On the relationship between Pathogenic Potential and Infective Inoculum

The dynamics of Cryptococcus neoformans infection in Galleria mellonella

Galleria mellonella has emerged as an important host for the study of fungal virulence, insect immune responses, and the evaluation of antifungal agents. In this study, we investigated the dynamics of fungal infections in G. mellonella using Cryptococcus neoformans, a human pathogenic fungus. Since the analysis of infection dynamics requires a fine temporal resolution of larval death, we employed a photographic time-lapse technique that allowed us to simultaneously measure death by proxy of larval melanization and absence of movement. Larval mortality occurred in two phases, early and late, which differed in their timing of melanization. Early phase deaths occurred with rapid whole-body onset of melanization, followed by sudden cessation of movement several hours later. Contrastingly, late phase deaths occurred with a gradual cessation of movement, followed by melanization, typically radiating from one location on the larva. The differences in mortality kinetics suggest differences in fungal pathogenesis, with one population succumbing early while the rest linger for later death. Subsequent analysis of mortality data using the inversion method revealed predictable deterministic dynamics but did not observe evidence of chaotic signatures. While this does not preclude the existence of chaos, it indicates that this C. neoformans-G. mellonella infection model may behave differently than bacterial-insect models.IMPORTANCEThe ability to predict the course of an infection is critical in anticipating disease progression and effectively treating patients. Similarly, the ability to make predictions about pathogenesis in laboratory infection models could further our understanding of pathogenesis and lead to new treatments. As fungal diseases are expected to rise, understanding the dynamics of fungal infections will be important to anticipate and mitigate future threats. Here, we developed a time-lapse method to visualize infections of Galleria mellonella larvae with the fungal pathogen Cryptococcus neoformans. This method provided insight into infection progression that is not apparent from standard survival measurement protocols, including the relationship between melanization and death. Further, it enabled us to explore the dynamics of disease progression in this system, which revealed deterministic dynamics without evidence of chaos, implying predictability in the outcome of cryptococcal infection in this moth.

The Dynamics of Cryptococcus neoformans infection in Galleria mellonella

Galleria mellonella has emerged as an important host for the study of fungal virulence, insect immune responses, and the evaluation of antifungal agents. In this study we investigated the dynamics of fungal infections in G. mellonella using Cryptococcus neoformans, a human pathogenic fungus. Since the analysis of infection dynamics requires a fine temporal resolution of larval death, we employed a photographic timelapse technique that allowed us to simultaneously measure death by proxy of larval melanization and absence of movement. Larval mortality occurred in two phases, early and late, which differed in their timing of melanization. Early phase deaths occurred with rapid whole-body onset of melanization, followed by sudden cessation of movement several hours later. Contrastingly, late phase deaths occurred with a gradual cessation of movement, followed by melanization, typically radiating from one location on the larva. The differences in mortality kinetics suggests differences in fungal pathogenesis with one population succumbing early while the rest linger for later death. Subsequent analysis of mortality data using the inversion method revealed predictable deterministic dynamics without evidence for chaotic signatures, indicating that this C. neoformans-G. mellonella infection model behaves differently than bacterial-insect models.

Comparative Cross-Kingdom DDA- and DIA-PASEF Proteomic Profiling Reveals Novel Determinants of Fungal Virulence and a Putative Druggable Target

Accurate and reliable detection of fungal pathogens presents an important hurdle to manage infections, especially considering that fungal pathogens, including the globally important human pathogen, Cryptococcus neoformans, have adapted diverse mechanisms to survive the hostile host environment and moderate virulence determinant production during coinfections. These pathogen adaptations present an opportunity for improvements (e.g., technological and computational) to better understand the interplay between a host and a pathogen during disease to uncover new strategies to overcome infection. In this study, we performed comparative proteomic profiling of an in vitro coinfection model across a range of fungal and bacterial burden loads in macrophages. Comparing data-dependent acquisition and data-independent acquisition enabled with parallel accumulation serial fragmentation technology, we quantified changes in dual-perspective proteome remodeling. We report enhanced and novel detection of pathogen proteins with data-independent acquisition-parallel accumulation serial fragmentation (DIA-PASEF), especially for fungal proteins during single and dual infection of macrophages. Further characterization of a fungal protein detected only with DIA-PASEF uncovered a novel determinant of fungal virulence, including altered capsule and melanin production, thermotolerance, and macrophage infectivity, supporting proteomics advances for the discovery of a novel putative druggable target to suppress C. neoformans pathogenicity.

Characterizing the molecular epidemiology of anaesthesia work area transmission of Staphylococcus aureus sequence type 5

BACKGROUND

Staphylococcus aureus sequence type 5 (ST5) is an emerging global threat.

AIM

To characterize the epidemiology of ST5 transmission in the anaesthesia work area.

METHODS

The retrospective cohort study analysed transmitted, prophylactic antibiotic-resistant Staphylococcus aureus isolates involving anaesthesia work area reservoirs. Using whole-genome analysis, the epidemiology of ST5 transmission was characterized by reservoir(s) of origin, transmission location(s), portal of entry, and mode(s) of transmission. All patients were followed for at least 30 days for surgical site infection (SSI) development.

FINDINGS

Forty-one percent (18/44; 95% confidence interval: 28-56%) of isolates were ST5. Provider hands were the reservoir of origin for 28% (5/18) of transmitted ST5 vs 4% (1/26) for other STs. Provider hands were the transmission location for 28% (5/18) of ST5 vs 7% (2/26) of other STs. Stopcock contamination occurred for 8% (1/13) of ST5 isolates vs 12% (3/25) of other STs. Sixty-three percent of transmission events occurring between cases on separate operative dates involved ST5. ST5 was more likely to harbour resistance traits (ST5 median (interquartile range) 3 (2-3) vs 2 (1-2) other STs; P < 0.001) and had greater resistance to cefazolin, piperacillin-tazobactam, and/or ciprofloxacin (ST5: 3 (2-3) vs 2 (1-3) other STs; P = 0.02). ST5 was associated with three of six SSIs.

CONCLUSION

ST5 is prevalent among transmitted, prophylactic antibiotic-resistant isolates in the anaesthesia work area. Transmission involves provider hands and one patient to another on future date(s). ST5 is associated with a greater number of resistance traits and reduced in-vitro susceptibility vs other intraoperative meticillin-resistant S. aureus.

Health risk posed by direct ingestion of yeasts from polluted river water

River water is an essential human resource that may be contaminated with hazardous microorganisms. However, the risk of yeast infection through river water exposure is unclear because it is highly dependant on individual susceptibility and has therefore not been well-studied, to date. To evaluate this undefined risk, we analysed the fungal communities in less polluted (LP) and highly polluted (HP) river water, as determined using principal coordinate analysis of pollution indicators. We enumerated culturable yeasts using a thermally selective isolation procedure (37 °C) and thus promoted the growth of potentially opportunistic species. Yeast species identified as clinically relevant were then tested for antifungal resistance. In addition, we propose a quantitative microbial risk assessment (QMRA) framework to quantitatively assess the potential risk of yeast infection. Our results indicated that pollution levels significantly altered fungal communities (p = 0.007) and that genera representing opportunistic and pathogenic members were significantly more abundant in HP waters (p = 0.038). Additionally, the yeast species Candida glabrata and Clavispora lusitaniae positively correlated with other pollution indicators, demonstrating the species' indicator potential. Our QMRA results further indicate that higher risk of infection is associated with increased water pollution levels (considering both physicochemical and bacterial indicators). Furthermore, yeast species with higher pathogenic potential present an increased risk of infection despite lower observed concentrations in the river water. Interestingly, the bloom of Meyerozyma guilliermondii during the wet season suggests that other environmental factors, such as dissolved oxygen levels and water turbulence, might affect growth characteristics of yeasts in river water, which consequently affects the distribution of annual infection risks. The presence of antifungal resistant yeasts, observed in this study, could further contribute to variation in risk distribution. Research on the ecophysiology of yeasts in these environments is therefore necessary to ameliorate the uncertainty and sensitivity of the proposed QMRA model. In addition to the vital knowledge on opportunistic and pathogenic yeast occurrence in river water and their observed association with pollution, this study provides valuable methods and insights to initiate future QMRAs of yeast infections.

Correction: On the relationship between Pathogenic Potential and Infective Inoculum

[This corrects the article DOI: 10.1371/journal.ppat.1010484.].