Genomic characteristics of cfr and fexA carrying Staphylococcus aureus isolated from pig carcasses in Korea.

The emergence of transferable linezolid resistance genes poses significant challenges to public health, as it does not only confer linezolid resistance but also reduces susceptibility to florfenicol, which is widely used in the veterinary field. This study evaluated the genetic characteristics of linezolid-resistant Staphylococcus aureus strains isolated from pig carcasses and further clarified potential resistance and virulence mechanisms in a newly identified sequence type. Of more than 2500 strains isolated in a prior study, 15 isolated from pig carcasses exhibited linezolid resistance (minimum inhibitory concentration ≥ 8 mg/L). The strains were characterized in detail by genomic analysis. Linezolid-resistant S. aureus strains exhibited a high degree of genetic lineage diversity, with one strain (LNZ_R_SAU_64) belonging to ST8004, which has not been reported previously. The 15 strains carried a total of 21 antibiotic resistance genes, and five carried mecA associated with methicillin resistance. All strains harbored cfr and fexA, which mediate resistance to linezolid, phenicol, and other antibiotics. Moreover, the strains carried enterotoxin gene clusters, including the hemolysin, leukotoxin, and protease genes, which are associated with humans or livestock. Some genes were predicted to be carried in plasmids or flanked by ISSau9 and the transposon Tn554, thus being transmittable between staphylococci. Strains carrying the plasmid replicon repUS5 displayed high sequence similarity (99%) to the previously reported strain pSA737 in human clinical samples in the United States. The results illustrate the need for continuous monitoring of the prevalence and transmission of linezolid-resistant S. aureus isolated from animals and their products.

Rapid and Simultaneous Authentication of Six Laver Species Using Capillary Electrophoresis-Based Multiplex PCR.

Lavers are typically consumed in dried or seasoned forms. However, commercially processed lavers can lead to seafood fraud because it is impossible to authenticate the original species based on morphological characteristics alone. In this study, we developed a capillary electrophoresis-based multiplex polymerase chain reaction (PCR) to authenticate six different laver species. The species-specific primer sets to target the chloroplast rbcL or rbcS genes were newly designed. We successfully established both singleplex and multiplex conditions, which resulted in specific amplicons for each species (N. dentata, 274 bp; N. yezoensis, 211 bp; N. seriata, 195 bp; N. tenera, 169 bp; N. haitanensis, 127 bp; P. suborbiculata, 117 bp). Moreover, the assays were sensitive enough to detect DNA ranging from 10 to 0.1 pg of DNA. The optimized capillary electrophoresis-based multiplex PCR was successfully applied to 40 commercial laver products. In addition to detecting the laver species as stated on the commercial label, the assay discovered cases where less expensive species were mixed in. With its advantageous properties, such as short amplicon size, high specificity, and superior sensitivity, this assay could be used for the authentication of the six laver species.

Strain-Programmed Adhesive Patch for Accelerated Photodynamic Wound Healing.

As an alternative to tissue adhesives, photochemical tissue bonding is investigated for advanced wound healing. However, these techniques suffer from relatively slow wound healing with bleeding and bacterial infections. Here, the versatile attributes of afterglow luminescent particles (ALPs) embedded in dopamine-modified hyaluronic acid (HA-DOPA) patches for accelerated wound healing are presented. ALPs enhance the viscoelastic properties of the patches, and the photoluminescence and afterglow luminescence of ALPs maximize singlet oxygen generation and collagen fibrillogenesis for effective healing in the infected wounds. The patches are optimized to achieve the strong and rapid adhesion in the wound sites. In addition, the swelling and shrinking properties of adhesive patches contribute to a nonlinear behavior in the wound recovery, playing an important role as a strain-programmed patch. The protective patch prevents secondary infection and skin adhesion, and the patch seamlessly detaches during wound healing, enabling efficient residue clearance. In vitro, in vivo, and ex vivo model tests confirm the biocompatibility, antibacterial effect, hemostatic capability, and collagen restructuring for the accelerated wound healing. Taken together, this research collectively demonstrates the feasibility of HA-DOPA/ALP patches as a versatile and promoting solution for advanced accelerated wound healing, particularly in scenarios involving bleeding and bacterial infections.

Classification of Latilactobacillus sakei subspecies based on MALDI-TOF MS protein profiles using machine learning models.

Latilactobacillus sakei is an important bacterial species used as a starter culture for fermented foods; however, two subspecies within this species exhibit different properties in the foods. Matrix-assisted laser desorption/ionization-time of flight mass spectrometer (MALDI-TOF MS) is the gold standard for microbial fingerprinting. However, the resolution power is down to the species level. This study was to combine MALDI-TOF mass spectra and machine learning to develop a new method to identify two L. sakei subspecies (L. sakei subsp. sakei and L. sakei subsp. carnosus) and non-L. sakei species. Totally, 227 strains were collected, with 908 spectra obtained via on- and off-plate protein extraction. Only 68.7% of strains were correctly identified at the subspecies level in the Biotyper database; however, a high level of performance was observed from the machine learning models. Partial least squares-discriminant analysis (PLS-DA), principal component analysis-K-nearest neighbor (PCA-KNN), and support vector machine (SVM) demonstrated 0.823, 0.914, and 0.903 accuracies, respectively, whereas the random forest (RF) achieved an accuracy of 0.954, with an area under the receiver operating characteristic (AUROC) curve of 0.99, outperforming the other algorithms in distinguishing the subspecies. The machine learning proved to be a promising technique for the rapid and high-resolution classification of L. sakei subspecies using MALDI-TOF MS. IMPORTANCE: Latilactobacillus sakei plays a significant role in the realm of food bacteria. One particular subspecies of L. sakei is employed as a protective agent during food fermentation, whereas another strain is responsible for food spoilage. Hence, it is crucial to precisely differentiate between the two subspecies of L. sakei. In this study, machine learning models based on protein mass peaks were developed for the first time to distinguish L. sakei subspecies. Furthermore, the efficacy of three commonly used machine learning algorithms for microbial classification was evaluated. Our results provide the foundation for future research on developing machine learning models for the classification of microbial species or subspecies. In addition, the developed model can be used in the food industry to monitor L. sakei subspecies in fermented foods in a time- and cost-effective method for food quality and safety.

Comparative analysis of LC-MS/MS and real-time PCR assays for efficient detection of potential allergenic silkworm.

The silkworm (Bombyx mori) has long been valued food and feed in East Asia for its abundant nutritional and medicinal attributes, conversely, it can elicit allergic responses in susceptible individuals. Therefore, the development of silkworm detection method is required to avert allergenic incidents. In this study, two methodologies, tandem mass spectrometry (LC-MS/MS) and real-time PCR, were developed to achieve effective silkworm detection. These methods exhibited exceptional sensitivity in identifying silkworm presence in processed foods. Furthermore, model cookies spiked with silkworm were used to validate the sensitivities of LC-MS/MS (0.0005%) and real-time PCR (0.001%). Overall, these techniques were useful for trace silkworm detection in food products; therefore, they may help prevent allergic reactions. To the best of our knowledge, this study represents the first comparison of LC-MS/MS and real-time PCR methods for silkworm detection, marking an important contribution to the field. Data are available from ProteomeXchange under identifier PXD042494.

Highly Elastic, Bioresorbable Polymeric Materials for Stretchable, Transient Electronic Systems.

Substrates or encapsulants in soft and stretchable formats are key components for transient, bioresorbable electronic systems; however, elastomeric polymers with desired mechanical and biochemical properties are very limited compared to non-transient counterparts. Here, we introduce a bioresorbable elastomer, poly(glycolide-co-ε-caprolactone) (PGCL), that contains excellent material properties including high elongation-at-break (< 1300%), resilience and toughness, and tunable dissolution behaviors. Exploitation of PGCLs as polymer matrices, in combination with conducing polymers, yields stretchable, conductive composites for degradable interconnects, sensors, and actuators, which can reliably function under external strains. Integration of device components with wireless modules demonstrates elastic, transient electronic suture system with on-demand drug delivery for rapid recovery of post-surgical wounds in soft, time-dynamic tissues.

CD81 and CD82 expressing tumor-infiltrating lymphocytes in the NSCLC tumor microenvironment play a crucial role in T-cell activation and cytokine production.

Introduction: To understand the immune system within the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC), it is crucial to elucidate the characteristics of molecules associated with T cell activation. Methods: We conducted an in-depth analysis using single-cell RNA sequencing data obtained from tissue samples of 19 NSCLC patients. T cells were classified based on the Tumor Proportion Score (TPS) within the tumor region, and molecular markers associated with activation and exhaustion were analyzed in T cells from high TPS areas. Results: Notably, tetraspanins CD81 and CD82, belonging to the tetraspanin protein family, were found to be expressed in activated T cells, particularly in cytotoxic T cells. These tetraspanins showed strong correlations with activation and exhaustion markers. In vitro experiments confirmed increased expression of CD81 and CD82 in IL-2-stimulated T cells. T cells were categorized into CD81highCD82high and CD81lowCD82low groups based on their expression levels, with CD81highCD82high T cells exhibiting elevated activation markers such as CD25 and CD69 compared to CD81lowCD82low T cells. This trend was consistent across CD3+, CD8+, and CD4+ T cell subsets. Moreover, CD81highCD82high T cells, when stimulated with anti-CD3, demonstrated enhanced secretion of cytokines such as IFN-γ, TNF-α, and IL-2, along with an increase in the proportion of memory T cells. Bulk RNA sequencing results after sorting CD81highCD82high and CD81lowCD82low T cells consistently supported the roles of CD81 and CD82. Experiments with overexpressed CD81 and CD82 showed increased cytotoxicity against target cells. Discussion: These findings highlight the multifaceted roles of CD81 and CD82 in T cell activation, cytokine production, memory subset accumulation, and target cell cytolysis. Therefore, these findings suggest the potential of CD81 and CD82 as promising candidates for co-stimulatory molecules in immune therapeutic strategies for cancer treatment within the intricate TME.

Exploring aryl hydrocarbon receptor expression and distribution in the tumor microenvironment, with a focus on immune cells, in various solid cancer types.

Introduction: Aryl hydrocarbon receptor (AhR) is a transcription factor that performs various functions upon ligand activation. Several studies have explored the role of AhR expression in tumor progression and immune surveillance. Nevertheless, investigations on the distribution of AhR expression, specifically in cancer or immune cells in the tumor microenvironment (TME), remain limited. Examining the AhR expression and distribution in the TME is crucial for gaining insights into the mechanism of action of AhR-targeting anticancer agents and their potential as biomarkers. Methods: Here, we used multiplexed immunohistochemistry (mIHC) and image cytometry to investigate the AhR expression and distribution in 513 patient samples, of which 292 are patients with one of five solid cancer types. Additionally, we analyzed the nuclear and cytosolic distribution of AhR expression. Results: Our findings reveal that AhR expression was primarily localized in cancer cells, followed by stromal T cells and macrophages. Furthermore, we observed a positive correlation between the nuclear and cytosolic expression of AhR, indicating that the expression of AhR as a biomarker is independent of its localization. Interestingly, the expression patterns of AhR were categorized into three clusters based on the cancer type, with high AhR expression levels being found in regulatory T cells (Tregs) in non-small cell lung cancer (NSCLC). Discussion: These findings are anticipated to serve as pivotal evidence for the design of clinical trials and the analysis of the anticancer mechanisms of AhR-targeting therapies.