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Replication rates of bacteria in both human and environmental microbiomes are measured without reference genome sequences. Culture-independent microbiome studies have increased our understanding of the complexity and metabolic potential of microbial communities. However, to understand the contribution of individual microbiome members to community functions, it is important to determine which bacteria are actively replicating. We developed an algorithm, iRep, that uses draft-quality genome sequences and single time-point metagenome sequencing to infer microbial population replication rates. The algorithm calculates an index of replication (iRep) based on the sequencing coverage trend that results from bi-directional genome replication from a single origin of replication. We apply this method to show that microbial replication rates increase after antibiotic administration in human infants. We also show that uncultivated, groundwater-associated, Candidate Phyla Radiation bacteria only rarely replicate quickly in subsurface communities undergoing substantial changes in geochemistry. Our method can be applied to any genome-resolved microbiome study to track organism responses to varying conditions, identify actively growing populations and measure replication rates for use in modeling studies.

The structure and dynamics of bacterial communities in the airways of persons with cystic fibrosis (CF) remain largely unknown. We characterized the bacterial communities in 126 sputum samples representing serial collections spanning 8–9 y from six age-matched male CF patients. Sputum DNA was analyzed by bar-coded pyrosequencing of the V3–V5 hypervariable region of the 16S rRNA gene, defining 662 operational taxonomic units (OTUs) from >633,000 sequences. Bacterial community diversity decreased significantly over time in patients with typically progressive lung disease but remained relatively stable in patients with a mild lung disease phenotype. Antibiotic use, rather than patient age or lung function, was the primary driver of decreasing diversity. Interpatient variability in community structure exceeded intrapatient variability in serial samples. Antibiotic treatment was associated with pronounced shifts in community structure, but communities showed both short- and long-term resilience after antibiotic perturbation. There was a positive correlation between OTU occurrence and relative abundance, with a small number of persistent OTUs accounting for the greatest abundance. Significant changes in community structure, diversity, or total bacterial density at the time of pulmonary exacerbation were not observed. Despite decreasing community diversity in patients with progressive disease, total bacterial density remained relatively stable over time. These findings show the critical relationship between airway bacterial community structure, disease stage, and clinical state at the time of sample collection. These features are the key parameters with which to assess the complex ecology of the CF airway.

Background and objective: Management of skin cancer comprises a substantial proportion of general practitioner (GP) workload in Australia. Flap and graft procedures below the knee have an increased risk of infection. Antibiotic resistance is a threat to global health, and any decision about antibiotic prophylaxis must balance adverse outcomes of antibiotic use with patient morbidity. This study will investigate the effectiveness of two interventions to prevent surgical site infection (SSI) after below-knee surgery: (1) 450 mg of clindamycin preoperatively and postoperatively; and (2) preoperative chlorhexidine wash and nasal mupirocin. Methods; This prospective randomised controlled trial will be conducted across three skin cancer clinics over nine months, with 155 participants. Consecutive patients presenting for below-knee flap and graft procedures will be eligible to participate. The primary outcome is superficial SSI in the first 30 days following excision. Secondary outcomes include adverse effects (anaphylaxis, skin irritation and foreign body reaction) and patterns of antibiotic resistance. Results: As this is a study protocol paper, there are no results available to present. Discussion: As this is a study protocol paper, there are no results to be discussed.

Huanglongbing (HLB, also known as citrus greening) is considered to be the most devastating disease that has significantly damaged the citrus industry globally. HLB is caused by the Candidatus Liberibacter asiaticus (CLas), the fastidious phloem-restricted gram-negative bacterium, vectored by the asian citrus psyllid. To date, there is no effective control available against CLas. To alleviate the effects of HLB on the industry and protect citrus farmers, there is an urgent need to identify or develop inhibitor molecules to suppress or eradicate CLas from infected citrus plant. In this paper, we demonstrate for the first time an in planta efficacy of two antimicrobial compounds against CLas viz. 2S albumin (a plant based protein; ~12.5 kDa), Nano-Zinc Oxide (Nano-ZnO; ~ 4.0 nm diameter) and their combinations. Aqueous formulations of these compounds were trunk-injected to HLB affected Mosambi plants (Citrus sinensis) grafted on 3-year old rough lemon (C. jambhiri) rootstock with known CLas titer maintained inside an insect-free screen house. The effective concentration of 2S albumin (330 ppm) coupled with the Nano-ZnO (330 ppm) at 1:1 ratio was used. The dynamics of CLas pathogen load of treated Mosambi plants was assessed using TaqMan-qPCR assay every 30 days after treatment (DAT) and monitored till 120 days. We observed that 2S albumin-Nano-ZnO formulation performed the best among all the treatments decreasing CLas population by 96.2%, 97.6%, 95.6%, and 97% of the initial bacterial load (per 12.5 ng of genomic DNA) at 30, 60, 90, and 120 DAT, respectively. Our studies demonstrated the potency of 2S albumin-Nano-ZnO formulation as an antimicrobial treatment for suppressing CLas in planta and could potentially be developed as a novel anti CLas therapeutics to mitigate the HLB severity affecting the citrus industry worldwide.

Background. We evaluated the impact of extended azithromycin (1.5g over 5 days) on selection of macrolide resistance and microbiological cure in men with Mycoplasma genitalium urethritis during 2013–2015 and compared this to cases treated with azithromycin 1g in 2012–2013. Methods. Microbiological cure was determined for men with M. genitalium urethritis treated with azithromycin 1.5g using quantitative polymerase chain reaction specific for M. genitalium DNA on samples 14–100 days post-treatment. Pre- and post-treatment macrolide resistance mutations were detected by sequencing the 23 S gene. Results. There was no difference in proportions with microbiological cure between azithromycin 1.5g and 1g: 62/106 (58%; 95% confidence interval [CI], 49%, 68%) and 56/107 (52%; 95%CI 42–62%), P = .34, respectively. Also, there was no difference in the proportion of wild-type 23 S rRNA (presumed macrolide sensitive) infections cured after 1.5g and azithromycin 1g: 28/34 (82%; 95%CI 65–92%) and 49/60 (82%; 95%CI 70–90%), P=1.0, respectively. There was no difference between 1.5g and 1g in the proportions of wild-type infections with post-treatment resistance mutations: 4/34 (12%; 95%CI 3–27%) and 11/60 (18%; 95%CI 10–30%), respectively, P = .40. Pre-treatment resistance was present in 51/98 (52%; 95%CI 42–62%) cases in 2013–2015 compared to 47/107 (44%; 95%CI 34–54%) in 2012–2013, P = .25. Conclusions. Extended azithromycin 1.5g was no more effective than a single 1g dose at achieving cure of M. genitalium urethritis and importantly did not reduce the selection of macrolide resistance. Nonmacrolide and new approaches for the treatment of M. genitalium urethritis are required.

The inoculum effect (IE) is an increase in the minimum inhibitory concentration (MIC) of an antibiotic as a function of the initial size of a microbial population. The IE has been observed in a wide range of bacteria, implying that antibiotic efficacy may depend on population density. Such density dependence could have dramatic effects on bacterial population dynamics and potential treatment strategies, but explicit measures of per capita growth as a function of density are generally not available. Instead, the IE measures MIC as a function of initial population size, and population density changes by many orders of magnitude on the timescale of the experiment. Therefore, the functional relationship between population density and antibiotic inhibition is generally not known, leaving many questions about the impact of the IE on different treatment strategies unanswered. To address these questions, here we directly measured real-time per capita growth of Enterococcus faecalis populations exposed to antibiotic at fixed population densities using multiplexed computer-automated culture devices. We show that density-dependent growth inhibition is pervasive for commonly used antibiotics, with some drugs showing increased inhibition and others decreased inhibition at high densities. For several drugs, the density dependence is mediated by changes in extracellular pH, a community-level phenomenon not previously linked with the IE. Using a simple mathematical model, we demonstrate how this density dependence can modulate population dynamics in constant drug environments. Then, we illustrate how time-dependent dosing strategies can mitigate the negative effects of density-dependence. Finally, we show that these density effects lead to bistable treatment outcomes for a wide range of antibiotic concentrations in a pharmacological model of antibiotic treatment. As a result, infections exceeding a critical density often survive otherwise effective treatments.

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.

Populations of genetically identical bacteria are phenotypically heterogeneous, giving rise to population functionalities that would not be possible in homogeneous populations. For instance, a proportion of non-dividing bacteria could persist through antibiotic challenges and secure population survival. This heterogeneity can be studied in complex environmental or clinical samples by spreading the bacteria on agar plates and monitoring time to growth resumption in order to infer their metabolic state distribution. We present ColTapp, the Colony Time-lapse application for bacterial colony growth quantification. Its intuitive graphical user interface allows users to analyze time-lapse images of agar plates to monitor size, color and morphology of colonies. Additionally, images at isolated timepoints can be used to estimate lag time. Using ColTapp, we analyze a dataset of Staphylococcus aureus time-lapse images including populations with heterogeneous lag time. Colonies on dense plates reach saturation early, leading to overestimation of lag time from isolated images. We show that this bias can be corrected by taking into account the area available to each colony on the plate. We envision that in clinical settings, improved analysis of colony growth dynamics may help treatment decisions oriented towards personalized antibiotic therapies.

Background There is evidence that bacterial colonisation in chronic obstructive pulmonary disease (COPD) is associated with increased neutrophilic airway inflammation. This study tested the hypothesis that different bacterial phyla and species cause different inflammatory profiles in COPD patients. Methods Sputum was analysed by quantitative polymerase chain reaction (qPCR) to quantify bacterial load and 16S rRNA gene sequencing to identify taxonomic composition. Sputum differential cell counts (DCC) and blood DCC were obtained at baseline and 6 months. Patients were categorised into five groups based on bacterial load defined by genome copies/ml of ≥ 1 × 10 4 , no colonisation and colonisation by Haemophilus influenzae ( H. influenzae ), Moraxella catarrhalis ( M. catarrhalis ), Streptococcus pneumoniae ( S. pneumoniae ), or > 1 potentially pathogenic microorganism (PPM). Results We observed an increase in sputum neutrophil (%), blood neutrophil (%) and neutrophil–lymphocyte ratio (NLR) in patients colonised with H. influenzae (82.6, 67.1, and 3.29 respectively) compared to those without PPM colonisation at baseline (69.5, 63.51 and 2.56 respectively) (p < 0.05 for all analyses), with similar findings at 6 months. The bacterial load of H. influenzae and Haemophilus determined by qPCR and 16s rRNA gene sequencing respectively, and sputum neutrophil % were positively correlated between baseline and 6 months visits (p < 0.0001, 0.0150 and 0.0002 with r = 0.53, 0.33 and 0.44 respectively). Conclusions These results demonstrate a subgroup of COPD patients with persistent H. influenzae colonisation that is associated with increased airway and systemic neutrophilic airway inflammation, and less eosinophilic airway inflammation.

Objectives This randomized split-mouth clinical trial was designed to evaluate the efficacy of scaling and root planing associated to the high-intensity diode laser on periodontal therapy by means of clinical parameters and microbial reduction. Materials and methods A total of 36 chronic periodontitis subjects, of both genders, were selected. One pair of contralateral single-rooted teeth with pocket depth >5 mm was chosen from each subject. All patients received non-surgical periodontal treatment, after which the experimental teeth were designated to either test or control groups. Both teeth received scaling, root planing and coronal polishing (SRP) and teeth assigned to the test group (SRP + DL) were irradiated with the 808 ± 5 nm diode laser, for 20 s, in two isolated appointments, 1 week apart. The laser was used in the continuous mode, with 1.5 W and power density of 1,193.7 W/cm 2 . Clinical and microbiological data were collected at baseline, 6 weeks and 6 months after therapy. Results There was a significant improvement of all the clinical parameters—clinical attachment level (CAL), probing depth (PD), plaque index (PI) and Bleeding on Probing (BOP)—for both groups ( P  < 0.001), with no statistical difference between them at the 6 weeks and the 6 months examinations. As for microbiological analysis, a significant reduction after 6 weeks ( P  > 0.05) was observed as far as colony forming units (CFU) is concerned, for both groups. As for black-pigmented bacteria, a significant reduction was observed in both groups after 6 months. However, the difference between test and control groups was not significant. There was no association between group and presence of Porphyromonas gingivalis , Prevotella intermedia and Aggregatibacter actinomycetemcomitans at any time of the study. Conclusions After 6 months of evaluation, the high-intensity diode laser has not shown any additional benefits to the conventional periodontal treatment. Clinical relevance The high intensity diode laser did not provide additional benefits to non-surgical periodontal treatment. More studies are necessary to prove the actual need of this type of laser in the periodontal clinical practice.