Biology subjects

Cho, H.

Publications and source records attributed to Cho, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses

Designing and selecting cell culture media and feed are a key strategy to maximize culture performance in industrial biopharmaceutical processes. However, this is a major challenge for therapeutic proteins production since mammalian cells are very sensitive to their culture environment and require specific nutritional needs to grow and produce high-quality proteins such as antibodies. In this regard, in our previous study, we developed data-driven and in-silico model-guided systematic framework to investigate the effect of growth media on Chinese hamster ovary (CHO) cell culture performance, allowing us to design a new media formulation. To expand our exploration to feed, in this study, we evaluated two chemically defined feed media, A and B, in Ambr15 bioreactor runs using a monoclonal antibody-producing CHO K1 cell line. The feeds had a significant impact on cell growth, longevity, viability, and productivity and toxic metabolites production. Specifically, concentrated feed A was not sufficient to support prolonged cell culture and high titer compared to feed B. The framework systematically characterized the major metabolic bottlenecks in the TCA cycle and its related amino acid transferase reactions, and identified key design components, such as asparagine, aspartate, and glutamate, needed for highly productive cell cultures. From our results, we designed three new feeds by adjusting the levels of those amino acids and successfully validated their effectiveness in promoting cell growth and/or titer.

bioengineering↗

bioRxiv2023

Dynamic network-guided CRISPRi screen reveals CTCF loop-constrained nonlinear enhancer-gene regulatory activity in cell state transitions

Comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Our network modeling revealed that nonlinear enhancer-gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Utilizing hESC definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core endoderm lineage-specifying transcription factors, and many enhancers had strong effects mid-transition but weak effects post-transition. Through integrating enhancer activity measurements and three-dimensional enhancer-promoter interaction information, we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.

genetics↗

bioRxiv2023

BZINB model-based pathway analysis and module identification facilitates integration of microbiome and metabolome data

Integration of multi-omics data is a challenging but necessary step to advance our understanding of the biology underlying human health and disease processes. To date, investigations seeking to integrate multi-omics (e.g., microbiome and metabolome) employ simple correlation-based network analyses; however, these methods are not always well-suited for microbiome analyses because they do not accommodate the excess zeros typically present in these data. In this paper, we introduce a bivariate zero-inflated negative binomial (BZINB) model-based network and module analysis method that addresses this limitation and improves microbiome-metabolome correlation-based model fitting by accommodating excess zeros. We use real and simulated data based on a multi-omics study of childhood oral health (ZOE 2.0; investigating early childhood dental disease, ECC) and find that the accuracy of the BZINB model-based correlation method is superior compared to Spearmans rank and Pearson correlations in terms of approximating the underlying relationships between microbial taxa and metabolites. The new method, BZINB-iMMPath facilitates the construction of metabolite-species and species-species correlation networks using BZINB and identifies modules of (i.e., correlated) species by combining BZINB and similarity-based clustering. Perturbations in correlation networks and modules can be efficiently tested between groups (i.e., healthy and diseased study participants). Upon application of the new method in the ZOE 2.0 study microbiome-metabolome data, we identify that several biologically-relevant correlations of ECC-associated microbial taxa with carbohydrate metabolites differ between healthy and dental caries-affected participants. In sum, we find that the BZINB model is a useful alternative to Spearman or Pearson correlations for estimating the underlying correlation of zero-inflated bivariate count data and thus is suitable for integrative analyses of multi-omics data such as those encountered in microbiome and metabolome studies.

bioinformatics↗

bioRxiv2023

MARCH5-dependent NLRP3 ubiquitination is an essential step for NEK7 docking on the mitochondria

The NLRP3 inflammasome is a global immune-sensor that is activated by a repertoire of endogenous and exogenous stimuli. NLRP3 translocates to mitochondria but whether mitochondria involvement in the inflammasome assembly is unclear. Here, we show that the mitochondrial E3 ligase MARCH5 is a key regulator of NLRP3 inflammasome assembly. Myeloid cell-specific March5 conditional knockout (March5 cKO) mice exhibited an attenuated mortality rate upon LPS or Pseudomonas aeruginosa challenge. Macrophages derived from March5 cKO mice failed to secrete IL-1{beta} and IL-18 after microbial infection. Mechanistically, MARCH5 interacts with the NACHT domain of NLRP3 and promotes K27-linked polyubiquitination of K324 and K430 residues of NLRP3. Ubiquitination-defective NLRP3 mutants neither bind to NEK7, nor form NLRP3 oligomers, but remain binding to MAVS. Accordingly, NLRP3 mutants led to abortive ASC speck formation and diminished IL-1{beta} production. We propose that MARCH5-dependent NLRP3 ubiquitination creates a docking site for NEK7 binding, playing as a fundamental step-wise regulator on the mitochondria.

immunology↗

bioRxiv2022

Secure and Federated Genome-Wide Association Studies for Biobank-Scale Datasets

Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variants linked to health and disease1, 2. However, existing data sharing regulations limit the scope of such collaborations3. Although cryptographic tools for secure computation promise to enable collaborative analysis with formal privacy guarantees, existing approaches either are computationally impractical or support only simplified analyses4-7. We introduce secure federated genome-wide association studies (SF-GWAS), a novel combination of secure computation frameworks and distributed algorithms that empowers efficient and accurate GWAS on private data held by multiple entities while ensuring data confidentiality. SF-GWAS supports the most widely-used GWAS pipelines based on principal component analysis (PCA) or linear mixed models (LMMs). We demonstrate the accuracy and practical runtimes of SF-GWAS on five datasets, including a large UK Biobank cohort of 410K individuals, showcasing an order-of-magnitude improvement in runtime compared to previous work. Our work realizes the power of secure collaborative genomic studies at unprecedented scale.

bioinformatics↗

bioRxiv2022

Baculoviral COVID-19 Delta DNA vaccine cross-protects against SARS-CoV2 variants in K18-ACE2 transgenic mice

After severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) made the world tremble with a global pandemic, SARS-CoV2 vaccines were developed. However, due to the coronaviruss intrinsic nature, new variants emerged, such as Delta and Omicron, refractory to the vaccines derived using the original Wuhan strain. We developed an HERV-enveloped recombinant baculoviral DNA vaccine against SARS-CoV2 (AcHERV-COVID19S). A non-replicating recombinant baculovirus that delivers the SARS-CoV2 spike gene showed a protective effect against the homologous challenge in a K18-hACE2 Tg mice model; however, it offered only a 50% survival rate against the SARS-CoV2 Delta variant. Therefore, we further developed the AcHERV-COVID19 Delta vaccine (AcHERV-COVID19D). Cross-protection experiments revealed that mice vaccinated with the AcHERV-COVID19D showed 100% survival upon challenge with Delta and Omicron variants and 71.4% survival against prototype SARS-CoV2. These results support the potential of the viral vector vaccine, AcHERV-COVID19D, in preventing the spread of coronavirus variants such as Omicron and SARS-CoV2 variants. Author SummaryAfter the SARS-CoV2 pandemic, it is known that the existing vaccine has diminished efficacy against the emerging variants. We developed a baculoviral COVID19 DNA vaccine for the Delta variant (AcHERV-COVIS19D). Compared to AcHERV-COVID19S, designed to protect from the prototype of SARS-CoV2, AcHERV-COVID19D elicited higher humoral and cellular immunity and showed perfect protection against SARS-CoV2 delta strain and Omicron challenge. The broad and robust cellular immunity of the AcHERV-COVID19D vaccine appears to have played a significant role in the cross-protection of the Omicron variant. Our AcHERV-COVID19D can be a potential vaccine against emerging SARS-CoV2 variants.

immunology↗

bioRxiv2022

Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables

In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on proposing a precise mathematical model, then analyzing experimental data in the context of the chosen model. In this work, we present the first application of the sparse identification of non-linear dynamics (SINDy) algorithm to a real biological system in order discover cell-cell interaction dynamics in in vitro experimental data, using chimeric antigen receptor (CAR) T-cells and patient-derived glioblastoma cells. By combining the techniques of latent variable analysis and SINDy, we infer key aspects of the interaction dynamics of CAR T-cell populations and cancer. Importantly, we show how the model terms can be interpreted biologically in relation to different CAR T-cell functional responses, single or double CAR T-cell-cancer cell binding models, and density-dependent growth dynamics in either of the CAR T-cell or cancer cell populations. We show how this data-driven model-discovery based approach provides unique insight into CAR T-cell dynamics when compared to an established model-first approach. These results demonstrate the potential for SINDy to improve the implementation and efficacy of CAR T-cell therapy in the clinic through an improved understanding of CAR T-cell dynamics.

cancer biology↗

bioRxiv2022

The glutathione S-transferase Gstt1 is a robust driver of survival and dissemination in metastases

Identifying adaptive mechanisms of metastatic cancer cells remains an elusive question in the treatment of metastatic disease, particularly in pancreatic cancer (PDA), where the majority of patients present with metastatic lesions at the time of diagnosis. A loss-of-function shRNA targeted screen in metastatic-derived cells identified Gstt1, a member of the glutathione S-transferase superfamily, as uniquely required for metastasis and dissemination however dispensable for primary tumor growth. Gstt1 is expressed in early disseminated tumor cells (DTCs), is retained within a subpopulation of slow-cycling cells within established metastases and its inhibition led to a regression of macrometastatic lesions. This distinct Gstt1high population is highly metastatic and retains slow-cycling phenotypes, EMT features, and DTC characteristics compared to the Gstt1low population. Mechanistic studies indicate that in this subset of cells, Gstt1 maintains metastases by binding to and modifying intracellular fibronectin, regulating Fibronectin secretion from cancer cells and deposition into the metastatic microenvironment. We identified Gstt1 as a novel mediator of metastasis, highlighting the importance of metastatic heterogeneity and its influence on the metastatic tumor microenvironment.

cancer biology↗

bioRxiv2022

Proteome-scale induced proximity screens reveal highly potent protein degraders and stabilizers

Targeted protein degradation and stabilization are promising therapeutic modalities due to their potency and versatility. However, only few E3 ligases and deubiquitinases have been harnessed for this purpose. Moreover, there may be other protein classes that could be exploited for protein stabilization or degradation. Here, we used a proteome-scale platform to identify hundreds of human proteins that can promote the degradation or stabilization of a target protein in a proximity-dependent manner. This allowed us to comprehensively compare the activities of human E3s and deubiquitinases, characterize non-canonical protein degraders and stabilizers, and establish that effectors have vastly different activities against diverse targets. Notably, the top degraders were more potent against multiple therapeutically relevant targets than the currently used E3s CBRN and VHL. Our study provides a functional catalogue of effectors for targeted protein degradation and stabilization and highlights the potential of induced proximity screens for discovery of novel proximity-dependent protein modulators.

molecular biology↗

bioRxiv2022

Genetic architecture of creativity and extensive genetic overlap with psychiatric disorders revealed from genome-wide association analyses of 241,736 individuals

Creativity is heritable and exhibits familial aggregation with psychiatric disorders, but its genomic basis and genetic relationship with psychiatric disorders remain largely unknown. Here, we conducted a genome-wide association study (GWAS) using an expanded, machine learning-based definition of creativity in individuals of European ancestry from the UK Biobank (n = 241,736) and identified 25 creativity-associated loci. Extensive genetic overlap with psychiatric disorders, including schizophrenia, major depression, bipolar I disorder, attention deficit/hyperactivity disorder, and anorexia nervosa, was demonstrated by the genetic correlation, polygenic risk score, and MiXeR analyses. The condFDR and conjFDR analyses identified additional loci for creativity and psychiatric disorders, as well as shared genetic loci between creativity and psychiatric disorders. This GWAS showed significant correlations with GWASs using traditional definitions of creativity and GWASs adjusted for educational attainment. Our findings contribute to the understanding of the genetic architecture of creativity and reveal its polygenic relationships with psychiatric disorders.

genomics↗

bioRxiv2022

Life history strategies and niches of soil bacteria emerge from interacting thermodynamic, biophysical, and metabolic traits

Efficient biochemical transformation of belowground carbon by microorganisms plays a critical role in determining the long-term fate of soil carbon. As plants assimilate carbon from the atmosphere, up to 50% is exuded into the area surrounding growing roots, where it may be transformed into microbial biomass and subsequently stabilized through mineral associations. However, due to a hierarchy of interacting microbial traits, it remains elusive how emergent life-history strategies of microorganisms influence the processing of root exudate carbon. Here, by combining theory-based predictions of substrate uptake kinetics for soil bacteria and a new genome-informed trait-based dynamic energy budget model, we predicted life history traits and trade-offs of a broad range of soil bacteria growing on 82 root exudate metabolites. The model captured resource-dependent trade-offs between growth rate (power) and growth efficiency (yield) that are fundamental to microbial fitness in communities. During early phases of plant development, growth rates of bacteria were largely constrained by maximum growth potential, highlighting the predictive power of genomic traits during nutrient-replete soil conditions. In contrast, selection for efficiency was important later in the plant growing season, where the model successfully predicted microbial substrate preferences for aromatic organic acids and plant hormones. The predicted carbon-use efficiencies for growth on organics acids were much higher than typical values observed in soil. These predictions provide mechanistic underpinning for the apparent efficiency of the microbial route to mineral stabilization in the rhizosphere and add an additional layer of complexity to rhizosphere microbial community assembly.

ecology↗

bioRxiv2022

An epigenetic barrier sets the timing of human neuronal maturation

The pace of human brain development is highly protracted compared to most other species. The maturation of cortical neurons is particularly slow, extending over months to years to reach adult-like functions. Remarkably, such protracted timing is retained in cortical neurons derived from human pluripotent stem cell (hPSC) during in vitro differentiation or upon transplantation into the murine brain in vivo. Those findings suggest the presence of a cell intrinsic clock that sets the pace of neuronal maturation, though the molecular nature of such a clock has remained elusive. Here, we identify an epigenetic developmental program which sets the timing of human neuronal maturation. First, we developed a human PSC-based approach to synchronize the birth of cortical neurons in vitro which allowed us to define a detailed atlas of progressive morphological, functional, and molecular maturation in human cortical neurons. Interestingly, we observed a slow, temporal unfolding of maturation programs that is limited by the retention of a specific set of epigenetic factors. Loss-of-function studies for several of those factors in cortical neurons enables precocious molecular and physiological maturation. Remarkably, transient inhibition of EZH2, EHMT1/2 or DOT1L, at the progenitor stage primes newly born neurons to rapidly acquire mature properties upon differentiation. Therefore, our findings reveal that the rate at which human neurons mature is set well before neurogenesis through the establishment of an "epigenetic barrier" in progenitor cells. Mechanistically, this barrier acts by holding transcriptional maturation programs in a poised state that gets gradually released during neuronal differentiation to ensure the prolonged timeline characteristic of human cortical neuron maturation.

developmental biology↗

bioRxiv2022

Secure and federated linear mixed model association tests

Privacy-preserving algorithms for genome-wide association studies (GWAS) promise to facilitate data sharing across silos to accelerate new discoveries. However, existing approaches do not support an important, prevalent class of methods known as linear mixed model (LMM) association tests or would provide limited privacy protection, due to the high computational burden of LMMs under existing secure computation frameworks. Here we introduce SafeGENIE, an efficient and provably secure algorithm for LMM-based association studies, which allows multiple entities to securely share their data to jointly compute association statistics without leaking any intermediary results. We overcome the computational burden of LMMs by leveraging recent advances in LMMs and secure computation, as well as a novel scalable dimensionality reduction technique. Our results show that SafeGENIE obtains accurate association test results comparable to a state-of-the-art centralized algorithm (REGENIE), and achieves practical runtimes even for large datasets of up to 100K individuals. Our work unlocks the promise of secure and distributed algorithms for collaborative genomic studies.1

bioinformatics↗

bioRxiv2021

Oncomodulin derived from regeneration-associated macrophages in dorsal root ganglia promotes axon regeneration in the spinal cord

Preconditioning nerve injury drives pro-regenerative perineuronal macrophage activation in dorsal root ganglia (DRG). The present study reports that oncomodulin (ONCM) is produced from the regeneration-associated macrophages (RAMs) and strongly influences regeneration of DRG sensory axons. Preconditioning injury upregulated ONCM in DRG macrophages in a CCR2 dependent manner. ONCM in macrophages was necessary to produce RAMs in the in vitro model of neuron-macrophage interaction and played an essential role in for preconditioning or CCL2-induced neurite outgrowth. ONCM potently increased neurite outgrowth in cultured DRG neurons by activating a distinct gene set, particularly neuropeptide-related genes. Increasing extracellularly secreted ONCM in DRGs sufficiently enhanced capacity of neurite outgrowth. To achieve sustained ONCM activity in vivo, recombinant ONCM was encapsulated by a reducible epsilon-poly(L-lysine)-nanogel (REPL-NG) system based on electrostatic interaction. Localized injection of REPL-NG/ONCM complex into DRGs achieved a remarkable long-range axonal regeneration beyond spinal cord lesion, surpassing the extent of the preconditioning effects.

neuroscience↗

bioRxiv2021

Secretin channel-interactors prevent antibiotic influx during type IV pili assembly in P. aeruginosa

Type IV pili (T4P) are important virulence factors involved in host attachment and other aspects of bacterial pathogenesis. In Gram-negative bacteria, the T4P filament is polymerized from pilin subunits at the platform complex in the inner membrane (IM) and exits the outer membrane (OM) through the OM secretin channel. Although essential for T4P assembly and function, the OM secretin complexes can potentially impair the permeability barrier function of the OM and allow the entry of antibiotics and other toxic molecules. The mechanism by which Gram-negative bacteria prevent secretin-mediated OM leakage is currently not well understood. Here, we report a discovery of SlkA and SlkB (PA5122 and PA5123) that prevent permeation of several classes of antibiotics through the secretin channel of Pseudomonas aeruginosa type IV pili. We found these periplasmic proteins interact with the OM secretin complex and prevent toxic molecules from entering through the channel when there is a problem in the assembly of the T4P IM subcomplexes or when docking between the OM and IM complexes is defective. Thus, our results indicate that the secretin channel-interacting proteins play an important role in maintaining the OM permeability barrier, suggesting they may be attractive targets for potentiators that sensitize Gram-negative pathogens to antibiotics that are normally ineffective at penetrating the OM.

microbiology↗

bioRxiv2021

TREM2 regulates purinergic receptor-mediated calcium signaling and motility in human iPSC-derived microglia

The membrane protein TREM2 (Triggering Receptor Expressed on Myeloid cells 2) regulates key microglial functions including phagocytosis and chemotaxis. Loss-of-function variants of TREM2 are associated with increased risk of Alzheimers disease (AD). Because abnormalities in Ca2+ signaling have been observed in several AD models, we investigated TREM2 regulation of Ca2+ signaling in human induced pluripotent stem cell-derived microglia (iPSC-microglia) with genetic deletion of TREM2. We found that iPSC-microglia lacking TREM2 (TREM2 KO) show exaggerated Ca2+ signals in response to purinergic agonists, such as ADP, that shape microglial injury responses. This ADP hypersensitivity, driven by increased expression of P2Y12 and P2Y13 receptors, results in greater release of Ca2+ from the endoplasmic reticulum (ER) stores, which triggers sustained Ca2+ influx through Orai channels and alters cell motility in TREM2 KO microglia. Using iPSC-microglia expressing the genetically encoded Ca2+ probe, Salsa6f, we found that cytosolic Ca2+ tunes motility to a greater extent in TREM2 KO microglia. Despite showing greater overall displacement, TREM2 KO microglia exhibit reduced directional chemotaxis along ADP gradients. Accordingly, the chemotactic defect in TREM2 KO microglia was rescued by reducing cytosolic Ca2+ using a P2Y12 receptor antagonist. Our results show that loss of TREM2 confers a defect in microglial Ca2+ response to purinergic signals, suggesting a window of Ca2+ signaling for optimal microglial motility.

neuroscience↗

bioRxiv2021

A Combination Strategy of Solubility Enhancers for Effective Production of Soluble and Bioactive Human Enterokinase

Enterokinase is one of the hydrolases that catalyze hydrolysis to regulate biological processes in intestinal visceral mucosa. Enterokinase plays an essential role in accelerating the process of protein digestion as it converts trypsinogen into active trypsin by accurately recognizing and cleaving a specific peptide sequence, (Asp)4-Lys. Due to its exceptional substrate specificity, enterokinase is widely used as a versatile molecular tool in various bioprocessing, especially in removing fusion tags from recombinant proteins. Despite its biotechnological importance, mass production of soluble enterokinase in bacteria still remains an unsolved challenge. Here, we present an effective production strategy of human enterokinase using tandemly linked solubility enhancers consisting of thioredoxin, phosphoglycerate kinase or maltose-binding protein. The resulting enterokinases exhibited significantly enhanced solubility and bacterial expression level while retaining enzymatic activity, which demonstrates that combinatorial design of fusion proteins has the potential to provide an efficient way to produce recombinant proteins in bacteria.

bioengineering↗

bioRxiv2021

Distribution-based comprehensive evaluation ofmethods for differential expression analysis inmetatranscriptomics

Understanding the function of the human microbiome is important; however, the development of statistical methods specifically for the microbial gene expression (i.e., metatranscriptomics) is in its infancy. Many currently employed differential expression analysis methods have been designed for different data types and have not been evaluated in metatranscriptomics settings. To address this gap, we undertook a comprehensive evaluation and benchmarking of ten differential analysis methods for metatranscriptomics data. We used a combination of real and simulated data to evaluate performance (i.e., model fit, type I error, false discovery rate, and sensitivity) of the methods: log-normal (LN), logistic-beta (LB), MAST, DESeq2, metagenomeSeq, ANCOM-BC, LEfSe, ALDEx2, Kruskal-Wallis, and two-part Kruskal-Wallis. The simulation was informed by supragingival biofilm microbiome data from 300 preschool-age children enrolled in a study of early childhood caries (ECC), whereas validations were sought in two additional datasets from an ECC study and an inflammatory bowel disease (IBD) study. The LB test showed the highest sensitivity in both small and large samples and reasonably controlled type I error. Contrarily, MAST was hampered by inflated type I error. Upon application of the LN and LB tests in the ECC study, we found that genes C8PHV7 and C8PEV7, harbored by the lactate-producing Campylobacter gracilis, had the strongest association with childhood dental diseases. This comprehensive model evaluation offer practical guidance for selection of appropriate methods for rigorous analyses of differential expression in metatranscriptomics. Selection of an optimal method increases the possibility of detecting true signals while minimizing the chance of claiming false ones.

bioinformatics↗