Susceptible, intermediate, and resistant - the intensity of antibiotic action

Megaplasmid Dissemination in Multidrug-Resistant Salmonella Serotypes from Backyard and Commercial Broiler Production Systems in the Southeastern United States

Over the past decade, there has been a rise in U.S. backyard poultry ownership, raising concern for residential area antimicrobial-resistant (AMR) Salmonella contamination. This study aims to lay the groundwork to better understand the persistence of AMR Salmonella in residential broiler production systems and make comparisons with commercial systems. Ten backyard and 10 commercial farms were sampled at three time points across bird production. Both fecal (n = 10) and environmental (soil, n = 5, litter/compost, n = 5, feeder, and waterer swabs, n = 6) samples were collected at each visit on days 10, 31, and 52 of production for backyard farms and days 10, 24, and 38 of production for commercial farms. AMR Salmonella was characterized phenotypically by broth microdilution and genotypically by whole-genome sequencing. Overall, Salmonella was more prevalent in commercial farm samples (52.31%) over backyard farms (19.10%). Kentucky (sequence type (ST) 152) was the most common serotype found in both backyard and commercial farms. Multidrug-resistant (MDR, resistance to ≥3 or more antimicrobial classes) isolates were found in both production systems, while ciprofloxacin- and nalidixic acid-resistant and intermediate isolates were more prevalent in commercial (33%) than backyard samples (1%). Plasmids that have been associated with MDR were found in Kentucky and Infantis isolates, particularly IncFIB(K)_1_Kpn3 megaplasmid (Infantis). Our study emphasizes the need to understand the selection pressures in disseminating megaplasmids in MDR Salmonella in distinct broiler production systems.

Machine Learning Assisted MALDI Mass Spectrometry for Rapid Antimicrobial Resistance Prediction in Clinicals

Antimicrobial susceptibility testing (AST) plays a critical role in assessing the resistance of individual microbial isolates and determining appropriate antimicrobial therapeutics in a timely manner. However, conventional AST normally takes up to 72 h for obtaining the results. In healthcare facilities, the global distribution of vancomycin-resistant Enterococcus fecium (VRE) infections underscores the importance of rapidly determining VRE isolates. Here, we developed an integrated antimicrobial resistance (AMR) screening strategy by combining matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) with machine learning to rapidly predict VRE from clinical samples. Over 400 VRE and vancomycin-susceptible E. faecium (VSE) isolates were analyzed using MALDI-MS at different culture times, and a comprehensive dataset comprising 2388 mass spectra was generated. Algorithms including the support vector machine (SVM), SVM with L1-norm, logistic regression, and multilayer perceptron (MLP) were utilized to train the classification model. Validation on a panel of clinical samples (external patients) resulted in a prediction accuracy of 78.07%, 80.26%, 78.95%, and 80.54% for each algorithm, respectively, all with an AUROC above 0.80. Furthermore, a total of 33 mass regions were recognized as influential features and elucidated, contributing to the differences between VRE and VSE through the Shapley value and accuracy, while tandem mass spectrometry was employed to identify the specific peaks among them. Certain ribosomal proteins, such as A0A133N352 and R2Q455, were tentatively identified. Overall, the integration of machine learning with MALDI-MS has enabled the rapid determination of bacterial antibiotic resistance, greatly expediting the usage of appropriate antibiotics.

Resistance Transition of Pseudomonas aeruginosa in SARS-CoV-2-Uninfected Hospitalized Patients in the Pandemic

Objective

To investigate the impact of coronavirus disease 2019 (COVID-19) specified preventive and control measures on the distribution and resistance transition of Pseudomonas aeruginosa (P. aeruginosa) in uninfected hospitalized patients during the pandemic.

Methods

This retrospective study retrieved data from 316 P. aeruginosa isolates in the year pre-COVID-19 (n=131) pandemic and the year under COVID-19 specified preventive and control (post-pandemic year, n=185), compared the general characteristics, laboratory results, and antimicrobial susceptibility tests of P. aeruginosa between the two groups.

Results

Compared with the pre-pandemic year, the isolation rate of P. aeruginosa (14.35% vs 22.31%, P<0.001) increased, while the rate of drug resistant P. aeruginosa decreased significantly (29.77% vs 19.45%, P<0.001) in the post-pandemic year; Prescription of β-Lactams (30.5% vs 50.0%, P<0.01) also increased significantly. The resistance rates of P. aeruginosa isolates to ceftazidime (P<0.01), ciprofloxacin (P<0.01), and gentamicin (P<0.001) increased, whereas the resistance rates to piperacillin/tazobactam (P<0.01) and imipenem (P<0.05) decreased significantly.

Conclusion

The COVID-19 specified preventive and control measures have influenced the distribution and resistance transition of P. aeruginosa, further verifications are needed in future research.

Phenotypic and genomic characterization of Pseudomonas aeruginosa isolates recovered from catheter-associated urinary tract infections in an Egyptian hospital

Catheter-associated urinary tract infections (CAUTIs) represent one of the major healthcare-associated infections, and Pseudomonas aeruginosa is a common Gram-negative bacterium associated with catheter infections in Egyptian clinical settings. The present study describes the phenotypic and genotypic characteristics of 31 P. aeruginosa isolates recovered from CAUTIs in an Egyptian hospital over a 3 month period. Genomes of isolates were of good quality and were confirmed to be P. aeruginosa by comparison to the type strain (average nucleotide identity, phylogenetic analysis). Clonal diversity among the isolates was determined; eight different sequence types were found (STs 244, 357, 381, 621, 773, 1430, 1667 and 3765), of which ST357 and ST773 are considered to be high-risk clones. Antimicrobial resistance (AMR) testing according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines showed that the isolates were highly resistant to quinolones [ciprofloxacin (12/31, 38.7 %) and levofloxacin (9/31, 29 %) followed by tobramycin (10/31, 32.5 %)] and cephalosporins (7/31, 22.5 %). Genotypic analysis of resistance determinants predicted all isolates to encode a range of AMR genes, including those conferring resistance to aminoglycosides, β-lactamases, fluoroquinolones, fosfomycin, sulfonamides, tetracyclines and chloramphenicol. One isolate was found to carry a 422 938 bp pBT2436-like megaplasmid encoding OXA-520, the first report from Egypt of this emerging family of clinically important mobile genetic elements. All isolates were able to form biofilms and were predicted to encode virulence genes associated with adherence, antimicrobial activity, anti-phagocytosis, phospholipase enzymes, iron uptake, proteases, secretion systems and toxins. The present study shows how phenotypic analysis alongside genomic analysis may help us understand the AMR and virulence profiles of P. aeruginosa contributing to CAUTIs in Egypt.

Hygiene of Medical Devices and Minimum Inhibitory Concentrations for Alcohol-Based and QAC Disinfectants among Isolates from Physical Therapy Departments

Disinfectants are used intensively to control and prevent healthcare-associated infections. With continuous use and exposure to disinfectants, bacteria may develop reduced susceptibility. The study aimed to check the hygiene of devices in the physiotherapy department. For isolated bacterial strains, we aimed to determine the minimum inhibitory concentration of five different disinfectant wipe products currently in use. Microbiological environmental sampling in four various institutions in four different cities from two counties was performed, followed by CFU calculation and identification using matrix-assisted laser desorption and ionization with time-of-flight analyzer mass spectrometry (MALDI-TOF). The sampling was performed on three different occasions: before patient use, after patient use, and after disinfection. The susceptibility of isolates to three different alcohol-based and three different quaternary ammonium compounds (QAC) disinfectant wipes was examined by determining the minimal inhibitory concentrations (MIC). We identified 27 different bacterial species from 11 different genera. Gram-positive bacteria predominated. The most abundant genera were Staphylococcus, Micrococcus, and Bacillus. The average MIC values of alcohol-based disinfectants range between 66.61 and 148.82 g/L, and those of QAC-based disinfectants range between 2.4 and 3.5 mg/L. Distinctive strains with four-fold increases in MIC values, compared to average values, were identified. The widespread use of disinfectants can induce a reduction in the susceptibility of bacteria against disinfectants and affect the increase in the proportion of antibiotic-resistant bacteria. Therefore, it is urgent to define clear criteria for defining a microorganism as resistant to disinfectants by setting epidemiological cut-off (ECOFF) values and standardizing protocols for testing the resistance of microorganisms against disinfectants.

Effective antibiotic dosing in the presence of resistant strains

Mathematical models can be very useful in determining efficient and successful antibiotic dosing regimens. In this study, we consider the problem of determining optimal antibiotic dosing when bacteria resistant to antibiotics are present in addition to susceptible bacteria. We consider two different models of resistance acquisition, both involve the horizontal transfer (HGT) of resistant genes from a resistant to a susceptible strain. Modeling studies on HGT and study of optimal antibiotic dosing protocols in the literature, have been mostly focused on transfer of resistant genes via conjugation, with few studies on HGT via transformation. We propose a deterministic ODE based model of resistance acquisition via transformation, followed by a model that takes into account resistance acquisition through conjugation. Using a numerical optimization algorithm to determine the 'best' antibiotic dosing strategy. To illustrate our optimization method, we first consider optimal dosing when all the bacteria are susceptible to the antibiotic. We then consider the case where resistant strains are present. We note that constant periodic dosing may not always succeed in eradicating the bacteria while an optimal dosing protocol is successful. We determine the optimal dosing strategy in two different scenarios: one where the total bacterial population is to be minimized, and the next where we want to minimize the bacterial population at the end of the dosing period. We observe that the optimal strategy in the first case involves high initial dosing with dose tapering as time goes on, while in the second case, the optimal dosing strategy is to increase the dosing at the beginning of the dose cycles followed by a possible dose tapering. As a follow up study we intend to look at models where 'persistent' bacteria may be present in additional to resistant and susceptible strain and determine the optimal dosing protocols in this case.

Antimicrobial Resistance of Clinical and Commensal Escherichia coli Canine Isolates: Profile Characterization and Comparison of Antimicrobial Susceptibility Results According to Different Guidelines

Background: Pyometra is a diestrual chronic disease frequently associated with Escherichia coli. Initial pyometra treatment involves empiric antimicrobial therapy whose suitability should be confirmed by antimicrobial susceptibility testing. Antimicrobial resistance is a major health issue for veterinary medicine, rendering surveillance studies essential. Our goal was to determine the susceptibility profile of E. coli isolates obtained from healthy and pyometra-presenting dogs and to compare the application of different antimicrobial susceptibility guidelines. Methods: The antimicrobial susceptibility profile (ASP) of 74 E. coli isolates was determined by disk diffusion, using six antimicrobials commonly used in veterinary medicine. Profiles were assessed by CLSI VET01S, CLSI M100 and EUCAST guidelines. β-lactamases-encoding genes blaTEM, blaSHV and blaOXA were detected by multiplex PCR. Biofilm production ability was evaluated by pellicle formation assays in Luria–Bertani medium. Results: Variations in the resistance frequency were observed for amoxicillin/clavulanic acid, cephalexin and cefotaxime (29.7–54.1%, 10.8–16.2% and 1.4–4.1%, respectively). Results varied slightly between clinical and commensal isolates, as well as their biofilm-forming ability. Genes blaTEM, blaSHV and blaOXA were detected in 25.5%, 11.8% and 9.8% of isolates, respectively. Conclusions: Results show the importance of ASP determination in veterinary isolates and the need for using standardized and validated testing methods and harmonized interpretive criteria.

Meropenem-Resistant Achromobacter xylosoxidans, Subspecies Denitrificans Bacteremia in a Patient With Stage IV Adenocarcinoma of the Lung

Achromobacter xylosoxidans,subspecies denitrificans is a rare Gram-negative bacillus that causes health care associated infections in immunocompromised hosts. Carbapenems and anti-pseudomonal penicillins are listed as suitable empiric therapy in the literature. Herein, we report a case of a 77-year-old male with stage IV adenocarcinoma of the lung who presented with and was improving from Salmonella javiana enterocolitis, only to subsequently develop A. xylosoxidans,subspecies denitrificans bacteremia that was resistant to both meropenem and piperacillin-tazobactam. With empiric antibiotic coverage falling short of microbial clearance, timelyin vitrosusceptibility testing and prompt infectious disease consultation are of the utmost importance for treatment.

The role of artificial intelligence in the battle against antimicrobial-resistant bacteria

Antimicrobial resistance (AMR) in bacteria is a global health crisis due to the rapid emergence of multidrug-resistant bacteria and the lengthy development of new antimicrobials. In light of this, artificial intelligence in the form of machine learning has been viewed as a potential counter to delay the spread of AMR. With the aid of AI, there are possibilities to predict and identify AMR in bacteria efficiently. Furthermore, a combination of machine learning algorithms and lab testing can help to accelerate the process of discovering new antimicrobials. To date, many machine learning algorithms for antimicrobial-resistance discovery had been created and vigorously validated. Most of these algorithms produced accurate results and outperformed the traditional methods which relied on sequence comparison within a database. This mini-review will provide an updated overview of antimicrobial design workflow using the latest machine-learning antimicrobial discovery algorithms in the last 5 years. With this review, we hope to improve upon the current AMR identification and antimicrobial development techniques by introducing the use of AI into the mix, including how the algorithms could be made more effective.

Analysis of virulence phenotypes and antibiotic resistance in clinical strains of Acinetobacter baumannii isolated in Nashville, Tennessee

BACKGROUND

Acinetobacter baumannii is a gram-negative bacterium which causes opportunistic infections in immunocompromised hosts. Genome plasticity has given rise to a wide range of strain variation with respect to antimicrobial resistance profiles and expression of virulence factors which lead to altered phenotypes associated with pathogenesis. The purpose of this study was to analyze clinical strains of A. baumannii for phenotypic variation that might correlate with virulence phenotypes, antimicrobial resistance patterns, or strain isolation source. We hypothesized that individual strain virulence phenotypes might be associated with anatomical site of isolation or alterations in susceptibility to antimicrobial interventions.

METHODOLOGY

A cohort of 17 clinical isolates of A. baumannii isolated from diverse anatomical sites were evaluated to ascertain phenotypic patterns including biofilm formation, hemolysis, motility, and antimicrobial resistance. Antibiotic susceptibility/resistance to ampicillin-sulbactam, amikacin, ceftriaxone, ceftazidime, cefotaxime, ciprofloxacin, cefepime, gentamicin, levofloxacin, meropenem, piperacillin, trimethoprim-sulfamethoxazole, ticarcillin- K clavulanate, tetracyclin, and tobramycin was determined.

RESULTS

Antibiotic resistance was prevalent in many strains including resistance to ampicillin-sulbactam, amikacin, ceftriaxone, ceftazidime, cefotaxime, ciprofloxacin, cefepime, gentamicin, levofloxacin, meropenem, piperacillin, trimethoprim-sulfamethoxazole, ticarcillin- K clavulanate, tetracyclin, and tobramycin. All strains tested induced hemolysis on agar plate detection assays. Wound-isolated strains of A. baumannii exhibited higher motility than strains isolated from blood, urine or Foley catheter, or sputum/bronchial wash. A. baumannii strains isolated from patient blood samples formed significantly more biofilm than isolates from wounds, sputum or bronchial wash samples. An inverse relationship between motility and biofilm formation was observed in the cohort of 17 clinical isolates of A. baumannii tested in this study. Motility was also inversely correlated with induction of hemolysis. An inverse correlation was observed between hemolysis and resistance to ticarcillin-k clavulanate, meropenem, and piperacillin. An inverse correlation was also observed between motility and resistance to ampicillin-sulbactam, ceftriaxone, ceftoxamine, ceftazidime, ciprofloxacin, or levofloxacin.

CONCLUSIONS

Strain dependent variations in biofilm and motility are associated with anatomical site of isolation. Biofilm and hemolysis production both have an inverse association with motility in the cohort of strains utilized in this study, and motility and hemolysis were inversely correlated with resistance to numerous antibiotics.

Developing Rapid Antimicrobial Susceptibility Testing for Motile/Non-Motile Bacteria Treated with Antibiotics Covering Five Bactericidal Mechanisms on the Basis of Bead-Based Optical Diffusometry

Rapid antimicrobial susceptibility testing (AST) is an effective measure in the treatment of infections and the prevention of bacterial drug resistance. However, diverse antibiotic types and bacterial characteristics have formed complicated barriers to rapid diagnosis. To counteract these limitations, we investigated the interactions between antibiotic-treated bacteria and functionalized microbeads in optical diffusometry. The conjugation with bacteria increased the effective microbead complex size, thereby resulting in a temporal diffusivity change. The yielded data were sorted and analyzed to delineate a pattern for the prediction of antimicrobial susceptibility. The outcome showed that a completed rapid AST based on the trend of microbead diffusivity could provide results within 3 h (2 h measurement + 1 h computation). In this research, we studied four bacterial strains, including Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Staphylococcus aureus, and six antibiotics. Despite the different inhibitory effects caused by various antibiotics, similar trends in diffusivity alteration for all susceptible and resistant cases in the last 40 min of the 2-h measurement period were deduced. In addition, the AST results obtained using optical diffusometry showed good agreement with those acquired from the commercial instrument and conventional culture methods. Finally, we conducted a single-blinded clinical test, and the sensitivity, specificity, and accuracy of the system reached 92.9%, 91.4%, and 91.8%, respectively. Overall, the developed optical diffusometry showcased rapid AST with a small sample volume (20 μL) and low initial bacterial count (10⁵ CFU/mL). This technique provided a promising way to achieve early therapy against microbial diseases in the future.

Amino Acid k-mer Feature Extraction for Quantitative Antimicrobial Resistance (AMR) Prediction by Machine Learning and Model Interpretation for Biological Insights

Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new information about resistance mechanisms. Different feature extraction methods, such as SNP calling and counting nucleotide k-mers have been proposed for presenting DNA sequences to the model. However, there are trade-offs between interpretability, computational complexity and accuracy for different feature extraction methods. In this study, we have proposed a new feature extraction method, counting amino acid k-mers or oligopeptides, which provides easier model interpretation compared to counting nucleotide k-mers and reaches the same or even better accuracy in comparison with different methods. Additionally, we have trained machine learning algorithms using different feature extraction methods and compared the results in terms of accuracy, model interpretability and computational complexity. We have built a new feature selection pipeline for extraction of important features so that new AMR determinants can be discovered by analyzing these features. This pipeline allows the construction of models that only use a small number of features and can predict resistance accurately.

Risk assessment studies of the impact of occupational exposure of pharmaceutical workers on the development of antimicrobial drug resistance

Pharmaceutical workers involved with the production of antimicrobial drugs are exposed to various antimicrobial chemicals in different steps of manufacturing such as grinding, sieving, compression, granulation, mixing, and filling. These exposures may lead to the development of multidrug resistance (MDR) in bacteria. Scientific reports on the occupational health hazard of pharmaceutical workers involved in manufacturing antibiotics are scarce. The present study aimed to compare the degree of bacterial resistance in pharmaceutical workers in India to that of individuals not involved in the pharmaceutical field. Twenty male workers from 5 local pharmaceutical companies and 20 male subjects not involved in the pharmaceutical field (non-pharmaceutical subjects) were randomly selected. Nasal fluid and mucus/cough specimens were collected from each subject and were cultured separately at 37 °C for 24 hr to obtain bacterial growth. The cultured species were then identified, isolated, and subjected to microbial sensitivity testing against 18 different antibiotics from 8 different groups by the disk diffusion method. Staphylococcus spp., Pseudomonas spp., and Escherichia coli were identified and isolated from the culture of nasal fluids and mucuses, respectively. All the isolated species of bacteria exhibited significant enhancement of the degree of MDR in pharmaceutical workers compared with non-pharmaceutical subjects. Workers with a longer working history had greater degree of antibiotic resistance and vice versa. It can be certainly considered that the exposure of pharmaceutical workers to antibiotic agents resulted in a high incidence of multidrug resistance. Effective steps should be taken to minimize inherent exposure of pharmaceutical workers to antibiotics during work to prevent antimicrobial drug resistance.

Research Note: Repetitive element-based polymerase chain reaction genotyping improves efficiency of Salmonella surveillance in a model broiler production system

The genetic relatedness and antimicrobial susceptibility profiles of Salmonella isolated from poultry and their environment were determined. One broiler breeder flock (BBF1) and 2 broiler flocks (BF1 and BF2) were reared over a 1.75-year period on the same poultry research farm. Hatching eggs were obtained from BBF1 to produce BF1 chicks, while BF2 chicks were progeny of a separate, unsampled broiler breeder flock. BF1 and BF2 were reared in the same housing facilities but 6 mo apart. Salmonella isolates were collected via litter sock sampling (BF1), cecal excision (BF1 and BF2), or cloacal swabs (BBF1). Serotyping identified Salmonella enterica subsp. enterica serovar Altona (SA) in BBF1 and S. enterica subsp. enterica serovar Senftenberg (SS) in BF1 and BF2. Genotypic fingerprinting was achieved with Rep-PCR using the (GTG)₅ primer and revealed sequence homology among Senftenberg isolates from BF1 and BF2. For each isolate, the minimum inhibitory concentration was determined for 27 antimicrobial agents using Sensititre plates with formularies specific to antimicrobials used in poultry production or those used to control gram negative pathogens. Isolates from the 3 flocks were resistant to clindamycin, erythromycin, novobiocin, penicillin, and tylosin tartrate and demonstrated intermediate resistance to azithromycin, florfenicol, and spectinomycin. These data demonstrated that serovar Altona and Senftenberg were harbored by poultry, the latter appeared to persist in broiler flocks, and both serotypes shared similar patterns of antimicrobial susceptibility in an integrated research operation. In the case of multiple Salmonella isolates, combining genotypic fingerprinting methods with serotyping of representative isolates would reduce the number of samples required for serotyping and more clearly identify relatedness of isolates. These methods facilitate effective surveillance in poultry production systems, thus allowing for implementation of precise Salmonella control measures.

Identification and characterization of virulent Aeromonas hydrophila Ah17 from infected Channa striata in river Cauvery and in vitro evaluation of shrimp chitosan

Aeromonas hydrophila, an inhabitant in the aquatic ecosystem is considered as an important foodborne bacterial zoonotic pathogen in aquaculture. The present study aimed to identify virulent A. hydrophila from naturally infected Channa striata in river Cauvery and in vitro evaluation of shrimp chitosan. Rimler Shotts (RS) and blood agar medium identified the presence of pathogenic Aeromonas sp. from the infected C. striata. A. hydrophila Ah17 was identified using 16S rRNA nucleotide sequence. Extracellular enzymes such as amylase, lipase, and protease were screened in A. hydrophila Ah17. Antibiotic susceptibility tests showed A. hydrophila Ah17 was highly resistant against β-lactam, glycopeptide, macrolides, phosphonic, fucidin, and oxazolidinone classes of antibiotics. Virulent genes such as hemolysin (aer and hly), heat-labile enterotoxin (act), cytotonic heat-stable enterotoxin (ast), elastase (ahyB), and lipase (lip) were identified. Growth and the viable cell population of virulent A. hydrophila Ah17 were significantly reduced in a dose-dependent manner against shrimp chitosan (CHS) from Penaeus indicus (P. indicus). Thus, the present study isolated virulent A. hydrophila Ah17 from the environmental source and characterized in vitro with shrimp chitosan.

Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

Antimicrobials

This chapter introduces the reader to the treatment of infections with antimicrobial drugs. In doing so, an ecological and evolutionary approach is taken that sees humans as just one part of the biosphere, which is the totality of life on earth. Our interaction with microorganisms is constant and ever changing, and it is this dynamic relationship between evolving organisms that makes the treatment of infectious diseases so challenging.

Early in the chapter, this ecological approach is introduced, followed by the key to treating infectious diseases, which is the concept of selective toxicity. After that the key groups of organisms and their treatment are discussed, most notably bacteria, viruses and fungi, but also protozoa and helminths. More general topics of identification, testing and resistance are then discussed and before the chapter ends with consideration of opportunistic infections and pharmacological approaches to prevention.

Current Perspectives on Treatment of Gram-Positive Infections in India: What Is the Way Forward?

The emerging antimicrobial resistance leading to gram-positive infections (GPIs) is one of the major public health threats worldwide. GPIs caused by multidrug resistant bacteria can result in increased morbidity and mortality rates along with escalated treatment cost and hospitalisation stay. In India, GPIs, particularly methicillin-resistant Staphylococcus aureus (MRSA) prevalence among invasive S. aureus isolates, have been reported to increase exponentially from 29% in 2009 to 47% in 2014. Apart from MRSA, rising prevalence of vancomycin-resistant enterococci (VRE), which ranges from 1 to 9% in India, has raised concerns. Moreover, the overall mortality rate among patients with multidrug resistant GPIs in India is reported to be 10.8% and in ICU settings, the mortality rate is as high as 16%. Another challenge is the spectrum of adverse effects related to the safety and tolerability profile of the currently available drugs used against GPIs which further makes the management and treatment of these multidrug resistant organisms a complex task. Judicious prescription of antimicrobial agents, implementation of antibiotic stewardship programmes, and antibiotic policies in hospitals are essential to reduce the problem of drug-resistant infections in India. The most important step is development of newer antimicrobial agents with novel mechanisms of action and favourable pharmacokinetic profile. This review provides a synopsis about the current burden, treatment options, and the challenges faced by the clinicians in the management of GPIs such as MRSA, Quinolone-resistant Staphylococcus, VRE, and drug-resistant pneumococcus in India.

Antibacterial Activities of Crude Secondary Metabolite Extracts from Pantoea Species Obtained from the Stem of Solanum mauritianum and Their Effects on Two Cancer Cell Lines

Endophytes are microorganisms that are perceived as non-pathogenic symbionts found inside plants since they cause no symptoms of disease on the host plant. Soil conditions and geography among other factors contribute to the type(s) of endophytes isolated from plants. Our research interest is the antibacterial activity of secondary metabolite crude extracts from the medicinal plant Solanum mauritianum and its bacterial endophytes. Fresh, healthy stems of S. mauritianum were collected, washed, surface sterilized, macerated in PBS, inoculated in the nutrient agar plates, and incubated for 5 days at 30 °C. Amplification and sequencing of the 16S rRNA gene was applied to identify the isolated bacterial endophytes. These endophytes were then grown in nutrient broth for 7⁻14 days, after which sterilized Amberlite® XAD7HP 20⁻60 mesh (Merck KGaA, Darmstadt, Germany) resin was added to each culture to adsorb the secondary metabolites, which were later extracted using ethyl acetate. Concentrated crude extracts from each bacterial endophyte were tested for antibacterial activity against 11 pathogenic bacteria and two human cancer cell lines. In this study, a total of three bacterial endophytes of the Pantoea genus were identified from the stem of S. mauritianum. The antibacterial test showed that crude secondary metabolites of the endophytes and stem of S. mauritianum possessed antibacterial properties against pathogenic microbes such as Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa, with concentrations showing inhibition ranging from 0.0625 to 8.0000 mg/mL. The anticancer analysis showed an increase in cell proliferation when A549 lung carcinoma and UMG87 glioblastoma cell lines were treated with both the plant and endophytes' crude extracts. As far as we know, this is the first study of its kind on Solanum mauritianum in South Africa showing S. mauritianum endophytes having activity against some of the common human pathogenic organisms.

Underscoring interstrain variability and the impact of growth conditions on associated antimicrobial susceptibilities in preclinical testing of novel antimicrobial drugs

In the era of multidrug resistant (MDR) organisms, reliable efficacy testing of novel antimicrobials during developmental stages is of paramount concern prior to introduction in clinical trials. Unfortunately, interstrain variability is often underappreciated when appraising the efficacy of innovative antimicrobials as preclinical testing of a limited number of standardized strains in unvarying conditions does not account for the vastness and potential for hyperdiversity among and within microbial populations. In this review, the importance of accounting for interstrain variability's potential to impact breadth of novel drug efficacy evaluation in the early stages of drug development will be discussed. Additionally, testing under varying microenvironmental conditions that may influence drug efficacy will be discussed. Biofilm growth, the influence of polymicrobial growth, mechanisms of antimicrobial resistance, pH, anaerobic conditions, and other virulence factors are some of critical issues that require more attention and standardization during preclinical drug efficacy evaluation. Furthermore, potential solutions for addressing this issue in pre-clinical antimicrobial development are proposed via centralization of microbial characterization and drug target databases, testing of a large number of clinical strains, inclusion of mutator strains in testing and the use of growth parameter mathematical models for testing.

Surveillance of Antibiotic Use and Resistance in Intensive Care Units (SARI)

BACKGROUND

The project entitled Surveillance of Antibiotic Use and Resistance in Intensive Care Units (SARI) was initiated in Germany in 2000. In this article, we describe developments in antibiotic use and resistance rates in the participating intensive care units over the years 2001-2015.

METHODS

The intensive care units supplied monthly figures on patient days, antibiotic use (in defined daily doses, DDD), and resistance data for 13 pathogens. The density of antibiotic use per 1000 patient days was calculated on the basis of antibiotic use, DDD, and patient days, and the resistance density per 1000 patient days was calculated from the number of resistant pathogens.

RESULTS

In the years 2001-2015, data on 2 920 068 patient days were collected in 77 intensive care units. The average overall antibiotic use rose by 19% over this period, with a marked increase in the density of carbapenem use (from 76 to 250 DDD per 1000 patient days, +230%) and piperacillin-tazobactam use (from 42 to 146 DDD per 1000 patient days, +247%). The proportion of Escherichia coli and Klebsiella pneumoniae isolates that were resistant to third-generation cephalosporins increased markedly initially, then remained stable over the remainder of the observation period. The proportion of methicillin-resistant Staphylococcus aureus was stable over the entire period. The rates of vancomycin resistance among Enterococcus faecium isolates and imipenem resistance among gram-negative pathogens increased from 2.3% to 13.3% and from 0.1% to 0.3%, respectively.

CONCLUSION

The resistance density of gram-negative multiresistant pathogens in the participating intensive care units increased markedly. The rise in imipenem-resistant pathogens arouses particular concern. The increased use of broad-spectrum/reserve antibiotics may well have contributed to this development. Efforts to use antibiotics rationally, e.g., with the support of multidisciplinary "antibiotic stewardship" teams, are therefore vitally important. As participation in SARI is voluntary, these surveillance data cannot be considered representative of Germany as a whole.

Prevalence and Characterization of Staphylococcus aureus Isolated From Women and Children in Guangzhou, China

The prevalent Staphylococcus aureus clones and antibiotic susceptibility profiles are known to change dynamically and geographically; however, recent S. aureus strains causing infections in women and children in China have not been characterized. In this study, we analyzed the molecular epidemiology and antimicrobial resistance of S. aureus isolated from patients in four centers for women and children in Guangzhou, China. In total, 131 S. aureus isolates (100 from children and 31 from women) were analyzed by spa typing, multi-locus sequence typing, virulence gene and antimicrobial resistance profiling, staphylococcal chromosomal cassette mec typing, and mutation analyses of rpoB. A total of 58 spa types, 27 sequence types (STs), and 10 clonal complexes (CCs) were identified. While CC59 (ST59-IV, 48.8%; ST338-III, 35.7%) and CC45 (ST45-IV, 100%) were the major clones (84.4%) among MRSA isolates, CC5 (ST188, 24.3%; ST1, 21.6%) and CC398 (ST398, 70%) were the major ones (70.1%) among MSSA isolates. ST338-MRSA-III mostly found in pus but hardly in respiratory tract samples while ST45-MRSA-IV was on the opposite, even though they both found in blood and cerebrospinal fluid sample frequently. Staphylococcal enterotoxin genes seb-seq-sek were strongly associated with ST59 and ST338, while sec was associated with ST45, ST121, ST22, and ST30. All ST338, ST1232, and SCCmec III isolates carried lukF/S-PV genes. A total of 80% of ST338 isolates were resistant to erythromycin, clindamycin, and tetracycline. All ST45 isolates exhibited intermediate or complete resistance to rifampicin. In total, 481 HIS/ASN mutations in rpoB were found in rifampicin-resistant or intermediate-resistant isolates. ST338-III and ST45-IV emerged as two of three major clones in MRSA isolates from women and children in Guangzhou, China, though ST59-MRSA-IV remained the most prevalent MRSA clone. Clonal distribution of S. aureus varied, depending on the specimen source. Virulence genes and antibiograms were closely associated with the clonal lineage. These results clarified the molecular epidemiology of S. aureus from women and children in Guangzhou, China, and provide critical information for the control and treatment of S. aureus infections.

Differential Activity of the Combination of Vancomycin and Amikacin on Planktonic vs. Biofilm-Growing Staphylococcus aureus Bacteria in a Hollow Fiber Infection Model

Combining currently available antibiotics to optimize their use is a promising strategy to reduce treatment failures against biofilm-associated infections. Nevertheless, most assays of such combinations have been performed in vitro on planktonic bacteria exposed to constant concentrations of antibiotics over only 24 h and the synergistic effects obtained under these conditions do not necessarily predict the behavior of chronic clinical infections associated with biofilms. To improve the predictivity of in vitro combination assays for bacterial biofilms, we first adapted a previously described Hollow-fiber (HF) infection model by allowing a Staphylococcus aureus biofilm to form before drug exposure. We then mimicked different concentration profiles of amikacin and vancomycin, similar to the free plasma concentration profiles that would be observed in patients treated daily over 5 days. We assessed the ability of the two drugs, alone or in combination, to reduce planktonic and biofilm-embedded bacterial populations, and to prevent the selection of resistance within these populations. Although neither amikacin nor vancomycin exhibited any bactericidal activity on S. aureus in monotherapy, the combination had a synergistic effect and significantly reduced the planktonic bacterial population by -3.0 to -6.0 log₁₀ CFU/mL. In parallel, no obvious advantage of the combination, as compared to amikacin alone, was demonstrated on biofilm-embedded bacteria for which the addition of vancomycin to amikacin only conferred a further maximum reduction of 0.3 log₁₀ CFU/mL. No resistance to vancomycin was ever found whereas a few bacteria less-susceptible to amikacin were systematically detected before treatment. These resistant bacteria, which were rapidly amplified by exposure to amikacin alone, could be maintained at a low level in the biofilm population and even suppressed in the planktonic population by adding vancomycin. In conclusion, by adapting the HF model, we were able to demonstrate the different bactericidal activities of the vancomycin and amikacin combination on planktonic and biofilm-embedded bacterial populations, suggesting that, for biofilm-associated infections, the efficacy of this combination would not be much greater than with amikacin monotherapy. However, adding vancomycin could reduce possible resistance to amikacin and provide a relevant strategy to prevent the selection of antibiotic-resistant bacteria during treatments.

Prevalence, Aetiological Agents, and Antimicrobial Sensitivity Pattern of Bacterial Meningitis Among Children Receiving Care at KCMC Referral Hospital in Tanzania

Background:

Bacterial meningitis is an inflammation of the meninges that occurs in response to bacteria, causing a significant number of morbidity and mortality worldwide, especially in newborns and people living in low-income countries. Diagnosis of bacterial meningitis combines a high index of clinical suspicion and laboratory confirmation through cerebrospinal fluid (CSF) analysis. Despite antibiotic treatment, mortality remains high and many children end with long-term consequences, which include neurological deficits, hearing loss, and cognitive impairment.

Objective:

To determine prevalence, aetiological agents, and antimicrobial sensitivity pattern among children aged less than 13 years with bacterial meningitis at Kilimanjaro Christian Medical Centre (KCMC), Moshi, Tanzania.

Methods:

This was a hospital-based cross-sectional study carried out in the KCMC paediatric ward from December 2013 to May 2014 and from June 2015 to April 2016. In total, 161 children aged less than 13 years suspected of having meningitis were consecutively recruited. Each child submitted to a lumber puncture and CSF collected for microscopy, cultures, antimicrobial sensitivity testing, a latex agglutination test, and a polymerase chain reaction (PCR) test. PCR was run on 129 of the selected CSF samples. Data were collected using structured questionnaires and laboratory data sheet. Aetiological agents were identified, and antibiotic sensitivity was tested. Analyses were performed using SPSS version 20.0.

Results:

Overall, 24 children had confirmation of having acute bacterial meningitis. Of the 161 participants, Gram stain and culture identified 4 (2.5%) children; whereas, of the 129 samples tested using the PCR, infection was confirmed in 24 (18.6%) children. Escherichia coli (n=18) was the most common organism isolated followed by Listeria monocytogenes (n=3), Streptococcus pneumonia (n=1), Group B Streptococcus (n=1), and Klebsiella species (spp.) (n=1). With the exception of Klebsiella spp., the isolated organisms were sensitive to the following commonly used antibiotics: ampicillin, chloramphenicol, gentamycin, and cephalosporin.

Conclusion:

PCR yielded more organisms. E. coli was the most common organism and was sensitive to the empirically used antibiotics for treatment of bacterial meningitis tested in our study.

Racing on the Wrong Track

The preclinical in vitro and in vivo benchmark figures of cationic antimicrobial peptides have to be revisited based on the newly discovered alternative modes of action.

Selective Pressure Promotes Tetracycline Resistance of Chlamydia Suis in Fattening Pigs

In pigs, Chlamydia suis has been associated with respiratory disease, diarrhea and conjunctivitis, but there is a high rate of inapparent C. suis infection found in the gastrointestinal tract of pigs. Tetracycline resistance in C. suis has been described in the USA, Italy, Switzerland, Belgium, Cyprus and Israel. Tetracyclines are commonly used in pig production due to their broad-spectrum activity and relatively low cost. The aim of this study was to isolate clinical C. suis samples in cell culture and to evaluate their antibiotic susceptibility in vitro under consideration of antibiotic treatment on herd level.

Swab samples (n = 158) identified as C. suis originating from 24 farms were further processed for isolation, which was successful in 71% of attempts with a significantly higher success rate from fecal swabs compared to conjunctival swabs. The farms were divided into three treatment groups: A) farms without antibiotic treatment, B) farms with prophylactic oral antibiotic treatment of the whole herd consisting of trimethoprime, sulfadimidin and sulfathiazole (TSS), or C) farms giving herd treatment with chlortetracycline with or without tylosin and sulfadimidin (CTS). 59 isolates and their corresponding clinical samples were selected and tested for the presence or absence of the tetracycline resistance class C gene [tet(C)] by conventional PCR and isolates were further investigated for their antibiotic susceptibility in vitro. The phenotype of the investigated isolates was either classified as tetracycline sensitive (Minimum inhibitory concentration [MIC] < 2 μg/ml), intermediate (2 μg/ml ≤ MIC < 4 μg/ml) or resistant (MIC ≥ 4 μg/ml). Results of groups and individual pigs were correlated with antibiotic treatment and time of sampling (beginning/end of the fattening period). We found clear evidence for selective pressure as absence of antibiotics led to isolation of only tetracycline sensitive or intermediate strains whereas tetracycline treatment resulted in a greater number of tetracycline resistant isolates.

Integrating Antimicrobial Therapy with Host Immunity to Fight Drug-Resistant Infections: Classical vs. Adaptive Treatment

Antimicrobial resistance of infectious agents is a growing problem worldwide. To prevent the continuing selection and spread of drug resistance, rational design of antibiotic treatment is needed, and the question of aggressive vs. moderate therapies is currently heatedly debated. Host immunity is an important, but often-overlooked factor in the clearance of drug-resistant infections. In this work, we compare aggressive and moderate antibiotic treatment, accounting for host immunity effects. We use mathematical modelling of within-host infection dynamics to study the interplay between pathogen-dependent host immune responses and antibiotic treatment. We compare classical (fixed dose and duration) and adaptive (coupled to pathogen load) treatment regimes, exploring systematically infection outcomes such as time to clearance, immunopathology, host immunization, and selection of resistant bacteria. Our analysis and simulations uncover effective treatment strategies that promote synergy between the host immune system and the antimicrobial drug in clearing infection. Both in classical and adaptive treatment, we quantify how treatment timing and the strength of the immune response determine the success of moderate therapies. We explain key parameters and dimensions, where an adaptive regime differs from classical treatment, bringing new insight into the ongoing debate of resistance management. Emphasizing the sensitivity of treatment outcomes to the balance between external antibiotic intervention and endogenous natural defenses, our study calls for more empirical attention to host immunity processes.

Valproic Acid Induces Antimicrobial Compound Production in Doratomyces microspores

One of the biggest challenges in public health is the rising number of antibiotic resistant pathogens and the lack of novel antibiotics. In recent years there is a rising focus on fungi as sources of antimicrobial compounds due to their ability to produce a large variety of bioactive compounds and the observation that virtually every fungus may still contain yet unknown so called “cryptic,” often silenced, compounds. These putative metabolites could include novel bioactive compounds. Considerable effort is spent on methods to induce production of these “cryptic” metabolites. One approach is the use of small molecule effectors, potentially influencing chromatin landscape in fungi. We observed that the supernatant of the fungus Doratomyces (D.) microsporus treated with valproic acid (VPA) displayed antimicrobial activity against Staphylococcus (S.) aureus and two methicillin resistant clinical S. aureus isolates. VPA treatment resulted in enhanced production of seven antimicrobial compounds: cyclo-(L-proline-L-methionine) (cPM), p-hydroxybenzaldehyde, cyclo-(phenylalanine-proline) (cFP), indole-3-carboxylic acid, phenylacetic acid (PAA) and indole-3-acetic acid. The production of the antimicrobial compound phenyllactic acid was exclusively detectable after VPA treatment. Furthermore three compounds, cPM, cFP, and PAA, were able to boost the antimicrobial activity of other antimicrobial compounds. cPM, for the first time isolated from fungi, and to a lesser extent PAA, are even able to decrease the minimal inhibitory concentration of ampicillin in MRSA strains. In conclusion we could show in this study that VPA treatment is a potent tool for induction of “cryptic” antimicrobial compound production in fungi, and that the induced compounds are not exclusively linked to the secondary metabolism. Furthermore this is the first discovery of the rare diketopiperazine cPM in fungi. Additionally we could demonstrate that cPM and PAA boost antibiotic activity against antibiotic resistant strains, suggesting a possible application in combinatorial antibiotic treatment against resistant pathogens.

High prevalence of multiple-antibiotic-resistant (MAR) Escherichia coli in river bed sediments of the Apies River, South Africa

This study aimed at investigating the presence of antibiotic-resistant Escherichia coli in river bed sediments of the Apies River, Gauteng, South Africa, in order to better inform health management decisions designed to protect users of the river. Overall, 180 water and sediment samples were collected at 10 sites along the Apies River from January to February 2014. E. coli was enumerated using the Colilert® 18/Quanti-Tray® 2000 (IDEXX). Isolates were purified by streaking on eosin methylene blue agar followed by the indole test. Pure E. coli isolates were tested for resistance to nine antibiotics by the Kirby-Bauer disc diffusion method. Over 98% of the isolates were resistant to at least one of the antibiotics tested. The highest resistance was observed against nitrofurantoin (sediments) and ampicillin (water). Over 80% of all resistant isolates showed multiple antibiotic resistance (resistance to ≥3 antibiotics). The abundance of E. coli in the sediments not only adds to the evidence that sediments are a reservoir for bacteria and possibly other pathogens including antibiotic-resistant bacteria but also suggests that antibiotic-resistant genes could be transferred to pathogens due to the high prevalence of multiple-antibiotic-resistant (MAR) strains of E. coli observed in the sediment. Using untreated water from the Apies River following resuspension for drinking and other household purposes could pose serious health risks for users. Our results suggest that river bed sediments could serve as reservoirs for MAR bacteria including pathogens under different climatic conditions and their analysis could provide information of public health concerns.