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Lim, W.

Publications and source records attributed to Lim, W..

At least 19 recordsLinked to original sources

Estimating Divergence Times and Diversification Rates with the Unresolved Fossilized Birth-Death Process

Tip-dating using Fossilized Birth-Death (FBD) models offers a favorable alternative to conventional node-dating analyses of the evolutionary timescale, bypassing various conceptual and technical difficulties. However, despite their increasing popularity in phylogenetic studies, their use has remained rather limited in taxonomic scope because of the difficulty in collecting morphological data, which is often required for tip-dating analyses, and computational intractability when a large number of fossils are present. Recent studies, however, suggest that FBD models can also be used in a principled way as priors for molecular clock analyses, even in the absence of morphological data, relying only on temporal information and given clade assignments. Heath et al. (2014) introduced an "unresolved" FBD model in which uncertainty in fossil placements is analytically integrated out when morphological data are unavailable, providing a potential solution to this problem. Here, we show that the topological enumeration scheme used by Heath et al. (2014) to marginalize over unresolved fossil attachments overcounts configurations in which multiple fossil taxa can be resolved as a clade, and we provide a correction to this factor, yielding a valid marginalized unresolved likelihood. We apply our implementation to empirical datasets of Cetacea, Emydidae, and Palaeodictyopterida, and show that our method converges and yields reasonable estimates within a reasonable amount of time, even when hundreds of fossils are present.

evolutionary biology↗

DICAROS: Diffeomorphic Ancestral Shape Reconstruction on Phylogenies

Reconstructing ancestral morphologies on a phylogenetic tree is a central task in evolutionary morphometrics. Established reconstruction methods, including multivariate Brownian-motion approaches, rely on linear assumptions and do not directly model the correlations between landmarks within a shape, which can oversimplify the reconstructed morphology. The DICAROS method (Diffeomorphic Independent Contrasts for Ancestral Reconstruction of Shapes; Severinsen et al., 2026) instead fuses sibling shapes along branches with large-deformation diffeomorphic (LDDMM) landmark dynamics that model these correlations, so that ancestors remain on the shape manifold. DICAROS was shown to outperform ordinary least-squares, Brownian-motion, and penalized-likelihood reconstruction, particularly on non-symmetric trees. The dicaros package repackages that pipeline as a documented, pip-installable tool that runs on arbitrary landmark datasets from a single command. It handles 2D and 3D landmarks, Newick and NEXUS trees, a choice of Euclidean or Frechet species means, optional anchor-based alignment, and tips backed by a single specimen, and it returns the reconstructed shapes for all nodes together with the tree relabelled at its internal nodes. We demonstrate dicaros on two new datasets: a 2D leaf dataset (217 species) and a 3D guenon skull dataset (22 species).

evolutionary biology↗

A hierarchical Bayesian framework accommodates intraspecific and interspecific variation in multivariate traits

Phylogenetic comparative methods are a critical tool in biology, providing the framework to test evolutionary hypotheses of phenotypic diversification. Accommodating intraspecific variation in multivariate analyses is critical for accurate evolutionary inference, but current methods that incorporate intraspecific variation either 1) assume that traits evolve independently or 2) that all taxa share the same intraspecific covariance structure. Violations of these assumptions can produce biased estimates of evolutionary parameters. Here, we introduce a hierarchical Bayesian framework for multivariate traits that jointly estimates taxon-specific intraspecific covariance structures alongside the underlying evolutionary process. This framework propagates uncertainty from sample size discrepancies and missing data, enabling the incorporation of highly variable morphological traits into phylogenetic analyses. Analysis of simulated data confirms that the model and implementation are well calibrated under the assumed generative model, including challenging datasets with more traits than individuals and substantial missing observations. Applied to perikymata spacing across the great ape clade, including modern humans and Neandertals, the framework recovers intraspecific covariance structures that differ among taxa and yields evolutionary rate estimates markedly more uniform across the tooth crown than those obtained when taxon means are fixed. Our method, which is applicable to other multivariate traits, provide a flexible, tractable approach to joint estimation of intraspecific variation and evolutionary process in multivariate traits.

evolutionary biology↗

STEM-LM: Spatio-Temporal Ecological Modeling via Masked Language Model for Joint Species Distribution

Joint species distribution models (JSDMs) are central to biodiversity forecasting and conservation decision-making. As ecological datasets grow in size, dimensionality, and spatio-temporal resolution, there is a need for flexible yet scalable JSDMs tailored to large-scale species observation data. Recent advances in masked language modeling for text and genomics suggest a natural alternative: by treating each species presence or absence as a token, and a sites species assemblage together with its spatio-temporal and ecological covariates as a sentence, we can learn joint co-occurrence structure by reconstructing masked species from their neighboring sites. We propose STEM-LM1, a Transformer-based JSDM that frames joint species distribution modeling as masked language modeling. By varying the masking rate during training, a single trained model supports both purely spatiotemporal/ecological prediction and conditioning on arbitrary subsets of observed species for joint co-occurrence inference at a given site. On a North American butterfly and a global plant distribution dataset, STEM-LM performs better or on par with other statistical and deep-learning based methods in terms of discriminative ranking, while producing substantially better rank-calibrated occurrence probabilities. Utilizing partial species observations at the same site greatly enhances prediction performance.

ecology↗

Ultra-large targeted DNA integrations in primary human cells

Genetic engineering experiments and therapies are constrained by the size of DNA integrations into human cells genomes. Existing AAV, lentiviral, and non-viral methods rapidly decrease in integration efficiency beyond [~]5kb of sequence. Through systematic evaluation of non-viral DNA template formats, we identified circular ssDNA and dsDNA as capable of mediating >5kb integrations. Large circular DNA delivery efficiency and its impacts on cell viability and payload expression could be significantly improved with small DNA "helper" plasmids, mRNA-encoded nucleases, and sequence design optimizations. Collectively, these modifications enabled ultra-large--up to 10 kb DNA--integrations at >20% efficiency in primary human T cells at the TRAC locus and at >60% efficiency in human iPSCs at the AAVS1 locus. Finally, we demonstrate that GMP clinical-manufactured T cells with ultra-large integrations are functional in vitro and in vivo. Overall, we identified optimal template architectures, delivery modes, and sequence design rules for ultra-large DNA integrations in both research and clinical settings to accelerate basic genetic research and next-generation cellular therapies.

genetics↗

Labile iron overload reprograms microglia and neurons for lipid droplet synthesis in the aging brain

Lipid-droplet (LD) accumulation emerges in microglia and neurons with age. Because neither cell type is specialized for lipid storage, LDs are linked to dysfunction. The upstream drivers of LD formation and their effects on neighboring cells remain unclear. Here, we identify a mitochondrial-iron axis that promotes LD formation in aging microglia via reactive oxygen species (ROS), which secondarily reshapes neuronal iron handling. LD-enriched microglia show reduced mitochondrial mass and increased labile iron, ROS, and lipid peroxidation. Chelating labile iron or scavenging ROS suppresses LD formation. Conditioned media from iron-stressed microglia alter neuronal iron homeostasis, indicating transcellular coupling. In primary neurons, iron overload increases LDs and activates coordinated iron, ROS, and lipogenesis programs, whereas antioxidant treatment attenuates iron-driven LD accumulation. Together, these findings position iron overload as an upstream regulator of ROS-dependent LD biogenesis in microglia and neurons and reveal a microglia-neuron axis that regulates neuronal iron metabolism during aging.

immunology↗

ATOMIC: A graph attention neural network for ATOpic dermatitis prediction on human gut MICrobiome

Atopic dermatitis (AD) is a chronic inflammatory skin disease driven by complex interactions among genetic, environmental, and microbial factors; however, its etiology remains unclear. Recent studies have reported the role of gut microbiota dysbiosis in AD pathogenesis, leading to increased interest in microbiome-targeted therapeutic strategies such as probiotics and fecal microbiota transplantation. Building on these findings, recent advances in computational modeling have introduced machine learning and deep learning-based approaches to capture the nonlinear relationships between gut microbiota and diseases. However, these models focus on diseases other than AD and often fail to capture complex microbial interactions or incorporate microbial genomic information, thereby offering limited interpretability. To address these limitations, we propose ATOMIC, an interpretable graph attention network-based model that incorporates microbial co-expression networks to predict AD. Microbial co-expression networks incorporate microbial genomic information as node features, thereby enhancing their ability to capture functionally relevant microbial patterns. To train and test our model, we collected and processed 99 gut microbiome samples from adult patients with AD and healthy controls at Kangwon National University Hospital (KNUH). As a result, ATOMIC achieved an AUROC of 0.810 and an AUPRC of 0.927 on the KNUH dataset. Furthermore, ATOMIC identified microbes potentially associated with AD prediction and proposed candidate microbial biomarkers that may inform future therapeutic strategies. To facilitate future research, we publicly released a gut microbial abundance dataset from KNUH. The source code and processed abundance data are available from ATOMIC GitHub repository at https://www.github.com/KU-MedAI/ATOMIC. Author summaryAtopic dermatitis (AD) is a chronic inflammatory skin disease affecting approximately 120 million people worldwide, often leading to a reduced quality of life, including sleep disturbances and stress. Current treatment methods rarely achieve complete remission, and the precise cause of AD remains unclear. The association between imbalances in the gut microbiota and the pathogenesis of AD has highlighted the gut microbiota as a promising target for therapeutic strategies. Exploring the potential role of the gut microbiota in modulating host immune responses is likely to have a positive impact on future AD treatment. Consequently, the growing need to develop machine learning and deep learning-based predictive models using gut microbiome data. However, existing models often suffer from limited interpretability owing to their black-box nature and frequently overlook microbial interactions and genomic contexts. To address these limitations, we propose a novel model called ATOMIC, which integrates microbial co-expression networks and genomic information to predict AD. Our model achieved superior performance in terms of AUROC, AUPRC, and F1 scores compared with existing models and provided interpretable insights through an attention mechanism, thereby offering promising potential for identifying relevant biomarkers. Together, these results highlight ATOMICs potential for the accurate prediction of AD and for identifying biologically meaningful microbial signatures.

systems biology↗

Astrocytic Ryk signaling coordinates scarring and wound healing after spinal cord injury

Wound healing after spinal cord injury involves highly coordinated interactions among multiple cell types, which is poorly understood. Astrocytes play a central role in creating a border against the non-neural lesion core. To do so, astrocytes undergo dramatic morphological changes by first thickening the processes and then elongating and overlap them. We show here show that the expression of a cell-surface receptor, Ryk, is induced in astrocytes after injury in both rodent and human spinal cord. Astrocyte-specific knockout of Ryk dramatically elongated the reactive astrocytes and accelerated the formation of the border and reduced the size of the scar. Astrocyte-specific knockout of Ryk also accelerated the injury responses of multiple cell types, including the resolution of neuroinflammation. Single cell transcriptomics analyses revealed a broad range of changes cell signaling among astrocytes, microglia, fibroblasts, endothelial cell, etc, after astrocyte-specific Ryk knockout, suggesting that Ryk not only regulates the injury response of astrocytes but may also regulate signals which coordinate the responses of multiple cell types. The elongation is mediated by NrCAM, a cell adhesion molecule induced by astrocyte-specific conditional knockout of Ryk after spinal cord injury. Our findings suggest a promising therapeutic target to accelerate wound healing and promote neuronal survival and enhance functional recovery.

neuroscience↗

Tissue-specific modulation of CRISPR activity by miRNA-sensing guide RNAs

Nucleic acid nanostructures offer unique opportunities for biomedical applications due to their sequence-programmable structures and functions, which enable the design of complex responses to molecular cues. Control of the biological activity of therapeutic cargoes based on endogenous molecular signatures holds the potential to overcome major hurdles in translational research: cell specificity and off-target effects. Endogenous microRNAs can be used to profile cell type and cell state and are ideal inputs for RNA nanodevices. Here we present CRISPR MiRAGE (miRNA-activated genome editing), a tool comprising a dynamic single-guide RNA that senses miRNA complexed with Argonaute proteins and controls downstream CRISPR activity based on the detected miRNA signature. We study the operation of the miRNA-sensing single-guide RNA and attain muscle-specific activation of gene editing through CRISPR MiRAGE in models of Duchenne muscular dystrophy. By enabling RNA-controlled gene editing activity, this technology creates opportunities to advance tissue-specific CRISPR treatments for human diseases.

bioengineering↗

Quantitative Analysis of Roles of Direct and Indirect Pathways for Action Selection in The Basal Ganglia

We are concerned about action selection in the basal ganglia (BG). We quantitatively analyze functions of direct pathway (DP) and indirect pathway (IP) for action selection in a spiking neural network with 3 competing channels. For such quantitative analysis, in each channel, we obtain the competition degree [C]d, given by the ratio of strength of DP ([S]DP) to strength of IP ([S]IP) (i.e., [C]d = [S]DP /[S]IP). Then, a desired action is selected in the channel with the largest [C]d. Desired action selection is made mainly due to strong focused inhibitory projection to the output nucleus, SNr (substantia nigra pars reticulata) via the DP in the corresponding channel. Unlike the case of DP, there are two types of IPs; intra-channel IP and inter-channel IP, due to widespread diffusive excitation from the STN (subthalamic nucleus). The intra-channel IP serves a function of brake to suppress the desired action selection. In contrast, the inter-channel IP to the SNr in the neighboring channels suppresses competing actions, leading to highlight the desired action selection. In this way, function of the inter-channel IP is opposite to that of the intra-channel IP. However, to the best of our knowledge, no quantitative analysis for such functions of the DP and the two IPs was made. Here, through direct calculations of the DP and the intra- and the inter-channel IP presynaptic currents into the SNr in each channel, we obtain the competition degree of each channel to determine a desired action, and then functions of the DP and the intra- and inter-channel IPs are quantitatively made clear. PACS numbers87.19.lj, 87.19.lu, 87.19.rs

neuroscience↗

Break-up and Recovery of Harmony between Direct and Indirect Pathways in The Basal Ganglia; Huntington's Disease and Treatment

The basal ganglia (BG) in the brain exhibit diverse functions for motor, cognition, and emotion. Such BG functions could be made via competitive harmony between the two competing pathways, direct pathway (DP) (facilitating movement) and indirect pathway (IP) (suppressing movement). As a result of break-up of harmony between DP and IP, there appear pathological states with disorder for movement, cognition, and psychiatry. In this paper, we are concerned about the Huntingtons disease (HD), which is a genetic neurodegenerative disorder causing involuntary movement and severe cognitive and psychiatric symptoms. For the HD, the number of D2 SPNs (ND2) is decreased due to degenerative loss, and hence, by decreasing xD2 (fraction of ND2), we investigate break-up of harmony between DP and IP in terms of their competition degree[C] d, given by the ratio of strength of DP ([S]DP) to strength of IP (([S]IP) (i.e.,[C] d = ([S]DP /([S]IP). In the case of HD, the IP is under-active, in contrast to the case of Parkinsons disease with over-active IP, which results in increase in[C] d (from the normal value). Thus, hyperkinetic dyskinesia such as chorea (involuntary jerky movement) occurs. We also investigate treatment of HD, based on optogenetics and GP ablation, by increasing strength of IP, resulting in recovery of harmony between DP and IP. Finally, we study effect of loss of healthy synapses of all the BG cells on HD. Due to loss of healthy synapses, disharmony between DP and IP increases, leading to worsen symptoms of the HD.

biophysics↗

Ying-Yang Competitive Harmony between Direct and Indirect Pathways in A Spiking Neural Network of The Basal Ganglia

The basal ganglia (BG) show a variety of functions for motor and cognition. There are two competitive pathways in the BG; direct pathway (DP) which facilitates movement and indirect pathway (IP) which suppresses movement. It is well known that diverse functions of the BG may be made through "balance" between DP and IP. But, to the best of our knowledge, so far no quantitative analysis for such balance was done. In this paper, as a first time, we introduce the competition degree [C]d between DP and IP. Then, by employing [C]d, we quantify their competitive harmony (i.e., competition and cooperative interplay), which could lead to improving our understanding of the traditional "balance" so clearly and quantitatively. We first consider the case of normal dopamine (DA) level of {phi}* = 0.3. In the case of phasic cortical input (10 Hz), a healthy state with [Formula] (i.e., DP is 2.82 times stronger than IP) appears. In this case, normal movement occurs via harmony between DP and IP. Next, we consider the case of decreased DA level,{phi} ={phi} *(= 0.3) xDA (1 > xDA [≥] 0). With decreasing xDA from 1, the competition degree [C]d between DP and IP decreases monotonically from[Formula], which results in appearance of a pathological Parkinsonian state with reduced [C]d. In this Parkinsonian state, strength of IP is much increased than that in the case of normal healthy state, leading to disharmony between DP and IP. Due to such break-up of harmony between DP and IP, impaired movement occurs. Finally, we also study treatment of the pathological Parkinsonian state via recovery of harmony between DP and IP. PACS numbers87.19.lj, 87.19.lu, 87.19.rs

neuroscience↗

Enhanced fungal specificity and in vivo therapeutic efficacy of a C-22 modified FK520 analog against C. neoformans

Fungal infections are of mounting global concern, and the current limited treatment arsenal poses challenges when treating such infections. In particular, infections by Cryptococcus neoformans are associated with high mortality, emphasizing the need for novel therapeutic options. Calcineurin is a protein phosphatase that mediates fungal stress responses, and calcineurin inhibition by the natural product FK506 blocks C. neoformans growth at 37{degrees}C. Calcineurin is also required for pathogenesis. However, because calcineurin is conserved in humans, and inhibition with FK506 results in immunosuppression, the use of FK506 as an anti-infective agent is precluded. We previously elucidated the structures of multiple fungal calcineurin-FK506-FKBP12 complexes and implicated the C-22 position on FK506 as a key point for differential modification of ligand inhibition of the mammalian versus fungal target proteins. Through in vitro antifungal and immunosuppressive testing of FK520 (a natural analog of FK506) derivatives, we identified JH-FK-08 as a lead candidate for further antifungal development. JH-FK-08 exhibited significantly reduced immunosuppressive activity and both reduced fungal burden and prolonged survival of infected animals. JH-FK-08 exhibited additive activity in combination with fluconazole in vivo. These findings further advance calcineurin inhibition as an antifungal therapeutic approach. ImportanceFungal infections cause significant morbidity and mortality globally. The therapeutic armamentarium against these infections is limited and development of antifungal drugs has been hindered by the evolutionary conservation between fungi and the human host. With rising resistance to the current antifungal arsenal and an increasing at-risk population, there is an urgent need for the development of new antifungal compounds. The FK520 analogs described in this study display potent antifungal activity as a novel class of antifungals centered on modifying an existing orally-active FDA approved therapy. This research advances the development of much needed newer antifungal treatment options with novel mechanisms of action.

microbiology↗

Effect of Adult Neurogenesis on Sparsely Synchronized Rhythms of The Granule Cells in The Hippocampal Dentate Gyrus

We are concerned about the main encoding granule cells (GCs) in the hippocampal dentate gyrus (DG). Young immature GCs (imGCs) appear through adult neurogenesis. In comparison to the mature GCs (mGCs) (born during development), the imGCs show high activation due to lower firing threshold. On the other hand, they receive low excitatory drive from the entorhinal cortex via perforant paths and from the hilar mossy cells with lower connection probability pc (= 20 x %) (x : synaptic connectivity fraction; 0 [≤] x [≤] 1) than the mGCs with the connection probability pc (= 20 %). Thus, the effect of low excitatory innervation (reducing activation degree) for the imGCs counteracts the effect of their high excitability. We consider a spiking neural network for the DG, incorporating both the mGCs and the imGCs. With decreasing x from 1 to 0, we investigate the effect of young adult-born imGCs on the sparsely synchronized rhythms (SSRs) of the GCs (mGCs, imGC, and whole GCs). For each x, population and individual firing behaviors in the SSRs are characterized in terms of the amplitude measure [Formula] (X = m, im, w for the mGCs, the imGCs, and the whole GCs, respectively) (representing the population synchronization degree) and the random phase-locking degree [Formula] (characterizing the regularity of individual single-cell discharges), respectively. We also note that, for 0 [≤] x [≤] 1, the mGCs and the imGCs exhibit pattern separation (i.e., a process of transforming similar input patterns into less similar output patterns) and pattern integration (making association between patterns), respectively. Quantitative relationship between SSRs and pattern separation and integration is also discussed. PACS numbers87.19.lj, 87.19.lm, 87.19.lv

neuroscience↗

Effect of Adult-Born Immature Granule Cells on Pattern Separation in The Hippocampal Dentate Gyrus

Young immature granule cells (imGCs) appear via adult neurogenesis in the hippocampal dentate gyrus (DG). In comparison to mature GCs (mGCs) (born during development), the imGCs exhibit two competing distinct properties such as high excitability and low excitatory innervation. We develop a spiking neural network for the DG, incorporating the imGCs, and investigate their effect on pattern separation (i.e., a process of transforming similar input patterns into less similar output patterns). We first consider the effect of high excitability. The imGCs become very highly active due to their low firing threshold. Then, because of high activation, strong pattern correlation occurs, which results in pattern integration (i.e., making association between events). On the other hand, the mGCs exhibit very sparse firing activity due to strongly increased feedback inhibition (caused by the high activation of the imGCs). As a result of high sparsity, the pattern separation efficacy (PSE) of the mGCs becomes very high. Thus, the whole population of GCs becomes a heterogeneous one, composed of a (major) subpopulation of mGCs (i.e., pattern separators) with very low activation degree [Formula] and a (minor) subpopulation of imGCs (i.e., pattern integrators) with very high activation degree [Formula]. In the whole heterogeneous population, the overall activation degree [Formula] of all the GCs is a little reduced in comparison to the activation degree [Formula] in the presence of only mGCs without imGCs. However, no pattern separation occurs, due to heterogeneous sparsity, in contrast to the usual intuitive thought that sparsity could improve PSE. Next, we consider the effect of low excitatory innervation for the imGCs, counteracting the effect of their high excitability. With decreasing the connection probability of excitatory inputs to the imGCs, [Formula] decreases so rapidly, and their effect becomes weaker. Then, the feedback inhibition to the mGCs is also decreased, leading to increase in [Formula] of the mGCs. Accordingly, [Formula] of the whole GCs also increases. In this case of low excitatory connectivity, the imGCs perform pattern integration. On the other hand, due to increase in [Formula], the PSE of the mGCs decreases from a high value to a limit value. In the whole population of all the GCs, when the excitatory connection probability decreases through a threshold, pattern separation starts, the overall PSE increases and approaches that of the mGCs. However, due to heterogeneity caused by the imGCs, the overall PSE becomes deteriorated, in comparison with that in the presence of only mGCs.

biophysics↗

Iron regulatory pathways differentially expressed during Madurella mycetomatis grain development in Galleria mellonella

BackgroundMycetoma is a neglected, chronic granulomatous infection of the subcutaneous tissue, most often caused by the fungal pathogen Madurella mycetomatis. Characteristic of the infection is the formation of grains. However, knowledge of the function and formation of the grain is limited. To map the processes leading to M. mycetomatis grain formation, we used a Galleria mellonella larvae infection model and time-course transcriptomic profiling. MethodsGalleria mellonella larvae were infected with M. mycetomatis genome strain mm55. At 4h, 24h, 72h and 168h post-inoculation, RNA was extracted from larval content. Two types of sequencing libraries were prepared for time-course transcriptomic profiling and analysis. FindingsIn the infected G. mellonella, 88.0% of the RNA sequence reads mapped to G. mellonella, while only 0.01% mapped to M. mycetomatis. Differential Gene Expression analysis revealed that 3,498 G. mellonella and 136 M. mycetomatis genes were differentially expressed during infection. Most of the enriched GO terms of both host and pathogen are linked to energy pathways, nucleobase metabolic process as well as cation and iron transport. Genes related to iron transport were highly expressed by both G. mellonella (transferrin and ferritin) and M. mycetomatis (SidA, SidD and SidI). A protein-protein interaction network analysis of D. melanogaster homologous genes in M. mycetomatis revealed the expression of the entire siderophore biosynthesis pathway throughout infection. InterpretationThe identification of the importance of iron acquisition during grain formation can be exploited as a potential novel diagnostic and therapeutic strategy for mycetoma. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMycetoma is a chronic, neglected tropical infectious disease, characterised by a large subcutaneous mass and the formation of black grains in the affected tissue. Treatment for mycetoma is disappointing as in 25-50% of the patients recurrences are noted and up to 15% of patients will have to undergo amputation. The main reason behind this poor treatment response is the formation of protective structures by the pathogen upon entering the human body. These structures are called grains and provide a strong barrier for antifungal agents. Although grains are the hallmark of mycetoma, it is currently not known how these grains are formed. To improve the current therapy, it is important to gain insights in grain formation. Added value of this studyWe unravel the processes leading to grain formation and development in an invertebrate model of Madurella mycetomatis grain. We were able to build a model of grain formation and demonstrated that iron sequestering plays an important role in this process. Our findings were an important milestone in understanding the pathogenesis of mycetoma which has been a mystery for decades. Implications of all the available evidenceThe findings, will provide leads for future drug development of mycetoma treatment and therefore, improve patients live and end the need for amputations.

microbiology↗

Exploration of mechanisms of drug resistance by polyaneuploid cancer cells in a microfluidic device and patient tissues

Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium. In vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis all showed that chemoresistance arose from failed epigenetic control of the nuclear protein-1 (NUPR1)/histone deacetylase 11 (HDAC11) axis, and high Nupr1 expression correlated with poor clinical outcomes. These results suggest that the chip can rapidly induce resistant cells that increase tumor heterogeneity and chemoresistance, highlighting the need for further studies on the epigenetic control of the NUPR1/HDAC11 axis in TNBC.

cancer biology↗

The interplay of supercoiling and thymine dimers inDNA

AO_SCPLOWBSTRACTC_SCPLOWThymine dimers are a major mutagenic photoproduct induced by UV radiation. While they have been the subject of extensive theoretical and experimental investigations, questions of how DNA supercoiling affects local defect properties, or, conversely, how the presence of such defects changes global supercoiled structure, are largely unexplored. Here we introduce a model of thymine dimers in the oxDNA forcefield, parametrised by comparison to melting experiments and structural measurements of the thymine dimer induced bend angle. We performed extensive molecular dynamics simulations of double-stranded DNA as a function of external twist and force. Compared to undamaged DNA, the presence of a thymine dimer lowers the supercoiling densities at which plectonemes and bubbles occur. For biologically relevant supercoiling densities and forces, thymine dimers can preferentially segregate to the tips of the plectonemes, where they enhance the probability of a localized tip-bubble. This mechanism increases the probability of highly bent and denatured states at the thymine dimer site, which may facilitate repair enzyme binding. Thymine dimer-induced tip-bubbles also pin plectonemes, which may help repair enzymes to locate damage. We hypothesize that the interplay of supercoiling and local defects plays an important role for a wider set of DNA damage repair systems.

biophysics↗