Biology subjects

Tong, B.

Publications and source records attributed to Tong, B..

8 recordsLinked to original sources

bioRxiv2025

Predicting allergy and postpartum depression from incomplete compositional microbiome

Time series of compositional data are a common format for many high-throughput studies of biological molecules, e.g., analyzing the response to a treatment or with the aim of predicting an outcome. However, data from some time points may be missing, which reduces the size of the complete dataset. We propose a method for binary classification that includes imputation for missing values and logarithmic transformation of compositional data. Imputation approaches entail models that incorporate artificial data alongside true measurements, thereby supplementing the dataset. We consider two datasets from prospective analyses with as-sociated target labels, aiming to improve prediction accuracy. We predict infants food allergies from their gut microbiome with a balanced accuracy of 0.72. We forecast postpartum depression based on gut microbiome data collected during pregnancy, with a balanced accuracy of 0.62. Features extracted from the microbiome time series, specifically ratios of bacterial abundance, are statistically significant indicators of depression.

bioinformatics↗

bioRxiv2024

Discovery of molecular glues that bind FKBP12 and novel targets using DNA-barcoded libraries

Molecular glues are small molecules that engage their target and presenter proteins cooperatively. FKBP12 molecular glues (FK506 and rapamycin) were discovered several decades ago and have been used clinically, but our understanding of the breadth of FKBP12 molecular glues and targets has yet to be fully revealed. To identify novel targets of FKBP12 molecular glues, we constructed and screened a multi-million-member non-macrocyclic FKBP12-ligand DNA-encoded library using 25 structurally distinct proteins. Synthesis and validation of selected hits in biophysical and cell-based assays confirm FKBP12-dependent molecular-glue recruitment to bromodomain-containing protein 9 (BRD9) and quinoid dihydropteridine reductase (QDPR). One glue showed no measurable binding to QDPR alone but had appreciable binding in the presence of FKBP12 using either purified proteins or intact cells. The sites of recruitment were characterized with mutational analysis, competition-based methods and X-ray crystallography. The results of this study confirm that FKBP12-binding DELs can yield novel molecular glues generating highly selective FKBP12-target protein interactions.

biophysics↗

bioRxiv2023

Rational screening for cooperativity in small-molecule inducers of protein-protein associations

The hallmark of a molecular glue is its ability to induce cooperative protein-protein interactions, leading to the formation of a ternary complex, despite weaker binding towards one or both individual proteins. Notably, the extent of cooperativity distinguishes molecular glues from bifunctional compounds, a second class of inducers of protein-protein interactions. However, apart from serendipitous discovery, there have been limited rational screening strategies for the high cooperativity exhibited by molecular glues. Here, we propose a binding-based screen of DNA-barcoded compounds on a target protein in the presence and absence of a presenter protein, using the "presenter ratio", the ratio of ternary enrichment to binary enrichment, as a predictive measure of cooperativity. Through this approach, we identified a range of cooperative, noncooperative, and uncooperative compounds in a single DNA-encoded library screen with bromodomain (BRD)9 and the VHL-elongin C-elongin B (VCB) complex. Our most cooperative hit compound, 13-7, exhibits micromolar binding affinity to BRD9 but nanomolar affinity for the ternary complex with BRD9 and VCB, with cooperativity comparable to classical molecular glues. This approach may enable the discovery of molecular glues for pre-selected proteins and thus facilitate the transition to a new paradigm of molecular therapeutics.

biophysics↗

bioRxiv2023

Chemoproteomic Profiling Reveals that Anti-Cancer Natural Product Dankastatin B Covalently Targets Mitochondrial VDAC3

Chlorinated gymnastatin and dankastatin alkaloids derived from the fungal strain Gymnascella dankaliensis have been reported to possess significant anti-cancer activity but their mode of action is unknown. These members possess electrophilic functional groups that may undergo covalent bond formation with specific proteins to exert their biological activity. To better understand the mechanism of action of this class of natural products, we mapped the proteome-wide cysteine-reactivity of the most potent of these alkaloids, dankastatin B, using activitybased protein profiling chemoproteomic approaches. We identified a primary target of dankastatin B in breast cancer cells as cysteine C65 of the voltage-dependent anion selective channel on the outer mitochondrial membrane VDAC3. We demonstrated direct and covalent interaction of dankastatin B with VDAC3. VDAC3 knockdown conferred hyper-sensitivity to dankastatin B-mediated anti-proliferative effects in breast cancer cells indicating that VDAC3 was at least partially involved in the anti-cancer effects of this natural product. Our study reveals a potential mode of action of dankastatin B through covalent targeting of VDAC3 and highlight the utility of chemoproteomic approaches in gaining mechanistic understanding of electrophilic natural products.

biochemistry↗

bioRxiv2022

S373P Mutation of Spike Protein in SARS-CoV-2 Stabilizes Omicron

A cluster of several newly occurring mutations on Omicron are found at the {beta}-core region of spike proteins receptor-binding domain (RBD), where mutation rarely happened before. Notably, the binding of SARS-CoV-2 to human receptor ACE2 via RBD happens in a dynamic airway environment, where mechanical force caused by coughing or sneezing occurs and applies to the proteins. Thus, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to measure the stability of RBDs and found that the mechanical stability of Omicron RBD increased by ~20% compared with the wild-type. Molecular dynamics simulations revealed that Omicron RBD showed more hydrogen bonds in the {beta}-core region due to the closing of the -helical motif caused primarily by mutation S373P, which was further confirmed experimentally. Moreover, the binding ability of Omicron to ACE2 is promoted with a stabilized RBD. This work reveals the effect of the highly conserved mutation S373P which is present in most Omicron subvariants, including BA.1-5, BQ. 1, XBB, and CH.1.1.

biophysics↗

bioRxiv2021

Mutation N501Y in RBD of Spike Protein Strengthens the Interaction between COVID-19 and its Receptor ACE2

SARS-CoV-2 is spreading around the world for the past year. Enormous efforts have been taken to understand its mechanism of transmission. It is well established now that the receptor-binding domain (RBD) of the spike protein binds to the human angiotensin-converting enzyme 2 (ACE2) as its first step of entry. Being a single-stranded RNA virus, SARS-CoV-2 is evolving rapidly. Recently, several variants such as B.1.1.7, B.1.351, and P.1, with a key mutation N501Y on the RBD, appear to be more infectious to humans. To understand its mechanism, we combined cell surface binding assay, kinetics study, single-molecule technique, and computational method to investigate the interaction between these RBD (mutations) and ACE2. Remarkably, RBD with the N501Y mutation exhibited a considerably stronger interaction characterized from all these methodologies, while the other two mutations from B.1.351 contributed to a less effect. Fluorescence-activated cell scan (FACS) assays found that RBD N501Y mutations are of higher binding affinity to ACE2 than the wild type. Surface plasmon resonance further indicated that N501Y mutation had a faster association rate and slower dissociation rate. Consistent with the kinetics study, atomic force microscopy-based single-molecule force microscopy quantify their strength on living cells, showing a higher binding probability and unbinding force for the mutation. Finally, Steered Molecular Dynamics (SMD) simulations on the dissociation of RBD-ACE2 complexes revealed that the N501Y introduced additional {pi}-{pi} and {pi}-cation interaction for the higher force/interaction. Taken together, we suggested that the reinforced interaction from N501Y mutation in RBD should play an essential role in the higher transmission of COVID-19 variants.

biophysics↗

bioRxiv2020

A Nimbolide-Based Kinase Degrader Preferentially Degrades Oncogenic BCR-ABL

Targeted protein degradation (TPD) and proteolysis-targeting chimeras (PROTACs) have arisen as powerful therapeutic modalities for degrading specific protein targets in a proteasome-dependent manner. However, a major limitation to broader TPD applications is the lack of E3 ligase recruiters. Recently, we discovered the natural product nimbolide as a covalent ligand for the E3 ligase RNF114. When linked to the BET family inhibitor JQ1, the resulting heterobifunctional PROTAC molecule was capable of selectively degrading BRD4 in cancer cells. Here, we show the broader utility of nimbolide as an E3 ligase recruiter for TPD applications. We demonstrate that a PROTAC linking nimbolide to the kinase and BCR-ABL fusion oncogene inhibitor dasatinib, BT1, selectively degrades BCR-ABL over c-ABL in leukemia cancer cells, compared to previously reported cereblon or VHL-recruiting BCR-ABL degraders that show opposite selectivity or in some cases inactivity. Further contrasting from cereblon or VHL-recruiting degradation, we show that BT1 treatment not only leads to BCR-ABL degradation, but also stabilizes the endogenous RNF114 substrate and tumor suppressor substrate p21. This leads to additional anti-proliferative effects in leukemia cancer cells beyond those observed with cereblon or VHL-recruiting BCR-ABL PROTACs. Thus, we further establish nimbolide as an additional general E3 ligase recruiter for PROTACs with unique additional benefits for oncology applications. We also further demonstrate the importance of expanding upon the arsenal of E3 ligase recruiters, as such molecules confer differing and unpredictable selectivity for the degradation of neo-substrate proteins.

biochemistry↗

bioRxiv2019

Integration of gut microbiome, host biomarkers, and urine metabolome data reveals networks of interactions associated with distinct clinical phenotypes

BackgroundComprehensive analyses of multi-omics data may provide insights into interactions between different biological layers in relation to distinct clinical features. Here we integrated data on the gut microbiota, blood parameters and urine metabolites of treatment-naive individuals presenting a wide range of metabolic disease phenotypes to delineate clinically meaningful associations.\n\nResultsTrans-omics correlation networks revealed that candidate gut microbial biomarkers and urine metabolite features covaried with distinct clinical phenotypes. Integration of the gut microbiome, the urine metabolome and the phenome revealed that variations in one of these three systems correlated with changes in the other two. Of specific note in relation to clinical parameters of liver function, we identified Eubacterium eligens, Faecalibacterium prausnitzii and Ruminococcus lactaris to be associated with a healthy liver function, whereas Clostridium bolteae, Tyzzerella nexills, Ruminococcus gnavus, Blautia hansenii, and Atopobium parvulum were associated with blood biomarkers for liver diseases. Variations in these microbiota features paralleled changes in specific urine metabolites. Network modeling yielded two core clusters including one large gut microbe-urine metabolite close-knit cluster and one triangular cluster composed of a gut microbe-blood-urine network, demonstrating close inter-system crosstalk especially between the gut microbiome and the urine metabolome.\n\nConclusionsDistinct clinical phenotypes are manifested in both the gut microbiome and the urine metabolome, and inter-domain connectivity takes the form of high-dimensional networks. Such networks may further our understanding of complex biological systems, and may provide a basis for identifying biomarkers for diseases.

microbiology↗