(1) Background: CRISPR-Cas systems provide adaptive immunity against mobile genetic elements (MGEs) carrying antimicrobial resistance (AMR) genes. Carbapenem-resistant (CR) Klebsiella pneumoniae is a major public health concern, and the role of CRISPR-Cas in its resistance is understudied. This study explored CRISPR-Cas associations with multidrug resistance in clinical K. pneumoniae. (2) Methods: 400 K. pneumoniae isolates (200 CR and 200 carbapenem susceptible (CS)) were analyzed. Carbapenemase genes (bla_OXA-48, bla_NDM-1, bla_KPC-2), cas1, rpoB, and CRISPR1-3 loci were identified by PCR, while only CRISPR loci were sequenced. Genetic relatedness was assessed via PFGE, MLST, and spacer analysis. Statistical analysis utilized chi-squared and Fisher’s exact tests. (3) Results: CRISPR-Cas was present in 15.8% of isolates, mainly subtypes I-E and I-E* (93.3%), with CRISPR3 loci showing the greatest spacer diversity. Clonal complexes ST14/15/101 (CR) and ST35 (CS) were identified. bla_OXA-48 was linked to CRISPR-Cas-negative strains, while bla_NDM-1 and bla_KPC-2 were more frequent in CRISPR-Cas-positive strains (p < 0.0001). Imipenem/relebactam resistance was higher in CRISPR-Cas-negative isolates. (4) Conclusions: K. pneumoniae CRISPR-Cas systems correlate with specific carbapenemase profiles, suggesting pressure against bla_OXA-48 acquisition. The coexistence of I-E and I-E* subtypes highlight synergies in targeting MGEs. CRISPR loci could be tools for subtyping organisms following MLST.

We investigated the intra-hospital distribution of C. difficile strains by whole-genome sequencing (WGS) of isolates collected in 2022 at the University Hospital Centre (UHC) Zagreb. In total, 103 patients with first-episode CDI in 2022 at UHC Zagreb were included, based on the screening stool antigen test for GDH (RidaQuick CD GDH; R-Biopharm AG, Germany), confirmed by Eazyplex C. difficile assays (Eazyplex CD assay; AmplexDiagnostics GmbH, Germany) specific for A, B, and binary toxins. Demographic and clinical data were retrospectively analyzed from electronic medical records. All samples were subjected to WGS analysis. Genetic clusters were formed from isolates with no more than six allelic differences according to core genome MLST. We identified six clusters containing 2–59 isolates with 15 singletons and 30 instances of possible intra-hospital transmission, mostly in the COVID-19 ward. WGS analysis proved useful in identifying clusters of isolates connecting various patient wards with possible transmission routes in the hospital setting. It could be used to support local and national surveillance of CDI infections and their transmission pathways.