Biology subjects

Son, A.

Publications and source records attributed to Son, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Persistent Malignant Stem Cells Drive Relapse After Transplantation in the Myelodysplastic Neoplasms

The myelodysplastic neoplasms (MDS) are initiated in hematopoietic stem cells (HSCs). Allogeneic transplantation is the only curative treatment, but relapse remains common. To detect rare MDS HSCs, we developed an ultra-low-input DNA sequencing assay and applied it to a multicenter post-transplant cohort. HSC mutation detection preceded relapse by a mean of 98 days and strongly predicted relapse (95.7% vs. 30.3%; hazard ratio, 8.8; P=1.5e-7). Mutations detected only in unfractionated marrow did not predict relapse. We developed methods to measure donor-host HSC chimerism, improving relapse prediction sensitivity. Single-cell protein, DNA, and RNA analyses with mitochondrial lineage tracing confirmed MDS cell enrichment within immunophenotypically- and transcriptionally-defined HSCs, identifying shared ribosomal gene downregulation and candidate mechanisms of venetoclax sensitivity. Venetoclax/azacytidine depleted detectable MDS HSCs in longitudinally evaluated patients. These findings establish that HSC mutation detection predicts post-transplant relapse, provide a rationale for preemptive intervention, and define shared biological features of transplant-resistant MDS HSCs.

cancer biology↗

bioRxiv2026

Structural proteomics reveals a coagulation-complement accessibility signature of macrovascular invasion in hepatocellular carcinoma

Macrovascular invasion (MVI) and extrahepatic spread (EHS) define the most aggressive, treatment-refractory hepatocellular carcinoma (HCC), yet blood-based markers that report the underlying protein-network biology are lacking. Conventional proteomics measures protein abundance but not the conformational and protein-protein-interaction (PPI) states that govern function. We applied covalent proteome painting (CPP)--a dimethylation-based accessibility assay that reads out binding-site openness--to matched tumor and serum, reasoning that intravascular tumor dissemination remodels plasma protein complexes in a manner detectable as changes in accessibility. Eight treatment-native HCC patients were profiled by CPP using matched FFPE tumor and top-14- depleted serum on a Q Exactive Orbitrap HF. The 85 tumor-serum common proteins defined an 81-protein targeted panel, validated by multiple-reaction-monitoring (MRM) mass spectrometry with heavy stable-isotope-standard peptides (296 peptides; 3,717 light/heavy transition pairs) in 22 FFPE tumors and 22 matched sera. Accessibility was the light/heavy ratio (high, open; low, closed). We assessed differential accessibility, serum-tissue translatability, pathway enrichment, and biomarker/survival performance. Aggressive disease showed broadly decreased protein accessibility. MVI-associated changes were directionally concordant between tumor and serum (Spearman {rho}=0.21; 59% concordant), driven by coagulation and complement proteins (FGG, CTSD, LBP, C4BPA); the EHS axis did not translate. Decreased-accessibility proteins were enriched for complement-coagulation cascades and IGF/IGFBP transport. A six-protein serum accessibility signature discriminated MVI (leave-one-out cross-validated AUC 0.80; best single markers ceruloplasmin 0.83 and haemoglobin- 0.77), and MVI status trended with shorter overall survival (log-rank p=0.06). Accessibility-based serum proteomics captures MVI-associated protein-complex remodeling that abundance assays miss, nominating a coagulation/complement-anchored serum signature for vascular-invasive HCC that warrants prospective validation.

systems biology↗

bioRxiv2026

A targeted plasma-proteomic axis separates autoimmune thyroid disease from growth-hormone deficiency

Targeted mass spectrometry (multiple-reaction monitoring, MRM) enables reproducible, multiplexed quantification of plasma proteins, but whether a fixed targeted panel can resolve endocrine disorders with overlapping systemic features is unknown. We analyzed a 256-protein targeted panel (1,894 peptides; 3,790 transitions) quantified in 57 participants spanning autoimmune thyroid disease (Hashimotos thyroiditis, n=7; Graves disease, n=5) and growth-hormone deficiency (GHD; partial, n=26; complete, n=19). Protein abundances were obtained by transition summation, log2 transformation, and per-sample median normalization. We applied unsupervised analysis (PCA, PERMANOVA), differential expression (limma), an ordered severity-trend test, and leave-one-out cross-validated classification with feature selection performed strictly inside each fold. All 256 proteins were quantified in every sample (median inter-sample r=0.875). PC1 (36% variance) separated autoimmune thyroid disease from GHD (p=0.016), whereas the global four-group structure was not significant (PERMANOVA p=0.17). No protein reached FDR<0.05, but the autoimmune-versus-GHD contrast was strongly enriched for low p-values (26 proteins at p<0.05; binomial p=5.4x10-4). The signal was biologically coherent: immunoglobulin/B-cell-receptor proteins, including CD79A, were lower, whereas proteasome subunits (PSMC5, PSMC3) and the NF-{kappa}B subunit RELA were higher in autoimmune disease. A cross-validated classifier separated the two classes (AUC 0.72; permutation p=0.05; eight proteins selected in all folds), whereas GHD severity was not predictable (AUC 0.31). A fixed 256-protein targeted panel reproducibly captures an immunoglobulin/B-cell-receptor and proteasome/NF-{kappa}B axis that distinguishes autoimmune thyroid disease from GHD but cannot resolve within-class severity.

systems biology↗

bioRxiv2026

Sex and race shape serum protein biomarkers and bias diagnostic reference intervals

Clinical protein biomarkers--whether measured by FDA-cleared in-vitro diagnostic (IVD) assays or deployed as laboratory-developed tests (LDTs)--are routinely interpreted against fixed, population-agnostic reference intervals. Whether the baseline serum concentrations of these proteins differ systematically by sex and by self-reported race in healthy individuals has not been tested across a broad clinical panel on a single standardized platform. Using scheduled multiple reaction monitoring - mass spectrometry (MRM-MS) with stable-isotope-labelled internal standards, we quantified 87 proteins (39 FDA-cleared analytes; 48 LDT/research markers) in 60 healthy, age-matched donors balanced across three races (White, Hispanic, Black) and both sexes. Sex was a pervasive axis of variation: donors separated by sex in unsupervised multivariate space (PERMANOVA p = 0.020) but not by race (p = 0.14). Three FDA-target proteins differed by sex at FDR q < 0.05--sex hormone-binding globulin, haemoglobin- and albumin--with directions preserved within every race. Race differences were real but protein-specific, exemplified by ancestry-associated CD14. Critically, applying a single pooled 95% reference interval mis-flagged as many as [~]25% of a demographic subgroup as abnormal, versus the 5% expected. Demographic context should therefore be incorporated into reference intervals and decision thresholds for protein-based diagnostics.

molecular biology↗

bioRxiv2026

A targeted mass-spectrometry plasma proteome for simultaneous multi-disease screening

Population health screening is fragmented across dozens of single-condition assays. We asked whether one targeted mass-spectrometry measurement of the plasma proteome could screen simultaneously for many common diseases. Using multiple-reaction-monitoring LC-MS/MS, we quantified 126 proteins (509 peptides) directly in crude plasma from 490 individuals spanning 16 diseases (eight cancers, three inflammatory or renal conditions, and five metabolic and lifestyle disorders) plus age- and sex-matched controls, each protein referenced to a stable-isotope-labelled internal standard. Proteome variation was organised primarily by disease rather than demographics. Cross-validated classifiers detected each disease against matched controls with a mean AUROC of 0.979, a 17-way model identified the specific disease at roughly ten times chance, and a 20-protein subset reproduced full-panel performance. We show that these within-cohort estimates are optimistic upper bounds because each disease was acquired as a separate case-control batch without independent validation. We quantify this, establishing analytical feasibility and defining the validation required for translation.

molecular biology↗

bioRxiv2026

Age-dependent Structural Reorganization of the Human Plasma Proteome

Aging is characterized by progressive physiological decline, yet the molecular mechanisms underlying these changes remain incompletely understood. Although extensive work has examined age-related alterations in protein abundance, the age-dependent structural reorganization of proteins and their interaction networks remains largely unexplored. Here, we quantitatively characterize the structural dynamics of plasma proteins across healthy adult aging and identify age-dependent accessibility patterns that may serve as candidate structural biomarkers. We employed Covalent Protein Painting (CPP) coupled with multiple reaction monitoring (MRM)-based LC-MS/MS to analyze plasma from 24 healthy individuals spanning four age groups (20s to 50s, n = 6 per group). Lysine surface accessibility changes were analyzed using cosine similarity trajectory matching and limma-based linear modeling. The intersection of the two approaches defined five reproducible age-dependent trajectories encompassing 27 proteins and 57 peptides. Integrating STRING/Cytoscape network analysis with AlphaFold3 multimer complex prediction localized several CPP-detected peptides to within [~]5 [A] of predicted protein-protein interaction interfaces (KNG1, C3; REN, ALB; and ALB, FGB), suggesting that age-associated accessibility changes are organized at interaction interfaces rather than occurring as isolated local events. Our findings indicate that the human plasma proteome undergoes coordinated, network-level changes in structural accessibility during adult aging, providing a framework for structure-based biomarker discovery. Because CPP signal reflects both conformational accessibility and protein abundance, and because the cohort is modest and cross-sectional, the trajectories reported here are framed as hypothesis-generating and are interpreted with these constraints made explicit throughout.

molecular biology↗

bioRxiv2026

Structural basis of chaperone mechanisms in cells and the evolutionary emergence of the protein world

How chaperones mediate protein folding in the crowded cell environment remains poorly understood. To gain insight, we developed CHAP-SEQ to examine how chaperones affect protein folding in cells at high throughput and amino acid resolution. Performing CHAP-SEQ using three chaperone proteins and one chaperone RNA reveals distinct modes of folding assistance. Chaperone proteins act preferentially on hydrophobic core residues, whereas chaperone RNA primarily targets structural or dynamic signatures. Furthermore, while the chaperone RNA has little preference for clients baseline foldability, the chaperone proteins favor clients with greater intrinsic foldability. These differences are consistent with an evolutionary hypothesis in which greater chaperone complexity played a role in the formation of stable hydrophobic cores, suggesting a potential link between chaperone function and the evolution of protein folding.

biochemistry↗

bioRxiv2025

Essential Resources for Curated Immune Markers and Antibody Panels in Cytometry Analysis

The immune system, fundamental to numerous biological research fields, is increasingly investigated at single-cell resolution using high-dimensional flow cytometry and mass cytometry technologies. These approaches require comprehensive immunomarker information and carefully designed antibody panels that address the technical challenges of isotopic and spectral overlap inherent in metal/fluorescent-labeled antibodies. While immune cell markers have been extensively characterized and systematically catalogued, antibody panel information remains fragmented across the literature. To bridge this critical gap, we present ImapDB (Immune cell Marker and Panel Database), a novel Python-based graphical user interface that consolidates curated information on cell markers and antibody panels. ImapDB integrates data from commercial guidebooks, peer-reviewed literature, and validated research sources, currently focusing on normal human immune cell states. The database encompasses 127 distinct immune cell subtypes with over 350 validated markers and includes 45 commercial and 23 custom research antibody panels. Available on GitHub (https://github.com/kimlab-cnu/Cell_Marker_GUI), ImapDB serves as a centralized repository designed to streamline immune profiling assays and enhance research efficiency.

bioinformatics↗

bioRxiv2025

Biomarker Discovery via Integrative Multi-omics for Children exposed to Humidifier Disinfectant

RationaleExposure to humidifier disinfectants has been linked to an array of pulmonary disorders and diminished lung functionality particularly reduced Forced Vital Capacity (FVC). ObjectivesThis investigation sought to identify diagnostic biomarkers for early detection of children at elevated risk of developing chronic respiratory conditions following such exposure. MethodsOur research employed a comprehensive multi-omics strategy analyzing 70 pediatric patients alongside 10 controls, seamlessly integrating clinical assessments with transcriptomics, methylomics, proteomics, and metabolomics data. The analytical framework utilized a sophisticated combination of Non-negative Matrix Factorization (NMF), Multi-Omics Factor Analysis (MOFA), and advanced machine learning algorithms. Measurements and Main ResultsNMF clustering uncovered distinctive protein expression patterns associated with integrin-mediated signaling pathways and immune response mechanisms. Complementarily, MOFA identified latent factors correlating with lung function metrics, highlighting critical molecular pathways involved in integrin cell surface interactions and lipid metabolism regulation. Machine learning-based analysis facilitated the development of a multi-marker panel-comprising IGHV2-70, LysoPC (16:0), and hexadecyl ferulate-which achieved 81.46% accuracy in identifying pulmonary dysfunction cohort. ConclusionsThese findings suggest that alterations in integrin-related signaling networks and dysregulation of lipid metabolism play pivotal roles in mediating the long-term pulmonary consequences of humidifier disinfectant exposure. The proposed multi-marker panel offers significant potential for enhanced risk stratification and timely therapeutic intervention. At a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSExtensive epidemiological evidence has established the causal relationship between humidifier disinfectant exposure and pulmonary dysfunction; however, clinically validated biomarkers for predicting chronic lung disease progression remain limited. Pediatric populations demonstrate unique pathophysiological mechanisms distinct from adults, highlighting the critical necessity for biomarker identification grounded in comprehensive molecular understanding. Despite advances in omics technologies, recent investigations have encountered significant obstacles in achieving deeper mechanistic insights, predominantly attributable to methodological constraints in harmonizing clinical phenotypes with high-dimensional molecular datasets. What This Study Adds to the FieldThis investigation elucidates the fundamental contributions of integrin-mediated signaling cascades and lipid metabolic networks to persistent pulmonary dysfunction following humidifier disinfectant exposure. Our analyses revealed coordinated regulation of integrin signaling pathways and immune response networks through NMF clustering, indicating dynamic temporal evolution of inflammatory responses during chronic disease progression, with temporally distinct molecular signatures identified across discrete observation intervals. Multi-omics factor analysis (MOFA) corroborated integrin pathway dysregulation while additionally uncovering systematic suppression of lipid metabolic processes. Furthermore, machine learning algorithms enabled development of a robust three-component biomarker panel--encompassing IGHV2-70, LysoPC (16:0), and hexadecyl ferulate--demonstrating 81.46% classification accuracy for pulmonary dysfunction phenotypes. Collectively, these findings substantially advance mechanistic understanding of chronic lung injury in vulnerable pediatric cohorts and identify clinically relevant biomarkers with translational potential for risk stratification and therapeutic targeting in clinical practice.

systems biology↗

bioRxiv2025

Proteomic Signatures of Hepatitis B Virus Mutations Reveal Genotype-Specific Host Responses and Biomarker Candidates

Hepatitis B virus (HBV) remains a global health challenge, with viral genetic heterogeneity and mutation-driven resistance complicating treatment outcomes. While previous genomic and transcriptomic studies have characterized HBV mutations, the proteomic consequences of these variants remain underexplored. In this study, we applied liquid chromatography- mass spectrometry (LC-MS)-based proteomics and systems biology approaches to serum samples from 60 HBV-infected patients, stratified by mutation-defined genotype signatures. Four genotype groups were generated, including those harboring mutation related to liver disease progression (rt269/s184) and basal core promoter/precore mutations (A1762T/G1896A). Comparative analyses of 406 high-abundance plasma proteins revealed distinct proteomic signatures, particularly in the ##AG group lacking mutation related to liver disease progression motifs. This group exhibited elevated CRISPLD2 and HSPD1 expression, implicating a dual axis of anti-inflammatory buffering and chaperone-mediated viral processes. Network and co-expression analyses identified modules enriched in focal adhesion, extracellular matrix remodeling, angiogenesis, and PI3K/Akt signaling--pathways tightly linked to hepatocarcinogenesis. Protein-protein interaction enrichment further highlighted disruption of chaperone networks, cytoskeletal regulation, and unfolded protein response. These findings provide molecular evidence for genotype-specific host-virus interactions, nominate CRISPLD2 and HSPD1 as biomarker candidates, and suggest therapeutic strategies targeting PI3K/Akt and microenvironmental pathways. Our results underscore the value of proteomics in refining genotype-informed risk stratification and personalized management in chronic HBV.

systems biology↗

bioRxiv2025

In Silico Design of APOE ε4 Interaction Inhibitor Peptides for Alzheimer's Disease

BackgroundProtein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzheimers disease (AD), characterized by its complex pathogenesis, poses an increasing societal burden with population aging. The APOE {varepsilon}4 allele represents the strongest genetic risk factor for late-onset AD, yet its pathological mechanisms remain incompletely understood. MethodsWe employed artificial intelligence-driven peptide design to elucidate the pathological interaction between APOE {varepsilon}4 and amyloid precursor protein (APP). Using advanced AI algorithms, we identified critical binding interfaces and designed mimetic peptides targeting the APOE {varepsilon}4-APP interaction site. Peptide efficacy was evaluated through comprehensive molecular dynamics simulations. ResultsOur analysis revealed key residues mediating APOE {varepsilon}4-APP binding. The designed inhibitory peptides demonstrated stable interaction with target sites, favorable binding energetics, and sustained structural integrity throughout simulations. Lead candidate effectively disrupted APOE {varepsilon}4- APP complex formation in silico. ConclusionThis study presents a novel AI-powered approach for developing PPI-targeted therapeutics against AD. Our computationally validated peptide inhibitors offer promising therapeutic candidates that warrant experimental validation. These findings demonstrate the potential of integrating artificial intelligence with structural biology for accelerating drug discovery in neurodegenerative diseases.

bioinformatics↗

bioRxiv2025

Integrative Analysis of Proteomics and Metabolomics Reveals Impacts of Sam2 Knockout on Autism Spectrum Disorders

Neurokine Sam2 deficiency is associated with behavioral abnormalities including heightened anxiety and fear responses across evolutionarily conserved model organisms. Here, we employed an integrated proteomics and metabolomics approach using liquid chromatography-mass spectrometry (LC-MS) to elucidate molecular signatures associated with autism spectrum disorder (ASD) in Sam2 knockout mice. Comparative analysis of blood plasma samples from Sam2 knockout and wild-type mice revealed substantial alterations in both proteomic and metabolomic profiles. Proteomic analysis identified 68 differentially expressed proteins (comprising 102 peptides), with notable upregulation of complement component C1qc and downregulation of apolipoprotein A1 (Apoa1), implicating dysregulation of complement cascade pathways. Metabolomic profiling uncovered 15 significantly altered metabolites: nine upregulated species including D-glucuronic acid and 5,10-Methylenetetrahydrofolate, and six downregulated metabolites including folinic acid and acetate. Integrative pathway analysis revealed perturbations in glycolysis/gluconeogenesis and glycerophospholipid metabolism, providing mechanistic insights into the molecular consequences of Sam2 deficiency. These findings identify potential biomarkers for anxiety-related disorders and ASD while advancing our understanding of the complex interplay between genetic alterations and proteomic-metabolomic networks in neurodevelopmental conditions. Our results establish a foundation for developing targeted therapeutic interventions and highlight the utility of multi-omics approaches in dissecting the molecular basis of behavioral disorders.

systems biology↗

bioRxiv2025

Th9-endothelial cell crosstalk promotes inflammatory atherosclerotic cardiovascular disease

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death, and understanding its pathogenic drivers is critical for effective prevention and treatment. Inflammation has a critical role in ASCVD, and patients with inflammatory diseases are at increased risk. However, the key inflammatory mediator promoting ASCVD are incompletely understood, a major barrier when targeting inflammation to prevent ASCVD. Here, we found that interleukin-9 (IL-9) producing T helper cells (Th9) were significantly associated with ASCVD in patients with the autoimmune disease psoriasis. Th9 cells were poised to migrate to coronary vessels and were identified in atherosclerotic plaque. In vivo, murine inflammatory atherogenesis was prevented by IL-9 blockade and by IL-9 receptor (IL-9R) deletion in endothelial cells. In human arterial endothelial cells, IL-9R/STAT3 signaling promoted endothelial dysfunction, angiogenesis, and release of leukocyte chemoattractants. These findings suggest that in autoimmune diseases like psoriasis, Th9/IL-9 promote atherosclerosis by directly targeting endothelial cells, and that IL-9R/STAT3 signaling could be a promising therapeutic target for ASCVD. eTOC SummaryBaral et. al. investigate individuals who are at high risk for atherosclerosis due to underlying inflammatory disease and use mouse models of cardiovascular disease to uncover a role for interleukin-9-producing T helper 9 cells in the pathogenesis of inflammatory atherosclerosis.

immunology↗

bioRxiv2024

Elucidating Interactome Dynamics of the A2A Adenosine Receptor

Polydeoxyribonucleotide (PDRN) is a tissue regeneration substance that resembles human DNA and is present in human cells, mullets, salmons, and flatfish. It stimulates physiological regeneration and metabolic activity. The regenerative and metabolic effects of PDRN are attributed to the activation of Adenosine A2A receptors (ADORA2A), which increases the production of angiogenesis factors and growth factors. Activation of ADORA2A leads to the activation of ADORA2A-interacting proteins with similar functions. To investigate the changes and dynamics of proteins in the presence of PDRN, we conducted selected reaction monitoring-mass spectrometry (SRM-MS) to quantify 491 proteins, 3,852 peptides. Through peptide-level analysis, we founded 374 proteins and 1,193 peptides demonstrating both up-regulation and down-regulation in expression. We conducted gene ontology (GO) analysis and physical network analysis and discovered a novel network of proteins related to neuronal differentiation among the ADORA2A-interacting protein. Based on network analysis, we found indirect interactions with MAPK1 and MP2K1, which are known to influence neuronal cell differentiation and suggest the formation of a network involving MAPK signaling transduction. Finally, using AlphaFold multimer, we were able to predict interaction sites among ADORA2A-interacting proteins in the network associated with neuronal cell differentiation. Specifically, we predicted five interaction sites between ADORA2A and NTRK1 (which interacts with ADORA2A), forming the edge. Thus, we provided indicators for further research using ADORA2A present in robust network and highlighted the potential of PDRN to impact neuronal differentiation.

systems biology↗

bioRxiv2023

In vivo Protein Footprinting Reveals the Dynamic Conformational Changes of Proteome of Multiple Tissues in Progressing Alzheimer's Disease

Numerous studies have investigated changes in protein expression at the system level using proteomic mass spectrometry, but only recently have studies explored the structure of proteins at the proteome level. We developed covalent protein painting (CPP), a protein footprinting method that quantitatively labels exposed lysine, and have now extended the method to whole intact animals to measure surface accessibility as a surrogate of in vivo protein conformations. We investigated how protein structure and protein expression change as Alzheimers disease (AD) progresses by conducting in vivo whole animal labeling of AD mice. This allowed us to analyze broadly protein accessibility in various organs over the course of AD. We observed that structural changes of proteins related to energy generation, carbon metabolism, and metal ion homeostasis preceded expression changes in the brain. We found that proteins in certain pathways undergoing structural changes were significantly co-regulated in the brain, kidney, muscle, and spleen.

systems biology↗

bioRxiv2023

PPIAT:Target mass spectrometry based Protein-Protein interaction analytics tool

MotivationThe formation of protein networking is critical for understanding the biological functions of proteins and the underlying mechanisms of disease. To gain insights into target proteins that interact with a particular disease, we need to profiling all the proteins involved in the disease beforehand. However, the profiling results may not necessarily match with an experimental target protein. Therefore, it is necessary to identify physical protein-protein interactions (PPIs) using various methods. The cross-linking mass spectrometry (XL-MS) method is a representative approach to identify physical interactions between proteins, but there are many challenges in calculating theoretical mass values for application to target mass spectrometry. ResultsThe research team developed PPIAT, which integrates information on reviewed human proteins, protein-protein interactions, cross-linkers, enzymes, and modifications. All functions are available for free on the web application. Availability and implementationThe PPIAT is available at www.ppiat.cnu.ac.kr Contactkimlab@cnu.ac.kr

bioinformatics↗

bioRxiv2023

The Role of Terminal Uridyl Transferases in the Circadian Rhythm

The 3 terminal oligo-uridylation, a post-transcriptional mRNA modification, is conserved among eukaryotes and drives mRNA degradation, thereby affecting several key biological processes such as animal development and viral infection. Our TAIL-seq experiment of mouse liver mRNA collected from six zeitgeber times reveals transcripts with rhythmic poly(A) tail lengths and demonstrates that overall 3 terminal uridylation frequencies at mRNA poly(A) tail very-ends undergo rhythmic change. Consistently, major terminal uridylyl transferases, TUT4 and TUT7, have cycling protein expression in mouse liver corresponding to 3 terminal uridylation rhythms, indicating that the cycling expression of TUTases correlates with the rhythmic pattern of uridylation. Furthermore, the double knockdown of TUT4 and TUT7 in U2OS cells lengthens the circadian period and decreases the rhythmic amplitude of clock gene expression. Our work thoroughly profiles the dynamic changes in poly(A) tail lengths and terminal modifications and uncovers uridylation as a post-transcriptional modulator in the mammalian circadian clock.

molecular biology↗

bioRxiv2022

G-quadruplexes rescuing protein folding

Maintaining the health of the proteome is a critical cellular task. Recently, we found G-quadruplex (G4) nucleic acids are especially potent at preventing protein aggregation in vitro and could at least indirectly improve the protein folding environment of E. coli. However, the roles of G4s in protein folding were not yet explored. Here, through in vitro protein folding experiments, we discover that G4s can accelerate protein folding by rescuing kinetically trapped intermediates to both native and near-native folded states. Time-course folding experiments in E. coli further demonstrate that these G4s primarily improve protein folding quality in E. coli as opposed to preventing protein aggregation. The ability for a short nucleic acid to rescue protein folding opens up the possibility of nucleic acids and ATP-independent chaperones to play considerable roles in dictating the ultimate folding fate of proteins.

biophysics↗