Biology subjects

Gan, M.

Publications and source records attributed to Gan, M..

11 recordsLinked to original sources

bioRxiv2026

Parallel Emergence and Adaptive Evolution of Multicountry Circulating Mycobacterium abscessus Clones

Mycobacterium abscessus (MAB) is a recently emerged bacterial pathogen causing an increasing number of human infections. Despite increasing recognition that different circulating clones contribute disproportionately to MAB population expansion, the global population dynamics and the evolutionary pressures underlying the emergence and spread of MAB clones remain incompletely understood. We analyzed 11,314 publicly available genomes of MAB isolates sampled from 30 countries and identified 38 recently emerged clones that have spread across multiple countries, including the seven previously described Dominant Circulating Clones (DCCs). There was a significant association between the time since the emergence of each circulating clone and its population size, with older clones generally having larger populations. Among the 26 circulating clones of M. abscessus subsp. abscessus, 12 carried the macrolide-susceptible erm(41) 28C genotype, highlighting clone-level variation in macrolide susceptibility. Genome-wide analyses identified 55 genes that were previously under purifying selection but showed evidence of positive selection during recent clade expansion. Collectively, our findings reveal that the recent global expansion of MAB comprises a broad continuum of newly emerged clones, accompanied by widespread shifts in gene-level selective pressures indicative of ongoing adaptation to new ecological environments.

microbiology↗

bioRxiv2026

Encoded metabolic remodeling amplifies drug resistance in Mycobacterium tuberculosis

Antibiotic pressure causes pathogens to evolve many forms of altered drug susceptibility. In addition to target or activator mutations conferring canonical drug resistance, mutations can serve as steppingstones to or enhancers of resistance. In clinical strains of Mycobacterium tuberculosis (Mtb), we find that idsA2, which encodes an isoprenyl pyrophosphate synthase involved in the synthesis of precursors for essential components of the cell wall and electron transport chain, is undergoing diversifying selection and that these mutations are associated with the acquisition of first-line antibiotic resistance. By engineering isogenic Mtb strains that express clinically prevalent variants of idsA2, we show that clinical variants increase the minimum inhibitory concentration of ethambutol and, to a lesser extent, of isoniazid. Targeted lipid analyses reveal that disrupting IdsA2 function redirects limited resources in the isoprenoid synthesis pathway, leading to increased production of decaprenylphosporyl pentose which can compete with ethambutol for binding to arabinosyltransferases. IdsA2 mutations most often occur after embB mutation and lead to a multiplicative increase in ethambutol resistance. Thus, identification of idsA2 mutations can be utilized to improve the specificity of genotypic ethambutol susceptibility testing. Together, this work defines idsA2 as an ethambutol resistance gene and demonstrates how metabolic remodeling can augment drug resistance. Author SummaryTuberculosis is the deadliest infectious disease in the world and becomes more difficult to treat with the acquisition of drug resistance. Defining the mechanisms and genetic basis of drug resistance will allow for improved screening and drug regimen optimization for treatment success. To identify previously unrecognized mechanisms of altered drug susceptibility, we have combined population genomics and experimental genetics approaches, focusing on Mycobacterium tuberculosis genes evolving in clinical strains. We identified idsA2 as a target of frequent mutations that are associated with drug resistance. Experimental data indicate that idsA2 variants decrease the susceptibility of the bacteria to multiple antibiotics through isoprenoid synthesis remodeling, with the strongest effect on ethambutol resistance. IdsA2 mutations often occur after embB mutations to multiplicatively increase ethambutol resistance. These data suggest that inclusion of idsA2 variants in drug resistance testing could improve the specificity of genotypic detection of ethambutol resistance.

microbiology↗

bioRxiv2025

Desiccation-induced DNA damage facilitates drug resistance in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is an obligate human pathogen that depends on its ability to spread from host-to-host to survive as a species. Yet, knowledge of transmission-specific traits remains lacking. Here, we report the discovery of a specific adaptive response to desiccation, a stress intrinsically linked to the generation of the aerosol droplets within which Mtb transmits. We show that desiccation inflicts oxidative damage and activates Mtbs DNA repair responses but that this repair is imperfect and results in mutations. We further show that activation of these DNA repair responses is accompanied by increased expression of the transcription-coupled repair factor, mfd, but that this expression serves to buffer the fitness cost of specific resistance-conferring mutations in rpoB, the target of the frontline drug rifampin, rather than to facilitate transcription-coupled DNA repair. Silencing mfd during aerosolization impairs survival of strains harboring the rifampin resistance allele S450L. This function is further supported by whole genome sequence data from over 50,000 clinically circulating strains. These studies indicate that Mtb has evolved transmission-specific stress responses that have enabled it to leverage desiccation-induced DNA damage as a potential source of genetic diversification and drug resistance.

microbiology↗

bioRxiv2025

Divergent conformational mechanisms of JAK2V617F and TYK2V678F mutations in Thrombocythemia and related disorders: Molecular Dynamics insights into pathway activation and therapeutic targeting

Thrombocythemia and related disorders are primarily driven by persistent activation of the JAK-STAT signaling pathway, which is frequently associated with valine-to-phenylalanine (VF) point mutations in the JAK2 and TYK2 proteins. However, the precise mechanisms underlying the sustained downstream pathway activation induced by these mutations remain unclear. To investigate this, we employed molecular dynamics simulations and computational biophysical approaches to examine how VF mutations sustain JAK-STAT pathway activation. Our analyses, encompassing energetics, interaction forces, and surface electrostatic charge distributions, revealed that these mutations predominantly alter the spatial conformations and stability of the proteins by modulating inter-dimeric interaction forces and binding free energies. Specifically, the V617F mutation in JAK2 enhanced the stability of the JAK2 dimer and suppressed the activity of the JH2 pseudokinase domain. Similarly, the V678F mutation in TYK2 reducing the binding strength of the JH1 kinase domain and the binding free energy, increasing the binding affinity at the dimer interface. Both mutations ultimately resulted in heightened JH1 kinase domain activity and aberrant activation of downstream signaling pathways. Electrostatic analyses further demonstrated that JAK2V617F strengthened attractive forces within the dimer and TYK2V678F mutation mitigated repulsive forces. Decreased binding free energy confirmed enhanced dimer stability in JAK2V617F and TYK2V678F mutants, driven by distinct mechanisms: reinforced JH2 domain interactions in JAK2V617F and domain compaction with reoriented interfaces in TYK2V678F. These insights delineate the mutation-specific allosteric networks that underpin the pathogenesis of thrombocythemia. Furthermore, they establish a molecular foundation for designing isoform-selective inhibitors that target conformational vulnerabilities, thereby presenting novel therapeutic opportunities. Author SummaryO_LIThe VF mutations located in JAK2 and TYK2 stabilizes the JH2 pseudokinase domain and enhances dimer interfaces to disrupt autoinhibition in JAK2, while it induces structural reorganization of the dimer FERM/SH2 domains and JH1 kinase conformation to promote substrate accessibility in TYK2. C_LIO_LIWe developed a novel multiscale analyses framework, integrating conformational analysis, electrostatic analysis, hydrogen bond and salt bridges, and free energy decomposition, to collaboratively elucidate the effects of VF mutations on the protein multimers. C_LIO_LIThese findings highlights divergent allosteric networks underlying pathogenic signaling, offering a molecular mechanisms for designing isoform-selective inhibitors targeting conformational vulnerabilities in myeloproliferative disorders. C_LI

biophysics↗

bioRxiv2025

Granuloma Dual RNA-Seq Reveals Composite Transcriptional Programs Driven by Neutrophils and Necrosis within Tuberculous Granulomas

Mycobacterial granulomas lie at the center of tuberculosis (TB) pathogenesis and represent a unique niche where infecting bacteria survive in nutrient-restricted conditions and in the face of a host immune response. The granulomas necrotic core, where bacteria reside extracellularly in humans, is difficult to assess in many experimentally tractable models. Here, using necrotic mycobacterial granulomas in adult zebrafish, we develop dual RNA-seq across different host genotypes to identify the transcriptional alterations that enable bacteria to survive within this key microenvironment. Through pharmacological and genetic interventions, we find that neutrophils within mature, necrotic granulomas promote bacterial growth, in part through upregulation of the bacterial devR regulon. We identify conserved suites of bacterial transcriptional programs induced only in the context of this unique necrotic extracellular niche, including bacterial modules related to K+ transport and rpf genes. Analysis of Mycobacterium tuberculosis strains across diverse lineages and human populations suggests that granuloma-specific transcriptional modules are targets for bacterial genetic adaptation in the context of human infection. Summary sentenceDual host-pathogen transcriptional profiling defines granuloma-specific programs during mycobacterial infection.

immunology↗

bioRxiv2024

Immunopeptidomics informs discovery and delivery of Mycobacterium tuberculosis MHC-II antigens for vaccine design

No currently licensed vaccine reliably prevents pulmonary tuberculosis (TB), a leading cause of infectious disease mortality. Developing effective new vaccines will require identifying which of the roughly 4000 proteins in the Mycobacterium tuberculosis (Mtb) proteome are presented on MHC class II (MHC-II) by infected human phagocytes and can be recognized by CD4+ T cells to mediate protective immunity. Vaccines must also elicit T cell responses recognizing the same peptide-MHC complexes presented by infected cells, and successful presentation of target human MHC-II peptides is currently challenging to evaluate and optimize. Here, we define antigenic targets for TB vaccine development by using mass spectrometry (MS) for proteome-wide discovery of Mtb epitopes presented on MHC-II by infected human cells. We next iteratively design and evaluate candidate mRNA vaccine immunogens, revealing design principles that enhance presentation of target MHC-II peptides. Our results will inform the development of new TB vaccine candidates.

microbiology↗

bioRxiv2023

Mycobacterial DnaQ is an Alternative Proofreader Ensuring DNA Replication Fidelity

Remove of mis-incorporated nucleotides ensures replicative fidelity. Although the {varepsilon}-exonuclease DnaQ is a well-established proofreader in the model organism Escherichia coli, proofreading in mycobacteria relies on the polymerase and histidinol phosphatase (PHP) domain of replicative polymerase despite the presence of an alternative DnaQ homolog. Here, we show that depletion of DnaQ in Mycolicibacterium smegmatis results in increased mutation rate, leading to AT-biased mutagenesis and elevated insertions/deletions in homopolymer tract. We demonstrated that mycobacterial DnaQ binds to the {beta}-clamp and functions synergistically with the PHP domain to correct replication errors. Further, we found that the mycobacterial DnaQ sustains replicative fidelity upon chromosome topological stress. Intriguingly, we showed that a naturally evolved DnaQ variant prevalent in clinical Mycobacterium tuberculosis isolates enables hypermutability and is associated with extensive drug resistance. These results collectively establish that the alternative DnaQ functions in proofreading, and thus reveal that mycobacteria deploy two proofreaders to maintain replicative fidelity.

microbiology↗

bioRxiv2023

GLI1 facilitates rheumatoid arthritis by collaborative regulation of DNA methyltransferases

Rheumatoid arthritis (RA) is characterized by joint synovitis and bone destruction, the etiology of which remains to be explored. Overactivation of M1 macrophages and osteoclasts has been thought a direct cause of joint inflammation and bone destruction. Glioma-associated oncogene homolog 1 (GLI1) has been revealed to be closely linked to bone metabolism. In this study, GLI1-expression in synovial tissue of RA patients showed to be positively correlated with RA-related scores and was highly expressed in collagen-induced arthritis (CIA) mouse articular macrophage-like cells. The decreased expression and inhibition of nuclear transfer of GLI1 downregulated macrophage M1 polarization and osteoclast activation, the effect of which was achieved by modulation of DNA methyltransferases (DNMTs) via transcriptional regulation and protein interaction ways. By pharmacological inhibition of GLI1, the proportion of proinflammatory macrophages and the number of osteoclasts were significantly reduced, and the joint inflammatory response and bone destruction in CIA mice were alleviated. This study clarified the mechanism of GLI1 in macrophage phenotypic changes and activation of osteoclasts, suggesting potential applications of GLI1 inhibitor in the clinical treatment of RA.

cell biology↗

bioRxiv2022

Dissecting Mutational Allosteric Effects in Alkaline Phosphatases Associated with Different Hypophosphatasia Phenotypes: An Integrative Computational Investigation

Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization, is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach for large-scale analysis of ALPL mutations - from nonpathogenic to severe HPPs is proposed. Allosteric molecular signatures of ALPL mutations were determined using an integrated pipeline of synergistic approaches including sequence and energetic-based analysis, structural topology network modeling and elastic network models. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control and mild and severe HPP phenotypes, and the developed machine learning model suggested that the topological network parameters could serve as is a robust indicator for severe mutations. Molecular dynamics simulations coupled with protein structure network was employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and we found that severe disease-associated mutations have a significantly greater effect on allosteric communications. The results of this study suggested that ALPL mutations associated with mild and severe HPPs tend to have different effects on protein stability on local scale and long-range communications caused by network rewiring. By linking disease phenotypes with allosteric molecular signatures, the proposed integrative computational approach elucidates the complex sequence-structure-allostery relationships of ALPL mutations and dissects the role of allosteric effects in the pathogenesis of HPPs. Author SummaryThe understanding of mutational genotype- disease phenotype relationship is a fundamental step for enabling precision medicine. It remains a challenging task to assess the molecular principle of the genotype- phenotype relationship. By focusing on Hypophosphatasia, a rare inherited disorder, as an example, we performed comprehensive analysis of single-amino-acid mutations in the encoded protein of Tissue Nonspecific Alkaline Phosphatase associated in terms of their sequence, structure, and dynamics properties. We further developed a machine learning -based method to classify different disease phenotypes, and the interpretability of the classification model was addressed by the structural-functional analysis of network topological important mutations. Our results highlighted the allosteric propensity of severe mutations, and show the potential allosteric principle of genotype- phenotype relationship.

biophysics↗

bioRxiv2020

Intra-host Variation and Evolutionary Dynamics of SARS-CoV-2 Population in COVID-19 Patients

As of middle May 2020, the causative agent of COVID-19, SARS-CoV-2, has infected over 4 million people with more than 300 thousand death as official reports1,2. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown. Here, using deep sequencing data, we achieved and characterized consensus genomes and intra-host genomic variants from 32 serial samples collected from eight patients with COVID-19. The 32 consensus genomes revealed the coexistence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparison of allele frequencies of the iSNVs revealed genetic divergence between intra-host populations of the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events among intra-host transmissions. Nonetheless, we observed a maintained viral genetic diversity within GIT, showing an increased population with accumulated mutations developed in the tissue-specific environments. The iSNVs identified here not only show spatial divergence of intra-host viral populations, but also provide new insights into the complex virus-host interactions.

genomics↗

bioRxiv2018

DeepCAPE: a deep convolutional neural network for the accurate prediction of enhancers

The establishment of a landscape of enhancers across human cells is crucial to deciphering the mechanism of gene regulation, cell differentiation, and disease development. High-throughput experimental approaches, though having successfully reported enhancers in typical cell lines, are still too costly and time consuming to perform systematic identification of enhancers specific to different cell lines under a variety of disease status. Existing computational methods, though capable of predicting regulatory elements purely relying on DNA sequences, lack the power of cell line-specific screening. Recent studies have suggested that chromatin accessibility of a DNA segment is closely related to its potential function in regulation, and thus may provide useful information in identifying regulatory elements. Motivated by the above understanding, we integrate DNA sequences and chromatin accessibility data to accurately predict enhancers in a cell line-specific manner. We proposed DeepCAPE, a deep convolutional neural network to predict enhancers via the integration of DNA sequences and DNase-seq data. We demonstrate that our model not only consistently outperforms existing methods in the classification of enhancers against background sequences, but also accurately predicts enhancers across different cell lines. We further visualize kernels of the first convolutional layer and show the match of identified sequence signatures and known motifs. We finally demonstrate the potential ability of our model to explain functional implications of putative disease-associated genetic variants and discriminate disease-related enhancers.

bioinformatics↗