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Background

Antibiotic heteroresistance is a common bacterial phenotype characterised by the presence of small resistant subpopulations within a susceptible population. During antibiotic exposure, these resistant subpopulations can be enriched and potentially lead to treatment failure. In this study, we examined the prevalence, misclassification, and clinical effect of heteroresistance in Escherichia coli bloodstream infections for the clinically important antibiotics cefotaxime, gentamicin, and piperacillin–tazobactam.

Methods

We conducted a retrospective cohort analysis of patients (n=255) admitted to in-patient care and treated for E coli bloodstream infections within the Uppsala region in Sweden between Jan 1, 2014, and Dec 31, 2015. Patient inclusion criteria were admission to hospital on suspicion of infection, starting systemic antibiotics at the time of admission, positive blood cultures for the growth of E coli upon admission, and residency in the Uppsala health-care region at the time of admission. Exclusion criteria were growth of an additional pathogen than E coli in blood cultures taken at admission or previous inclusion of the patients in the study for another bloodstream infection. Antibiotic susceptibility of preserved blood culture isolates of E coli was assessed for cefotaxime, gentamicin, and piperacillin–tazobactam by disk diffusion and breakpoint crossing heteroresistance (BCHR) was identified using population analysis profiling. The clinical outcome parameters were obtained from patient records. The primary outcome variable was length of hospital stay due to the E coli bloodstream infection, defined as the time between admission and discharge from inpatient care as noted on the physician’s notes. Secondary outcomes were time to fever resolution, admission to intermediary care unit or intensive care unit during time in hospital, switching or adding another intravenous antibiotic treatment, re-admission to hospital within 30 days of original admission, recurrent E coli infection within 30 days of admission to hospital, and all-cause mortality within 90 days of admission.

Findings

A total of 255 participants with a corresponding E coli isolate (out of 500 screened for eligibility) met the inclusion criteria, with 135 female patients and 120 male patients. One (<1%) of 255 strains was BCHR for cefotaxime, 109 (43%) of 255 strains were BCHR for gentamicin, and 22 (9%) of 255 strains were BCHR for piperacillin–tazobactam. Clinical susceptibility testing misclassified 120 (96%) of 125 heteroresistant bacterial strains as susceptible. The BCHR phenotypes had no correlation to length of hospital stay due to the E coli bloodstream infection. However, patients with piperacillin–tazobactam BCHR strains who received piperacillin–tazobactam had 3·1 times higher odds for admittance to the intermediate care unit (95% CI 1·1–9·6, p=0·041) than the remainder of the cohort, excluding those treated with gentamicin. Similarly, those infected with gentamicin BCHR who received gentamicin showed higher odds for admittance to the intensive care unit (5·6 [1·1–42·0, p=0·043]) and mortality (7·1 [1·2–49·2, p=0·030]) than patients treated with gentamicin who were infected with non-gentamicin BCHR E coli.

Interpretation

In a cohort of patients with E coli bloodstream infections, heteroresistance is common and frequently misidentified in routine clinical testing. Several negative effects on patient outcomes are associated with heteroresistant strains.

Treatments with antibiotic combinations are becoming increasingly important even though the supposed clinical benefits of combinations are, in many cases, unclear. Here, we systematically examined how several clinically used antibiotics interact and affect the antimicrobial efficacy against five especially problematic Gram-negative pathogens. A total of 232 bacterial isolates were tested against different pairwise antibiotic combinations spanning five classes, and the ability of all combinations in inhibiting growth was quantified. Descriptive statistics, principal component analysis (PCA), and Spearman's rank correlation matrix were used to determine the correlations between the different combinations on interaction outcome. Several important conclusions can be drawn from the 696 examined interactions. Firstly, within a species, the interactions are in general conserved but can be isolate-specific for a given antibiotic combination and can range from antagonistic to synergistic. Secondly, additive and antagonistic interactions are the most common observed across species and antibiotics, with 87.1% of isolate-antibiotic combinations being additive, 11.6% antagonistic, and only 0.3% showing synergy. These findings suggest that to achieve the highest precision and efficacy of combination therapy, not only isolate-specific interaction profiling ought to be routinely performed, in particular to avoid using drug combinations that show antagonistic interaction and an expected associated reduction in efficacy, but also discovering rare and potentially valuable synergistic interactions.IMPORTANCEAntibiotic combinations are often used to treat bacterial infections, which aim to increase treatment efficacy and reduce resistance evolution. Typically, it is assumed that one specific antibiotic combination has the same effect on different isolates of the same species, i.e., the interaction is conserved. Here, we tested this idea by examining how several clinically used antibiotics interact and affect the antimicrobial efficacy against several bacterial pathogens. Our results show that, even though within a species the interactions are often conserved, there are also isolate-specific differences for a given antibiotic combination that can range from antagonistic to synergistic. These findings suggest that isolate-specific interaction profiling ought to be performed in clinical microbiology routine to avoid using antagonistic drug combinations that might reduce treatment efficacy. Antibiotic combinations are often used to treat bacterial infections, which aim to increase treatment efficacy and reduce resistance evolution. Typically, it is assumed that one specific antibiotic combination has the same effect on different isolates of the same species, i.e., the interaction is conserved. Here, we tested this idea by examining how several clinically used antibiotics interact and affect the antimicrobial efficacy against several bacterial pathogens. Our results show that, even though within a species the interactions are often conserved, there are also isolate-specific differences for a given antibiotic combination that can range from antagonistic to synergistic. These findings suggest that isolate-specific interaction profiling ought to be performed in clinical microbiology routine to avoid using antagonistic drug combinations that might reduce treatment efficacy.

Objectives: High frequency of antimicrobial prescription and the nature of prolonged illness in COVID-19 increases risk for complicated bacteriuria and antibiotic resistance. We investigated risk factors for bacteriuria in the ICU and the correlation between antibiotic treatment and persistent bacteria.

Methods: We conducted a prospective longitudinal study with urine from indwelling catheters of 101 ICU patients from Uppsala University Hospital, Sweden. Samples were screened and isolates confirmed with MALDI-TOF and whole genome sequencing. Isolates were analyzed for AMR using broth microdilution. Clinical data were assessed for correlation with bacteriuria.

Results: Length of stay linearly correlated with bacteriuria (R² = 0.99, p ≤ 0.0001). 90% of patients received antibiotics, primarily the beta-lactams (76%) cefotaxime, piperacillin-tazobactam, and meropenem. We found high prevalence of Enterococcus (42%) being associated with increased cefotaxime prescription. Antibiotic-susceptible E. coli were found to cause bacteriuria despite concurrent antibiotic treatment when found in co-culture with Enterococcus.

Conclusion: Longer stays in ICUs increase the risk for bacteriuria in a predictable manner. Likely, high use of cefotaxime drives Enterococcus prevalence, which in turn permit co-colonizing Gram-negative bacteria. Our results suggest biofilms in urinary catheters as a reservoir of pathogenic bacteria with the potential to develop and disseminate AMR.

Biofilms are arguably the most important mode of growth of bacteria, but how antibiotic resistance emerges and is selected in biofilms remains poorly understood. Several models to study evolution of antibiotic resistance have been developed, however, their usability varies depending on the nature of the biological question. Here, we developed and validated a microfluidic chip (Brimor) for studying the dynamics of enrichment of antibiotic-resistant bacteria in biofilms using real-time monitoring with confocal microscopy. In situ extracellular cellulose staining and physical disruption of the biomass confirmed Escherichia coli growth as biofilms in the chip. We showed that seven generations of growth occur in 16 h when biofilms were established in the growth chambers of Brimor, and that bacterial death and growth rates could be estimated under these conditions using a plasmid with a conditional replication origin. Additionally, competition experiments between antibiotic-susceptible and -resistant bacteria at sub-inhibitory concentrations demonstrated that the antibiotic ciprofloxacin selected for antibiotic resistance in bacterial biofilms at concentrations 17-fold below the minimal inhibitory concentration of susceptible planktonic bacteria. Overall, the microfluidic chip is easy to use and a relevant model for studying the dynamics of selection of antibiotic resistance in bacterial biofilms and we anticipate that the Brimor chip will facilitate basic research in this area.

Background

Treatment of Blood Stream Infections (BSIs) with a combination of a β-lactam and an aminoglycoside antibiotic is widely used in intensive care units (ICUs) around the world. However, no studies have systematically examined how these drugs interact and potentially influence the antimicrobial efficacy of the overall treatment.

Methods

We collected 500 E. coli isolates from the Uppsala University hospital that were isolated from blood of patients with suspicion of infection. Of those we tested the efficacy of combinations of 2 common β-lactam antibiotics (Ampicillin and Cefotaxime) combined with 2 common aminoglycosides (Gentamicin and Tobramycin) on 254 isolates. The efficacy of all 4 pairwise combinations in inhibiting bacterial growth was then examined on all susceptible strains. That was done by quantifying the Fractional Inhibitory index (FICi), a robust metric for antibiotic combinatorial behaviour, of all possible treatments on every strain. When non additive interactions were identified, results of the original screen were verified with time kill assays. Finally, combination behaviours were analysed for potential cross correlations.

Findings

Out of the 4 antibiotic combinations screened none exhibited synergistic effects on any of the 254 strains. On the contrary all 4 exhibited important antagonistic effects on several isolates. Specifically, the combinations of AMP-GEN and CTX-GEN were antagonistic in 1.97% and 1.18% of strains respectively. Similarly, the combinations of AMP-TOB were antagonistic on 0.78% of all strains. PCA analysis revealed that an important factor on the responses to the combination treatments was the choice of a specific aminoglycoside over another. Subsequent cross correlation analysis revealed that the interaction profiles of combinations including the same aminoglycoside are significantly correlated (Spearman's cross correlation test p<0.001).

Interpretation

The findings of this study elucidate potential risks of the common combination treatment for blood stream infections. They also demonstrate, previously unquantified metrics on how antibiotics in combination therapies are not interchangeable with others of the same class. Finally, they reiterate the need for case-by-case testing of antibiotic interactions in a clinical setting.

Many patients with severe infections receive inappropriate empirical treatment, and rapid detection of bacterial antibiotic susceptibility can improve clinical outcome and reduce mortality. To this end, we have developed a multiplex fluidic chip for rapid phenotypic antibiotic susceptibility testing of bacteria. A total of 21 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus were acquired from the EUCAST Development Laboratory and tested against amikacin, ceftazidime, and meropenem (Gram-negative bacteria) or gentamicin, ofloxacin, and tetracycline (Gram-positive bacteria). The bacterial samples were mixed with agarose and loaded in an array of growth chambers in the chip where bacterial microcolony growth was monitored over time using automated image analysis. MIC values were automatically obtained by tracking the growth rates of individual microcolonies in different regions of antibiotic gradients. Stable MIC values were obtained within 2 to 4 h, and the results showed categorical agreement with reference MIC values as determined by broth microdilution in 86% of the cases.

Antibiotic combination therapies are important for the efficient treatment of many types of infections, including those caused by antibiotic-resistant pathogens. Combination treatment strategies are typically used under the assumption that synergies are conserved across species and strains, even though recent results show that the combined treatment effect is determined by specific drug-strain interactions that can vary extensively and unpredictably, both between and within bacterial species. To address this problem, we present a new method in which antibiotic synergy is rapidly quantified on a case-by-case basis, allowing for improved combination therapy. The novel CombiANT methodology consists of a 3D-printed agar plate insert that produces defined diffusion landscapes of 3 antibiotics, permitting synergy quantification between all 3 antibiotic pairs with a single test. Automated image analysis yields fractional inhibitory concentration indices (FICis) with high accuracy and precision. A technical validation with 3 major pathogens,Escherichia coli,Pseudomonas aeruginosa, andStaphylococcus aureus, showed equivalent performance to checkerboard methodology, with the advantage of strongly reduced assay complexity and costs for CombiANT. A synergy screening of 10 antibiotic combinations for 12E.coliurinary tract infection (UTI) clinical isolates illustrates the need for refined combination treatment strategies. For example, combinations of trimethoprim (TMP) + nitrofurantoin (NIT) and TMP + mecillinam (MEC) showed synergy, but only for certain individual isolates, whereas MEC + NIT combinations showed antagonistic interactions across all tested strains. These data suggest that the CombiANT methodology could allow personalized clinical synergy testing and large-scale screening. We anticipate that CombiANT will greatly facilitate clinical and basic research of antibiotic synergy.

The function and behaviour of any given cell in a healthy tissue, or in a tumor, is affected by interactions with its neighboring cells. It is therefore important to create methods that allow for reconstruction of tissue niches in vitro for studies of cell-cell signaling and associated cell behaviour. To this end we created the cell assembly generator (CAGE), a microfluidic device which enables the organization of different cell types into precise cell clusters in a flow chamber compatible with high-resolution microscopy. In proof-of-concept paracrine signalling experiments, 4-cell clusters consisting of one pancreatic -cell and three breast cancer cells were formed. It has previously been established that extracellular ATP induces calcium (Ca2+) release from the endoplasmic reticulum (ER) to the cytosol before it is cleared back into the ER via sarcoplasmic/ER Ca2+ ATPase (SERCA) pumps. Here, ATP release from the -cell was stimulated by depolarization, and dynamic changes in Ca2+ levels in the adjacent cancer cells measured using imaging of the calcium indicator Fluo-4. We established that changes in the concentration of cytosolic Ca2+ in the cancer cells were proportional to the distance from the ATP-releasing -cell. Additionally, we established that the relationship between distance and cytosolic calcium changes were dependent on Ca2+-release from the ER using 5-cell clusters composed of one -cell, two untreated cancer cells and two cancer cells pretreated with Thapsigargin (to deplete the ER of Ca2+). These experiments show that the CAGE can be used to create exact cell clusters, which affords precise control for reductionist studies of cell-cell signalling and permits the formation of heterogenous cell models of specific tissue niches.

Microfluidic systems are very useful for in vitro studies of interactions between blood cells and vascular endothelial cells under flow, and several commercial solutions exist. However, the availability of customizable, user-designed devices is largely restricted to researchers with expertise in photolithography and access to clean room facilities. Here we describe a strategy for producing tailor-made modular microfluidic systems, cast in PDMS from 3D-printed molds, to facilitate studies of leukocyte adherence to endothelial cells. A dual-chamber barrier module was optimized for culturing two endothelial cell populations, separated by a 250 μm wide dividing wall, on a glass slide. In proof-of-principle experiments one endothelial population was activated by TNFα, while the other served as an internal control. The barrier module was thereafter replaced with a microfluidic flow module, enclosing both endothelial populations in a common channel. A suspension of fluorescently-labeled leukocytes was then perfused through the flow module and leukocyte interactions with control and tnfα-treated endothelial populations were monitored in the same field of view. Time-lapse microscopy analysis confirmed the preferential attachment of leukocytes to the TNFα-activated endothelial cells. We conclude that the functionality of these modular microfluidic systems makes it possible to seed and differentially activate adherent cell types, and conduct controlled side-by-side analysis of their capacity to interact with cells in suspension under flow. Furthermore, we outline a number of practical considerations and solutions associated with connecting and switching between the microfluidic modules, and the advantages of simultaneously and symmetrically analyzing control and experimental conditions in such a microfluidic system.