Colonization by Staphylococcus aureus is a characteristic feature of several inflammatory skin diseases and is often followed by epidermal damage and invasive infection. In this study, we investigated the mechanism of skin colonization by a virulent community-acquired methicillin-resistant S. aureus (CA-MRSA) strain, MW2, using a murine ear colonization model. MW2 does not produce a hemolytic toxin, beta-hemolysin (Hlb), due to integration of a prophage, Sa3mw, inside the toxin gene (hlb). However, we found that strain MW2 bacteria that had successfully colonized murine ears included derivatives that produced Hlb. Genome sequencing of the Hlb-producing colonies revealed that precise excision of prophage Sa3mw occurred, leading to reconstruction of the intact hlb gene in their chromosomes. To address the question of whether Hlb is involved in skin colonization, we constructed MW2-derivative strains with and without the Hlb gene and then subjected them to colonization tests. The colonization efficiency of the Hlb-producing mutant on murine ears was more than 50-fold greater than that of the mutant without hlb. Furthermore, we also showed that Hlb toxin had elevated cytotoxicity for human primary keratinocytes. Our results indicate that S. aureus Hlb plays an important role in skin colonization by damaging keratinocytes, in addition to its well-known hemolytic activity for erythrocytes.

Complete reconstitution of the vancomycin-intermediate Staphylococcus aureus (VISA) phenotype of strain Mu50 was achieved by sequentially introducing mutations into six genes of vancomycin-susceptible S. aureus (VSSA) strain N315ΔIP. The six mutated genes were detected in VISA strain Mu50 but not in N315ΔIP. Introduction of the mutation Ser329Leu into vraS, encoding the sensor histidine kinase of the vraSR two-component regulatory (TCR) system, and another mutation, Glu146Lys, into msrR, belonging to the LytR-CpsA-Psr (LCP) family, increased the level of vancomycin resistance to that detected in heterogeneous vancomycin-intermediate S. aureus (hVISA) strain Mu3. Introduction of two more mutations, Asn197Ser into graR of the graSR TCR system and His481Tyr into rpoB, encoding the β subunit of RNA polymerase, converted the hVISA strain into a VISA strain with the same level of vancomycin resistance as Mu50. Surprisingly, however, the constructed quadruple mutant strain ΔIP4 did not have a thickened cell wall, a cardinal feature of the VISA phenotype. Subsequent study showed that cell wall thickening was an inducible phenotype in the mutant strain, whereas it was a constitutive one in Mu50. Finally, introduction of the Ala297Val mutation into fdh2, which encodes a putative formate dehydrogenase, or a 67-amino-acid sequence deletion into sle1 [sle1(Δ67aa)], encoding the hydrolase of N-acetylmuramyl-l-alanine amidase in the peptidoglycan, converted inducible cell wall thickening into constitutive cell wall thickening. sle1(Δ67aa) was found to cause a drastic decrease in autolysis activity. Thus, all six mutated genes required for acquisition of the VISA phenotype were directly or indirectly involved in the regulation of cell physiology. The VISA phenotype seemed to be achieved through multiple genetic events accompanying drastic changes in cell physiology.

Vancomycin-intermediately resistant Staphylococcus aureus (VISA) and heterogeneous VISA (hVISA) are associated with treatment failure. hVISA contains only a subpopulation of cells with increased minimal inhibitory concentrations, and its detection is problematic because it is classified as vancomycin-susceptible by standard susceptibility testing and the gold-standard method for its detection is impractical in clinical microbiology laboratories. Recently, a research group developed a machine-learning classifier to distinguish VISA and hVISA from vancomycin-susceptible S. aureus (VSSA) according to matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) data. Nonetheless, the sensitivity of hVISA classification was found to be 76%, and the program was not completely automated with a graphical user interface. Here, we developed a more accurate machine-learning classifier for discrimination of hVISA from VSSA and VISA among MRSA isolates in Japanese hospitals by means of MALDI-TOF MS data. The classifier showed 99% sensitivity of hVISA classification. Furthermore, we clarified the procedures for preparing samples and obtaining MALDI-TOF MS data and developed all-in-one software, hVISA Classifier, with a graphical user interface that automates the classification and is easy for medical workers to use; it is publicly available at https://github.com/bioprojects/hVISAclassifier. This system is useful and practical for screening MRSA isolates for the hVISA phenotype in clinical microbiology laboratories and thus should improve treatment of MRSA infections.

The COVID-19 pandemic forced many educational institutions to turn to electronic learning to allow education to continue under the stay-at-home orders/requests that were commonly instituted in early 2020. In this cross-sectional study, we evaluated the effects of the COVID-19 pandemic on medical education in terms of students’ attitudes toward online classes and their online accessibility; additionally, we examined the impacts of any disruption caused by the pandemic on achievement test performance based on the test results. The participants were 674 students (412 in pre-clinical, 262 in clinical) at Juntendo University Faculty of Medicine; descriptive analysis was used to examine the respondents’ characteristics and responses. The majority of respondents (54.2%) preferred asynchronous classes. Mann–Whitney U tests revealed that while pre-clinical students preferred asynchronous classes significantly more than clinical students (39.6%, p < .001), students who preferred face-to-face classes had significantly higher total achievement test scores (U = 1082, p = .021, r = .22). To examine the impacts of pandemic-induced changes in learning, we conducted Kruskal–Wallis tests and found that the 2020 and 2021 scores were significantly higher than those over the last three years. These results suggest that while medical students may have experienced challenges adapting to electronic learning, the impact of this means of study on their performance on achievement tests was relatively low. Our study found that if possible, face-to-face classes are preferable in an electronic learning environment. However, the benefit of asynchronous classes, such as those that allow multiple viewings, should continue to be recognized even after the pandemic.

We previously reported a novel phenotype of vancomycin-intermediate Staphylococcus aureus (VISA), i.e., “slow VISA,” whose colonies appear only after 72 h of incubation. Slow-VISA strains can be difficult to detect because prolonged incubation is required and the phenotype is unstable. To develop a method for detection of slow-VISA isolates, we studied 23 slow-VISA isolates derived from the heterogeneous VISA (hVISA) clinical strain Mu3. We identified single nucleotide polymorphisms (SNPs) in genes involved in various pathways which have been implicated in the stringent response, such as purine/pyrimidine synthesis, cell metabolism, and cell wall peptidoglycan synthesis. We found that mupirocin, which also induces the stringent response, caused stable expression of vancomycin resistance. On the basis of these results, we developed a method for detection of slow-VISA strains by use of 0.032 μg/ml mupirocin (Yuki Katayama, 7 March 2017, patent application PCT/JP2017/008975). Using this method, we detected 53 (15.6%) slow-VISA isolates among clinical methicillin-resistant S. aureus (MRSA) isolates. In contrast, the VISA phenotype was detected in fewer than 1% of isolates. Deep-sequencing analysis showed that slow-VISA clones are present in small numbers among hVISA isolates and proliferate in the presence of vancomycin. This slow-VISA subpopulation may account in part for the recurrence and persistence of MRSA infection.