Phenotypic Screening Research Articles

Proteus mirabilis and Klebsiella variicola associated with onion bacterial streak and bulb rot

The bulb onion (Allium cepa) is second only to tomatoes in value of vegetable crops cultivated worldwide. Water-soaked lesions, bleaching and blight on leaves and slippery skin, sour skin, soft rot near the neck and centre rot on onion bulbs were observed in surveys of the onion fields, storage as well as fruit and vegetable markets of northwestern provinces of Iran in 2020. Thirty-four samples were collected from onion fields of East Azerbaijan, West Azerbaijan and Zanjan provinces and the central storage of Bonab city. Fifty bacterial strains were isolated from symptomatic samples. Pathogenicity of the strains was confirmed by inoculating on onion bulb cultivars Azarshahr and Ghermez Anari. Twenty-eight strains were able to induce soft rot on the inoculated sites of cut onion bulbs. Onion bulbs turned dark brown at lesion sites and became odorous over time. All pathogenic strains were Gram-negative, facultative aerobic and catalase positive. Strains mainly varied in starch and aesculin hydrolysis, potato rot and hypersensitive reaction. Pathogenic strains separated into four groups based on phenotypic assays. In the phylogenetic tree based on concatenated sequences of gyrB and infB genes, the strains were divided into four clusters containing the type strains of Enterobacter ludwigii, Klebsiella variicola, Proteus mirabilis and Pantoea agglomerans, confirming their identity as belonging to these four species. This is the first report of P. mirabilis as a plant pathogen and of K. variicola as a causal agent of onion bulb rot. Moreover, this is the first report of E. ludwigii and P. agglomerans associated with onion bulb rot in Iran.

Functional analysis of all succinate dehydrogenase subunits in Fusarium fujikuroi

Fusarium fujikuroi, the causal agent of rice bakanae disease (RBD), contains five succinate dehydrogenase (Sdh) subunits: FfSdhA, FfSdhB, FfSdhC1, FfSdhC2, and FfSdhD. However, the role of these subunits in regulating sensitivity to succinate dehydrogenase inhibitors (SDHIs) is largely unknown. Here, we conducted targeted gene disruption and phenotypic assays for all Sdh subunits and found that the deletion mutants of FfSdhA, FfSdhB, and FfSdhD exhibited severe defects in hyphal growth, conidiation, virulence, and sensitivity to CaCl2 and oxidative stresses. To a lesser extent, the mycelial growth rate and conidial production of ΔFfSdhC1 were also decreased as compared to those of the wild-type strain JS16. In addition, fungicide sensitivity assays showed that deletion of FfSdhA, B, C1, or D led to decreased sensitivity to all SDHIs tested. Unexpectedly, we were unable to obtain a FfSdhC1 + C2 double mutant and further found significant up-regulation of FfSdhC2 in ∆FfSdhC1, indicating that FfSdhC1 and -C2 might be essential for fungal growth although the FfSdhC2 deletion mutant was indistinguishable from the wild-type strain. These findings provide useful information for enhancing our understanding of the biological functions of the Sdh subunits in pathogenic fungi.

AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery.

Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents numerous opportunities for augmenting phenotypic drug screening on microfluidic platforms, leveraging its predictive capabilities, data analysis, efficient data processing, etc. Microfluidics coupled with AI is poised to revolutionize the landscape of phenotypic drug discovery. By integrating advanced microfluidic platforms with AI algorithms, researchers can rapidly screen large libraries of compounds, identify novel drug candidates, and elucidate complex biological pathways with unprecedented speed and efficiency. This review provides an overview of recent advances and challenges in AI-based microfluidics and their applications in drug discovery. We discuss the synergistic combination of microfluidic systems for high-throughput screening and AI-driven analysis for phenotype characterization, drug-target interactions, and predictive modeling. In addition, we highlight the potential of AI-powered microfluidics to achieve an automated drug screening system. Overall, AI-powered microfluidics represents a promising approach to shaping the future of phenotypic drug discovery by enabling rapid, cost-effective, and accurate identification of therapeutically relevant compounds.

Lactone-to-Lactam Editing Alters the Pharmacology of Bilobalide.

Precise transformations of natural products (NPs) can fine-tune their physicochemical properties while preserving inherently complex and evolutionarily optimized parent scaffolds. Here, we report an unprecedented lactone-to-lactam transformation on bilobalide, thus improving its stability and paving the way for biological exploration of previously inaccessible chemical space that is highly representative of the parent structure. This late-stage molecular editing of bilobalide enables facile access to a unique library of lactam analogues with altered pharmacology. Through phenotypic screening, we identify BB10 as a hit compound with unexpected inhibition of ferroptotic cell death. We further reveal that BB10 suppresses ferroptosis by restoring the expression of glutathione peroxidase 4 (GPX4) in brain cells. This study highlights that even subtle changes on NP scaffolds can confer new pharmacological properties, inspiring the exploration of simple yet critical transformations on complex NPs.

Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.

Computational approaches are widely applied in drug discovery to explore properties related to bioactivity, physiochemistry, and toxicology. Over at least the last 20 years, the exploitation of machine learning on molecular data sets has been used to understand the structure-activity relationships that exist between biomolecules and druggable targets. More recently, these methods have also seen application for phenotypic screening data for neglected diseases such as tuberculosis and malaria. Herein, we apply machine learning to build quantum Quantitative Structure Activity Relationship models from antimalarial data sets. There is a continual need for new antimalarials to address drug resistance, and the readily available in vitro data sets could be utilized with newer machine learning approaches as these develop. Furthermore, quantum machine learning is a relatively new method that uses a quantum computer to perform the calculations. First, we present a classical-quantum hybrid computational approach by building a Latent Bernoulli Autoencoder machine learning model for compressing bit-vector descriptors to a size that can be adapted to quantum computers for classification tasks with limited loss of embedded information. Second, we apply our method for feature map compression to quantum classification algorithms, including a completely novel machine learning algorithm with no analogy in classical computers: the Quantum Fourier Transform Classifier. We apply both these approaches to build quantum machine learning models for small-molecule antimalarials with quantum simulation software and then benchmark these quantum models against classical machine learning approaches. While there are many challenges currently facing the development of reliable quantum computers, our results demonstrate that there is potential for the use of this technology in the field of drug discovery.

Lipid-orchestrated paracrine circuit coordinates mast cell maturation and anaphylaxis through functional interaction with fibroblasts

Interaction of mast cells (MCs) with fibroblasts is essential for MC maturation within tissue microenvironments, although the underlying mechanism is incompletely understood. Through a phenotypic screening of >30 mouse lines deficient in lipid-related genes, we found that deletion of the lysophosphatidic acid (LPA) receptor LPA1, like that of the phospholipase PLA2G3, the prostaglandin D2 (PGD2) synthase L-PGDS, or the PGD2 receptor DP1, impairs MC maturation and thereby anaphylaxis. Mechanistically, MC-secreted PLA2G3 acts on extracellular vesicles (EVs) to supply lysophospholipids, which are converted by fibroblast-derived autotaxin (ATX) to LPA. Fibroblast LPA1 then integrates multiple pathways required for MC maturation by facilitating integrin-mediated MC-fibroblast adhesion, IL-33-ST2 signaling, L-PGDS-driven PGD2 generation, and feedforward ATX-LPA1 amplification. Defective MC maturation resulting from PLA2G3 deficiency is restored by supplementation with LPA1 agonists or PLA2G3-modified EVs. Thus, the lipid-orchestrated paracrine circuit involving PLA2G3-driven lysophospholipid, eicosanoid, integrin, and cytokine signaling fine-tunes MC-fibroblast communication, ensuring MC maturation.

Targeted Protein Degradation: Current and Emerging Approaches for E3 Ligase Deconvolution.

Targeted protein degradation (TPD), including the use of proteolysis-targeting chimeras (PROTACs) and molecular glue degraders (MGDs) to degrade proteins, is an emerging strategy to develop novel therapies for cancer and beyond. PROTACs or MGDs function by inducing the proximity between an E3 ligase and a protein of interest (POI), leading to ubiquitination and consequent proteasomal degradation of the POI. Notably, one major issue in TPD is the lack of ligandable E3 ligases, as current studies predominantly use CUL4CRBN and CUL2VHL. The TPD community is seeking to expand the landscape of ligandable E3 ligases, but most discoveries rely on phenotypic screens or serendipity, necessitating systematic target deconvolution. Here, we examine and discuss both current and emerging E3 ligase deconvolution approaches for degraders discovered from phenotypic screens or monovalent glue chemistry campaigns, highlighting future prospects for identifying more ligandable E3 ligases.

In Silico and In Vitro Studies of Terpenes from the Fabaceae Family Using the Phenotypic Screening Model against the SARS-CoV-2 Virus.

In 2019, the emergence of the seventh known coronavirus to cause severe illness in humans triggered a global effort towards the development of new drugs and vaccines for the SARS-CoV-2 virus. These efforts are still ongoing in 2024, including the present work where we conducted a ligand-based virtual screening of terpenes with potential anti-SARS-CoV-2 activity. We constructed a Quantitative Structure-Activity Relationship (QSAR) model from compounds with known activity against SARS-CoV-2 with a model accuracy of 0.71. We utilized this model to predict the activity of a series of 217 terpenes isolated from the Fabaceae family. Four compounds, predominantly triterpenoids from the lupane series, were subjected to an in vitro phenotypic screening in Vero CCL-81 cells to assess their inhibitory activity against SARS-CoV-2. The compounds which showed high rates of SARS-CoV-2 inhibition along with substantial cell viability underwent molecular docking at the SARS-CoV-2 main protease, papain-like protease, spike protein and RNA-dependent RNA polymerase. Overall, virtual screening through our QSAR model successfully identified compounds with the highest probability of activity, as validated using the in vitro study. This confirms the potential of the identified triterpenoids as promising candidates for anti-SARS-CoV-2 therapeutics.

Prevalence and mechanisms of aminoglycoside resistance among drug-resistant Pseudomonas aeruginosa clinical isolates in Iran

BackgroundAminoglycosides have been a cornerstone of the treatment of nosocomial infections caused by Pseudomonas aeruginosa for over 80 years. However, escalating emergence of resistance poses a significant challenge. Therefore, this study aimed to investigate the prevailing patterns of aminoglycoside resistance among clinical isolates of P. aeruginosa in Iran; as well as the underlying resistance mechanisms observed in patients referred to Ardabil hospitals.MethodsA total of 200 isolates from five hospitals were evaluated. The resistance profiles of P. aeruginosa isolates to tobramycin, amikacin, and netilmicin were determined using the disk diffusion method. The capacity of aminoglycoside-resistant isolates to form biofilms was assessed through a phenotypic assay, and the results were confirmed using the gene amplification technique. The presence of genes associated with aminoglycoside resistance was detected using polymerase chain reaction (PCR). Quantitative reverse transcription PCR (qRT-PCR) was performed to measure the expression levels of genes encoding the MexXY-OprM efflux pump and PhoPQ two-component system (TCS).ResultsThe prevalence of aminoglycoside-resistant P. aeruginosa isolates was 48%, with 94.7% demonstrating multidrug resistance (MDR). All aminoglycoside-resistant P. aeruginosa strains exhibited biofilm-forming capabilities and harbored all the genes associated with biofilm production. Among the nine genes encoding 16S rRNA methylase and aminoglycoside-modifying enzymes, three genes were detected in these isolates: aac(6’)-Ib (85.4%), ant(2’’)-Ia (18.7%), and aph(3’)-VI (3.1%). Additionally, all aminoglycoside-resistant P. aeruginosa isolates carried mexY and phoP genes, although the expression levels of mexY and phoP were 75% and 87.5%, respectively.ConclusionGiven the considerably high prevalence of aminoglycoside-resistant P. aeruginosa strains, urgent measures are warranted to transition towards the use of novel aminoglycosides and to uphold vigilant surveillance of resistance patterns.

3DSGIMD: An accurate and interpretable molecular property prediction method using 3D spatial graph focusing network and structure-based feature fusion

A comprehensive representation of molecular structure is essential for establishing accurate and reliable molecular property prediction models. However, fully extracting and learning intrinsic molecular structure information, especially spatial structure features, remains a challenging task, leading that many molecular property prediction models still have no enough accuracy for the real application. In this study, we developed an innovative and interpretable deep learning method, termed 3DSGIMD, which predicted the molecular properties by integrating and learning the spatial structure and substructure information of molecules at multiple levels, and generated the focusing weights by aggregating spatial and adjacency information of molecules to improve understanding of prediction results. We evaluated the model on 10 public datasets and 14 cell-based phenotypic screening datasets. Extensive experimental results indicated that 3DSGIMD achieved superior or comparable predictive performance compared with some existing models, and the individually designed components contributed significantly to the advanced performance of the model. In addition, we also provided insight into the interpretability of our model via visualizing the focusing weights and perturbation analysis, and the results showed that 3DSGIMD can pinpoint crucial local structures and bits of molecular descriptors associated with the predicted properties. In summary, 3DSGIMD is a competitive molecular property prediction method that holds the potential to aid drug design and optimization.

Analysis of the molecular epidemiological characteristics of carbapenem-resistant Klebsiella pneumoniae in a hospital in Hunan Province

To examine the molecular epidemiology of carbapenem-resistant Klebsiella pneumoniae (CRKP) and investigate the horizontal transmission of blaKPC and blaNDM genes for the prevention and treatment of CRKP. A total of 49 clinically isolated CRKP strains were retrospectively analyzed from January to December 2022 at The First Hospital of Hunan University of Chinese Medicine. Phenotypic screening was performed using modified carbapenem inactivation assay (mCIM) and EDTA-carbapenem inactivation assay (eCIM). Polymerase chain reaction (PCR) was utilized to identify carbapenem resistance genes, β-lactamase resistance genes, and virulence genes, while multi-locus sequence analysis (MLST) was employed to assess the homology of CRKP strains. Conjugation experiments were conducted to infer the horizontal transmission mechanism of blaKPC and blaNDM genes. The results showed that the study included 49 CRKP strains, with 44 carrying blaKPC and 8 carrying blaNDM, Three strains were identified as blaKPC+blaNDM-CRKP. In this study, 28 out of 49 CRKP strains (57.2%) were found to carry virulence genes. Additionally, one CRKP strain tested positive in the string test and was found to carry both Aerobactin and rmpA virulence genes. MLST results revealed a total of 5 ST types, with ST11 being predominant (41/49, 83.7%). Successful conjugation was observed in all 3 blaKPC-CRKP strains, while only 1 out of 3 blaNDM-CRKP strains showed successful conjugation. The transconjugant exhibited significantly reduced susceptibility to imipenem and cephalosporin antibiotics. In conclusion, the resistance mechanism of CRKP in this study is primarily attributed to the production of KPC enzymes, along with the presence of multiple β-lactamase resistance genes. Additionally, there is a local prevalence of hv-CRKP and blaKPC+blaNDM-CRKP. blaKPC and blaNDM can be horizontally transmitted through plasmids, with varying efficiency among different strains.

From hit to vial: Precision discovery and development of an imidazopyrimidine TLR7/8 agonist adjuvant formulation.

Vaccination can help prevent infection and can also be used to treat cancer, allergy, and potentially even drug overdose. Adjuvants enhance vaccine responses, but currently, the path to their advancement and development is incremental. We used a phenotypic small-molecule screen using THP-1 cells to identify nuclear factor-κB (NF-κB)-activating molecules followed by counterscreening lead target libraries with a quantitative tumor necrosis factor immunoassay using primary human peripheral blood mononuclear cells. Screening on primary cells identified an imidazopyrimidine, dubbed PVP-037. Moreover, while PVP-037 did not overtly activate THP-1 cells, it demonstrated broad innate immune activation, including NF-κB and cytokine induction from primary human leukocytes in vitro as well as enhancement of influenza and SARS-CoV-2 antigen-specific humoral responses in mice. Several de novo synthesis structural enhancements iteratively improved PVP-037's in vitro efficacy, potency, species-specific activity, and in vivo adjuvanticity. Overall, we identified imidazopyrimidine Toll-like receptor-7/8 adjuvants that act in synergy with oil-in-water emulsion to enhance immune responses.

Differences in stomatal sensitivity to CO2 and light influence variation in water use efficiency and leaf carbon isotope composition in two genotypes of the C4 plant Zea mays.

The ratio of net CO2 uptake (Anet) and stomatal conductance (gs) is an intrinsic measurement of leaf water use efficiency (WUEi); however, its measurement can be challenging for large phenotypic screens. Measurements of the leaf carbon isotope composition (δ13Cleaf) may be a scalable tool to approximate WUEi for screening because it in part reflects the competing influences of Anet and gs on the CO2 partial pressure (pCO2) inside the leaf over time. However, in C4 photosynthesis, the CO2-concentrating mechanism complicates the relationship between δ13Cleaf and WUEi. Despite this complicated relationship, several studies have shown genetic variation in δ13Cleaf across C4 plants. Yet there has not been a clear demonstration of if Anet or gs are the causal mechanisms controlling WUEi and δ13Cleaf. Our approach was to characterize leaf photosynthetic traits of two Zea mays recombinant inbred lines (Z007E0067 and Z007E0150) which consistently differ for δ13Cleaf even though they have minimal confounding genetic differences. We demonstrate that these two genotypes contrasted in WUEi driven by differences in the speed of stomatal responses to changes in pCO2 and light that lead to unproductive leaf water loss. These findings provide support that differences in δ13Cleaf in closely related genotypes do reflect greater WUEi and further suggest that differences in stomatal kinetic response to changing environmental conditions is a key target to improve WUEi.

A molecular glue degrader of the WIZ transcription factor for fetal hemoglobin induction.

Sickle cell disease (SCD) is a prevalent, life-threatening condition attributable to a heritable mutation in β-hemoglobin. Therapeutic induction of fetal hemoglobin (HbF) can ameliorate disease complications and has been intently pursued. However, safe and effective small-molecule inducers of HbF remain elusive. We report the discovery of dWIZ-1 and dWIZ-2, molecular glue degraders of the WIZ transcription factor that robustly induce HbF in erythroblasts. Phenotypic screening of a cereblon (CRBN)-biased chemical library revealed WIZ as a previously unknown repressor of HbF. WIZ degradation is mediated by recruitment of WIZ(ZF7) to CRBN by dWIZ-1, as resolved by crystallography of the ternary complex. Pharmacological degradation of WIZ was well tolerated and induced HbF in humanized mice and cynomolgus monkeys. These findings establish WIZ degradation as a globally accessible therapeutic strategy for SCD.

Preliminary snapshot reveals a relationship between multidrug-resistance and biofilm production among enterobacteriaceae isolated from fecal samples of farm-raised poultry in ceará, Brazil

Antimicrobial resistance and biofilm formation by microbial pathogens pose a significant challenge to poultry production systems due to the persistent risk of dissemination and compromise of bird health and productivity. In this context, the study aimed to investigate the occurrence of different multiresistance phenotypes and the biofilm-forming ability of Enterobacteriaceae isolated from broiler chicken excreta in poultry production units in Ceará, Brazil. Samples were collected from three distinct broiler breeding facilities and subjected to isolation, identification, antibiotic susceptibility testing, phenotypic screening for β-lactamases enzymes, and biofilm formation evaluation. Seventy-one strains were identified, being Escherichia coli (37 %) and Proteus mirabilis (32 %), followed by Klebsiella pneumoniae (11 %), Providencia stuartii (9 %), Klebsiella aerogenes (6 %), Alcaligenes faecalis (4 %), and Salmonella sp. (1 %). A significant proportion (87 %) of multiresistant strains were detected. For the phenotypic evaluation of β-lactamases production, strains with resistance to second and third-generation cephalosporins and carbapenems were tested. About 4 of 6 and 10 of 26 were positive for inducible chromosomal AmpC β-lactamase and extended-spectrum β-lactamase (ESBL), respectively. Regarding biofilm formation, it was observed that all MDR strains were capable of forming biofilm. In this sense the potential of these MDR bacteria to develop biofilms becomes a significant concern, representing a real threat to both human and animal health, as biofilms offer stability, antimicrobial protection, and facilitate genetic transfer.

Making a Pathogen? Evaluating the Impact of Protist Predation on the Evolution of Virulence in Serratia marcescens.

Opportunistic pathogens are environmental microbes that are generally harmless and only occasionally cause disease. Unlike obligate pathogens, the growth and survival of opportunistic pathogens do not rely on host infection or transmission. Their versatile lifestyles make it challenging to decipher how and why virulence has evolved in opportunistic pathogens. The coincidental evolution hypothesis postulates that virulence results from exaptation or pleiotropy, i.e. traits evolved for adaptation to living in one environment that have a different function in another. In particular, adaptation to avoid or survive protist predation has been suggested to contribute to the evolution of bacterial virulence (the training ground hypothesis). Here, we used experimental evolution to determine how the selective pressure imposed by a protist predator impacts the virulence and fitness of a ubiquitous environmental opportunistic bacterial pathogen that has acquired multidrug resistance: Serratia marcescens. To this aim, we evolved S. marcescens in the presence or absence of generalist protist predator, Tetrahymena thermophila. After 60 d of evolution, we evaluated genotypic and phenotypic changes by comparing evolved S. marcescens with the ancestral strain. Whole-genome shotgun sequencing of the entire evolved populations and individual isolates revealed numerous cases of parallel evolution, many more than statistically expected by chance, in genes associated with virulence. Our phenotypic assays suggested that evolution in the presence of a predator maintained virulence, whereas evolution in the absence of a predator resulted in attenuated virulence. We also found a significant correlation between virulence, biofilm formation, growth, and grazing resistance. Overall, our results provide evidence that bacterial virulence and virulence-related traits are maintained by selective pressures imposed by protist predation.

The Pseudo-Natural Product Tafbromin Selectively Targets the TAF1 Bromodomain 2.

Phenotypic assays detect small-molecule bioactivity at functionally relevant cellular sites, and inherently cover a variety of targets and mechanisms of action. They can uncover new small molecule-target pairs and may give rise to novel biological insights. By means of an osteoblast differentiation assay which employs a Hedgehog (Hh) signaling agonist as stimulus and which monitors an endogenous marker for osteoblasts, we identified a pyrrolo[3,4-g]quinoline (PQ) pseudo-natural product (PNP) class of osteogenesis inhibitors. The most potent PQ, termed Tafbromin, impairs canonical Hh signaling and modulates osteoblast differentiation through binding to the bromodomain 2 of the TATA-box binding protein-associated factor 1 (TAF1). Tafbromin is the most selective TAF1 bromodomain 2 ligand and promises to be an invaluable tool for the study of biological processes mediated by TAF1(2) bromodomains.

Development of a Novel Prognostic Panel for Colorectal Cancer Based on Cancer Functional Status, and Validation of STC2 as a Promising Biomarker.

Improving the clinical outcome of colorectal cancer (CRC) patients remains a major challenge. This study aimed to develop a new predictive classifier for CRC and to examine its relationship with the immune environment and therapeutic response. A comprehensive bioinformatics analysis was applied to develop a risk panel comprised of cancer function status-related genes (CFSRGs). This panel was evaluated for prognostic utility by Area Under the Curve (AUC) and Kaplan-Meier (KM) analyses. Differences between high- and low-risk groups were subsequently investigated using multi-omics data. Immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (qRT-PCR), and cell phenotype assays were also employed to ascertain the clinical value of STC2 expression. Significant differences were observed in the survival rate between high- and low-risk groups defined by our 7-CFSRG panel, both in internal and external CRC patient cohorts. The AUC for prediction of survival at 1-, 3- and 5-years was satisfactory in all cohorts. Detailed analysis revealed that tumor mutation burden, drug sensitivity, and pathological stage were closely associated with the risk score. Elevated expression of STC2 in CRC tissues relative to normal paraneoplastic tissues was associated with less favorable patient outcomes. qRT-PCR experiments confirmed that STC2 expression was significantly upregulated in several CRC cell lines (HCT116, SW480, and LOVO) compared to a normal intestinal epithelial cell line (NCM460). The proliferation, migration, and invasion of CRC cells were all significantly inhibited by knockdown of STC2. Our 7-CFSRG panel is a promising classifier for assessing the prognosis of CRC patients. Moreover, the targeting of STC2 may provide a novel therapeutic approach for improving patient outcomes.

Genomic insights into NDM-1-producing Pseudomonas aeruginosa: Current status in a Bulgarian tertiary hospital and on the Balkans.

The present study aimed to explore the genomic characteristics of eight New Delhi metallo-β-lactamase-1 (NDM-1)-producing carbapenem-resistant Pseudomonas aeruginosa (CRPA) isolates from a Bulgarian tertiary hospital (2021-2023) in comparison to blaNDM-1-positive strains originating from the Balkans. Antimicrobial susceptibility testing, phenotypic assays for carbapenemase activity, PCR screening, whole-genome sequencing (WGS), and phylogenomic analysis were performed. Seven of the CRPA isolates investigated (Minimum inhibitory concentration values of imipenem and meropenem >32 mg L-1) were also resistant to piperacillin-tazobactam, ceftazidime, ceftazidime-avibactam, cefepime, ceftolozane-tazobactam, amikacin, tobramycin, ciprofloxacin, and levofloxacin, but were susceptible to colistin (0.5-2 mg L-1) and cefiderocol (0.25-1 mg L-1). The P. aeruginosa Pae57 isolate (designated Pae57) remained susceptible to aminoglycosides as well. WGS uncovered the co-existence of blaNDM-1 and blaGES-1. The isolates belonged to the ST654 high-risk clone, except for Pae57 (ST611). Alignment against reference sequences revealed the presence of a Tn21 transposon harboring bleMBL-blaNDM-1-ISAba125. It was similar to that found in the P. aeruginosa ST654 NDM1_1 strain (GCA_020404785.1) from Serbia. Phylogenomic analysis of our isolates indicated that seven of them (ST654) differed from each other in no more than 44 single-nucleotide polymorphisms (SNPs). Pae57 (ST611) was strikingly different (>21,700 SNPs) compared to all Balkan strains. In conclusion, to our knowledge this is the first report of blaNDM-1-positive P. aeruginosa ST611 isolation, which indicates the transmission dynamics of this determinant between high-risk and potentially high-risk P. aeruginosa clones. Obtained results unveil the dissemination of clonally related NDM-1-producing P. aeruginosa strains in the monitored hospital for approximately a 2-year period.

Characterization of ST15-KL112 Klebsiella pneumoniae Co-Harboring Bla oxa-232 and rmtF in China.

This study aimed to investigate the emergence and characteristics of carbapenem-resistant Klebsiella pneumoniae (CRKP) strains that demonstrate resistance to multiple antibiotics, including aminoglycosides and tigecycline, in a Chinese hospital. A group of ten CRKP strains were collected from the nine patients in a Chinese hospital. Antimicrobial Susceptibility Testing (AST) and phenotypic inhibition assays precisely assess bacterial antibiotic resistance. Real-time quantitative PCR (RT-qPCR) was used to analyze the mRNA levels of efflux pump genes (acrA/acrB and oqxA/oqxB) and the regulatory gene (ramA). The core-genome tree and PFGE patterns were analyzed to assess the clonal and horizontal transfer expansion of the strains. Whole-genome sequencing was performed on a clinical isolate of K. pneumoniae named Kpn20 to identify key resistance genes and antimicrobial resistance islands (ARI). The CRKP strains showed high resistance to carbapenems, aminoglycosides (CLSI, 2024), and tigecycline (EUCAST, 2024). The mRNA expression levels of efflux pump genes and regulatory genes were detected by RT-qPCR. All 10 isolates had significant differences compared to the control group of ATCC13883. The core-genome tree and PFGE patterns revealed five clusters, indicating clonal and horizontal transfer expansion. Three key resistance genes (blaoxa-232, blaCTX-M-15 , and rmtF) were observed in the K. pneumoniae clinical isolate Kpn20. Mobile antibiotic resistance islands were identified containing bla CTX-M-15 and rmtF, with multiple insertion sequences and transposons present. The coexistence of bla oxa-232 and rmtF in a high-risk K. pneumoniae strain was reported. Conjugation assay was utilized to investigate the transferability of bla oxa-232-encoding plasmids horizontally. The study highlights the emergence of ST15-KL112 high-risk CRKP strains with multidrug resistance, including to aminoglycosides and tigecycline. The presence of mobile ARI and clonal and horizontal transfer expansion of strains indicate the threat of transmission of these strains. Future research is needed to assess the prevalence of such isolates and develop effective control measures.