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Ding, Y.

Publications and source records attributed to Ding, Y..

At least 73 records · Page 4Linked to original sources

Natural evolution of intermale sexual behavior by multiple pheromone switches among Drosophila species

We have identified a Drosophila species which exhibits spontaneous and robust intermale sexual behavior. D. santomea males distinguish conspecific sexes but court both vigorously and seldom attack. Elevated intermale courtship stems from at least three evolutionarily derived pheromonal changes. In males, the sexually monomorphic cuticular pheromone 7-tricosene promotes rather than inhibits courtship and the courtship-inhibiting olfactory pheromone cVA is reduced 84-92% compared to close relatives. The third switch is in D. santomea females, where cVA suppresses rather than promotes sexual receptivity. Female cVA aversion and male cVA reduction may have co-evolved to maintain efficient intraspecific mating but prevent hybridization with the sympatric sibling species D. yakuba. High intermale courtship and low cVA also co-occur and appear selectively derived in a distant monomorphic species D. persimilis, implying pheromonal and social behavioral convergence. Changes in pheromone valence and levels may therefore explain the recent evolutionary emergence of intermale sexual behavior in Drosophila.

evolutionary biology↗

KM-GPT: An Automated Pipeline for Reconstructing Individual Patient Data from Kaplan-Meier Plots

Reconstructing individual patient data (IPD) from Kaplan-Meier (KM) plots provides valuable insights for evidence synthesis in clinical research. However, existing approaches often rely on manual digitization, which is error-prone and lacks scalability. To address these limitations, we develop KM-GPT, the first fully automated, AI-powered pipeline for reconstructing IPD directly from KM plots with high accuracy, robustness, and reproducibility. KM-GPT integrates advanced image preprocessing, multi-modal reasoning powered by GPT-5, and iterative reconstruction algorithms to generate high-quality IPD without manual input or intervention. Its hybrid reasoning architecture automates the conversion of unstructured information into structured data flows and validates data extraction from complex KM plots. To improve accessibility, KM-GPT is equipped with a user-friendly web interface and an integrated AI assistant, enabling researchers to reconstruct IPD without requiring programming expertise. KM-GPT was rigorously evaluated on synthetic and real-world datasets, consistently demonstrating superior accuracy. To illustrate its utility, we applied KM-GPT to a meta-analysis of gastric cancer immunotherapy trials, reconstructing IPD to facilitate evidence synthesis and biomarker-based subgroup analyses. By automating traditionally manual processes and providing a scalable, web-based solution, KM-GPT transforms clinical research by leveraging reconstructed IPD to enable more informed downstream analyses, supporting evidence-based decision-making.

bioinformatics↗

Rat somatic genome editing enables ER+ breast cancer modeling

Genetically engineered mouse models have advanced cancer research but often fail to capture key features of certain human tumors. Rats, with distinct physiology and tumor biology, offer a powerful alternative, yet their use has been constrained by technical barriers to genome editing. Here, we report efficient somatic genome editing in rats, enabling both Indel and substitution mutations. We then apply this approach to model estrogen receptor (ER)-positive breast cancer, which accounts for [~]70% of human cases but remains poorly represented in mice. The resulting rat tumors reproduce hallmarks of human ER+ breast cancer, including ductal histology, hormone responsiveness, and immune-microenvironmental features. By contrast, identical genetic alterations in mice failed to yield ER+ tumors, underscoring critical species differences in tumorigenesis. Together, this work establishes a versatile platform for rapid generation of clinically relevant rat tumor models, opening new avenues to dissect tumor biology, therapeutic response, and immune interactions in previously inaccessible cancer subtypes.

cancer biology↗

Abnormal shear stress induces ferroptosis in endothelial cells via KLF6 downregulation

Stable laminar flow maintains vascular tone regulation, while abnormal blood flow, such as disturbed flow or extreme shear stress, causes endothelial dysfunction, but the underlying mechanism is yet to be explored. We used a microfluidic device to deform flat microchannel into tunnel-like macrochannel. The cross-sectional area of this macrochannel varies with the flow rate and the thickness of the deformable layer, creating three levels of shear stress: low (0.99 dyn/cm2, LSS), medium (4.78 dyn/cm2, MSS), and high (24 dyn/cm2, HSS). Comparing different shear stress exposure to endothelial cells for 24 h, prominent ferroptosis features emerged under either LSS or HSS compared to MSS. These features included increased C11 BODIPY-labeled lipid peroxidation and 4-hydroxynonenal accumulation, CoQ10 depletion, reduced SLC7A11 protein expression, and diminished cell death with Ferrostatin-1 treatment. RNA-seq analysis (LSS/MSS) showed that LSS significantly downregulated transcription of cholesterol homeostasis and unfolded protein response (UPR). Compared to MSS, Western blot results showed that both LSS and HSS reduced the expression of two key enzymes (MVD and IDI1) in the mevalonate pathway, as well as the expression of two main UPR signaling regulators (PERK and BiP). Based on the binding prediction between transcription factors and gene promoters from differentially expressed genes identified through RNA-seq, we found KLF6 to be a key transcription factor. It regulates the PERK-mediated UPR and the mevalonate pathway, which are associated with SLC7A11 expression and CoQ10 synthesis, respectively. The overexpression of KLF6 restored SLC7A11 and CoQ10 levels under both LSS and HSS, significantly reducing foam cell formation, monocyte adhesion, and lipid peroxidation. Our findings reveal KLF6 as a crucial regulator of atherosclerosis induced by abnormal shear stress.

cell biology↗

Systematic identification and characterization of regulators of aryl hydrocarbon receptor signaling

The human aryl hydrocarbon receptor (AHR) integrates chemical signals derived from the environment, gut microbes, and endogenous sources to regulate processes ranging from intestinal barrier integrity to xenobiotic detoxification. Despite strong evidence that dysregulation of AHR signaling is a causal factor in metabolic and autoimmune disorders, we currently lack a comprehensive understanding of the factors that regulate AHR activity in human cells. Here, we use genome-scale CRISPR screening to systematically identify regulators of AHR signaling in hepatocytes. The resulting datasets recapitulate the core AHR signaling pathway and identify a large network of regulators. Many of these factors have roles beyond AHR signaling, reflecting that AHR signaling is deeply integrated into human cell biology. We further dissect this network to reveal novel modes of regulation of AHR expression, protein levels, and signaling. For example, we find that the E3 ubiquitin ligase UBR5 sustains AHR signaling by counteracting degradation of ligand-bound AHR. Finally, we identify components of the AHR regulatory network that are specific to cell types and ligands as potential nodes to manipulate AHR signaling in a targeted manner for therapeutic benefit. Overall, our results define the regulatory network that underpins AHR activation, with implications for our understanding of host-microbe interactions and integrative chemosensation and the etiology of metabolic and inflammatory disorders.

genomics↗

Genome structural plasticity and copy number dynamics shape adaptive evolution in a barley fungal pathogen

Leaf rust, caused by Puccinia hordei, is one of the most important diseases of barley globally. Here, we report the first haplotype-resolved chromosome-level genome assembly for P. hordei. To gain deeper insight and understanding of the P. hordei genome, we generated such assemblies for two Australian isolates with contrasting virulence, one collected in the 1970s and one in 2001. The two haplotype-phased and chromosome-level assemblies were used to investigate genome architecture in P. hordei and to investigate variability and evolutionary relationships of 41 virulence-divergent isolates that were collected over a 54-year period (1966-2020) in Australia. We report, for the first time in a rust fungus, evidence of a conserved chromosome, chromosome 9, which is enriched for structural variation and accessory features that imply it functions as a compartmentalized core chromosome with regions subject to rapid diversification, potentially acting as a structural hotspot in adaptive evolution in P. hordei. Clear genetic stratification into clonal and recombining lineages was uncovered, with evidence of both long-term asexual propagation and recombination. Analyses of haplotype-resolved mating-type gene phylogenies and chromosome 9 k-mer profiles confirm divergence at key loci underpinning reproductive modes, distinguishing clonally derived from sexually recombined groups. We also identified pervasive copy number variation across the P. hordei genomes, with clonal lineage-specific duplications. Consistent with this finding, the study for the first time links copy number variation of the Cyp51 gene to fungicide insensitivity. This latter discovery is highly significant as it represents the first documented case of fungicide insensitivity in a rust pathogen in which an underlying genetic mechanism has been identified. Together, these findings illuminate how genome structure, recombination, and structural variation shape the evolution and adaptation of P. hordei, providing a guidance for future surveillance and management of this pathogen.

genomics↗

Patient-derived organoids reveal hypoxia-driven plasticity and therapeutic vulnerabilities in pheochromocytomas and paragangliomas

Pheochromocytomas and paragangliomas (PPGLs) are rare chromaffin cell-derived neuroendocrine tumors of sympathetic (catecholamine-producing) or parasympathetic (nonsecretory) origin, frequently driven by dysregulation of hypoxia-inducible factor (HIF) signaling, particularly HIF-2. Although often benign, PPGLs can metastasize unpredictably, with limited therapeutic options once disseminated. Progress has been hindered by the lack of robust preclinical models, especially those that capture their molecular complexity and microenvironmental influences. To address this gap, we established patient-derived tumor organoids (PDOs) from 35 PPGLs, encompassing a broad spectrum of clinical and molecular phenotypes. The organoids retained key immunohistochemical, genomic, transcriptomic, and catecholamine-secretory features of their parental tumors. PPGL organoids cultured under hypoxic conditions generally exhibited enhanced viability, supporting hypoxia as a driver of cell survival. Hypoxia activated HIF-1 and expanded ASCL1+ cell populations, suggesting a lineage shift toward an immature chromaffin state. In contrast, long-term normoxic cultures activated hypoxia inducible factor 2 (HIF-2) and acquired a hybrid sympathoblast-mesenchymal identity in subpopulations with upregulation of extracellular matrix and cell cycle markers, independent of genotype. These features resemble high-risk neuroblastoma subtypes and establish a molecular parallel suggestive of shared lineage plasticity and pathogenic programs, detectable in primary PPGLs. Drug screening across a library of up to 51 drugs and combinations revealed both shared and unique vulnerabilities, with response rates to approved therapies matching clinical observations. The CDK4/6 inhibitor abemaciclib, previously unexplored in PPGLs, elicited the strongest activity. Abemaciclib-responsive PDOs and their matched tumors, including a metastatic sample, exhibited epithelial mesenchyme transition enrichment, nominating potential biomarkers for patient stratification. Our results establish PDOs as a novel platform for modeling neuroendocrine tumor biology, reveal microenvironment-driven plasticity in PPGLs, with potential translational relevance, and identify actionable vulnerabilities in a disease with few effective systemic therapies. Main findingsO_LIPDOs can be successfully generated from PPGLs of various genetic backgrounds and reflect parental tumor properties C_LIO_LIPDO cultures grown in hypoxia retain main molecular features of parental tumors, have increased viability and a more immature developmental/biosynthetic profile C_LIO_LILong term PDOs grown for 4 weeks in normoxia activate HIF2, drift toward a hybrid sympathoblast-mesenchymal-like identity resembling relapsed/therapy resistant neuroblastomas, features that can be detected in primary tumors C_LIO_LIA subset of PDOs respond to Abemaciclib, a drug class not previously used therapeutically in PPGLs C_LI

cancer biology↗

Attention-related sampling of targets rhythmically alternates with increased susceptibility to co-occurring distractors

The Rhythmic Theory of Attention proposes that visual spatial attention is characterized by alternating states that promote either sampling at the present focus of attention or a higher likelihood of shifting attentional resources to another location. While theta-rhythmically (4-8 Hz) occurring windows of opportunity for shifting attentional resources might provide cognitive flexibility, these windows might also make us more susceptible to distractors. Here, we used EEG in humans to test how frequency-specific neural activity phasically influences behavioral performance and visual processing when high-contrast distractors co-occur with low-contrast targets. For trials with and without distractors, perceptual sensitivity at the cued target location depended on pre-stimulus theta phase ([~]7 Hz) recorded at central electrodes. For trials with distractors, there was a greater increase in false alarm rates at the same theta phase associated with lower hit rates (i.e., during the proposed shifting state), confirming theta-rhythmically occurring windows of increased susceptibility to distractors. In addition to these phase-behavior effects at central electrodes, we observed phase-behavior effects at frontocentral and occipital electrodes that (i) only occurred on trials with distractors, (ii) peaked in the alpha-frequency range ([~]9- 10 Hz) and (iii) were strongest at occipital electrodes that were contralateral to distractors. Alpha phase at these electrodes was also associated with fluctuations in the amplitude of distractor-evoked visual responses, consistent with an alpha-mediated gating of distractors. The present findings thus provide evidence for distinct theta- and alpha-mediated mechanisms of spatial attention that phasically modulate the influence of distractors on task performance. SignificanceThe Rhythmic Theory of Attention proposes that spatial attention is characterized by alternating states that promote either sampling at the present focus of attention or a higher likelihood of shifting attentional resources to another location. These alternating attentional states are associated with dynamic changes in attention-related neural and behavioral effects, occurring on a timescale in the theta-frequency range (4-8 Hz). Although interdigitated windows for shifting attentional resources might provide critical cognitive flexibility, they might also lead to an increased susceptibility to distractors. Here, we demonstrate such rhythmic fluctuations in susceptibility to high-contrast distractors that co-occur with low-contrast visual targets. Rhythmic attention-related sampling--while perhaps preventing us from becoming overly focused on any single location--can lead to behavioral disadvantages.

neuroscience↗

CIAdex: Single-Cell FTIR Spectral Fingerprinting for Cell Identity Verification and Aging Quantification in Therapeutic Cell Manufacturing

Ensuring the identity and optimal aging state of cell products is critical for the efficacy and safety of cell therapies. Despite rapid iterations, there remains an urgent need for robust and easy-to-implement tests to characterize cell products. Here, we present CIAdex (Cell Identification and Aging Index), an analytical framework that utilizes single-cell Fourier-transform infrared (FTIR) spectral fingerprints and machine learning to achieve precise label-free cell identity assessment and aging quantification. CIAdex employs a Feature Extraction Processor to automatically extract FTIR spectral variables corresponding to distinct cellular biomolecular features, enabling reliable distinction of lineage-, donor-, and batch-specific cell populations using linear discriminant analysis. Through application of the XGBoost algorithm, a quantitative aging index (trPDL/trPN) was further generated for tracking cellular aging dynamics along culture expansion. Notably, trPDL/trPN quantitatively represent subtle age-related shifts among different batches and drug-induced senescence or rejuvenation effects which are unmeasurable by existing methods. Together, our work demonstrates that CIAdex, by simultaneous label-free identity verification and aging quantification of cell populations, offers a transformative approach to interpret single-cell FTIR spectral fingerprints and provides novel metrics for quality control in cell manufacturing with significant potential for optimization and assurance of cell therapies safety and efficacy.

cell biology↗

Engineered lignin composition in Brachypodium distachyon modulates the root-associated microbiome

Lignin is a key component of the plant cell wall and a barrier to microbial interaction and biomass digestibility. While lignin biosynthesis has been engineered in grasses to reduce recalcitrance for agroindustrial applications, the consequences for root-associated microbial communities remain poorly understood. Here, we show in the model grass species Brachypodium distachyon that genetic modification of lignin biosynthetic genes, particularly caffeic acid O-methyltransferase (COMT), alters root lignin syringyl/guaiacyl (S/G) ratios, root exudate composition, and significantly reshapes the rhizosphere microbiome. Using a synthetic microbial community (SYNCOM) in controlled fabricated ecosystem (EcoFAB) environments, we observed a distinct reduction in Burkholderia colonization and enrichment of Rhodococcus in COMT mutant lines. LC-MS/MS profiling of root exudates revealed increased p-coumaric acid, caffeic acid and hydroxycinnamic acid amides in these lines, potentially linked to both metabolic remodeling and plant stress responses. These findings demonstrate that altering lignin composition can have profound, genotype-specific impacts on rhizosphere microbiome assembly, with implications for plant-microbe interactions, nutrient cycling, and biomass conversion strategies in bioenergy crops.

plant biology↗

Super-pangenome analysis of 3562 human and animal papillomavirus isolates illuminates their genome and pathogenicity evolution

Papillomaviruses (PVs) are groups of ubiquitous DNA viruses infecting a wide range of vertebrate hosts, including human. The infection of some human PVs (i.e., HPVs) are strongly associated with cancers, but it remains elusive how such pathogenicity evolved at the genomic level. Here we performed a super-pangenome analysis on a compendium of well-curated 3562 human and animal PV genomes. We found their global genomic diversity being strongly associated with their body sites and tissue origins, but not with their host, geographical, or disease specificity. By reconciling time-resolved phylogenies of PVs and their hosts, we revealed a high-resolution view on how virus-host cospeciation, horizontal host switches, and duplication/loss turnovers collectively shaped the evolution of PVs. We identified key selection-driven mutations that defined the genus-specific divergence of PVs, with those underlying the rise of Alpha-PVs highly enriched in the N-terminal domain of E1 gene. Especially, we identified a group of risk-defining variant sites showing contrasting genotypes between low-risk and high-risk HPVs. With four independent PV genome cohorts, we further validated their high sensitivity and specificity on HPV risk classification even at single site level, underscoring their application values in large-scale HPV screening tests. Finally, with cervical and oropharyngeal cancer patient cohorts assembled by this study, we also evaluated the prognostic value of specific HPV16 variants in predicting patient survival. Taken together, such illumination on the genome and pathogenicity evolution of PVs paves the road for better prevention, control, and treatment of PV-related cancers. Significance statementPapillomaviruses (PVs) are ancient and widespread DNA viruses co-evolved with many vertebrate hosts, including human. Some human PVs (e.g., HPV16 and HPV18) bear strong association with cancers, raising a pressing public health challenge. A better understanding of how such pathogenicity evolved holds the key in addressing this challenge. Here we systematically investigated the genomic and evolutionary diversity of PVs via a pangenome study on over 3500 human and animal PV isolates, which revealed key selection-driven mutations shaping their genome and pathogenicity evolution. With independently acquired HPV-associated cancer cohorts, we further demonstrated how some of these important HPV variants can serve as clinically informative predictive and prognostic biomarkers. Such comprehensive characterization on PVs genome diversity, pathogenicity evolution, and clinical implication paves the road for better prevention, control, and treatment of PV-related cancers.

genomics↗

Reading specific memories from human neurons before and after sleep

The ability to retrieve a single episode encountered just once is a hallmark of human intelligence and episodic memory[1]. Yet, decoding a specific memory from neuronal activity in the human brain remains a formidable challenge. Here, we develop a transformer neural network model[2, 3] trained on neuronal spikes from intracranial microelectrodes recorded during a single viewing of an audiovisual episode. Combining spikes throughout the brain via cross-channel attention[4], capable of discovering neural patterns spread across brain regions and timescales, individual participant models predict vocalization of specific concepts such as persons or places during out-of-distribution memory recall. Brain regions differentially contribute to memory decoding before and after sleep. Models trained using only medial temporal lobe (MTL) spikes significantly decode concepts before but not after sleep, while models trained using only frontal cortex (FC) spikes decode concepts after but not before sleep, with better FC decoding relating to increased non-REM sleep. These findings suggest a system-wide distribution of information across neural populations that transforms over wake/sleep cycles[5]. Such decoding of internally generated memories suggests a path towards brain-computer interfaces to treat episodic memory disorders through enhancement or muting of specific memories.

neuroscience↗

A Geometrical Optics Model of Individual Ommatidia in Compound Eyes and a Hypothesis for Monocular Stereopsis

This study proposes a novel geometrical optics-based visual model suggesting that individual ommatidia in insect compound eyes may possess intrinsic three-dimensional imaging capabilities and enable monocular stereoscopic perception. Building upon the authors previous hypothesis that certain vertebrate retinal cell nuclei act as microlenses, the optical model is extended in this work to the arthropod compound eye system. By conceptualizing the cornea, crystalline cones, and layered rhabdomeric nuclei as components of a "multi-angle miniature real-image telescope," we construct a three-tiered imaging system composed of objectives, relay conjugate lenses, and microlenses. The model predicts that an ommatidium can actively perceive spatial depth and object distance by adjusting the focal length of crystalline cones and the distance between focused planes, thus achieving stereoscopic imaging with a single eye. Simulations based on representative species such as Drosophila melanogaster, Viggiani parasitic wasps, and fireflies (Lampyris) support the feasibility of this model in distance perception across scales ranging from microns to meters. The model breaks away from the "one ommatidium--one image point" paradigm and offers a new theoretical architecture for understanding insect stereopsis. It also presents a promising framework for bioinspired 3D imaging systems and optical designs with multi-focal capabilities.

biophysics↗

ASC contributes to sustained glial reactivity and mild cognitive impairment after closed-head injury

Mild brain traumatic brain injury (mTBI) from closed-head injuries (CHI) can lead to prevalent neuropsychiatric disorders, including an increased risk for neurodegenerative diseases and dementia. Inflammasomes are molecular complexes crucial for neuroinflammation and secondary damage after trauma, however their role in mild CHI is poorly understood. In this study, we investigate the cellular expression of inflammasome-related genes and their functional significance in CHI models. Single-cell RNA sequencing of cortical tissue revealed selective expression of Pycard (PYD and CARD domain containing), also known as Asc (apoptosis-associated speck-like protein containing a caspase recruitment domain), which encodes the inflammasome adaptor ASC, predominantly in microglial clusters. Sustained upregulation of inflammasome-related proteins persisted up to 21 days in a model for mTBI, with this pattern significantly reduced in Asc-/- mice. Importantly, mild cognitive impairment induced after mild CHI was largely abrogated in Asc-/- mice. These findings suggest that ASC, as the primary inflammasome adaptor, plays a critical role in sustaining neuroinflammation and contributes to cognitive deficits after mild CHI. This study provides insights into the molecular neuroinflammatory mechanisms underlying CHI, potentially informing future therapeutic strategies.

neuroscience↗

Self-inactivating AAV-CRISPR at different ages enables sustained amelioration of Huntington's disease deficits in BAC226Q mice

Huntingtons disease (HD) is a monogenic autosomal dominant neurodegenerative disorder caused by a CAG repeat expansion in the first exon of the HTT gene, yielding a gain-of-toxic-function mutant Huntingtin protein mHTT. CRISPR/Cas9 is a potentially powerful therapeutic tool for treating HD by eliminating mutant HTT (mHTT) gene. We developed a specific SaCas9 guide RNA to target human mHTT, and a self-inactivating gene editing system that abolishes SaCas9 after a short transient expression for high gene editing efficiency and maximal safety to prevent off-target effects. Both conventional and the new self-inactivating gene editing systems achieved successful elimination of mHTT gene, 60-90% mHTT protein and 90% of mHTT aggregation in BAC226Q HD mouse brains, which resulted in significant long-term rescue of neural pathology, motor deficits, weight loss and shortened lifespan. These beneficial effects were observed when gene editing was applied before, at and well after the on-set of pathological and behavioral abnormalities. These proof-of-concept data demonstrate that gene editing can be a highly effective therapeutic approach for HD and other inherited neurodegenerative diseases. One Sentence SummarySelf-inactivating CRISPR for mutant huntingtin in HD mice achieved long-term rescue of neural pathology, motor deficits, weight loss and survival.

neuroscience↗

Persistent chromatin alterations and gene expression reprogramming follow widespread DNA damage in glioblastoma

DNA damage from routine cellular processes or exogenous insults can have a lasting impact on gene regulation beyond genetic mutations. The prevailing paradigm for the consequences of DNA damage repair revolves around restoration of the original genetic sequence, but long-term changes in chromatin configuration, gene expression and DNA modifications have not been analyzed. We introduced numerous, simultaneous Cas9-mediated DNA double strand breaks (DSBs) at defined locations in human glioblastoma cells and tracked both non-genetic and genetic alterations over time. Megabase-scale genomic alterations that endured two weeks after the initial damage were detected, involving a shift from transiently increased intra-TAD interactions to persistent long range cis and trans contacts, alterations in gene-expression and associated large structural variations. These findings reveal that widespread DNA damage, such as chemotherapy or radiotherapy, can trigger long-term genetic and non-genetic modifications which alter cellular function and may impact tumor outcome and the emergence of resistant cells.

genomics↗

Classifying Resting State Connectivity: Lag-One Autocorrelation and Pattern Differentiability

Resting state functional connectivity (rsFC) and resting state effective connectivity (rsEC) are two of the most common measures that can be extracted from resting state functional magnetic resonance imaging (rs-fMRI) data. RSFC is often used to indicate the statistical dependencies among different brain regions of interest, whereas rsEC describes the causal influences among them. Many studies have explored utilities of rsFC and rsEC measures for classifying psychiatric conditions. Several studies showed that rsEC were better than rsFC features for classifying major depression (Frassle et al., 2020; Geng et al., 2018) and schizophrenia ((Brodersen et al., 2014)). However, no study to-date has investigated whether rsEC is inherently better than rsFC for classifying psychiatric conditions or the impact of autocorrelation on classifying rsFC, even though autocorrelation is known to be present in rs-fMRI data. To fill these gaps, we performed a series of computational experiments, by varying the size of the network and the number of participants, to gain some insight into these two aspects of supervised classification with resting state connectivity. Contrary to what has been reported in the literature, the results from our study suggest that rsEC cannot be, in principle, better than rsFC features for classification. In fact, rsEC measures led to systematically worse classification results, compared to rsFC features. In terms of the impact of autocorrelation, we found that lag-one autocorrelation could lead to both false negative and false positive classification results for studies with a small sample size.

neuroscience↗

Salmonella hijacks a host glucose transporter for intravacuolar proliferation

AbstractsSalmonella is an intracellular pathogen that resides within a vacuole, which protects it from cytosolic host defenses at the expense of limited nutrient access. Glucose serves as a critical carbon source supporting Salmonellas intracellular replication. However, the molecular mechanisms driving glucose enhancement and the pathways by which cytosolic glucose becomes accessible to intravacuolar Salmonella remain poorly understood. Here, we elucidate a sophisticated three-pronged strategy through which Salmonella hijacks GLUT1 to co-opt host glucose metabolism for pathogenic advantage. Firstly, Salmonella infection upregulates the glucose transporter GLUT1 by activating the MAPK signaling cascade, enhancing host glucose uptake, and accelerating glycolytic flux. Secondly, Salmonella redirects GLUT1 to the bacterial vacuolar membrane to establish a glucose-import conduit that facilitates bacterial acquisition of cytosolic glucose. Thirdly, K29-linked ubiquitination modifications on bacterial vacuolar membranes are a previously unrecognized regulatory mechanism that potentiates GLUT1 transporter activity. Inhibition of GLUT1 potentiates Salmonella-triggered innate immune responses and attenuates bacterial virulence in vitro (RAW264.7 macrophages) and in vivo (murine infection model). Collectively, these findings delineate a novel paradigm of metabolic hijacking, wherein Salmonella systematically rewires host glucose metabolic networks to support intracellular proliferation, providing new insights into host-directed antimicrobial interventions.

microbiology↗