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Biology subjects

Qi, Q.

Publications and source records attributed to Qi, Q..

At least 19 recordsLinked to original sources

Dynamic Control of Prokaryotic Chromosome Ploidy Rewires Metabolic Networks to Enhance Product Biosynthesis

Building high-performance microbial cell factories requires dynamic coordination of resource allocation among cellular growth, target-product biosynthesis, and endogenous host metabolism. However, existing polyploid engineering strategies rely primarily on static manipulation of chromosome copy number. Although increasing gene dosage can enhance biosynthetic capacity, static designs cannot readily accommodate the changing metabolic demands encountered during fermentation. Here, we developed a metabolite-responsive dynamic polyploid engineering strategy that couples chromosome ploidy to the cellular metabolic state. We first constructed a high-performance L-threonine biosensor and used it to sense intracellular L-threonine levels and regulate ftsZ expression, a key cell-division gene, thereby establishing a dynamic polyploid system that requires neither exogenous inducers nor antibiotics. This system enabled engineered cells to progressively transition from polyploid to haploid during fermentation, accompanied by stage-specific remodeling of cellular physiology and metabolism. Physiological characterization revealed a marked increase in cell size and alterations in cell-envelope properties during the polyploid phase, followed by a gradual decrease in chromosome copy number as fermentation progressed. Transcriptomic and metabolomic analyses further demonstrated that dynamic ploidy transitions induced global metabolic network rewiring, remodeling the tricarboxylic acid cycle and amino acid metabolism while redirecting carbon flux toward the biosynthesis of aspartate-family amino acids. Ultimately, dynamic polyploid engineering substantially enhanced L-threonine production, enabling the engineered strain to achieve an L-threonine titer of 183.1 g/L and a yield of 0.67 g/g glucose in 5-L fed-batch fermentation without antibiotics or exogenous inducers. These findings show that dynamic regulation of chromosome ploidy can couple gene-dosage control with remodeling of cellular physiology and metabolic networks, providing a new engineering strategy to overcome the limitations of static polyploid designs and build high-performance microbial cell factories.

synthetic biology↗

A global metagenomic atlas uncovers ubiquitous biosynthetic potential linked to adaptation in extreme environments

Extreme environments impose severe physicochemical stresses that drive microorganisms to evolve specialized survival strategies. Microbial secondary metabolites determined by biosynthetic gene clusters (BGCs) are recognized as important mediators of microbial adaptation to environmental stress. However, their ecological roles, particularly habitat-dependent preferences across different environments, remain poorly understood. Although extreme environments provide opportunities to mine microbiomes for unique adaptations, such research is hampered by a lack of systematic overview of its genomic diversity, BGC diversity, and the relationships between them. Here, we constructed a standardized extremophilic genomic catalogue (SEGC) from 1,462 metagenomic samples spanning seven representative extreme habitats. The catalogue comprised 54,661 metagenome-assembled genomes representing 21,805 species, 66.1% of which were previously uncharacterized. With this catalogue, we identified 162,855 BGCs distributed across 81.5% of MAGs. Gene cluster family analysis showed the strong habitat dependence largely explained by species-level habitat specificity. Terpene biosynthetic pathways illustrated habitat-linked adaptive strategies, with hopan-22-ol biosynthesis enriched in acid mine, deep sea and hydrothermal plume environments, while retinal-based phototrophy predominated in cryosphere and saline-alkaline habitats. Metatranscriptomic analyses supported in situ activity of these pathways. In conclusion, we presented a global atlas of biosynthetic potential across extreme-environment microbiota and revealed habitat-dependent patterns of secondary metabolism linked to microbial survival.

microbiology↗

From nucleotides to semantics: genomic representation learning via joint-embedding predictive architecture

Decoding the regulatory syntax encoded in genomic sequences is a central objective in computational biology. Most existing genomic foundation models treat DNA as a language and adopt pretraining objectives from natural language processing. DNA sequences, however, lack explicit semantic boundaries and contain substantial evolutionary noise. Nucleotide-level reconstruction in a low-dimensional input space can therefore increase computational overhead and may yield representations with limited discriminative capacity. Downstream tasks often depend on expensive finetuning, which restricts practical use in many biology laboratories. Here we present GenoJEPA, a genomic representation learning framework based on joint-embedding predictive architecture. GenoJEPA combines continuous patching with semantic alignment, shifting the optimization from local base reconstruction to semantic alignment in latent space. Across 55 downstream tasks, GenoJEPA shows strong representational capacity and robust generalization while reducing parameter count and computational cost. The resulting semantic vectors from frozen GenoJEPA support lightweight GPU-free classifiers to achieve competitive accuracy. These results suggest a practical route towards efficient training and broad application of larger-scale genomic foundation models.

bioinformatics↗

Discovery of novel antimicrobial resistance genes in food and fertiliser using a high-throughput gene capture and functional screening platform

Integrons are genetic elements that drive bacterial adaptation by capturing and expressing mobile gene cassettes. They play a key role in dissemination of antimicrobial resistance (AMR) genes, particularly in Gram-negative bacteria. In addition to known AMR determinants, integron gene cassettes carry a vast reservoir of novel genes whose functions are largely uncharacterised, making it diNicult to assess their full contribution to the resistome. Contributing to this are limitations in current sequence-based prediction methods which often lack the ability to identify unknown AMR or other adaptive genes with novel mechanisms. To address this, we developed an integron gene cassette capture system, a functional screening platform that captures environmental gene cassettes for direct phenotypic testing. Using this system, we recovered previously unknown AMR determinants while also providing insights into the prevalence of known clinical AMR genes in a range of environmental samples, including food items. Here we provide experimental data on multiple novel bleomycin resistance genes and a stress response gene conferring gentamicin and tobramycin resistance. Our sequence analysis of the captured library also highlighted the diversity of the environmental cassette pool, with 656 unique cassettes recovered, the majority of which encoded proteins with unknown functions. The cassette capture system is a powerful tool for accessing hidden elements of the resistome and discovering novel adaptive genes that may go undetected using current sequence-based approaches. Environmental implicationAntimicrobial resistance (AMR) genes are hazardous biological contaminants, yet the vast majority of environmental integron gene cassettes remain functionally uncharacterised. This study addresses this sequence-to-function gap by deploying a novel functional capture platform directly on realistic environmental matrices, including agricultural fertilisers, coastal seawater, and commercial food products. By characterising these cassettes, we uncovered hidden reservoirs of both novel and clinically established AMR genes circulating in critical exposure pathways. This work reveals the true hazardous potential of the mobile environmental resistome, validating a proactive One Health surveillance tool for monitoring emerging biological threats.

microbiology↗

Explaining the unexplained admixture mapping signals via rare variants: the HCHS/SOL

In admixed populations, formed by a mixing of two or more previously isolated populations, genomic segments can be traced to their ancestral populations ("ancestries"). Admixture mapping (AM) associates local ancestry with outcomes in admixed populations, detecting signals when causal variants differ in frequency or effect across ancestral populations. Prior work showed that adjusting for nearby GWAS-identified common variants does not fully explain some AM signals. Here, we assessed two approaches to explain the previously unexplained AM signal: (1) including sets of rare variants; (2) increasing the genomic region considered when searching for common variants. We studied these hypotheses comprehensively using a whole-genome sequencing dataset coupled with metabolomics from the Hispanic Community Health Study/Study of Latinos. We detected multiple sets of rare variants with replicated association with metabolite levels. Yet these rare variants appear to explain only a small fraction of the AM signal, while inclusion of common variants from a larger genomic region appears to explain the majority of the AM signals.

genetics↗

Cholinergic synaptic plasticity shapes resilience and vulnerability to tau

Synaptic dysfunction is a hallmark of Alzheimers disease (AD). Yet due to their plasticity, synapses may also adapt to early AD pathology. Here, we demonstrate that cholinergic neurons mount a presynaptic response to tau pathology in the living human brain. Using multi-tracer positron emission tomography in cognitively normal older adults at risk for AD, we observe that cholinergic neurons increase presynaptic vesicular acetylcholine transporter (VAChT) protein levels when colocalized to tau, but not amyloid. Notably, stronger VAChT responses were associated with cognitive resilience over a decade. Whole-brain single-nucleus RNA sequencing in human and mouse tissue reveal that cholinergic neurons are enriched for a plasticity gene-network anchored to the microtubule-associated protein tau (MAPT) gene. In mice, forebrain-specific deletion of VAChT impairs cortical plasticity and hippocampal structural integrity. Overall, our findings identify cholinergic synaptic plasticity, and its failure, as a fundamental mechanism of resilience and vulnerability to tau in presymptomatic AD.

neuroscience↗

Unveiling the Developmental Dynamics and Functional Role of Odorant Receptor Co-receptor (Orco) in Aedes albopictus: A Novel Mechanism for Regulating Tuning Odorant Receptor Expression

As one of the most aggressive disease vectors, the Asian tiger mosquito Aedes albopictus relies heavily on its olfactory system to search for food in the larval stage, locate hosts after eclosion, and identify suitable oviposition sites after blood feeding. In mosquitoes and other insects, the olfactory system detects environmental odors primarily through a diverse repertoire of tuning odorant receptors (ORs), which require the highly conserved odorant receptor co-receptor (Orco) to function. While Orcos role in enabling tuning receptor function is well established, its cellular localization patterns, developmental expression dynamics, and system-wide impact on olfactory physiology and behavior remain understudied in Ae. albopictus. To address this knowledge gap, we leveraged the Q-system to systematically characterize Orco-expressing neurons (ORNs) across embryonic, larval, pupal and adult stages of Ae. albopictus. We uncovered a dramatic reorganization of the olfactory system during metamorphosis: ORNs were observed as early as the embryonic stage and expanded during larval development before rapid degeneration and re-generation in the pupal stage resulting in the final population of adult ORNs. Orco expression in adults spanned the olfactory neurons of the antennae, labella, and maxillary palps in both male and female mosquitoes, consistent with its conserved peripheral distribution. To further investigate the functional implications of Orco, we generated Orco knockout mutants and strikingly discovered that Orco knockout mutants displayed significant widespread downregulation of tuning Ors, suggesting that Orco may influence OR expression or stability. Electrophysiological recordings confirmed significantly attenuated responses to human volatiles in Orco mutants, and behavioral assays demonstrated a marked decline in blood-feeding efficiency and elimination of host preference in females. Together, these findings reveal dynamic reorganization of ORNs during mosquito development and uncover the critical role of Orco in maintaining the integrity and function of the olfactory system, providing insights that may inform novel, next-generation vector control strategies.

neuroscience↗

China Autism Brain Imaging Consortium: Charting Brain Growth in Chinese Children with Autism

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

neuroscience↗

Deep graph convolutional neural network for one-dimensional hepatic vascular haemodynamic prediction

Hepatic vascular hemodynamics is an important reference indicator in the diagnosis and treatment of hepatic diseases. However, Method based on Computational Fluid Dynamics(CFD) are difficult to promote in clinical applications due to their computational complexity. To this end, this study proposed a deep graph neural network model to simulate the one-dimensional hemodynamic results of hepatic vessels. By connecting residuals between edges and nodes, this framework effectively enhances network prediction accuracy and efficiently avoids over-smoothing phenomena. The graph structure constructed from the centerline and boundary conditions of the hepatic vasculature can serve as the network input, yielding velocity and pressure information corresponding to the centerline. Experimental results indicate that our proposed method achieves higher accuracy on a hepatic vasculature dataset with significant individual variations and can be extended to applications involving other blood vessels. Following training, errors in both the velocity and pressure fields are maintained below 1.5%. The trained network model can be easily deployed on low-performance devices and, compared to CFD-based methods, can output velocity and pressure along the hepatic vessel centerline at a speed three orders of magnitude faster. Author summaryWhen using deep learning methods for hemodynamic analysis, simple point cloud data cannot express the real geometric structure of the blood vessels, and it is necessary for the network to have additional geometric information extraction capability. In this paper, we use graph structure to express the structure of hepatic blood vessels, and deep graph neural network to predict the corresponding hemodynamic parameters. The graph structure can effectively express the geometric information of hepatic blood vessels and the topology of branch blood vessels, which can effectively improve the prediction accuracy with strong geometric generalisation ability. The results show that the method achieves the highest prediction accuracy in the one-dimensional hepatic vessel blood flow simulation dataset, and the experimental results on the human aorta also show that our method can be effectively applied to the blood flow simulation of other vascular organs.

systems biology↗

Weighted variance component test for the integrative multi-omics analysis of microbiome data

Metabolic dysregulation and alterations have been linked to various diseases and conditions. Innovations in high-throughput technology now allow rapid profiling of the metabolome and metagenome -- often the gene content of bacterial populations -- for characterizing metabolism. Due to the small sample sizes and high dimensionality of the data, pathway analysis (wherein the effect of multiple genes or metabolites on an outcome is cumulatively assessed) of metabolomic data is commonly conducted and also represents a standard for metagenomic analysis. However, how to integrate both data types remains unclear. Recognizing that a metabolic pathway can be complementarily characterized by both metagenomics and metabolomics, we propose a weighted variance components framework to test if the joint effect of genes and metabolites in a biological pathway is associated with outcomes. The approach allows analytic p-value calculation, correlation between data types, and optimal weighting. Power simulations show that our approach often outperforms other strategies while maintaining type I error. The approach is illustrated on real data.

bioinformatics↗

Heterogeneous hybrid immunity against Omicron variant JN.1 at 11 months following breakthrough infection

A highly transmissible SARS-CoV-2 variant JN.1 is rapidly spreading throughout the nation, becoming the predominant strain in China and worldwide. However, the current immunity against the circulating JN.1 at population level has yet to be fully evaluated. We recruited representative cohorts with stratified age groups and diverse combinations of vaccination and/or infection in recent months, and promptly assessed humoral immunity for these subjects predominantly exhibiting hybrid immunity. We report that at 11 months following BA.5-wave breakthrough infection (BTI), these vaccinated individuals generally showed above-the-threshold yet low level of neutralizing activity against JN.1, with slightly greater potency observed in children and adolescents compared to adults and seniors. Meanwhile, XBB/EG.5-wave reinfection post-BTI significantly boosted the neutralizing antibodies against Omicron variants, including JN.1 in both adults (13.4-fold increase) and seniors (24.9-fold increase). To better understand respiratory mucosal protection against JN.1 over an extended period of months post-BTI, we profiled the humoral immunity in bronchoalveolar lavage samples obtained from vaccinated subjects with or without BTI, and revealed increased potency of neutralizing activity against the BA.5 and JN.1 variants in the respiratory mucosa through natural infection. Notably, at 11 months post-BTI, memory B cell responses against prototype and JN.1 were detectable in both blood and respiratory mucosa, displaying distinct memory features in the circulation and airway compartments. XBB/EG.5-wave reinfection drove the expansion of JN.1-specific B cells, along with the back-boosting of B cells responding to the ancestral viral strain, suggesting the involvement of immune imprinting. Together, this study indicates heterogeneous hybrid immunity over 11 months post-BTI, and underscores the vulnerability of individuals, particularly high-risk seniors, to JN.1 breakthrough infection. An additional booster with XBB-containing vaccine may greatly alleviate the onward transmission of immune-evasive SARS-CoV-2 variants.

immunology↗

Ferroptosis induced by phenolic compound-iron complex

Phenolic compounds are the most ubiquitously distributed pollutants, and are highly toxic to living organisms, however the detailed mechanism how phenols exert toxic effects remains elusive. Here,Escherichia coli and phloroglucinol are adapted as proxy to elucidate the molecular mechanism of phenols toxicity. We demonstrated that phloroglucinol complexed with iron and promoted the generation of hydroxyl radicals in Fenton reaction, leading to reducing power depletion and lipid peroxidation, and further leading to ferroptosis-like cell death ofE. coli. This ferroptotic death can be triggered by various phenols in diverse organisms, from bacteria to mammalian cells. Furthermore, we demonstrated that phloroglucinol-induced ferroptosis suppressed tumor growth in mice effectively, indicating phloroglucinol as promising drug for therapy-resistant cancers. Its also discovered that repression of this ferroptosis-like cell death benefited microbial degradation or production of desired phenolic compounds, showing great application potential in biotechnology field.

microbiology↗

Remodeling the central metabolism of Escherichia coli enables a universal chassis

E. coli is the host of choice to produce a wide variety of chemicals and proteins. Overflow metabolism is considered as the widespread and major obstacle in microbial synthesis, and overcoming this common bottleneck may enable a universal chassis. Here, we constructed an E. coli universal chassis (ABKS strain) with significantly suppressed overflow metabolism, presenting similar growth rate, decreased glucose consumption, and increased production of desired chemicals and proteins when compared with wild-type BL21(DE3) strain. Furthermore, we demonstrated that metabolic flux of ABKS strain was reprogrammed from TCA cycle to glyoxylate bypass at isocitrate node via the synergistic effect of multi-layer regulation in gene transcription and protein modification. This metabolic reconfiguration alleviates overflow metabolism, avoids CO2 release in TCA cycle, finally improving the carbon atom economy in bioprocess. Our chassis has widespread and practical use for elevating the production and yield of multiple desired chemicals and proteins from different carbon source. The metabolic reconfiguration also provides theoretical basis for rational design of efficient bioproduction strains.

bioengineering↗

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase [~]50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

genomics↗

StocSum: stochastic summary statistics for whole genome sequencing studies

Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.

genetics↗

Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

genomics↗

Uncovering bacterial hosts of class 1 integrons in an urban coastal aquatic environment with a single-cell fusion-PCR technology

Horizontal gene transfer (HGT) is a key driver of bacterial evolution via transmission of genetic materials across taxa. Class 1 integrons are genetic elements that correlate strongly with anthropogenic pollution and contribute to the spread of antimicrobial resistance (AMR) genes via HGT. Despite their significance to human health, there is a shortage of robust, culture-free surveillance technologies for identifying uncultivated environmental taxa that harbour class 1 integrons. We developed a modified version of epicPCR (emulsion, paired isolation and concatenation polymerase chain reaction) that links class 1 integrons amplified from single bacterial cells to taxonomic markers from the same cells in emulsified aqueous droplets. Using this single-cell genomic approach and Nanopore sequencing, we successfully assigned class 1 integron gene cassette arrays containing mostly AMR genes to their hosts in coastal water samples that were affected by pollution. Our work presents the first application of epicPCR for targeting variable, multi-gene loci of interest. We also identified the Rhizobacter genus as novel hosts of class 1 integrons. These findings establish epicPCR as a powerful tool for linking taxa to class 1 integrons in environmental bacterial communities and offer the potential to direct mitigation efforts towards hotspots of class 1 integron-mediated dissemination of AMR. SynopsisWe present a novel single-cell genomic surveillance technology for identifying environmental bacterial hosts of a class of mobile genetic elements that are linked to anthropogenic pollution and contribute to the dissemination of antimicrobial resistance.

microbiology↗

Microbiota-stimulated Interleukin-22 regulates brain neurons and protects against stress-induced anxiety

Psychological stress and its sequelae are a major public health problem. While the immune system has been implicated in the development of stress-related disorders, how the immune signals modulate neural responses to stress is poorly understood. Contrary to our expectations, we found that the immune cytokine Interleukin (IL)-22 is the key mediator of an immune-to-brain pathway that diminishes, rather than amplifies, stress-induced anxiety. We showed that stress induced TH17 differentiation and IL-22 production in the intestine following barrier dysfunction and microbiota stimulation. IL-22 then directly signaled to septal neurons in the brain to mitigate anxiety-like behavior. Accordingly, mice treated with exogenous IL-22 showed resilience to chronic stress-induced anxiety disorders. Our study thus reveals a previously-unappreciated immune-to-brain axis that defends against psychological stress, suggesting a potential intervention strategy for stress-related mental diseases.

immunology↗