Cronobacter spp. are opportunistic pathogens of the Enterobacteriaceae family. The organism causes infections in all age groups, but the most serious cases occur in outbreaks related to neonates with meningitis and necrotizing enterocolitis. The objective was to determine the in silico and in vitro putative virulence factors of six Cronobacter sakazakii strains isolated from powdered milk (PM) in the Czech Republic. Strains were identified by MALDI-TOF MS and whole-genome sequencing (WGS). Virulence and resistance genes were detected with the Ridom SeqSphere+ software task template and the Comprehensive Antibiotic Resistance Database (CARD) platform. Adherence and invasion ability were performed using the mouse neuroblastoma (N1E-115 ATCCCRL-2263) cell line. The CRISPR-Cas system was searched with CRISPRCasFinder. Core genome MLST identified four different sequence types (ST1, ST145, ST245, and ST297) in six isolates. Strains 13755-1B and 1847 were able to adhere in 2.2 and 3.2 × 10⁶ CFU/mL, while 0.00073% invasion frequency was detected only in strain 1847. Both strains 13755-1B and 1847 were positive for three (50.0%) and four virulence genes, respectively. The cpa gene was not detected. Twenty-eight genes were detected by WGS and grouped as flagellar or outer membrane proteins, chemotaxis, hemolysins, and invasion, plasminogen activator, colonization, transcriptional regulator, and survival in macrophages. The colistin-resistance-encoding mcr-9.1 and cephalothin-resis-encoding bla_CSA genes and IncFII(pECLA) and IncFIB(pCTU3) plasmids were detected. All strains exhibited CRISPR matrices and four of them two type I-E and I-F matrices. Combined molecular methodologies improve Cronobacter spp. decision-making for health authorities to protect the population.

Cronobacter spp. have been recognized as causative agents of various severe infections in pre-term or full-term infants as well as elderly adults suffering from serious underlying disease or malignancy. A surveillance study was designed to identify antibiotic resistance among clinical Cronobacter spp. strains, which were isolated from patients of two hospitals between May 2007 and August 2013. Altogether, 52 Cronobacter spp. isolates were analyzed. Although MALDI-TOF mass spectrometry recognized all Cronobacter sakazakii and Cronobacter malonaticus strains, it could not identify Cronobacter muytjensii strain. Nevertheless, all strains were identified as Cronobacter spp. using multilocus sequence typing (MLST). Strains were tested against 17 types of antibiotics, using the standard microdilution method according to the 2018 European Committee on Antimicrobial Susceptibility Testing criteria. Three Cronobacter species were identified as C. sakazakii (n = 33), C. malonaticus (n = 18), and C. muytjensii (n = 1); all isolates were susceptible to all tested antibiotics. All strains were PCR-negative for bla _TEM, bla _SHV, and bla _CTX-M β-lactamase genes, as well. Even though the results of this study showed that Cronobacter spp. isolates were pan-susceptible, continued antibiotic resistance surveillance is warranted.

The objective of this study was to use whole-genome sequencing (WGS) to screen for genes encoding for antibiotic resistance, fitness and virulence in Cronobacter sakazakii strains that had been isolated from food and powdered-milk-producing environments. Virulence (VGs) and antibiotic-resistance genes (ARGs) were detected with the Comprehensive Antibiotic Resistance Database (CARD) platform, ResFinder and PlasmidFinder tools. Susceptibility testing was performed using disk diffusion. Fifteen presumptive strains of Cronobacter spp. were identified by MALDI-TOF MS and ribosomal-MLST. Nine C. sakazakii strains were found in the meningitic pathovar ST4: two were ST83 and one was ST1. The C. sakazakii ST4 strains were further distinguished using core genome MLST based on 3678 loci. Almost all (93%) strains were resistant to cephalotin and 33% were resistant to ampicillin. In addition, 20 ARGs, mainly involved in regulatory and efflux antibiotics, were detected. Ninety-nine VGs were detected that encoded for OmpA, siderophores and genes involved in metabolism and stress. The IncFIB (pCTU3) plasmid was detected, and the prevalent mobile genetic elements (MGEs) were ISEsa1, ISEc52 and ISEhe3. The C. sakazakii isolates analyzed in this study harbored ARGs and VGs, which could have contributed to their persistence in powdered-milk-producing environments, and increase the risk of infection in susceptible population groups.

Aims: Aim of this study was to monitor the environment at the Transplant Unit—Hemato-Oncology Clinic, University Hospital Olomouc (Olomouc, Czech Republic) and identify risks for the patients. Methods and Results: Microorganisms were cultivated under standard aerobic conditions. Strains were biochemically identified using the BD Phoenix™ PID Panel (USA). Legionella pneumophila was identified by DNA sequencing. From the air, the most frequently isolated strains were coagulase-negative staphylococci (94.3%), Micrococcus spp. and Bacillus spp. No Gram-negative strains were isolated from the air. From the surfaces, the most frequently isolated Gram-positive strains were coagulase-negative staphylococci (67.4%), Bacillus spp., enterococci (5.5%), Staphylococcus aureus (2.3%) and Micrococcus spp. (1.7%). From the surfaces, the most frequently isolated Gram-negative strains were from genera Pseudomonas (28%), Enterobacter (28%), E. coli (6%), and Klebsiella spp. (5%). From the personnel, the most frequently isolated Gram-positive strains were coagulase-negative staphylococci (59.6%), Bacillus spp. (24.1%) and Staphylococcus aureus (9.8%). From the personnel, the most frequently isolated Gram-negative strains were Enterobacter spp. (61%), Klebsiella oxytoca (18%), and E. coli (11%). Microscopic filamentous fungi were isolated in 13 cases (2.71%). Isolated strains were Aspergillus spp. (4), Trichoderma spp. (2), Penicillium spp. (2), one case of the strains Paecilomyces spp., Eurotium spp., Monilia spp. Conclusions: The study found no significant deviations in the microbial contamination of the cleanroom air. The personnel entrance of the Transplant Unit represent a high risk area, an extreme value (7270 CFU/m³) was recorded. Regime measures are fully effective, no other deficiencies were found. Significance and Impact of the Study: This epidemiological study, which was held for the duration of one year at the Transplant Unit—Hemato-Oncology Clinic, University Hospital Olomouc. The study monitored microbial contamination of the cleanroom air, surfaces, water, colonization of the personnel by bacterial strains of epidemiological consequence.

Environmental degradation is a significant concern that jeopardizes global sustainable production and consumption. In this instance, ASEAN (Association of South-East Asian Nations) has contributed to a considerable amount of carbon dioxide (CO₂) emissions throughout the modernization phase. However, there is a paucity of information within this region on the non-linear impact of transitions in green and sustainable technological innovation on CO₂ emissions. In response, the present work endeavors to bridge the existing research gap by examining the asymmetrical and periodic interactions between green and sustainable technological innovation and CO₂ emissions by employing cross-sectional time series data of 7-ASEAN economies over the period 1990 to 2017. The co-integrating connections between the specified parameters were established using the Wester-Lund cointegration technique. Further, the Cross-Sectionally Augmented Autoregressive Distributed Lag estimator revealed that negative disruptions in green and sustainable technological innovation lead to CO₂ emissions during downturns. Secondarily, the findings confirmed positive surges in green and sustainable technological innovation minimize CO₂ emissions during times of economic expansion. Also, as compared to foreign direct investment, current statistics indicate that renewable energy utilization seems to have a substantial impact on reducing carbon emissions. Besides, the robustness analysis corroborated the uniformity and validity of the given outcomes. Consequently, the outcomes divulged a counter-cyclical interaction between green and sustainable technological innovation and CO₂ emissions.