exploration of lichen ecology at an algific talus slope, Jangyeol-ri, in Korea. A total of 37 specimens were collected over 2017-2018. Morphological and sequencing analysis revealed 27 species belonging to 18 genera present in the area. Of particular interest among these species was Solorina saccata, as it has previously not been reported in Korea and most members of genus Solorina are known to inhabit alpine regions of the Northern Hemisphere. We provide here a taxonomic key for S. saccata alongside molecular phylogenetic analyses and prediction of potential habitats in South Korea. Sequences were generated from all S. saccata specimens collected in this study, together with three S. saccata specimens from China for comparison. Phylogenetic analysis based on nuclear small subunit (nuSSU) showed that all the S. saccata specimens are tightly grouped into one clade with high support values (P=0.99) and showed close relatedness to S. spongiosa than S. crocea. Additional analyses were carried out using concatenated sequences: 65 sequences of mitochondrial small subunit (mtSSU) combined with nuLSU and 66 sequences of RPB1 with nuLSU. In these analyses, genus Peltigera was found to be the closest genus to S. saccata. Furthermore, regions in South Korea potentially suitable for Solorina spp. were predicted based on climatic features of known habitats around the globe. Our results showed that the suitable areas are mostly at high altitudes in mountainous areas where the annual temperature range doesnt exceed 26.6{degrees}C. Further survey of other environmental conditions determining the suitability of Solorina spp. should lead to a more precise prediction of suitable habitats and trace the origin of Solorina spp. in Korea.

ecology↗

bioRxiv2019

Potential Autoimmune Association between Benign Paroxysmal Positional Vertigo and Immune-mediated Skin Conditions: Population-based Cohort Study

BackgroundBenign paroxysmal positional vertigo (BPPV), an idiopathic disorder of sudden sensorineural hearing loss and vertigo, shares many similarities with two common skin conditions, atopic dermatitis (AD) and vitiligo. Recent studies have suggested that BPPV may be related to or triggered by autoimmune conditions, notably hypothyroidism and giant cell arteritis (GCA).\n\nObjectiveThese evidences prompted the authors to entertain the possibility of immunological bridge between BPPV and the two skin conditions. The authors have tested this hypothesis with population-based cohort from the National Health Insurance Service Database of Korea.\n\nMethodsA cohort of 1.1 million patients was extracted from the DB. Using{chi} 2 tests, prevalence of the two skin disorders in terms of BPPV status was analysed.\n\nResultsIn AD patients, the prevalence of BPPV was 30% lower, while there was no statistically significant relationship between BPPV prevalence and vitiligo. The relationship between vitiligo and BPPV was significant in younger subgroup only. Socio-economic subgroup analysis revealed the observed patterns are primarily a middle-upper class phenomenon.\n\nLimitationsUncertainty regarding temporal sequence of onset, and lack of detail on disease severity and subtype might have kept the authors from drawing more refined conclusion.\n\nConclusionAD and vitiligo might be linked to BPPV through the action of certain components of cellular immunity, but follow-up studies based on large population cohort would be needed to add more substance to our findings.

epidemiology↗

bioRxiv2019

Genotype-dependent and non-gradient patterns of RSV gene expression

Respiratory syncytial virus (RSV) is a nonsegmented negative-strand (NNS) RNA virus and a leading cause of severe lower respiratory tract illness in infants and the elderly. Transcription of the ten RSV genes proceeds sequentially from the 3 promoter and requires conserved gene start (GS) and gene end (GE) signals. Previous studies using the prototypical GA1 genotype Long and A2 strains have indicated a gradient of gene transcription. However, recent reports show data that appear inconsistent with a gradient. To better understand RSV transcriptional regulation, mRNA abundances from five RSV genes were measured by quantitative real-time PCR (qPCR) in three cell lines and cotton rats infected with virus isolates belonging to four different genotypes (GA1, ON, GB1, BA). Relative mRNA levels reached steady-state between four and 24 hours post-infection. Steady-state patterns were genotype-specific and non-gradient, where mRNA levels from the G (attachment) gene exceeded those from the more promoter-proximal N (nucleocapsid) gene across isolates. Transcript stabilities could not account for the non-gradient patterns observed, indicating that relative mRNA levels more strongly reflect transcription than decay. While the GS signal sequences were highly conserved, their alignment with N protein in the helical ribonucleocapsid, i.e., N-phase, was variable, suggesting polymerase recognition of GS signal conformation affects transcription initiation. The effect of GS N-phase on transcription efficiency was tested using dicistronic minigenomes. Ratios of minigenome gene expression showed a switch-like dependence on N-phase with a period of seven nucleotides. Our results indicate that RSV gene expression is in part sculpted by polymerases that initiate transcription with a probability dependent on GS signal N-phase.\n\nAuthor SummaryRSV is a major viral pathogen that causes significant morbidity and mortality, especially in young children. Shortly after RSV enters a host cell, transcription from its nonsegmented negative-strand (NNS) RNA genome starts at the 3 promoter and proceeds sequentially. Transcriptional attenuation is thought to occur at each gene junction, resulting in a gradient of gene expression. However, recent studies showing non-gradient levels of RSV mRNA suggest that transcriptional regulation may have additional mechanisms. We show using RSV isolates belonging to four different genotypes that gene expression is genotype-dependent and one gene (the G or attachment gene) is consistently more highly expressed than an upstream neighbor. We hypothesize that variable alignment of highly conserved gene start (GS) signals with nucleoprotein (i.e., variable GS N-phase) can affect transcription and give rise to non-gradient patterns of gene expression. We show using dicistronic RSV minigenomes wherein the reporter genes differ only in the N-phase of one GS signal that GS N-phase affects gene expression. Our results suggest the existence of a novel mechanism of transcriptional regulation that might play a role in other NNS RNA viruses.

molecular biology↗

bioRxiv2018

Network-based prediction of protein interactions

As biological function emerges through interactions between a cells molecular constituents, understanding cellular mechanisms requires us to catalogue all physical interactions between proteins [1-4]. Despite spectacular advances in high-throughput mapping, the number of missing human protein-protein interactions (PPIs) continues to exceed the experimentally documented interactions [5, 6]. Computational tools that exploit structural, sequence or network topology information are increasingly used to fill in the gap, using the patterns of the already known interactome to predict undetected, yet biologically relevant interactions [7-9]. Such network-based link prediction tools rely on the Triadic Closure Principle (TCP) [10-12], stating that two proteins likely interact if they share multiple interaction partners. TCP is rooted in social network analysis, namely the observation that the more common friends two individuals have, the more likely that they know each other [13, 14]. Here, we offer direct empirical evidence across multiple datasets and organisms that, despite its dominant use in biological link prediction, TCP is not valid for most protein pairs. We show that this failure is fundamental - TCP violates both structural constraints and evolutionary processes. This understanding allows us to propose a link prediction principle, consistent with both structural and evo-lutionary arguments, that predicts yet uncovered protein interactions based on paths of length three (L3). A systematic computational cross-validation shows that the L3 principle significantly outperforms existing link prediction methods. To experimentally test the L3 predictions, we perform both large-scale high-throughput and pairwise tests, finding that the predicted links test positively at the same rate as previously known interactions, suggesting that most (if not all) predicted interactions are real. Combining L3 predictions with experimen-tal tests provided new interaction partners of FAM161A, a protein linked to retinitis pigmentosa, offering novel insights into the molecular mechanisms that lead to the disease. Because L3 is rooted in a fundamental biological principle, we expect it to have a broad applicability, enabling us to better understand the emergence of biological function under both healthy and pathological conditions.\n\nSummaryWe unveil a fundamental organizing principle of biological networks and demonstrate its predictive power for uncovering novel protein interactions.

systems biology↗

bioRxiv2017

Quantifying Immune-Based Counterselection of Somatic Mutations

It is now well established that somatic mutations in protein-coding regions can generate neoantigens, and that these can be recognized by the immune system and contribute to clearance of developing cancers. However, there is currently no model that can quantitatively predict the neoantigenic effect of any given somatic mutation. Here, we examined signatures of immune selection pressure on the distribution of somatic mutations. We quantified the extent to which somatic mutations are significantly depleted in peptides that are predicted to be displayed by major histocompatibility complex (MHC) class I proteins. We characterized the dependence of this depletion on expression level. We then examined whether immune selection pressure on somatic mutations changes depending on whether the patient had either one or two MHC-encoding alleles that can display the peptide. Our results indicate that MHC-encoding alleles are, in general, incompletely dominant, i.e., that having two copies of the display-enabling allele is more effective in displaying that peptide than having just one copy. More generally, a quantitative understanding of counter-selection of identifiable subclasses of neoantigenic somatic variation could guide immunotherapy or aid in developing personalized cancer vaccines.

genetics↗