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Li, P.

Publications and source records attributed to Li, P..

At least 181 records · Page 10Linked to original sources

Global and local adaptation to aridity in a desert plant Gymnocarpos przewalskii

In order to thrive and survive plant species need to combine stability in the long term and rapid response to environmental challenges in the short term. The former would be reflected by global adaptation across species and the latter by pronounced local adaptation among populations of the same species. It remains unclear how much overlap is to be expected between the parts of the genome associated to these two contrasted adaptation processes. In the present study, we generated a high-quality genome and re-sequenced 177 individuals for Gymnocarpos przewalskii, an important desert plant species from North-West China, to detect local adaptation. To test for global adaptation to aridity at the molecular level we compared genomic data of 15 species that vary in their ability to withstand drought. A total of 118 genes were involved in global adaptation to aridity. Sixty-five G. przewalskii genes were shared across all xerophytic species, of which sixty-three were under stabilizing selection and two under directional selection. While 20% of G. przewalskii genome showed signatures of local adaptation to aridity during population divergence, only 13 of those genes were also under global adaptation. Hence, our results suggest that long-term stability is crucial for adaptation to extreme environmental stress but is only maintained in a small group of highly pleiotropic genes while a rapid response to recent changes elicits a genome-wide response, including gene family expansion. The overlap between the two evolutionary mechanisms appears limited.

evolutionary biology↗

Central and peripheral clocks synergistically enhance circadian robustness, flexibility and performance of cardiac pacemaking

The strong circadian ([~]24h) rhythms in heart rate (HR) are critical for flexible regulation of cardiac pacemaking function throughout the day. While this circadian flexibility in HR is robustly sustained in diverse conditions, it declines as the heart ages, accompanied by reduced maximal HR performance. The intricate regulation of circadian HR patterns involves the orchestration of sympathetic and parasympathetic nervous activities (SNA and PNA) alongside local circadian rhythmicity (LCR) within the heart. However, their intricate interactions that sustain the resilience and adaptability of circadian rhythms, as well as the mechanisms that underpin their deterioration during the aging process, remain enigmatic. To address these questions, we developed a mathematical model describing autonomic control and LCR in sinoatrial nodal cells (SANC) that accurately captures distinct circadian patterns in adult and aged mice. Our model underscores the indispensable synergy among SNA, PNA, and LCR in preserving circadian flexibility, robustness, and performance in SANC. SNA predominantly enhances SANC robustness and performance, while PNA primarily drives SANC flexibility, complemented by LCR and SNA. LCR acts as a booster, further enhancing SANC flexibility and performance. However, the delicate balance of this synergy is disrupted with age, resulting in diminished SANC performance and flexibility. Specifically, age-related impairment of PNA selectively dampens SANC flexibility while ion channel remodeling disrupts all SANC functions. Our work shed light on their critical synergistic interactions in regulating time-of-day cardiac pacemaking function and dysfunction, which may help to identify potential therapeutic targets within the circadian clock for the prevention and treatment of cardiac arrhythmias. Author SummaryThe mammalian heart relies on the sinoatrial node, known as the cardiac pacemaker, to orchestrate heartbeats. These heartbeats slow down during sleep and accelerate upon waking, in anticipation of daily environmental changes. The hearts ability to rhythmically adapt to these 24-hour changes, known as circadian rhythms, is crucial for flexible cardiac performance throughout the day, accommodating various physiological states. However, with aging, the hearts circadian flexibility gradually weakens, accompanied by a decline in maximal heart rate. Previous studies have implicated the involvement of a master circadian clock and a local circadian clock within the heart, but their time-of-day interactions and altered dynamics during aging remain unclear. In this study, we developed a mathematical model to simulate the regulation of sinoatrial nodal cell pacemaking function by the master and local circadian clocks in adult and aged mice. Our results revealed distinct roles played by these clocks in determining circadian patterns of sinoatrial nodal cells and shed light on their critical synergistic interactions in regulating time-of-day cardiac pacemaking function and dysfunction.

physiology↗

CellGO: A novel deep learning-based framework and webserver for cell type-specific gene function interpretation

Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to account for complex interactions across genes and pathways under specific tissues and cell types. We introduce CellGO, a tool for cell type-specific gene functional analysis. CellGO employs a deep learning model to simulate signaling propagation within a cell, enabling the development of a heuristic pathway activity measuring system to identify cell type-specific active pathways given a single gene or a gene set. It is featured with additional functions to uncover pathway communities and the most active genes within pathways to facilitate mechanistic interpretation. This study demonstrated that CellGO can effectively capture cell type-specific pathways even when working with mixed cell-type markers. CellGOs performance was benchmarked using gene knockout datasets, and its implementation effectively infers the cell type-specific pathogenesis of risk genes associated with neurodevelopmental and neurodegenerative disorders, suggesting its potential in understanding complex polygenic diseases. CellGO is accessible through a python package and a four-mode web interface for interactive usage with pretrained models on 71 single-cell datasets from human and mouse fetal and postnatal brains.

bioinformatics↗

BrrRCO, encoding a homeobox protein, is involved in leaf lobe development in Brassica rapa

Leaf shape is a vital economic and developmental trait in leafy vegetable Chinese cabbage (Brassica rapa L. subsp. pekinensis), which varies from smooth to deeply lobed, whereas the molecular basis remains unclear. Here, we detected an incompletely dominant major quantitative trait locus (QTL) qBrrLLA10 for the lobed-leaf trait in B. rapa, and identified BrrRCO, encoding a HD-Zip transcription factor, as the casual gene underlying lobed leaf formation in B. rapa. Genotyping analysis showed that abundant variations in promoter of BrrRCO is responsible for leaf lobe variation, and the expression levels and promoter activity were significantly affected by the promoter variations between two parents. BrrRCO was a nucleus-specific protein and possess highest expression level at the bases of each lobe. Ectopic overexpression of BrrRCO in Arabidopsis led to deeply lobed leaves have never been seen in wild type, and leaf lobe development was blocked when BrrRCO expression was down-regulated through virus-induced gene silencing assays. Taken together, our findings revealed that BrrRCO positively regulate leaf lobe formation in Chinese cabbage, and the cis-regulatory element modifications result in functional variation of BrrRCO, providing a novel insight into the leaf shape improvement in Chinese cabbage and other Brassica species. HighlightBrrRCO is essential for leaf lobe formation by repressing local growth of leaf margin cells in B. rapa, and cis-regulatory modifications cause the different allele effects.

plant biology↗

Predictive Systems Biology Modeling: Unraveling Host Metabolic Disruptions and Potential Drug Targets in SARS-CoV-2 and Its Variants

BackgroundHost response is critical to the onset, progression, and outcome of viral infections. Since viruses hijack the host cellular metabolism for their replications, we hypothesized that restoring host cell metabolism can efficiently reduce viral production. ResultsHere, we present a viral-host Metabolic Modeling (vhMM) method to systematically evaluate the disturbances in host metabolism in viral infection and computationally identify targets for modulation by integrating genome-wide precision metabolic modeling and cheminformatics. We applied vhMM to SARS-CoV-2 infections and identified consistent changes in host metabolism and gene and endogenous metabolite targets between the original SARS-COV-2 and different variants (Alpha, Delta, and Omicron). Among six compounds predicted for repurposing, methotrexate, cinnamaldehyde, and deferiprone were tested in vitro and effective in inhibiting viral production with IC50 less than 4uM. Further, an analysis of real-world patient data showed that cinnamon usage significantly reduced the SARS-CoV-2 infection rate with an odds ratio of 0.65 [95%CI: 0.55[~]0.75]. ConclusionsThese results demonstrated that vhMM is an efficient method for predicting targets and drugs for viral infections.

systems biology↗

A Phase Separation-Fortified Bi-Specific Adaptor for Conditional Tumor Killing

A common approach in the development of therapeutic proteins is the use of synthetic ligands with multivalency, allowing for sophisticated control of signal transduction. Leveraging the emerging concept of liquid-liquid phase separation (LLPS) and its ability to organize cell surface receptors into functional compartments, we herein have designed modular ligands with phase-separation modalities to engineer programmable interreceptor communications and precise control of signal pathways, thus inducing the rapid, potent, and specific apoptosis of tumor cells. Despite their simplicity, these "triggers", named phase-separated Tumor Killers (hereafter referred to as psTK), are sufficient to yield interreceptor clustering of death receptors (represented by DR5) and tumor-associated receptors, with the following features: LLPS-mediated robust high-order organization, well-choreographed conditional activation, and broad-spectrum capacity for potently inducing apoptosis of tumor cells. The development of novel therapeutic proteins with phase-separation modalities showcases the power of spatially reorganizing signal transduction. This approach enables the branching of cell fate and holds promising potential for targeted therapies against challenging tumors. One-Sentence SummaryEngineered modular ligands with phase-separation modalities can drive lethal dialog with tumor cells.

bioengineering↗

Single transcript-level metabolic responsive landscape of human liver transcriptome

Direct knowledge of gene regulation in human liver by metabolic stimuli could fundamentally advance our understanding of metabolic physiology. This information, however, is largely unknown, and this void is deeply rooted in a paradox that is caused by the inaccessibility of human liver to treatments and the insufficient annotation of liver transcriptome. Recent advances have uncovered immense complexity of transcriptome, i.e., multiple transcripts produced from one gene and extensive RNA modifications, which are all highly regulated and often condition-dependent. Establishing an inclusive annotation to study liver transcriptome dynamics thus requires human liver samples of diverse conditions, which are paradoxically unavailable due to the inaccessibility of human liver to treatments. In this work, we addressed these challenges by coupling an isogenic humanized mouse model with Nanopore single-molecule direct RNA sequencing (DRS). We first generated mice that carried humanized livers of identical genetic background, which were equivalent to clones of a single human liver, and then subjected the mice to representative metabolic treatments. We then analyzed the humanized livers with Nanopore DRS, which directly reads full-length native RNAs to determine the expression level, m6A modification and poly(A) tail length of all RNA transcript isoforms. Thus, our system allows for constructing a de novo annotation of human liver transcriptomes reflecting metabolic responses and studying transcriptome dynamics in conjunction. Our analysis uncovered a vast number of novel genes and transcripts that have not been previously reported. Our transcript-level analysis of human liver transcriptomes also identified a multitude of regulated metabolic pathways that were otherwise invisible using conventional short read RNA-seq. We also revealed for the first time the dynamic changes in m6A and poly(A) tail length of human liver transcripts many of which are transcribed from key metabolic genes. Furthermore, we performed comparative analyses of gene regulation between human and mouse and between two individuals using the liver-specific humanized mice. This revealed that transcriptome dynamics are highly species- and genetic background-dependent, which may only be faithfully studied in a humanized system that entails clones of the same human liver. Hence our work revealed a complex metabolic responsive landscape of human liver transcriptome and also provided a framework to understand transcriptome dynamics of human liver in response to physiologically relevant metabolic stimuli.

systems biology↗

Structural and Biological Evaluations of a Non-Nucleoside STING Agonist Specific for Human STING-A230 Variants

Previously we identified a non-nucleotide tricyclic agonist BDW568 that activates human STING (stimulator of interferon genes) gene variant containing A230 in a human monocyte cell line (THP-1). STINGA230 alleles, including HAQ and AQ, are less common STING variants in human population. To further characterize the mechanism of BDW568, we obtained the crystal structure of the C-terminal domain of STINGA230 complexed with BDW-OH (active metabolite of BDW568) at 1.95 [A] resolution and found the planar tricyclic structure in BDW-OH dimerizes in the STING binding pocket and mimics the two nucleobases of the endogenous STING ligand 2,3-cGAMP. This binding mode also resembles a known synthetic ligand of human STING, MSA-2, but not another tricyclic mouse STING agonist DMXAA. Structure-activity-relationship (SAR) studies revealed that all three heterocycles in BDW568 and the S-acetate side chain are critical for retaining the compounds activity. BDW568 could robustly activate the STING pathway in human primary peripheral blood mononuclear cells (PBMCs) with STINGA230 genotype from healthy individuals. We also observed BDW568 could robustly activate type I interferon signaling in purified human primary macrophages that were transduced with lentivirus expressing STINGA230, suggesting its potential use to selectively activate genetically engineered macrophages in macrophage-based approaches, such as chimeric antigen receptor (CAR)-macrophage immunotherapies.

pharmacology and toxicology↗

Learning better with Dale's Law: A Spectral Perspective

Most recurrent neural networks (RNNs) do not include a fundamental constraint of real neural circuits: Dales Law, which implies that neurons must be excitatory (E) or inhibitory (I). Dales Law is generally absent from RNNs because simply partitioning a standard networks units into E and I populations impairs learning. However, here we extend a recent feedforward bio-inspired EI network architecture, named Dales ANNs, to recurrent networks, and demonstrate that good performance is possible while respecting Dales Law. This begs the question: What makes some forms of EI network learn poorly and others learn well? And, why does the simple approach of incorporating Dales Law impair learning? Historically the answer was thought to be the sign constraints on EI network parameters, and this was a motivation behind Dales ANNs. However, here we show the spectral properties of the recurrent weight matrix at initialisation are more impactful on network performance than sign constraints. We find that simple EI partitioning results in a singular value distribution that is multimodal and dispersed, whereas standard RNNs have an unimodal, more clustered singular value distribution, as do recurrent Dales ANNs. We also show that the spectral properties and performance of partitioned EI networks are worse for small networks with fewer I units, and we present normalised SVD entropy as a measure of spectrum pathology that correlates with performance. Overall, this work sheds light on a long-standing mystery in neuroscience-inspired AI and computational neuroscience, paving the way for greater alignment between neural networks and biology.

neuroscience↗

Uncovering Ghost Introgression Through Genomic Analysis of a Distinct East Asian Hickory Species

Although the possibility of introgression from ghost lineages (all unsampled extant and extinct taxa) is now widely recognized, detecting and characterizing ghost introgression remains a challenge. Here, we propose a combined use of the popular D-statistic method, which tests for the presence of introgression, and the full-likelihood method BPP, which determines which of the possible gene-flow scenarios, including ghost introgression, is truly responsible. We illustrate the utility of this approach by investigating the reticulation and bifurcation history of the genus Carya (Juglandaceae), including the beaked hickory Carya sinensis. To achieve this goal, we generated two chromosome-level reference genomes respectively for C. sinensis and C. cathayensis. Furthermore, we re-sequenced the whole genomes of 43 individuals from C. sinensis and one individual from each of the 11 diploid species of Carya. The latter dataset with one individual per species is used to reconstruct the phylogenetic networks and estimate the divergence time of Carya. Our results unambiguously demonstrate the presence of ghost introgression from an extinct lineage into the beaked hickory, dispelling certain misconceptions about the phylogenetic history of C. sinensis. We also discuss the profound implications of ghost introgression into C. sinensis for the historical biogeography of hickory species. [BPP; Carya; D-statistic; gene flow; ghost introgression]

evolutionary biology↗

Genetic Screen Identified Prmt5 as a Neuroprotection Target against Cerebral Ischemia

Epigenetic regulators present novel opportunities for both ischemic stroke research and therapeutic interventions. While previous work has implicated that they may provide neuroprotection by potentially influencing coordinated sets of genes and pathways, most of them remains largely uncharacterized in ischemic conditions. In this study, we used the oxygen-glucose deprivation (OGD) model in the immortalized mouse hippocampal neuronal cell line HT-22 and carried out an RNAi screen on epigenetic regulators. We identified Prmt5 as a novel negative regulator of neuronal cell survival after OGD, which presented a phenotype of translocation from the cytosol to the nucleus upon oxygen and energy depletion both in vitro and in vivo. Prmt5 bound to the chromatin and a large number of promoter regions to repress downstream gene expression. Silencing Prmt5 significantly dampened the OGD-induced changes for a large-scale of genes, and gene ontology analysis showed that Prmt5-target genes were highly enriched for Hedgehog signaling. Encouraged by the above observation, we treated mice with middle cerebral artery occlusion (MCAO) with the Prmt5 inhibitor EPZ015666 and found that Prmt5 inhibition sustain protection against neuronal death in vivo. Together, our findings revealed a novel epigenetic mechanism of Prmt5 in cerebral ischemia and uncovered a potential target for neuroprotection.

cell biology↗

A Two-Filter Adaptation to Achieve Hemodiafiltration with Enhanced Performance

IntroductionAdvancements in hemodialysis (HD) instrumentation have resulted in numerous breakthroughs in technology and significantly enhanced patient outcomes. Today, hemodiafiltration (HDF) which combines HD and hemofiltration has been widely used as an alternative to conventional HD in many countries. HDF is known to outperform conventional HD, offering more effective waste clearance and better fluid balance to patients. However, HDF requires newer-generation machines that are not accessible in many under-resourced geographical regions and societies. This study investigates a facile adaptation of conventional HD machines to achieve HDF. The objectives are to address the premature obsolescence of older but fully functional machines and to advocate for equal access to improved medical care and treatment. MethodsA bench-top experimental setup was established to evaluate the performance of HDF using a two-filter adaptation in comparison to that of standard HD. Urea clearance, human serum album loss, and hemolysis were assessed under identical operational conditions for both configurations. FindingsOur results show that the HDF configuration outperformed the HD configuration, with significantly higher urea clearance (268.31{+/-}44.17 mL/min via HDF vs. 53.33{+/-}13.20 mL/min via HD), but comparable human serum albumin loss and hemolysis levels. DiscussionThe explored two-filter adaptation presents a cost-effective method to achieve HDF with improved performance using conventional HD machines, with no added risk to patients. Further validation on patients in a hospital setting is necessary.

bioengineering↗

A new pipeline SPICE identifies novel JUN-IKZF1 composite elements

Transcription factor partners can cooperatively bind to DNA composite elements to augment gene transcription. Here, we report a novel protein-DNA binding screening pipeline, termed Spacing Preference Identification of Composite Elements (SPICE), that can systematically predict protein binding partners and DNA motif spacing preferences. Using SPICE, we successfully identified known composite elements, such as AP1-IRF composite elements (AICEs) and STAT5 tetramers, and also uncovered several novel binding partners, including JUN-IKZF1 composite elements. One such novel interaction was identified at CNS9, an upstream conserved noncoding region in the human IL10 gene, which harbors a non-canonical IKZF1 binding site. We confirmed cooperative binding of JUN and IKZF1 and showed that the activity of an IL10-luciferase reporter construct in primary B and T cells depended on both this site and the AP1 binding site within this composite element. Overall, our findings reveal an unappreciated global association of IKZF1 and AP1 and establish SPICE as a valuable new pipeline for predicting novel transcription binding complexes.

systems biology↗

Single-chain fluorescent integrators for mapping G-protein-coupled receptor agonists

GPCRs transduce the effects of many neuromodulators including dopamine, serotonin, epinephrine, acetylcholine, and opioids. The localization of synthetic or endogenous GPCR agonists impacts their action on specific neuronal pathways. In this paper, we show a series of single-protein chain integrator sensors to determine GPCR agonist localization in the whole brain. We previously engineered integrator sensors for the mu and kappa opioid receptor agonists called M- and K-SPOTIT, respectively. Here, we show a new integrator sensor design platform called SPOTall that we used to engineer sensors for the beta-2-adrenergic receptor (B2AR), the dopamine receptor D1, and the cholinergic receptor muscarinic 2 agonists. For multiplexed imaging of SPOTIT and SPOTall, we engineered a red version of the SPOTIT sensors. Finally, we used M-SPOTIT and B2AR-SPOTall to detect morphine, isoproterenol, and epinephrine in the mouse brain. The SPOTIT and SPOTall sensor design platform can be used to design a variety of GPCR integrator sensors for unbiased agonist detection of many synthetic and endogenous neuromodulators across the whole brain.

bioengineering↗

Structural principles of peptide-centric Chimeric Antigen Receptor recognition guide therapeutic expansion

Peptide-Centric Chimeric Antigen Receptors (PC-CARs), which recognize oncoprotein epitopes displayed by human leukocyte antigens (HLAs) on the cell surface, offer a promising strategy for targeted cancer therapy1. We have previously developed a PC-CAR targeting a neuroblastoma- associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes2. Here, we determine the 2.1 [A] structure of the PC-CAR:PHOX2B/HLA-A*24:02/{beta}2m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). The PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactivity group, covering a combined American population frequency of up to 25.2%. Comprehensive characterization using biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation and CAR-T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.

biochemistry↗

Diazo-carboxyl click chemistry enables rapid and sensitive quantification of carboxylic acid metabolites

Carboxylic acids are central metabolites in bioenergetics, signal transduction and post-translation protein regulation. Unlike its genomic and transcriptomic counterparts, the quest for metabolomic profiling in trace amounts of biomedical samples is prohibitively challenging largely due to the lack of sensitive and robust quantification schemes for carboxylic acids. Based on diazo-carboxyl click chemistry, here we demonstrate DQmB-HA method as a rapid derivatization strategy for the sensitive analysis of hydrophilic, low-molecular-weight carboxylic acids. To the investigated metabolites, DQmB-HA derivatization method renders 5 to 2,000-fold higher response on mass spectrometry along with improved chromatographic separation on commercial UHPLC-MS machines. Using this method, we present the near-single-cell analysis of carboxylic acid metabolites in mouse egg cells before and after fertilization. Malate, fumarate and {beta}-hydroxybutyrate were found to decrease in mouse zygotes. We also showcase the kinetic profiling of TCA-cycle intermediates inside adherent cells cultured in one well of 96-well plates during drug treatment. FCCP and AZD3965 were shown to have overlapped but different effects on the isotope labeling of carboxylic acids. Finally, we apply DQmB-HA method to plasma or serum samples (down to 5 L) from mice and humans collected on pathological and physiological conditions. The measured changes of succinate, {beta}-hydroxybutyrate, and lactate in blood corroborate previous literatures in ischemia-reperfusion injury mouse model, acute fasting-refeeding mouse model, and human individuals diagnosed with mitochondrial dysfunction diseases, respectively. Overall, DQmB-HA method offers a sensitive, rapid and user-friendly quantification scheme for carboxylic acid metabolites, paving the road toward the ultimate goals of single-cell metabolomic analysis and bedside monitoring of biofluid samples.

systems biology↗

Ebola Virus Sequesters IRF3 in Viral Inclusion Bodies to Evade Host Antiviral Immunity

Viral inclusion bodies (IBs) commonly form during the replication of Ebola virus (EBOV) in infected cells, but their role in viral immune evasion has rarely been explored. Here, we found that interferon regulatory factor 3 (IRF3), but not TANK-binding kinase 1 (TBK-1) or I{kappa}B kinase epsilon (IKK{varepsilon}), was recruited and sequestered in viral IBs when the cells were infected by EBOV transcription- and replication-competent virus-like particles (trVLPs). NP/VP35-induced IBs formation was critical for IRF3 recruitment and sequestration, probably through interaction with STING. Consequently, the association of TBK1 and IRF3, which plays a vital role in type I interferon (IFN-I) induction, was blocked by EBOV trVLPs infection. Additionally, IRF3 phosphorylation and nuclear translocation induced by Sendai virus (SeV) or poly(I:C) stimulation were suppressed by EBOV trVLPs. Furthermore, downregulation of STING significantly attenuated VP35-induced IRF3 accumulation in IBs. Coexpression of the viral proteins by which IBs-like structures formed was much more potent in antagonizing IFN-I than expression of the IFN-I antagonist VP35 alone. These results suggested a novel immune evasion mechanism by which EBOV evades host innate immunity. Impact statementEbola virus VP35 protein evades host antiviral immunity by interacting with STING to sequester IRF3 into inclusion bodies and inhibit type-I interferon production.

microbiology↗

Insight into the genetic diversity, resistance, and virulence of Listeria from the marine environment: reveal the risk of hypervirulent isolates

Listeria monocytogenes is a major human foodborne pathogen and a ubiquitous environmental saprophyte. In this study, we investigated the prevalence and characteristics of Listeria spp. from beach sand in the coastal environment. Three different Listeria spp., Listeria monocytogenes (n=16), Listeria fleishmanii (n=7), and Listeria aquatica (n=3) were isolated from 769 beach sand samples and demonstrated diverse biofilm forming capacity. The L. monocytogenes isolates belonged to four distinct sequence types (ST87, ST121, ST35, and ST85) and contained the majority of virulence genes, some isolates were hypervirulent clones or had close phylogenetic relatedness with clinical cases. The ST87 isolates showed higher ability of biofilm formation in seawater than other STs strains. As a reservoir of microbes from marine environments and human/animal excrement, coastal sand would play an important role in the spread of L. monocytogenes and is an environmental risk for human listeriosis.

microbiology↗