Are Standard Dosing Regimens of Ceftriaxone Adapted for Critically Ill Patients with Augmented Creatinine Clearance?

The objective of the present study was to determine whether augmented renal clearance (ARC) impacts negatively on ceftriaxone pharmacokinetic (PK)/pharmacodynamic (PD) target attainment in critically ill patients. Over a 9-month period, all critically ill patients treated with ceftriaxone were eligible. During the first 3 days of antimicrobial therapy, every patient underwent 24-h creatinine clearance (CLCR) measurements and therapeutic drug monitoring of unbound ceftriaxone. ARC was defined by a CLCR of ≥150 ml/min. Empirical underdosing was defined by a trough unbound ceftriaxone concentration under 2 mg/liter (percentage of the time that the concentration of the free fraction of drug remained greater than the MIC [fT>MIC], 100%). Monte Carlo simulation (MCS) was performed to determine the probability of target attainment (PTA) of different dosing regimens for various MICs and three groups of CLCR (<150, 150 to 200, and >200 ml/min). Twenty-one patients were included. The rate of empirical ceftriaxone underdosing was 62% (39/63). A CLCR of ≥150 ml/min was associated with empirical target underdosing with an odds ratio (OR) of 8.8 (95% confidence interval [CI] = 2.5 to 30.7; P < 0.01). Ceftriaxone PK concentrations were best described by a two-compartment model. CLCR was associated with unbound ceftriaxone clearance (P = 0.02). In the MCS, the proportion of patients who would have failed to achieve a 100% fT>MIC was significantly higher in ARC patients for each dosage regimen (OR = 2.96; 95% CI = 2.74 to 3.19; P < 0.01). A dose of 2 g twice a day was best suited to achieve a 100% fT>MIC When targeting a 100% fT>MIC for the less susceptible pathogens, patients with a CLCR of ≥150 ml/min remained at risk of empirical ceftriaxone underdosing. These data emphasize the need for therapeutic drug monitoring in ARC patients.

Is the subcutaneous route an alternative for administering ertapenem to older patients? PHACINERTA study.

BACKGROUND: Antibiotic administration by subcutaneous (SC) injection is common practice in French geriatric wards as an alternative to the intravenous (IV) route, but few pharmacokinetic/pharmacodynamic data are available. Ertapenem is useful for the treatment of infections with ESBL-producing enterobacteria. OBJECTIVES: To report and compare ertapenem pharmacokinetic data between IV and SC routes in older persons. METHODS: Patients >65 years of age receiving ertapenem (1 g once daily) for at least 48 h (IV or SC, steady-state) were prospectively enrolled. Total ertapenem concentrations [residual (C0), IV peak (C0.5) and SC peak (C2.5)] were determined by UV HPLC. Individual-predicted AUC0-24 values were calculated and population pharmacokinetic analyses were performed. Using the final model, a Monte Carlo simulation involving 10 000 patients evaluated the influence of SC or IV administration on the PTA. Tolerance to ertapenem and recovery were also monitored. ClinicalTrials.gov identifier: NCT02505386. RESULTS: Ten (mean ± SD age=87±7 years) and 16 (age=88±5 years) patients were included in the IV and SC groups, respectively. The mean C0 and C2.5 values were not significantly different between the IV and SC groups (C0=12±5.9 versus 12±7.4 mg/L, P=0.97; C2.5=97±42 versus 67±41 mg/L, P=0.99). The mean C0.5 was higher in the IV group compared with the SC group (C0.5=184±90 versus 51±66 mg/L, P=0.001). The mean individual AUCs (1126.92±334.99 mg·h/L for IV versus 1005.3±266.0 mg·h/L for SC, P=0.38) and PTAs were not significantly different between groups. No severe antibiotic-related adverse effects were noted. CONCLUSIONS: SC administration of ertapenem is an alternative to IV administration in older patients.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks.

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx.

Abundance and diversity of ammonia-oxidizing prokaryotes in the root-rhizosphere complex of Miscanthus × giganteus grown in heavy metal-contaminated soils.

Mine wastes have been considered as a source of heavy metal (HM) contamination in the environment and negatively impact many important ecosystem services provided by soils. Plants like Miscanthus, which tolerate high HM concentrations in soil, are often used for phytoremediation and provide the possibility to use these soils at least for the production of energy crops. However, it is not clear if plant growth at these sites is limited by the availability of nutrients, mainly nitrogen, as microbes in soil might be affected by the contaminant. Therefore, in this study, we investigated in a greenhouse experiment the response of ammonia-oxidizing microbes in the root-rhizosphere complex of Miscanthus × giganteus grown in soils with different levels of long-term arsenic (As) and lead (Pb) contamination. Quantitative PCR of the ammonia monooxigenease gene (amoA) was performed to assess the abundance of ammonia-oxidizing bacteria (AOB) and archaea (AOA) at two different points of plant growth. Furthermore, bulk soil samples before planting were analyzed. In addition, terminal restriction fragment length polymorphism (T-RFLP) analysis was used to investigate the diversity of archaeal amoA amplicons. Whereas high concentrations of As and Pb in soil (83 and 15 g/kg, respectively) resulted independent from plant growth in a clear reduction of AOA and AOB compared to the control soils with lower HM contents, in soils with contamination levels of 10 g/kg As and 0.2 g/kg Pb, only AOB were negatively affected in bulk soil samples. Diversity analysis of archaeal amoA genes revealed clear differences in T-RFLP patterns in response to the degree of HM contamination. Therefore, our results could clearly prove the different response patterns of AOA and AOB in HM-contaminated soils and the development of archaeal amoA phylotypes which are more tolerant towards HMs in soil samples from the areas that were impacted the most by mining waste, which could contribute to functional redundancy of ammonia-oxidizing microbes in soils and stability of nitrification pattern.

Scalable rule-based modelling of allosteric proteins and biochemical networks.

Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

Effect of sulfadiazine-contaminated pig manure on the abundances of genes and transcripts involved in nitrogen transformation in the root-rhizosphere complexes of maize and clover.

The antibiotic sulfadiazine (SDZ) can enter the environment by application of manure from antibiotic-treated animals to arable soil. Because antibiotics are explicitly designed to target microorganisms, they likely affect microbes in the soil ecosystem, compromising important soil functions and disturbing processes in nutrient cycles. In a greenhouse experiment, we investigated the impact of sulfadiazine-contaminated pig manure on functional microbial communities involved in key processes of the nitrogen cycle in the root-rhizosphere complexes (RRCs) of maize (Zea mays) and clover (Trifolium alexandrinum). At both the gene and transcript level, we performed real-time PCR using nifH, amoA (in both ammonia-oxidizing bacteria and archaea), nirK, nirS, and nosZ as molecular markers for nitrogen fixation, nitrification, and denitrification. Sampling was performed 10, 20, and 30 days after the application. SDZ affected the abundance pattern of all investigated genes in the RRCs of both plant species (with stronger effects in the RRC of clover) 20 and 30 days after the addition. Surprisingly, effects on the transcript level were less pronounced, which might indicate that parts of the investigated functional groups were tolerant or resistant against SDZ or, as in the case of nifH and clover, have been protected by the nodules.

Implementation of infliximab standardized doses after pharmacokinetic modelization in a cohort of patients with Crohn's disease.

BACKGROUND: According to infliximab (IFX) license in Crohn's disease (CD), infusion doses are based on patient's body-weight. Dose banding providing standardized doses (SD) has been implemented in parenteral chemotherapy in order to optimize aseptic unit capacity and reduce drug expenditure, duration of hospital stay and costs without decreasing efficacy. MATERIAL AND METHOD: The first part was a single-center retrospective analysis of consecutive CD patients receiving IFX maintenance therapy to determine standardized doses covering more than 50% of infusions. The second part was a prospective cohort study assessing the impact of SD compared to body-weight doses (BWD) on admission duration and costs. RESULTS: Six IFX SD covering more than 90% of infusion doses were implemented for dose banding. According to the Monte-Carlo simulation, there was no significant difference between IFX SD and BWD maintenance regimens. When assessed prospectively in 116 patients (75 patients treated with SD and 41 with BWD) corresponding to 128 infusions, hospitalization duration was shortened by 70 min per patient (p < 0.001). CONCLUSION: According to a pharmacokinetic model, IFX SD has a pharmacokinetic profile close to BWD and is associated with reduced length of hospitalization in a cohort of patients with CD. IFX SD implementation could optimize infusion units functioning and, save time and costs without decreasing efficacy.

Colored extrinsic fluctuations and stochastic gene expression.

Stochasticity is both exploited and controlled by cells. Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or 'noise', is predominantly generated by interactions of the system of interest with other stochastic systems in the cell or its environment. Such extrinsic fluctuations are nonspecific, affecting many system components, and have a substantial lifetime, comparable to the cell cycle (they are 'colored'). Here, we extend the standard stochastic simulation algorithm to include extrinsic fluctuations. We show that these fluctuations affect mean protein numbers and intrinsic noise, can speed up typical network response times, and can explain trends in high-throughput measurements of variation. If extrinsic fluctuations in two components of the network are correlated, they may combine constructively (amplifying each other) or destructively (attenuating each other). Consequently, we predict that incoherent feedforward loops attenuate stochasticity, while coherent feedforwards amplify it. Our results demonstrate that both the timescales of extrinsic fluctuations and their nonspecificity substantially affect the function and performance of biochemical networks.

Higher than standard dosing regimen are needed to achieve optimal antibiotic exposure in critically ill patients with augmented renal clearance receiving piperacillin-tazobactam administered by continuous infusion.

PURPOSE: To determine whether augmented renal clearance (ARC) impacts negatively on piperacillin-tazobactam unbound concentrations in critically ill patients receiving 16 g/2 g/day administered continuously. MATERIAL AND METHODS: Fifty nine critically ill patients without renal impairment underwent 24-h creatinine clearance (CrCL) measurement and therapeutic drug monitoring during the first three days of antimicrobial therapy by piperacillin-tazobactam. The main outcome was the rate of piperacillin underexposure, defined by at least one of three samples under 16 mg/L. Monte Carlo simulation was performed to predict the distribution of piperacillin concentrations for various CrCL and minimal inhibitory concentration (MIC) values. RESULTS: The rate of piperacillin underexposure was 19%, significantly higher in ARC patients (0 vs. 31%, p = .003). A threshold of CrCL ≥ 170 mL/min had a sensitivity and specificity of 1 (95%CI: 0.79-1) and 0.69 (95%CI: 0.61-0.76) to predict piperacillin underexposure. In ARC patients, a 20 g/2.5 g/24 h PTZ dosing regimen was associated with the highest probability to reach the 16 mg/L empirical target, without risk of excessive dosing. CONCLUSIONS: When targeting a theoretical MIC at the upper limit of the susceptibility range, the desirable target (100%fT>16) may not be achieved in patients with CrCL ≥ 170 mL/min receiving PTZ 16 g/2 g/day administered continuously.

Effects of repeated application of sulfadiazine-contaminated pig manure on the abundance and diversity of ammonia and nitrite oxidizers in the root-rhizosphere complex of pasture plants under field conditions.

In a field experiment, the impact of repeated application of the antibiotic sulfadiazine (SDZ)-contaminated pig manure was assessed on functional microbial communities involved in ammonia and nitrite oxidation in the root-rhizosphere complexes (RRCs) of diverse plants composing a pasture. We surveyed the abundance of ammonia-oxidizing archaea (AOA) and bacteria (AOB) as well as Nitrobacter- and Nitrospira-like nitrite-oxidizing bacteria (NOB) by quantitative PCR (qPCR), and the diversity of amoA AOA and Nitrobacter-like nxrA amplicons using a cloning-sequencing approach. Whereas the first SDZ-contaminated manure application caused only slight effects on the investigated microbial communities and did not change the diversity and abundance pattern significantly, the second application of SDZ-contaminated manure induced an up to 15-fold increased ratio of AOA:AOB and a reduction of nrxA genes. The diversity of AOA amoA increased after the second application of SDZ-contaminated manure compared to the control treatment whereas a clear reduction of nrxA OTUs was visible in the same samples. The results indicate that the application of SDZ may principally affect nitrite oxidation by NOB and alternative pathways like nitrite reduction might be favored under these conditions.

Nitrogen turnover in soil and global change.

Nitrogen management in soils has been considered as key to the sustainable use of terrestrial ecosystems and a protection of major ecosystem services. However, the microorganisms driving processes like nitrification, denitrification, N-fixation and mineralization are highly influenced by changing climatic conditions, intensification of agriculture and the application of new chemicals to a so far unknown extent. In this review, the current knowledge concerning the influence of selected scenarios of global change on the abundance, diversity and activity of microorganisms involved in nitrogen turnover, notably in agricultural and grassland soils, is summarized and linked to the corresponding processes. In this context, data are presented on nitrogen-cycling processes and the corresponding microbial key players during ecosystem development and changes in functional diversity patterns during shifts in land use. Furthermore, the impact of increased temperature, carbon dioxide and changes in precipitation regimes on microbial nitrogen turnover is discussed. Finally, some examples of the effects of pesticides and antibiotics after application to soil for selected processes of nitrogen transformation are also shown.

Facile: a command-line network compiler for systems biology.

BACKGROUND: A goal of systems biology is the quantitative modelling of biochemical networks. Yet for many biochemical systems, parameter values and even the existence of interactions between some chemical species are unknown. It is therefore important to be able to easily investigate the effects of adding or removing reactions and to easily perform a bifurcation analysis, which shows the qualitative dynamics of a model for a range of parameter values. RESULTS: We present Facile, a Perl command-line tool for analysing the dynamics of a systems biology model. Facile implements the law of mass action to automatically compile a biochemical network (written as, for example, E + S <-> C) into scripts for analytical analysis (Mathematica and Maple), for simulation (XPP and Matlab), and for bifurcation analysis (AUTO). Facile automatically identifies mass conservations and generates the reduced form of a model with the minimum number of independent variables. This form is essential for bifurcation analysis, and Facile produces a C version of the reduced model for AUTO. CONCLUSION: Facile is a simple, yet powerful, tool that greatly accelerates analysis of the dynamics of a biochemical network. By acting at the command-line and because of its intuitive, text-based input, Facile is quick to learn and can be incorporated into larger programs or into automated tasks.