Bacterial infections caused by multidrug-resistant (MDR) Gram-negatives are of great concern worldwide, as they are frequently associated with high mortality and morbidity rates. To date, two cases of VIM-2 metallo-β-lactamase (MBL)-producing Pseudomonas putida bacteremia have been ever reported in France and Spain between 2004 and 2010. Here, we present the first case of VIM-1-like-producing P. putida isolated in blood culture collected from an oncohematological pediatric patient admitted to Bambino Gesù Children’s Hospital (IRCCS) in Rome, Italy.

Candida viswanathii has been sporadically reported in Asia and South America but not in Europe. This study reports the first European outbreak of C. viswanathii in a paediatric hospital, outlining diagnostic challenges and containment measures. Fifteen C. viswanathii isolates were recovered from blood cultures of consecutive pediatric patients admitted to intensive care units between April and August 2025. Identification was performed using MALDI-TOF MS, chromogenic media, Fourier-transform infrared (FT-IR) spectroscopy, and whole-genome sequencing (WGS). Antifungal susceptibility testing was performed by broth microdilution. All isolates were initially misidentified as C. tropicalis by MALDI-TOF MS and undetected by the FilmArray BCID2 panel. WGS confirmed C. viswanathii, and FT-IR analysis revealed clonally related strains, indicating an outbreak. Colonies displayed a distinct deep-blue color on chromogenic CHROMagar™ medium. Elevated fluconazole minimum inhibitory concentrations were observed, while isolates remained susceptible to echinocandins and amphotericin B. A multidisciplinary infection-control response halted transmission within four weeks. This investigation documents the first C. viswanathii outbreak in Europe, highlighting diagnostic limitations of current commercial tools and the need for updated databases. Integration of FT-IR spectroscopy and WGS facilitated outbreak detection and containment, underscoring the importance of advanced diagnostics and surveillance for emerging fungal pathogens.

Background/Objectives: Paediatric osteoarticular infections (POAIs) present unique diagnostic and therapeutic challenges. Microbiological culture (MC) is typically time-consuming and lacks sensitivity, especially when patients have received antibiotics. The BIOFIRE^® Joint Infection Panel (BJIP) is a syndromic molecular assay for the direct identification of most pathogens causing POAIs. Methods: We evaluated BJIP in 17 synovial fluids, and then, we retrospectively assessed its utility in 93 off-label specimens (i.e., 25 purulent fluids/biopsies and 68 whole blood samples). All specimens were collected from October 2022 to March 2024 from paediatric patients admitted at the Bambino Gesù Children’s Hospital in Rome. Results: A bacterial pathogen was isolated in only one of 17 synovial fluid cultures, while BJIP identified eight additional microorganisms in MC-negative cases. The most frequently detected pathogen was S. aureus (44.5%, 4/9). BJIP performance in synovial fluids showed an overall positive percentage agreement (PPA) and negative percentage agreement (NPA) of 100% and 88.1%, respectively, compared to MC. All positive results (n/N = 9/17) were considered medically significant, with an increase in NPA to 100%. In purulent fluids/biopsies, BJIP and MC were concordant in 72% of cases (n/N = 18/25), with a per-sample PPA and NPA of 90% and 60%, respectively. For whole blood samples, almost all samples were negative by both methods (i.e., reference blood culture and BJIP), and the molecular test did not enable any further microbiological diagnosis. Conclusions: The BIOFIRE^® Joint Infection Panel rapidly and accurately enabled or excluded a diagnosis of a POAI (~1 vs. 24–96 h for MC), optimising antimicrobial therapy.

Background: Infant meningitis, particularly caused by Escherichia coli, remains a life-threatening condition, especially in premature and low-weight infants. Infections of the central nervous system can be fatal, necessitating prompt diagnosis and appropriate treatment. Acute infections caused by various pathogens, including E. coli, often present with similar clinical symptoms. The rapid identification of pathogens and their antimicrobial resistance mechanisms is critical for timely and effective treatment. We report the case of an 8-month-old patient who presented with fever, diarrhea, and convulsive seizures and was subsequently diagnosed with meningitis. Despite initial empirical treatment with ceftriaxone, the patient’s condition worsened. Methods: At Bambino Gesù Children’s Hospital, molecular diagnostic tools, including the FilmArray Meningitis/Encephalitis and Blood Culture Identification panels, were employed. Results: Although the Meningitis panel did not detect any pathogens due to the lack of the specific bacterial target, the off-label use of the Blood Culture Identification panel identified a non-K1 Escherichia coli strain carrying the CTX-M resistance gene, an extended-spectrum beta-lactamase (ESBL). Despite the rapid diagnostic approach and adjustment of antibiotic therapy, the patient succumbed to the infection due to the strain’s high virulence and multidrug resistance. Whole-genome sequencing further characterized the strain, revealing that it belonged to the ST131 group, a highly resistant and virulent strain associated with sepsis. Conclusions: This case highlights the importance of integrating advanced molecular diagnostics, such as whole-genome sequencing, with traditional methods to improve pathogen detection, especially in cases of emerging resistant strains that are not covered by standard diagnostic panels. It also emphasizes the need for the continuous adaptation of diagnostic tools to include non-K1 E. coli strains for more comprehensive and timely meningitis diagnosis.

Background: Bloodstream infections affect up to 20% of pediatric cancer patients receiving intensive care, contributing significantly to morbidity and mortality, with infection-related mortality rates reported to be as high as 16%. Methods: The identification of microorganisms directly from whole blood is difficult due to several factors, such as interference from host genomic material, low bacterial load, the endogenous components of whole blood and exogenous substances, which can interfere with the identification process. Nevertheless, rapid microbial diagnosis remains of paramount importance in these patients. Results and Conclusion: Here, we present the first case of bacterial pathogen identification directly from whole blood using MALDI-TOF mass spectrometry in an onco-hematological pediatric patient affected by sepsis and admitted to Bambino Gesù Children’s Hospital (IRCCS) in Rome, Italy.

Background: Since 2022, invasive Group A Streptococcus (GAS) infections have increased, mainly due to the spread of specific emm-types, such as emm1. As therapy may depend on the emm-type, rapid and cost-effective identification is crucial. Fourier-transform infrared spectroscopy (FTIR) has emerged as a promising alternative to sequencing for GAS typing. We applied machine learning (ML) to FTIR spectra to build a predictive model for emm-type identification. Methods: Twenty-four GAS strains were analyzed by whole-genome sequencing and FTIR. The model was trained on twenty-one strains (emm-types: 1, 3, 4, and 6), using leave-one-out cross validation (LOOCV). To test the model’s ability to avoid false positive results, the model was also tested with three strains belonging to emm-types not included in the training of the model (emm-types: 12, 89, and 75). Results: An artificial neural network trained for 400 cycles achieved the highest accuracy (90.7%) out of the thirteen different models tested. When the three strains belonging to emm-types not included in the model were predicted with this model, it produced low score values, confirming its ability to avoid false positive results. Conclusions: We developed a preliminary and proof-of-concept model capable of accurately predicting the four most-prevalent emm-types in our setting, including the highly virulent emm1. These findings support FTIR combined with ML as a rapid, low-cost tool for GAS typing, with potential for real-time clinical applications to guide timely treatment decisions. However, as a proof-of-concept study, the relatively small sample size and limited emm-type diversity underline the need for further validation with larger and more diverse datasets.