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• Mupirocin enhanced the biofilm formation of Staphylococcus epidermidis. • Mupirocin facilitated the eDNA release but did not affect PIA production. • Mupirocin regulated the expression of altE, cidA , and lrgAB. • The autolysin AltE is required for the induction of mupirocin on biofilm formation. The pathogenicity of Staphylococcus epidermidis is largely attributed to its exceptional ability to form biofilms. Here, we report that mupirocin, an antimicrobial agent widely used for staphylococcal decolonization and anti-infection, strongly stimulates the biofilm formation of S. epidermidis. Although the polysaccharide intercellular adhesin (PIA) production was unaffected, mupirocin significantly facilitated extracellular DNA (eDNA) release by accelerating autolysis, thereby positively triggering cell surface attachment and intercellular agglomeration during biofilm development. Mechanistically, mupirocin regulated the expression of genes encoding for the autolysin AtlE as well as the programmed cell death system CidA-LrgAB. Critically, through gene knockout, we found out that deletion of atlE , but not cidA or lrgA , abolished the enhancement of biofilm formation and eDNA release in response to mupirocin treatment, indicating that atlE is required for this effect. In Triton X-100 induced autolysis assay, mupirocin treated atlE mutant displayed a slower autolysis rate compared with the wild-type strain and complementary strain. Therefore, we concluded that subinhibitory concentrations of mupirocin enhance the biofilm formation of S. epidermidis in an atlE dependent manner. This induction effect could conceivably be responsible for some of the more unfavourable outcomes of infectious diseases. [ABSTRACT FROM AUTHOR]

Although the development of AI in games is remarkable, intelligent machines still lag behind humans in games that require the ability of language understanding. In this paper, we focus on the crossword puzzle resolution task. Solving crossword puzzles is a challenging task since it requires the ability to answer natural language questions with knowledge and the ability to execute a search over possible answers to find an optimal set of solutions for the grid. Previous solutions are devoted to exploiting heuristic strategies in search to find solutions while having limited ability to explore the search space. We build a comprehensive system for crossword puzzle resolution based on Monte Carlo Tree Search (MCTS). As far as we know, we are the first to model the crossword puzzle resolution problem as a Markov Decision Process and apply the MCTS to solve it. We construct a dataset for crossword puzzle resolution based on daily puzzles from The New York Times with detailed specifications of both the puzzle and clue database selection. Our method achieves state-of-the-art performance on the dataset. The code of the system and experiments in this paper is publicly available: https://www.github.com/lhlclhl/CP. [ABSTRACT FROM AUTHOR]

With the proliferation of knowledge graphs, modeling data with complex multi-relational structure has gained increasing attention in the area of statistical relational learning. One of the most important goals of statistical relational learning is link prediction, that is, predicting whether certain relations exist in the knowledge graph. A large number of models and algorithms have been proposed to perform link prediction, among which tensor factorization method has proven to achieve state-of-the-art performance in terms of computation efficiency and prediction accuracy. However, a common drawback of the existing tensor factorization models is that the missing relations and nonexisting relations are treated in the same way, which results in a loss of information. To address this issue, we propose a binary tensor factorization model with probit link, which not only inherits the computation efficiency from the classic tensor factorization model but also accounts for the binary nature of relational data. Our proposed probit tensor factorization (PTF) model shows advantages in both the prediction accuracy and interpretability. Supplementary files for this article are available online. [ABSTRACT FROM AUTHOR]

It is crucial to model missing ratings in recommender systems since user preferences learnt from only observed ratings are biased. One possible explanation for missing ratings is motivated by the spiral of silence theory. When the majority opinion is formed, a spiral process is triggered where users are more and more likely to show their ratings if they perceive that they are supported by the opinion climate. In this paper we first verify the existence of the spiral process in recommender systems by using a variety of different real-life datasets. We then study the characteristics of two key factors in the spiral process: opinion climate and the hardcore users who will give ratings even when they are minority opinion holders. Based on our empirical findings, we develop four variants to model missing ratings. They mimic different components of the spiral of silence based on the spiral process with global opinion climate, local opinion climate, hardcore users, relationships between hardcore users and items, respectively. We experimentally show that, the presented variants all outperform state-of-the-art recommendation models with missing rating components. [ABSTRACT FROM AUTHOR]

Spread through air spaces (STAS) is an emerging lung cancer infiltration pattern. Predicting its spread through CT scans is crucial. However, limited STAS data makes this prediction task highly challenging. Stable diffusion is capable of generating more diverse and higher-quality images compared to traditional GAN models, surpassing the dominating GAN family models in image synthesis over the past few years. To alleviate the issue of limited STAS data, we propose a method TDASD based on stable diffusion, which is able to generate high-resolution CT images of pulmonary nodules corresponding to specific nodular signs according to the medical professionals. First, we apply the stable diffusion method for fine-tuning training on publicly available lung datasets. Subsequently, we extract nodules from our hospital's lung adenocarcinoma data and apply slight rotations to the original nodule CT slices within a reasonable range before undergoing another round of fine-tuning through stable diffusion. Finally, employing DDIM and Ksample sampling methods, we generate lung adenocarcinoma nodule CT images with signs based on prompts provided by doctors. The method we propose not only safeguards patient privacy but also enhances the diversity of medical images under limited data conditions. Furthermore, our approach to generating medical images incorporates medical knowledge, resulting in images that exhibit pertinent medical features, thus holding significant value in tumor discrimination diagnostics. Our TDASD method has the capability to generate medically meaningful images by optimizing input prompts based on medical descriptions provided by experts. The images generated by our method can improve the model's classification accuracy. Furthermore, Utilizing solely the data generated by our method for model training, the test results on the original real dataset reveal an accuracy rate that closely aligns with the testing accuracy achieved through training on real data. The method we propose not only safeguards patient privacy but also enhances the diversity of medical images under limited data conditions. Furthermore, our approach to generating medical images incorporates medical knowledge, resulting in images that exhibit pertinent medical features, thus holding significant value in tumor discrimination diagnostics. • Our TDASD method enables stable diffusion training based on small-scale medical data. • Generate medical images with diagnostic significance in medical differentiation. • Learning non-spurious Image Representations. • Generated images help alleviate the scarcity of medical datasets. • Generating data effectively addresses patient privacy concerns. [ABSTRACT FROM AUTHOR]

How to enable intelligent machines to possess human commonsense knowledge is one of the central concerns of artificial intelligence. Consequently, a series of commonsense knowledge bases have been designed and constructed by scholars. However, as an important kind of commonsense knowledge, adjective-centric commonsense knowledge (a crucial type of adjective-concept pair such as (blue, sky), (eatable, food)) is far from satisfactory due to the lack of existing knowledge bases and limited acquisition methods. In this paper, we concentrate on automatically constructing large-scale adjective-centric commonsense knowledge bases and propose an effective framework to achieve the goal. The framework mainly contains a filtering module to remove unreasonable inputs, a clustering module, and a conceptualization module to obtain adjective-concept pairs and an evaluation module to assess their plausibility. Extensive automatic and human evaluation results demonstrate the effectiveness of our method, and we finally harvest over 200 k adjective-centric commonsense knowledge, where 81.56% of the implicit commonsense knowledge is not covered by WebChild. 1 1 WebChild is a large-scale commonsense knowledge base, which contains triples that connect nouns with adjectives via fine-grained relations. Moreover, we also show that our mined adjective-centric commonsense knowledge can benefit the downstream query conceptualization task. [ABSTRACT FROM AUTHOR]

Knowledge graphs (KGs) have achieved great success in many real applications, and great efforts have been dedicated to constructing larger knowledge graphs. An obvious trend in KG construction is that the KGs become ever-increasingly bigger. However, we argue that constructing a KG by directly inserting more triples may harm the performance of the KG, and one possible solution is KG compression. In this paper, we propose an exception-aware semantic lossless compression framework EASC to compress a KG. Since many triples can be inferred from other triples with semantic rules, we remove the triples that can be inferred and store the rules and exception cases. Specifically, we formalize the lossless compression problem as a weighted set cover problem, which is NP-hard, and propose a semantic lossless compression algorithm to get an approximation result. We conduct extensive experiments on seven real-world large-scale KGs. The results show that EASC achieves state-of-the-art performance in semantic compression methods. Furthermore, by combining EASC as an independent module with syntactic compression methods, we achieve state-of-the-art performance in lossless compression methods. • We propose an exception-aware semantic compression method for knowledge graphs. • We formalize the optimal lossless semantic compression of a KG as a weighted set cover problem. • Our method achieves the state-of-the-art performance in semantic compression methods. [ABSTRACT FROM AUTHOR]

Commonsense knowledge acquisition is one of the fundamental issues in realizing human-level AI. However, commonsense knowledge is difficult to obtain because it is a human consensus and rarely explicitly appears in texts or other data. In this paper, we focus on the automatic acquisition of a typical kind of implicit verb-oriented commonsense knowledge (e.g., " person eats food "), which is the concept-level knowledge of verb phrases. For this purpose, we propose a taxonomy-guided induction method to mine verb-oriented commonsense knowledge from verb phrases with the help of a probabilistic taxonomy. First, we design an entropy-based triplet filter to cope with noisy verb phrases. Then, we propose a joint model based on the minimum description length principle and a neural language model to generate verb-oriented commonsense knowledge. Besides, we introduce two strategies to accelerate the computation, including the simulated annealing-based approximate solution and the verb phrase clustering method. Finally, we conduct extensive experiments to prove that our solution is more effective than competitors in mining verb-oriented commonsense knowledge. We construct a commonsense knowledge base called VoCSK, containing 259 verbs and 18,406 verb-oriented commonsense knowledge. To verify the usefulness of VoCSK, we utilize the knowledge in this KB to improve the model performance on two downstream applications. [ABSTRACT FROM AUTHOR]

Text classification plays an important role in the areas of natural language processing and data mining. In general, a text is usually described around a collection of entities, i.e., the entities are the core part of the text. As a result, a deep understanding of the entities in a text benefits the classification of texts. To understand entities, traditional work tends to introduce concepts or web data for entities. However, we argue that the potential relations between entities are also important for the understanding of entity semantics, thus further supporting the classification of texts. In this paper, we focus on enhancing the performance of the existing text classification models by extracting features from entities with hierarchical graph learning. To this end, we mine the concepts of entities and the relations between them for a given text simultaneously, and further construct the semantic graph of the text. Then a novel hierarchical graph learning model is proposed to learn the graph embedding that well captures the node, relation, and graph structure information. Our experiments show that the proposed method has the ability to effectively improve the performance of the existing text classifiers. [ABSTRACT FROM AUTHOR]

Abstract: Behaviors of complex networks under intentional attacks guided by degree (degree attack) have been extensively studied. However, little is known about the behaviors of these networks under intentional attacks guided by damage (damage attack), in which adversaries choose the vertex with the largest damage to attack. In this article, we systematically investigate damage attack and behaviors of real networks as well as synthetic networks against damage attack. Empirical study shows that for real networks in a wide range of domains there exists a critical-point before which damage attack is more destructive than degree attack. This is further explained by the fact that degree attack tends to produce networks with more heterogeneous damage distribution than damage attack. Results in this article strongly suggest that damage attack is one of the most destructive attacks and deserves additional study. Our understanding about damage attack may also shed light on efficient solutions to protect real networks against damage attack. [Copyright &y& Elsevier]

Abstract: In this paper, we study a variant of reachability queries, called label-constraint reachability (LCR) queries. Specifically, given a label set S and two vertices u 1 and u 2 in a large directed graph G, we check the existence of a directed path from u 1 to u 2, where edge labels along the path are a subset of S. We propose the path-label transitive closure method to answer LCR queries. Specifically, we t4ransform an edge-labeled directed graph into an augmented DAG by replacing the maximal strongly connected components as bipartite graphs. We also propose a Dijkstra-like algorithm to compute path-label transitive closure by re-defining the “distance” of a path. Comparing with the existing solutions, we prove that our method is optimal in terms of the search space. Furthermore, we propose a simple yet effective partition-based framework (local path-label transitive closure+online traversal) to answer LCR queries in large graphs. We prove that finding the optimal graph partition to minimize query processing cost is a NP-hard problem. Therefore, we propose a sampling-based solution to find the sub-optimal partition. Moreover, we address the index maintenance issues to answer LCR queries over the dynamic graphs. Extensive experiments confirm the superiority of our method. [Copyright &y& Elsevier]

Knowledge graphs (KGs) are an important source repository for a wide range of applications and rule mining from KGs recently attracts wide research interest in the KG-related research community. Many solutions have been proposed for the rule mining from large-scale KGs, which however are limited in the inefficiency of rule generation and ineffectiveness of rule evaluation. To solve these problems, in this paper we propose a generation-then-evaluation rule mining approach guided by reinforcement learning. Specifically, a two-phased framework is designed. The first phase aims to train a reinforcement learning agent for rule generation from KGs, and the second is to utilize the value function of the agent to guide the step-by-step rule generation. We conduct extensive experiments on several datasets and the results prove that our rule mining solution achieves state-of-the-art performance in terms of efficiency and effectiveness. • We propose a reinforcement learning algorithm for rule generation. • We propose an efficient rule mining algorithm guided by the trained RL agent. • Our method achieves the state-of-the-art performance on serveral benchmark datasets. [ABSTRACT FROM AUTHOR]

Abstract: Diversity is one of the important perspectives to characterize behaviors of individuals in social networks. It is intuitively believed that diversity of social ties accounts for competition advantage and idea innovation. However, quantitative evidences in a real large social network can be rarely found in the previous research. Thanks to the availability of scientific publication records on WWW; now we can construct a large scientific collaboration network, which provides us a chance to gain insight into the diversity of relationships in a real social network through statistical analysis. In this article, we dedicate our efforts to perform empirical analysis on a scientific collaboration network extracted from DBLP, an online bibliographic database in computer science, in a systematical way, finding the following: distributions of diversity indices tend to decay in an exponential or Gaussian way; diversity indices are not trivially correlated to existing vertex importance measures; authors of diverse social ties tend to connect to each other and these authors are generally more competitive than others. [Copyright &y& Elsevier]

The widespread prevalence and dissemination of antibiotic-resistant bacteria, coupled with the diminishing supply of new antibiotics, emphasize the pressing necessity for the exploration of innovative antibacterial agents. Previously, we detailed the impact of the small-molecule compound CY-158-11 on S. aureus biofilm. By hindering adhesion and PIA-mediated biofilm formation, subinhibitory concentrations of CY-158-11 exhibit antibiofilm activity toward S. aureus . Here, we sought to elucidate the antibacterial activity and mode of action of this compound. Upon CY-158-11 treatment in culture, the inhibition of bacterial growth, coupled with MBC to MIC of >4, indicated that CY-158-11 exerted a bacteriostatic effect. Particularly, CY-158-11 showed strong antibacterial activity against a wide variety of S. aureus , including multidrug-resistant bacteria. We found that CY-158-11 promoted the permeability of cell membrane and propidium iodide absorption as well as caused the dissipation of membrane potential. The effect of CY-158-11 on the mammalian cytoplasmic membrane was measured using hemolytic and cytotoxicity assays, and the skin irritation and systemic toxicity of the drug were measured by injecting the compound into the skin and tail vein of mice. Moreover, CY-158-11 exhibited considerable efficacy in a subcutaneous abscess mouse model of S. aureus infection. In conclusion, CY-158-11 possesses antibacterial properties, including inhibition of bacterial growth, damage to cell membranes, and treatment of skin abscesses, which can be a promising therapeutic option for combating S. aureus ., Importance: The combination of the rising incidence of antibiotic resistance and the shrinking antibiotic pipeline has raised concern about the postantibiotic era. New antibacterial agents and targets are required to combat S. aureus -associated infections. In this study, we identified a maleimide-diselenide hybrid compound CY-158-11 exhibiting antibacterial activity against S. aureus in vitro and in vivo at relatively low concentrations. Furthermore, the investigation of its mode of action revealed that CY-158-11 can selectively perturb the cytoplasmic membrane of bacteria without harming mammalian cells or mouse organs. Thus, CY-158-11 is a compelling novel drug for development as a new therapy for S. aureus infections.

Methicillin-resistant Staphylococcus aureus (MRSA) sequence type 630 (ST630) is a rarely reported lineage worldwide. This study aimed to trace the dissemination of the emerging MRSA ST630 clones in China and investigate their virulence potential. We collected 22 ST630-MRSA isolates from across China and performed whole-genome sequencing analysis and virulence characterization on these isolates. Epidemiological results showed that MRSA ST630 isolates were primarily isolated from pus/wound secretions, mainly originating from Jiangxi province, and carried diverse virulence and drug resistance genes. Staphylococcal cassette chromosome mec type V (SCCmec V) predominated (11/22, 50.0%) among the MRSA ST630 isolates. Interestingly, nearly half (45.5%) of the 22 ST630-MRSA isolates tested lacked intact SCCmec elements. Phylogenetic analysis demonstrated that ST630-MRSA could be divided into two distinct clades, with widespread dissemination mainly in Chinese regions. Five representative isolates were selected for phenotypic assays, including hemolysin activity, real-time fluorescence quantitative PCR, western blot analysis, hydrogen peroxide killing assay, blood killing assay, cell adhesion and invasion assay, and mouse skin abscess model. The results showed that, compared to the USA300-LAC strain, ST630 isolates exhibited particularly strong invasiveness and virulence in the aforementioned phenotypic assays. This study described the emergence of a highly virulent ST630-MRSA lineage and improved our insight into the molecular epidemiology of ST630 clones in China.IMPORTANCEMethicillin-resistant Staphylococcus aureus (MRSA) sequence type 630 (ST630) is an emerging clone with an increasing isolation rate in China. This study raises awareness of the hypervirulent MRSA ST630 clones in China and alerts people to their widespread dissemination. ST630-staphylococcal cassette chromosome mec V is a noteworthy clone in China, and we present the first comprehensive genetic and phenotypic analysis of this lineage. Our findings provide valuable insights for the prevention and control of infections caused by this emerging MRSA clone., Competing Interests: The authors declare no conflict of interest.

The ability to form robust biofilms and secrete a diverse array of virulence factors are key pathogenic determinants of Staphylococcus aureus , causing a wide range of infectious diseases. Here, we characterized cwrA as a VraR-regulated gene encoding a cell wall inhibition-responsive protein (CwrA) using electrophoretic mobility shift assays. We constructed cwrA deletion mutants in the genetic background of methicillin-resistant S. aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) strains. Phenotypic analyses indicated that deletion of cwrA led to impaired biofilm formation, which was correlated with polysaccharide intercellular adhesin (PIA). Besides, the results of real-time quantitative PCR (RT-qPCR) and β-galactosidase activity assay revealed that CwrA promoted biofilm formation by influence the ica operon activity in S. aureus . Furthermore, cwrA deletion mutants released less extracellular DNA (eDNA) in the biofilm because of their reduced autolytic activity compared to the wild-type (WT) strains. We also found that cwrA deletion mutant more virulence than the parental strain because of its enhanced hemolytic activity. Mechanistically, this phenotypic alteration is related to activation of the SaeRS two-component system, which positively regulates the transcriptional levels of genes encoding membrane-damaging toxins. Overall, our results suggest that CwrA plays an important role in modulating biofilm formation and hemolytic activity in S. aureus .

Background: Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections are a great threat to public health worldwide. Ceftazidime-avibactam (CZA) is an effective β -lactam/ β -lactamase inhibitors against CRKP. However, reports of resistance to CZA, mainly caused by Klebsiella pneumoniae carbapenemase (KPC) variants, have increased in recent years. In this study, we aimed to describe the resistance characteristics of KPC-12, a novel KPC variant identified from a CZA resistant K. pneumoniae ., Methods: The K. pneumoniae YFKP-97 collected from a patient with respiratory tract infection was performed whole-genome sequencing (WGS) on the Illumina NovaSeq 6000 platform. Genomic characteristics were analyzed using bioinformatics methods. Antimicrobial susceptibility testing was conducted by the broth microdilution method. Induction of resistant strain was carried out in vitro as previously described. The G. mellonella killing assay was used to evaluate the pathogenicity of strains, and the conjugation experiment was performed to evaluate plasmid transfer ability., Results: Strain YFKP-97 was a multidrug-resistant clinical ST11-KL47 K. pneumoniae confers high-level resistance to CZA (16/4 μg/mL). WGS revealed that a KPC variant, KPC-12, was carried by the IncFII (pHN7A8) plasmids (pYFKP-97_a and pYFKP-97_b) and showed significantly decreased activity against carbapenems. In addition, there was a dose-dependent effect of bla KPC-12 on its activity against ceftazidime. In vitro inducible resistance assay results demonstrated that the KPC-12 variant was more likely to confer resistance to CZA than the KPC-2 and KPC-3 variants., Discussion: Our study revealed that patients who was not treated with CZA are also possible to be infected with CZA-resistant strains harbored a novel KPC variant. Given that the transformant carrying bla KPC-12 was more likely to exhibit a CZA-resistance phenotype. Therefore, it is important to accurately identify the KPC variants as early as possible., Competing Interests: We declare no conflicts of interest., (© 2024 Han et al.)

The emergence of antibiotic-resistant and biofilm-producing Staphylococcus aureus isolates presents major challenges for treating staphylococcal infections. Biofilm inhibition is an important anti-virulence strategy. In this study, a novel maleimide-diselenide hybrid compound (YH7) was synthesized and demonstrated remarkable antimicrobial activity against methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) in both planktonic cultures and biofilms. The minimum inhibitory concentration (MIC) of YH7 for S. aureus isolates was 16 µg/mL. Quantification of biofilms demonstrated that the sub-MIC (4 µg/mL) of YH7 significantly inhibits biofilm formation in both MSSA and MRSA. Confocal laser scanning microscopy analysis further confirmed the biofilm inhibitory potential of YH7. YH7 also significantly suppressed bacterial adherence to A549 cells. Moreover, YH7 treatment significantly inhibited S. aureus colonization in nasal tissue of mice. Preliminary mechanistic studies revealed that YH7 exerted potent biofilm-suppressing effects by inhibiting polysaccharide intercellular adhesin (PIA) synthesis, rather than suppressing bacterial autolysis. Real-time quantitative PCR data indicated that YH7 downregulated biofilm formation-related genes ( clfA , fnbA , icaA, and icaD ) and the global regulatory gene sarX , which promotes PIA synthesis. The sarX -dependent antibiofilm potential of YH7 was validated by constructing S. aureus NCTC8325 sarX knockout and complementation strains. Importantly, YH7 demonstrated a low potential to induce drug resistance in S. aureus and exhibited non-toxic to rabbit erythrocytes, A549, and BEAS-2B cells at antibacterial concentrations. In vivo toxicity assays conducted on Galleria mellonella further confirmed that YH7 is biocompatible. Overall, YH7 demonstrated potent antibiofilm activity supports its potential as an antimicrobial agent against S. aureus biofilm-related infections. IMPORTANCE Biofilm-associated infections, characterized by antibiotic resistance and persistence, present a formidable challenge in healthcare. Traditional antibacterial agents prove inadequate against biofilms. In this study, the novel compound YH7 demonstrates potent antibiofilm properties by impeding the adhesion and the polysaccharide intercellular adhesin production of Staphylococcus aureus . Notably, its exceptional efficacy against both methicillin-resistant and methicillin-susceptible strains highlights its broad applicability. This study highlights the potential of YH7 as a novel therapeutic agent to address the pressing issue of biofilm-driven infections., Competing Interests: The authors declare no conflict of interest.

Importance: Biofilms are an important virulence factor in Staphylococcus aureus and are characterized by a structured microbial community consisting of bacterial cells and a secreted extracellular polymeric matrix. Inhibition of biofilm formation is an effective measure to control S. aureus infection. Here, we have synthesized a small molecule compound S-342-3, which exhibits potent inhibition of biofilm formation in both MRSA and MSSA. Further investigations revealed that S-342-3 exerts inhibitory effects on biofilm formation by reducing the production of polysaccharide intercellular adhesin and preventing bacterial adhesion. Our study has confirmed that the inhibitory effect of S-342-3 on biofilm is achieved by downregulating the expression of genes responsible for biofilm formation. In addition, S-342-3 is non-toxic to Galleria mellonella larvae and A549 cells. Consequently, this study demonstrates the efficacy of a biologically safe compound S-342-3 in inhibiting biofilm formation in S. aureus, thereby providing a promising antibiofilm agent for further research., Competing Interests: The authors declare no conflict of interest.

Previous studies have shown that the increased prevalent ST764 clone in China, Japan, and other Asian areas. However, the knowledge of the genetic features and virulence characteristics of methicillin-resistant Staphylococcus aureus (MRSA) ST764 in China is still limited. In this study, we identified 52 ST764-SCC mec type II isolates collected from five cities in China between 2014 and 2021. Whole genome sequencing showed that the most common staphylococcal protein A ( spa ) types of ST764 in China were t002 (55.78%) and t1084 (40.38%). Virulence assays showed that ST764-t1084 isolates had high haemolytic activity and α-toxin levels. Of the critical regulatory factors affecting α-toxin production, only the SaeRS was highly expressed in ST764-t1084 isolates. Mouse abscess model indicated that the virulence of ST764-t1084 isolates was comparable to that of S. aureus USA300-LAC famous for its hypervirulence. Interestingly, ST764-t002 isolates exhibited stronger biofilm formation and cell adhesion capacities than ST764-t1084 isolates. This seems to explain why ST764-t002 subclone has become more prevalent in China in recent years. Phylogenetic analysis suggested that all ST764 isolates from China in Clade III were closely related to KUN1163 (an isolate from Japan). Notably, genomic analysis revealed that the 52 ST764 isolates did not carry arginine catabolic mobile element (ACME), which differed from ST764 isolates in Japan. Additionally, most ST764 isolates (69.23%) harboured an obvious deletion of approximately 5 kb in the SCC mec II cassette region compared to KUN1163. Our findings shed light on the potential global transmission and genotypic as well as phenotypic characteristics of ST764 lineage.

ST22 MRSA (methicillin-resistant Staphylococcus aureus ) strains are only sporadically reported in China. Through the phylogenetic reconstruction of 30 ST22 strains from China and 480 ST22 strains from global sources, we found that the global ST22 strains can be divided into three clades (I, II, and III). The China ST22 strains were found primarily in clade II (IIb and IIc) and also in clade III, indicating that the China ST22-MRSA clones have different origins. The China subclade IIb strains (SCC mec Vb-t309) may evolve from the native ST22 MSSA clone, while the China IIc strains may have spread from other countries. Subclade IIc (SCC mec IVa-t309) strains exhibited particularly strong lethality and invasiveness in Galleria mellonella infection and mouse skin abscess models in comparison to USA300 and other dominant China HA-MRSA (ST5 and ST239) or CA-MRSA (ST59) strains. This study described the emergence of a highly virulent ST22 MRSA subclade and improved our insight into the molecular epidemiology of ST22 strains in China. IMPORTANCE ST22 is a successful hospital-associated MRSA lineage which first appeared in the United Kingdom as EMRSA-15. At present, ST22 MRSA clones are spreading rapidly around the world and even replaced other dominant clones in some regions. We placed the Chinese ST22 in the worldwide phylogeny of ST22, demonstrating a distinctive molecular epidemiology and to our knowledge, this is the first time that a novel clade of ST22 has been found in China. Among the 15 ST22 MRSA strains belonging to the novel clade, 14 ST22 SCC mec IVa strains from different regions carried both pvl and tst and displayed significantly higher in vitro and in vivo virulence in comparison to other clade/subclade ST22 strains as well as other common China HA-MRSA or CA-MRSA strains. The further spread of this subclade of strains could pose a serious threat to the health system in China and other regions., Competing Interests: The authors declare no conflict of interest.

Staphylococcus aureus is an important human pathogen and brings about many community-acquired, hospital-acquired, and biofilm-associated infections worldwide. It tends to form biofilms, triggering the release of toxins and initiating resistance mechanisms. As a result of the development of S. aureus tolerance to antibiotics, there are few drugs can availably control biofilm-associated infections. In this study, we synthesized a novel small-molecule compound CY-158-11 (C 22 H 14 Cl 2 NO 2 Se 2 ) and proved its inhibitory effect on the biofilm formation of S. aureus at a subinhibitory concentration (1/8 MIC). The subinhibitory concentration of CY-158-11 not only did not affect the growth of bacteria but also had no toxicity to A549 cells or G. mellonella. Total biofilm biomass was investigated by crystal violet staining, and the results were confirmed by SYTO 9 and PI staining through confocal laser scanning microscopy. Moreover, CY-158-11 effectively prevented initial attachment and repressed the production of PIA instead of autolysis. RT-qPCR analysis also exhibited significant suppression of the genes involved in biofilm formation. Taken together, CY-158-11 exerted its inhibitory effects against the biofilm formation in S. aureus by inhibiting cell adhesion and the expression of icaA related to PIA production. IMPORTANCE Most bacteria exist in the form of biofilms, often strongly adherent to various surfaces, causing bacterial resistance and chronic infections. In general, antibacterial drugs are not effective against biofilms. The small-molecule compound CY-158-11 inhibited the biofilm formation of S. aureus at a subinhibitory concentration. By hindering adhesion and PIA-mediated biofilm formation, CY-158-11 exhibits antibiofilm activity toward S. aureus. These findings point to a novel therapeutic agent for combating intractable S. aureus-biofilm-related infections., Competing Interests: The authors declare no conflict of interest.

Methicillin-resistant Staphylococcus aureus (MRSA) sequence type 45 (ST45) was rarely found in China. This study was conducted to trace the transmission and evolution of emerging MRSA ST45 strains in mainland China and explore its virulence. A total of 27 ST45 isolates were included for whole-genome sequencing and genetic characteristic analysis. Epidemiological results showed that MRSA ST45 isolates were often obtained from blood, primarily originated in Guangzhou, and carried diverse virulence and drug resistance genes. Staphylococcal cassette chromosome mec type IV (SCC mec IV) dominated in MRSA ST45 (23/27, 85.2%). ST45-SCC mec V was located on a phylogenetic clade distinct from the SCC mec IV cluster. We selected two representative isolates, MR370 (ST45-SCC mec IV) and MR387 (ST45-SCC mec V), and performed hemolysin activity, a blood killing assay, a Galleria mellonella infection model, and a mouse bacteremia model, as well as real-time fluorescence quantitative PCR. MR370 was proved to have extreme virulence in the phenotypic assays and at the mRNA level compared with ST59, ST5, and USA300 MRSA strains. MR387 was comparable to USA300-LAC on the phenotype and was verified to have higher expression of scn , chp , sak , saeR , agrA , and RNAIII than USA300-LAC. The results emphasized the extraordinary performance of MR370 and the good potential of MR387 in virulence causing bloodstream infection. Meanwhile, we conclude that China MRSA ST45 showed two different clonotypes, which may be widespread in the future. The entire study is valuable as a timely reminder and reports virulence phenotypes of China MRSA ST45 for the first time. IMPORTANCE Methicillin-resistant Staphylococcus aureus ST45 is epidemic worldwide. This study contributed to the awareness of the Chinese hyper-virulent MRSA ST45 strains and served as a timely reminder of its wide dissemination of clonotypes. Further, we provide novel insights for prevention from the perspective of bloodstream infections. ST45-SCC mec V is a clonotype deserving special attention in China, and we performed genetic and phenotypic analyses for the first time on it.

Multi-drug resistant Staphylococcus aureus infection is still a serious threat to global health. Therefore, there is an urgent need to develop new antibacterial agents based on virulence factor therapy to overcome drug resistance. Previously, we synthesized SYG-180-2-2 (C 21 H 16 N 2 OSe), an effective small molecule compound against biofilm. The aim of this study was to investigate the anti-virulence efficacy of SYG-180-2-2 against Staphylococcus aureus . MIC results demonstrated no apparent antibacterial activity of the SYG-180-2-2. The growth curve assay showed that SYG-180-2-2 had nonlethal effect on S. aureus . Besides, SYG-180-2-2 strongly inhibited the hemolytic activity and staphyloxanthin synthesis in S. aureus . Inhibition of staphyloxanthin by SYG-180-2-2 enhanced the sensitivity of S. aureus to oxidants and human whole blood. In addition, SYG-180-2-2 significantly decreased the expression of saeR -mediated hemolytic gene hlb and staphyloxanthin-related crtM , crtN and sigB genes by quantitative polymerase chain reaction (qPCR). Meanwhile, the expression of oxidative stress-related genes sodA , sodM and katA also decreased. Galleria Mellonella assay revealed that SYG-180-2-2 was not toxic to larvae. Further, the larvae infection model showed that the virulence of bacteria was significantly reduced after 4 μg/mL SYG-180-2-2 treatment. SYG-180-2-2 also reduced skin abscess formation in mice by reducing bacterial burden and subcutaneous inflammation. In conclusion, SYG-180-2-2 might be a promising agent to attenuate the virulence of S. aureus by targeting genes associated with hemolytic activity and staphyloxanthin synthesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rao, Xu, Shen, Wang, Zhao, Wang, Zhang, Xiao, Guo, Sheng, Cheng, Song and Yu.)