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The spread of antimicrobial resistance has become a serious public health concern, making once-treatable diseases deadly again and undermining the achievements of modern medicine 1 , 2 . Drug combinations can help to fight multi-drug-resistant bacterial infections, yet they are largely unexplored and rarely used in clinics. Here we profile almost 3,000 dose-resolved combinations of antibiotics, human-targeted drugs and food additives in six strains from three Gram-negative pathogens— Escherichia coli , Salmonella enterica serovar Typhimurium and Pseudomonas aeruginosa —to identify general principles for antibacterial drug combinations and understand their potential. Despite the phylogenetic relatedness of the three species, more than 70% of the drug–drug interactions that we detected are species-specific and 20% display strain specificity, revealing a large potential for narrow-spectrum therapies. Overall, antagonisms are more common than synergies and occur almost exclusively between drugs that target different cellular processes, whereas synergies are more conserved and are enriched in drugs that target the same process. We provide mechanistic insights into this dichotomy and further dissect the interactions of the food additive vanillin. Finally, we demonstrate that several synergies are effective against multi-drug-resistant clinical isolates in vitro and during infections of the larvae of the greater wax moth Galleria mellonella , with one reverting resistance to the last-resort antibiotic colistin. Screening pairwise combinations of antibiotics and other drugs against three bacterial pathogens reveals that antagonistic and synergistic drug–drug interactions are specific to microbial species and strains.

Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from bacterial cells and numerous bacterial species and phenotypes. Here we generate an extensive dataset of bacterial Raman spectra and apply deep learning approaches to accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve average isolate-level accuracies exceeding 82% and antibiotic treatment identification accuracies of 97.0±0.3%. We also show that this approach distinguishes between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89±0.1% accuracy. We validate our results on clinical isolates from 50 patients. Using just 10 bacterial spectra from each patient isolate, we achieve treatment identification accuracies of 99.7%. Our approach has potential for culture-free pathogen identification and antibiotic susceptibility testing, and could be readily extended for diagnostics on blood, urine, and sputum. The use of Raman spectroscopy for pathogen identification is hampered by the weak Raman signal and phenotypic diversity of bacterial cells. Here the authors generate an extensive dataset of bacterial Raman spectra and apply deep learning to identify common bacterial pathogens and predict antibiotic treatment from noisy Raman spectra.

Background Pseudomonas aeruginosa is an opportunistic pathogen that causes a wide range of acute and chronic infections and is frequently associated with healthcare-associated infections. Because of its ability to rapidly acquire resistance to antibiotics, P. aeruginosa infections are difficult to treat. Alternative strategies, such as a vaccine, are needed to prevent infections . We collected a total of 413 P. aeruginosa isolates from the blood and cerebrospinal fluid of patients from 10 countries located on 4 continents during 2005–2017 and characterized these isolates to inform vaccine development efforts. We determined the diversity and distribution of O antigen and flagellin types and antibiotic susceptibility of the invasive P. aeruginosa . We used an antibody-based agglutination assay and PCR for O antigen typing and PCR for flagellin typing. We determined antibiotic susceptibility using the Kirby-Bauer disk diffusion method. Results Of the 413 isolates, 314 (95%) were typed by an antibody-based agglutination assay or PCR ( n  = 99). Among the 20 serotypes of P. aeruginosa , the most common serotypes were O1, O2, O3, O4, O5, O6, O8, O9, O10 and O11; a vaccine that targets these 10 serotypes would confer protection against more than 80% of invasive P. aeruginosa infections. The most common flagellin type among 386 isolates was FlaB (41%). Resistance to aztreonam (56%) was most common, followed by levofloxacin (42%). We also found that 22% of strains were non-susceptible to meropenem and piperacillin-tazobactam. Ninety-nine (27%) of our collected isolates were resistant to multiple antibiotics. Isolates with FlaA2 flagellin were more commonly multidrug resistant ( p  = 0.04). Conclusions Vaccines targeting common O antigens and two flagellin antigens, FlaB and FlaA2, would offer an excellent strategy to prevent P. aeruginosa invasive infections.

Studies on the possible association between bacteria and oral squamous cell carcinoma (OSCC) remain inconclusive, largely due to methodological variations/limitations. The objective of this study was to characterize the species composition as well as functional potential of the bacteriome associated with OSCC. DNA obtained from 20 fresh OSCC biopsies (cases) and 20 deep-epithelium swabs (matched control subjects) was sequenced for the V1-V3 region using Illumina’s 2 × 300 bp chemistry. High quality, non-chimeric merged reads were classified to species level using a prioritized BLASTN-algorithm. Downstream analyses were performed using QIIME, PICRUSt, and LEfSe. Fusobacterium nucleatum subsp . polymorphum was the most significantly overrepresented species in the tumors followed by Pseudomonas aeruginosa and Campylobacter sp . Oral taxon 44, while Streptococcus mitis , Rothia mucilaginosa and Haemophilus parainfluenzae were the most significantly abundant in the controls. Functional prediction showed that genes involved in bacterial mobility, flagellar assembly, bacterial chemotaxis and LPS synthesis were enriched in the tumors while those responsible for DNA repair and combination, purine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, ribosome biogenesis and glycolysis/gluconeogenesis were significantly associated with the controls. This is the first epidemiological evidence for association of F . nucleatum and P . aeruginosa with OSCC. Functionally, an “inflammatory bacteriome” is enriched in OSSC.

Defining the essential genome of bacterial pathogens is central to developing an understanding of the biological processes controlling disease. This has proven elusive for Pseudomonas aeruginosa during chronic infection of the cystic fibrosis (CF) lung. In this paper, using a Monte Carlo simulation-based method to analyze high-throughput transposon sequencing data, we establish the P. aeruginosa essential genome with statistical precision in laboratory media and CF sputum. Reconstruction of the global requirements for growth in CF sputum compared with defined growth conditions shows that the latter requires several cofactors including biotin, riboflavin, and pantothenate. Comparison of P. aeruginosa strains PAO1 and PA14 demonstrates that essential genes are primarily restricted to the core genome; however, some orthologous genes in these strains exhibit differential essentiality. These results indicate that genes with similar molecular functions may have distinct genetic roles in different P. aeruginosa strains during growth in CF sputum. We also show that growth in a defined growth medium developed to mimic CF sputum yielded virtually identical fitness requirements to CF sputum, providing support for this medium as a relevant in vitro model for CF microbiology studies. Significance The opportunistic pathogen Pseudomonas aeruginosa thrives in cystic fibrosis (CF) lung sputum. Here, we define the essential genome of two P. aeruginosa strains in laboratory media and in CF sputum. We also use genomic methods to profile P. aeruginosa genetic requirements for fitness in both natural and synthetic CF sputum. Finally, we show that the essential genomes of different strains of P. aeruginosa are distinct, suggesting that the architecture of genetic networks is a primary determinant of a gene’s role in fitness. This has implications for the development of strain-independent therapeutics and underscores the importance of functional studies in pathogenic strains of interest.

Verona Integron-encoded Metallo-beta-lactamase (VIM) is the most frequently-encountered carbapenemase in the healthcare-related pathogen Pseudomonas aeruginosa . In the Netherlands, a low-endemic country for antibiotic-resistant bacteria, no national surveillance data on the prevalence of carbapenemase-producing P. aeruginosa (CPPA) was available. Therefore, in 2016, a national surveillance pilot study was initiated to investigate the occurrence, molecular epidemiology, genetic characterization, and resistomes of CPPA among P. aeruginosa isolates submitted by medical microbiology laboratories (MMLs) throughout the country. From 1221 isolates included in the study, 124 (10%) produced carbapenemase (CIM-positive); of these, the majority (95, 77%) were positive for the bla VIM gene using PCR. Sequencing was performed on 112 CIM-positive and 56 CIM-negative isolates (n = 168), and genetic clustering revealed that 75/168 (45%) isolates were highly similar. This genetic cluster, designated Group 1, comprised isolates that belonged to high-risk sequence type ST111/serotype O12, had similar resistomes, and all but two carried the bla VIM-2 allele on an identical class 1 integron. Additionally, Group 1 isolates originated from around the country (i.e. seven provinces) and from multiple MMLs. In conclusion, the Netherlands had experienced a nationwide, inter-institutional, clonal outbreak of VIM-2-producing P. aeruginosa for at least three years, which this pilot study was crucial in identifying. A structured, national surveillance program is strongly advised to monitor the spread of Group 1 CPPA, to identify emerging clones/carbapenemase genes, and to detect transmission in and especially between hospitals in order to control current and future outbreaks.

Previous studies have demonstrated substantial genetic diversification of Pseudomonas aeruginosa across sub-compartments in cystic fibrosis (CF) lungs. Here, we isolate P. aeruginosa from five different sampling areas in the upper and lower airways of an explanted CF lung, analyze ex vivo transcriptional profiles by RNA-seq, and use colony re-sequencing and deep population sequencing to determine the genetic diversity within and across the various sub-compartments. We find that, despite genetic variation, the ex vivo transcriptional profiles of P. aeruginosa populations inhabiting different regions of the CF lung are similar. Although we cannot estimate the extent to which the transcriptional response recorded here actually reflects the in vivo transcriptomes, our results indicate that there may be a common in vivo transcriptional profile in the CF lung environment. Pseudomonas aeruginosa displays substantial genetic diversification across sub-compartments in cystic fibrosis (CF) lungs. Here, Kordes et al. show that, despite genetic variation, the ex vivo transcriptional profiles of P. aeruginosa populations are similar across five different areas in an explanted CF lung.

Chronic infection of the cystic fibrosis (CF) airway by the opportunistic pathogen Pseudomonas aeruginosa is the leading cause of morbidity and mortality for adult CF patients. Prolonged infections are accompanied by adaptation of P. aeruginosa to the unique conditions of the CF lung environment, as well as marked diversification of the pathogen into phenotypically and genetically distinct strains that can coexist for years within a patient. Little is known, however, about the causes of this diversification and its impact on patient health. Here, we show experimentally that, consistent with ecological theory of diversification, the nutritional conditions of the CF airway can cause rapid and extensive diversification of P. aeruginosa. Mucin, the substance responsible for the increased viscosity associated with the thick mucus layer in the CF airway, had little impact on within-population diversification but did promote divergence among populations. Furthermore, in vitro evolution recapitulated traits thought to be hallmarks of chronic infection, including reduced motility and increased biofilm formation, and the range of phenotypes observed in a collection of clinical isolates. Our results suggest that nutritional complexity and reduced dispersal can drive evolutionary diversification of P. aeruginosa independent of other features of the CF lung such as an active immune system or the presence of competing microbial species. We suggest that diversification, by generating extensive phenotypic and genetic variation on which selection can act, may be a key first step in the development of chronic infections.

Background Pseudomonas aeruginosa is a major cause of healthcare-associated infections (HAIs), particularly in immunocompromised patients, leading to high morbidity and mortality rates. This study aimed to investigate the antimicrobial resistance patterns, virulence gene profiles, and genetic diversity among P. aeruginosa isolates from hospitalized patients in Mazandaran, Iran. Methods From September 2021 to April 2022, 82 non-duplicate P. aeruginosa isolates were collected from diverse clinical sources. Identification was confirmed using API 20 NE (bioMérieux, Marcy l’Etoile, France). Antimicrobial susceptibility testing was conducted using the Kirby-Bauer disk diffusion method according to CLSI guidelines to assess resistance to a range of antibiotics. The virulence profile ( exoT , exoY , exoU , toxA , plcH , plcN , algD , aprA , lasB and exoS ) of each P. aeruginosa isolate was determined by PCR. The genetic diversity among the strains was evaluated using the random amplification of polymorphic DNA (RAPD) technique. Clustering was based on a Dice similarity coefficient of ≥ 85%. Results Of the 82 total strains, P. aeruginosa exhibited the highest and lowest resistance toward ticarcillin-clavulanate (98.78%) and colistin (0%), respectively. Moreover, 100% of the P. aeruginosa isolates were MDR. The following prevalence of virulence factor genes was observed: aprA , lasB , algD , toxA , plcH , exoY , and exoT in 100% of isolates. The plcN , exoS , and exoU were identified 98.78%, 67.07%, and 45.12%, respectively. The RAPD patterns obtained with primers 272 and 208 had respectively 2–19 and 6–17 bands. According to the Dice similarity coefficient of higher than 85%, 56 and 39 clusters were recognized. Conclusion The high rate of multidrug resistance combined with the widespread presence of virulence genes in P. aeruginosa isolates highlights the potential for increased infection severity, morbidity, and mortality in hospitalized patients. The substantial genetic diversity observed among isolates suggests that P. aeruginosa in this region may rapidly evolve, necessitating ongoing surveillance and more targeted antimicrobial strategies. Clinical trial number Not applicable.

Background Carbapenem-resistant Pseudomonas aeruginosa (CRPA) has emerged as a critical threat in bloodstream infections (BSIs), with rising global prevalence and elevated mortality rates. Traditional surveillance methods often lacks resolution for resistance-virulence-transmission interplay, highlighting the importance of high-resolution genomics. Whole-genome sequencing (WGS) has enabled unprecedented resolution in dissecting CRPA’s genetic landscape, revealing links between resistance, virulence, and outcomes. Results This study employed WGS to characterize 61 P. aeruginosa isolates from BSIs, with a focus on 18 CRPA strains. Clinical data linked central venous catheterization to CRPA BSI development (OR = 6.6, p  = 0.002) and identified carbapenem exposure, mechanical ventilation, and low hemoglobin as independent mortality risk factors. WGS identified 33.3% ( n  = 6, 6/18) of the strains harbored β-lactamase genes, and 44.4%( n  = 8, 8/18) of the strains carried truncated OprD protein due to frameshift mutations or point mutations inducing translational truncation. Efflux pump overexpression (61.1% with ≥ 2-fold upregulation) further contributed to this resistance phenotype. MLST identified 49 distinct STs (including 2 novel types) and a pattern of endemic diversification. O11 is strongly linked to carbapenem resistance (CRPA: p  = 0.02; MDRPA: p  = 0.004), correlating with oprD mutations ( p  = 0.008) and exoU +/ exoS -, indicating enhanced nosocomial adaptability. Conclusions A very high genetic diversity was noted amongst P. aeruginosa strains isolated from BSIs cases. The mechanism of carbapenem resistance is mainly attributed to oprD mutations and efflux pumps activation, with carbapenemases emerging as an additional mechanism of concern. These resistance mechanisms with high-risk clinical factors collectively indicate that strict policies are essential for in CRPA BSIs management.