- Volume 74, Issue 5, 2025

Infection with Trichophyton indotineae has been considered an important medical issue in recent times due to the rapid ability of this fungus to develop resistance to different antifungals and its widespread distribution across multiple countries. However, increasing cases of antifungal-resistant infections induce changes in the biological activity of fungi, enabling certain dermatophytes such as T. indotineae to infect both animals and humans. This behaviour has certainly had adverse consequences after expanding the host variety of resistant T. indotineae. The virulence of T. indotineae is predicted to increase, resulting in more difficult treatment for both human and animal infections.

Introduction. In recent years, with the increase of drug resistance of Candida, the incidence rate and mortality of candidemia have gradually increased, which has brought a huge economic and health burden to people.

Gap Statement. The epidemiological characteristics and antifungal drug sensitivity patterns in different regions have varied.

Aim. To analyse the distribution and antifungal susceptibility of Candida strains isolated from bloodstreams and provide a basis for the use of antifungal drugs for treatment.

Methodology. A total of 115 strains of Candida were collected from the bloodstream, and 28 strains of colonized Candida albicans were collected from the upper respiratory tract. Candida species were identified using matrix-assisted laser desorption/ionization time-of-flight technology. Antifungal susceptibility was assessed using broth microdilution combined with redox methods.

Results. There were eight types of Candida strains isolated from the bloodstream; C. albicans was the most common species (36.5%), followed by Candida parapsilosis (24.3%), Candida glabrata (17.4%) and Candida tropicalis (14.8%). There was no significant difference in the resistance of C. albicans to azole drugs between the bloodstream infection group and the upper respiratory tract colonization group, but there was a significant difference in the MIC values of micafungin and fluconazole, with P values of 0.017 and 0.003, respectively. Amphotericin B and echinocandins are the most susceptible drugs for all Candida species, but the MICs of echinocandins against C. parapsilosis are significantly higher than those of other Candida species. Candida (except for C. glabrata) is highly resistant to azoles, with C. parapsilosis showing resistance rates of 89.3% and 82.1% to itraconazole and posaconazole, respectively; the resistance rates of C. tropicalis are 100% and 94.1%, respectively.

Conclusion. C. albicans remains the predominant pathogen responsible for candidemia. Although the resistance of Candida to antifungals is relatively stable, there are significant differences in the MICs of antifungal drugs against Candida, indicating the importance of strain identification in the treatment of candidemia. For empirical treatment, the use of echinocandin drugs is recommended.

Background. The health system in Sierra Leone has limited infrastructure to provide data on the epidemiology of infectious diseases and to inform clinical decision-making. The diagnostic and research laboratory capacity at Masanga Teaching Hospital was systematically expanded with microbiology infrastructure-building as one of the centrepieces.

Objective. This study aims to report the spectrum of bacterial pathogens from bloodstream infections (BSIs) in a rural hospital in Sierra Leone during the first year after the implementation of a blood culture infrastructure and characterize the detected antimicrobial resistances.

Patients and methods. Patients treated at Masanga Hospital (Sierra Leone, March 2023–March 2024) were included in this database analysis if they were tested for BSI (BD BACTEC). Demographic and medical data were recorded for each patient. Antimicrobial susceptibility testing was done following EUCAST clinical guidelines.

Results. Of the 340 blood cultures, 34 (10%) were positive for obligate pathogens. The three most frequent pathogens were Escherichia coli (n=8), followed by Burkholderia cepacia complex (n=7) and Salmonella enterica (n=5). Almost all Klebsiella pneumoniae (n=3/3) and E. coli (n=7/8) were resistant to third-generation cephalosporins. All four Staphylococcus aureus isolates were methicillin susceptible (mecA negative). Carbapenem resistance was detected in Acinetobacter baumannii complex (bla NDM)

Conclusion. The proportion of positive blood cultures with obligate pathogens (10%) was within the suggested benchmark (5–15%). Gram-negative bacteria dominated the pathogen spectrum of BSI with high resistance rates to third-generation cephalosporins.

Introduction. Resistance to the β-lactam/β-lactamase inhibitor (BL/BLI) combination antibiotic piperacillin/tazobactam (TZP) predominantly occurs via β-lactamase enzymes, also leading to resistance to third-generation cephalosporins (3GCs). However, if β-lactamases inactive against 3GCs and inhibited by tazobactam are expressed at high levels, leading to enzyme hyperproduction, the surplus enzyme escapes inhibition by tazobactam and inactivates the antibiotic piperacillin.

Hypothesis/Gap statement. Understanding this mechanism is clinically relevant, as enzyme hyperproduction can emerge upon antibiotic administration, resulting in treatment failure despite initial resistance profiles supporting TZP use.

Aim. Our aim was to determine whether this was a case of within-patient evolution and by what mechanism or an acquisition of a second unrelated, more resistant, strain.

Methodology. Whole-genome sequencing was performed on the isolate to determine the genetic basis of resistance. We also assessed the impact of TZP exposure on the amplification of the bla TEM-1 gene and monitored the stability of gene copy number over 5 days in the absence of antibiotic pressure. In addition, we determined the MICs of ceftriaxone and TZP, with TZP MIC contextualized in relation to gene copy number and resistance levels.

Results. We report the identification of an Escherichia coli isolate that developed resistance to TZP during patient treatment but maintained sensitivity to ceftriaxone. We show that TZP resistance evolved via IS26-mediated duplication of a bla TEM-1 containing transposable unit on a plasmid, resulting in hyperproduction of TEM-1 β-lactamase, and that ten copies of bla TEM-1 induce resistance greater than 32 times the MIC. Furthermore, under experimental conditions, exposure to TZP further increases amplification of bla TEM-1, whereas, in the absence of TZP, gene copy number of IS26 and bla TEM-1 remains stable over 5 days, despite a 48,205 bp genome size increase compared to the pre-amplification isolate. We additionally detect phenotypic changes that might indicate host adaptation potentially linked to the additional genes that are amplified.

Conclusion. Our analysis advances the understanding of infections caused by isolates evolving β-lactamase hyperproduction, which represents a complex problem in both detection and treatment. As 40% of antibiotics active against WHO priority pathogens in the pre-clinical pipeline are BL/BLI combinations, further investigations are of urgent concern.

Introduction. Alterations in ocular surface microbiota (OSM) have been noted in both dry eye disease (DED) and glaucoma. However, the combined effects of these conditions on OSM have not been explored.

Hypothesis. We hypothesized that patients with both glaucoma and dry eye would exhibit distinct changes in OSM composition and diversity compared to those with only glaucoma, only dry eye or healthy individuals.

Aim. We employed amplicon sequencing to investigate OSM profiles in patients with glaucoma and/or dry eye disease.

Methods. Swab samples from the conjunctiva of both eyes were collected from 28 glaucomatous patients [13 without dry eye syndrome (G-only) and 15 with dry eye syndrome (G-DED)], 13 DED patients without glaucoma (DED-only) and 31 age-matched healthy controls (HCs). After V3–V4 16S rRNA sequencing, MOTHUR tools and R language were used to elucidate and compare OSM composition and diversity between groups.

Results. Our data revealed very diverse bacterial communities with 28 phyla and 785 genera. All the groups shared the three most abundant phyla, Actinobacteria (67.47%), Firmicutes (17.14%) and Proteobacteria (13.73%). Corynebacterium (54.75%), Staphylococcus (10.71%), Cutibacterium (8.77%) and Streptococcus (3.20%) were the most abundant genera. Only the G-DED group showed higher alpha diversity than the HC group (P<0.05). However, significant differences in beta diversity were observed between all three patient groups and the HC group. The Differential Expression for Sequencing 2 (DESeq2) analysis unveiled an increased presence of opportunistic bacteria across all pathological groups, with the G-DED group demonstrating the most pronounced alterations.

Conclusions. Our findings confirm the predominance of Gram-positive bacteria in normal OSM and the rise of opportunistic Gram-negative bacteria in glaucoma and dry eye disease. This is the first study to characterize OSM in glaucoma patients with DED.

Introduction. Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and negatively affects the health of mothers and infants. The aim of this study was to explore the associations between gut microbiota and the risk of GDM amongst overweight/obese women, and the interaction between gut microbiota dysbiosis and overweight/obesity in pregnant women with GDM.

Hypothesis/Gap statement. Previous studies revealed that there may be a link between gut microbiota and GDM and obesity, but these studies have not reported the associations between gut microbiota and the risk of GDM amongst overweight/obese women, whilst the interaction between gut microbiota dysbiosis and overweight/obesity in pregnant women with GDM remains unknown.

Aim. Based on a prospective cohort study, we explored the composition of gut microbiota in overweight/obese pregnant women and its association with GDM.

Methodology. Participants (n=1820) were enrolled from the Pregnancy Metabolic Disease and Adverse Pregnancy Outcome cohort in Guangzhou, China, between 2019 and 2021. The participants’ information and faecal samples were collected, and the relative abundance of faecal microbiota was profiled using 16S rRNA V4 region sequencing. Pregnant women were divided into four groups: non- overweight (NOW)/obese without GDM (OB- NGDM), overweight (OW)/OB- NGDM, NOW/obese with GDM (OB- GDM) and OW/OB- GDM. Linear discriminant analysis effect size (LEfSe) analysis, Spearman’s correlation analysis and t- test were performed to estimate the association amongst microbiota, pre- pregnancy BMI and oral glucose tolerance test (OGTT) glucose levels.

Results . Blautia, Anaerostipes, Synergistes (P<0.001) and Christensenellaceae_R_7_group (P=0.007) were significantly different between NOW/OB-GDM and OW/OB-GDM groups after adjusting for age. Odoribacter, Anaerostipes, Monoglobus, Romboutsia, Oscillospiraceae__UCG-003, Blautia and Dialister were significantly correlated with both OGTT 1 h (P<0.001) and 2 h (P<0.05) blood glucose levels , whilst Lactobacillus (P<0.001) were significantly correlated with OGTT 2 h blood glucose levels. Synergistes (P<0.001) were significantly correlated with OGTT fasting glucose levels, and Megasphaera and Odoribacter (P<0.05) were significantly correlated with pre-pregnancy BMI.

Conclusions. GDM and OB/OW women was experiencing microbiota dysbiosis, especially the microbial communities related to glucose metabolism.

Faecalibacterium prausnitzii has been considered one of the predominant microbes in the gut microbiota of healthy human adults. Moreover, due to its beneficial metabolites and its reduced population in patients with various disorders, this organism has been regarded as one of the key gut microbes in human health. However, following recent revisions in the taxonomy of the genus Faecalibacterium and F. prausnitzii, the reported population distribution and health benefits of this species have become unclear. In the present study, the population of nine species-level taxonomic groups (hereafter referred to as species) within Faecalibacterium was quantified at the species level in the faeces of healthy Japanese adults (n=88). qPCR, combined with rpoA-based species-specific primers, showed that Faecalibacterium taiwanense had the highest detection rate (prevalence) and copy number among Faecalibacterium spp., followed by Faecalibacterium longum, Faecalibacterium duncaniae and F. prausnitzii, while the remaining five species were detected only occasionally. The population of F. duncaniae varied significantly between age groups, being higher in individuals in their 40s and 50s compared to those in their 20s (P=0.047 and 0.002, respectively). The present study indicates that F. prausnitzii is not the predominant Faecalibacterium species in the healthy Japanese adults included in the present study. Future studies will shed light on the health benefits of the dominant Faecalibacterium spp.

Introduction. Pre-existing immunity to human coronaviruses (HCoVs) may shape the immune response in COVID-19 patients. Increasing evidence suggests that immune cross-reactivity between SARS-CoV-2 and other coronaviruses may determine clinical prognosis.

Hypothesis. SARS-CoV-2 disease severity is influenced by pre-existing immunity to HCoVs, with distinct antibody profiles and cross-reactivity patterns.

Aim. To investigate the antibody response of ICU and non-ICU SARS-CoV-2 patients against different HCoV proteins and assess the potential impact of pre-existing immunity on SARS-CoV-2 disease outcomes.

Methodology. This study used a comprehensive HCoVs antigen bead array to measure antibody response to pathogenic Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV, SARS-CoV-2 and the four seasonal HCoVs in 70 ICU and 63 non-ICU COVID-19 patients.

Results. Our analysis demonstrates an overall higher antibody response in ICU than in non-ICU COVID-19 patients. Interestingly, the anti-S1 IgG and IgA were significantly higher among ICU than in non-ICU patients. Similarly, the anti-S1 IgG against NL63 showed a lower response among ICU compared to non-ICU. Cross-reactivity was evident between SARS-CoV-2 and SARS-CoV antibodies but not with MERS-CoV and seasonal HCoVs. The subclass analysis of antibodies recognizing SARS-CoV-2 revealed that anti-S1 IgG1, IgG3, IgA1 and IgA2 were significantly higher in ICU compared to non-ICU. The predominant IgA subtype among SARS-CoV-2 patients was IgA1. We applied machine learning algorithms to subclass serological responses to build classifiers that could distinguish between ICU patients and patients with milder COVID-19. Out of 90 variables used in two different types of models, the variable of highest influence in determining the ICU status was IgG3 against SARS-CoV-2 S, and the top 8 variables of influence included the presence of IgG3 against S-trimer as well as IgA against SARS-CoV-2 S.

Conclusion. Understanding the complexities of humoral immunity in various patients is critical for early medical intervention, disease management, selective vaccination and passive immunotherapy.