LRRK2) lead to late-onset, autosomal dominant Parkinson's disease, characterized by the degeneration of dopamine neurons of the substantia nigra pars compacta, a deficit in dopamine neurotransmission and the development of motor and non-motor symptoms. The most prevalent Parkinson's disease LRRK2 mutations are located in the kinase (G2019S) and GTPase (R1441C) encoding domains of LRRK2. To better understand the sequence of events that lead to progressive neurophysiological deficits in vulnerable neurons and circuits in Parkinson's disease, we have generated LRRK2 bacterial artificial chromosome transgenic rats expressing either G2019S or R1441C mutant, or wild-type LRRK2, from the complete human LRRK2 genomic locus, including endogenous promoter and regulatory regions. Aged (18–21 months) G2019S and R1441C mutant transgenic rats exhibit L-DOPA-responsive motor dysfunction, impaired striatal dopamine release as determined by fast-scan cyclic voltammetry, and cognitive deficits. In addition, in vivo recordings of identified substantia nigra pars compacta dopamine neurons in R1441C LRRK2 transgenic rats reveal an age-dependent reduction in burst firing, which likely results in further reductions to striatal dopamine release. These alterations to dopamine circuit function occur in the absence of neurodegeneration or abnormal protein accumulation within the substantia nigra pars compacta, suggesting that nigrostriatal dopamine dysfunction precedes detectable protein aggregation and cell death in the development of Parkinson's disease. In conclusion, our longitudinal deep-phenotyping provides novel insights into how the genetic burden arising from human mutant LRRK2 manifests as early pathophysiological changes to dopamine circuit function and highlights a potential model for testing Parkinson's therapeutics.Mutations in leucine-rich repeat kinase 2 ( LRRK2/PARK8) gene lead to the development of autosomal dominant Parkinson's disease with pathology and characteristic motor and non-motor features highly similar to sporadic forms of the disease (LRRK2 gene encodes a large (286 kDa), multidomain protein consisting of several repeat-containing regions, followed by ROC-COR GTPase, kinase and WD40 domains . However, few exhibit age-dependent motor impairment that can be linked to altered dopaminergic neuron function or altered dopamine release, consistent with a Parkinsonian phenotype.A number of  disease –20. Rece disease –23 as ra disease . TogetheLRRK2 mutations on neural circuit function and the development of Parkinson's disease, we generated LRRK2 bacterial artificial chromosome (BAC) transgenic rats, expressing either G2019S or R1441C mutant or the wild-type forms of the entire human LRRK2 genomic locus. Our longitudinal deep-phenotyping approach allowed us to compare rats expressing mutant human LRRK2 to those with wild-type human LRRK2, and to establish whether any age-related changes in motor function were linked with progressive alterations to the nigrostriatal dopaminergic pathway. Here we report that aged LRRK2 mutant rats develop progressive motor dysfunction which is reversed by l-DOPA, and cognitive deficits, along with impaired striatal dopamine release and alterations in the firing properties of dopaminergic SNc neurons. These impairments occur in the absence of any overt neurodegeneration or molecular neuropathology within the SNc. Overall, these findings help elucidate processes of early, pre-degenerative dopaminergic dysfunction in dopamine neurons and synapses in LRRK2-dependent Parkinson's disease.To advance our understanding of the impact of LRRK2 transgenic rats were generated using previously developed BAC constructs . Three LRRK2 BAC transgenic lines were generated on a Sprague–Dawley background: one expressing human wild-type (hWT) LRRK2 and two mutant lines, expressing either the G2019S or R1441C mutant forms of the human gene. Anatomical transgene protein expression patterns were similar between lines throughout the brain . Fluorescent in situ hybridization analysis was conducted to confirm unique BAC integration sites .nstructs  consistiain Fig. , intenseSupplementary Material, Fig. S2A), subsequently confirmed by Western blot . Conversely, G2019S mutants showed a modest increase in phosphorylation at ser935.Changes in phosphorylation of LRRK2 at residues ser910/935 have been suggested to mediate the interaction of LRRK2 with 14-3-3 proteins which play an important role in cellular regulatory processes . MutatioLRRK2 rats develop motor impairment, we analysed performance on the accelerating rotarod . Compared with nTG controls at a young age (3–6 months), all transgenic lines showed no impairment on the rotarod, whereas G2019S showed an enhancement, as previously reported . The non-transgenic controls in each experimental cohort showed equivalent performance allowing us to integrate data from the two cohorts to perform additional analysis directly comparing all lines (G2019S v R1441C v hWT versus nTG). Importantly, we show that aged (18–21 months) G2019S and R1441C rats exhibited a significant age-dependent impaired performance compared with both nTG and hWT controls .Cohorts of G2019S, R1441C and non-transgenic (nTG) littermates, and of hWT and nTG littermates, were generated and underwent in-depth phenotyping. To determine whether reported ,28. At aols Fig. . We therl-DOPA treatment owing to the loss of nigrostriatal dopamine function. To investigate whether motor impairment in the rats was l-DOPA-responsive, we administered either l-DOPA or saline to aged G2019S, R1441C and nTG rats. l-DOPA reversed the rotarod performance deficits seen in both G2019S and R1441C rats . Transgenic rats did not display impaired grip strength , suggesting that motor deficits were likely not a consequence of muscle weakness, motor neuron alterations or motor plate neurotransmission that could potentially account for poor test performance. Taken together, these data suggest that LRRK2 mutations result in age- and dopamine-dependent motor impairments.Motor dysfunction in Parkinson's disease is clinically responsive to LRRK2 mutant rats exhibited similar non-motor symptoms. To evaluate cognitive ability, rat performance was assessed using the spontaneous alternation test of spatial short-term memory . Finally, to investigate gastrointestinal function, we examined stool frequency and composition; we detected no changes in G2019S, R1441C or hWT rats at either young or aged time points compared with nTG controls .The importance of non-motor symptoms of Parkinson's disease is becoming increasingly apparent. In particular, 36% of individuals with Parkinson's disease display cognitive impairment and around 40% of Parkinson's patients suffer from constipation ,31. We tm memory . No diffLRRK2 rats. To investigate this, we used fast-scan cyclic voltammetry (FCV) at carbon-fibre microelectrodes to detect evoked dopamine release and reuptake in real time in the striatum. In Parkinson's disease, SNc neurons that innervate the dorsal striatum are preferentially affected compared with ventral tegmental area neurons innervating the ventral striatum. We therefore measured evoked dopamine release in dorsal and ventral striatum in G2019S, R1441C and hWT LRRK2 rats compared with nTG controls. In dorsal striatum, mean peak [DA]o evoked by single electrical pulses were not significantly different between either G2019S or R1441C rats and nTG controls at 6 and 12 months of age . Therefore, the lower levels of evoked [DA]o in dorsal striatum of either G2019S, R1441C and hWT aged rats compared with nTG controls appear not to result from lower striatal dopamine content but rather to reduced ability to release dopamine. We examined whether LRRK2 mutations reduced the probability of dopamine release by exploring the short-term plasticity of release, a measure commonly used to infer release probability owing to their typical inverse relationship at many synapse types, including for dopamine , suggesting that the lower levels of evoked [DA]o in dorsal striatum of G2019S, R1441C and hWT aged rats compared with nTG rats were not due to deficits in initial release probability, including release regulated by cholinergic interneuron input . We additionally examined whether SNc neurons might express neuropathological markers prevalent in Parkinson's disease. Aged (18–21 month) animals were examined by immunohistochemistry for Parkinson's disease-related pathological molecular changes. No accumulation of immunoreactivity for alpha-synuclein, AT8, (pSer202/Thr205) tau or ubiquitin was seen in the SNc . Furthermore, no changes in the number of microglial cells labelled by Iba1 staining were seen in aged LRRK2 transgenic animals compared with nTG controls .To assess directly whether the behavioural changes and impaired dopamine release are a consequence of a loss of dopamine neurons in the SNc, we conducted an unbiased stereological count of TH-immunoreactive neurons in aged (18–21 month old) G2019S, R1441C and nTG control rats  anaesthetized nTG and R1441C rats . These data suggest that the human R1441C LRRK2 mutation significantly impacts on the firing patterns of SNc dopamine neurons in an age-dependent manner.Changes in the rate or pattern of SNc dopamine neuron firing can have a profound impact on the dynamics of extracellular striatal dopamine concentrations in vivo . In theosee Fig.  dependinats Fig. . Followiats Fig. A–I. We fpes Fig. J. Howevepes Fig. K. To detats Fig. B and E. ats Fig. J and K. ats Fig. L and M. LRRK2 mutations impact upon the function of dopaminergic neurons is important for elucidating the key pathophysiological changes underlying the core symptoms of Parkinson's disease. Here, we describe the generation and deep-phenotyping of novel LRRK2 BAC transgenic rat models of Parkinson's disease that express either the wild-type or R1441C or G2019S mutant forms of human LRRK2 and develop age-dependent Parkinsonian motor and non-motor symptoms. Strikingly, as seen in PD patients, motor symptoms were reversed by l-DOPA treatment, indicating that they were caused by the underlying functional alterations to the nigrostriatal dopaminergic pathway which include dysfunctional SNc dopamine neuron firing together with impaired striatal dopamine release. These alterations occur in the absence of any overt SNc neurodegeneration or pathological markers. It appears, therefore, that a reduction in dopamine neuron burst firing and dysfunctional synaptic transmission act together to reduce dopamine release and its dynamic variation in the striatum, prior to the development of molecular neuropathology or marked cell loss.Understanding how LRRK2 rat lines revealed widespread transgene expression that, although higher than endogenous levels in the rat, resemble expression patterns in the human brain . Confirmations of full gene integration, mutation presence, germline transmission and transgene integration site were performed and three lines were selected . Animals were bred in a hemizygous fashion, and animals were maintained in accordance with the UK Home Office regulations under the Animals (Scientific Procedures) Act of 1986.Rat lines were created using pronuclear injection of caesium chloride-purified BAC DNA containing the Female rats were placed on the accelerating rotarod (Ugo Basile 7700) revolving at 4 rpm facing away from the experimenter. Rotor speed was incrementally increased from 4 to 40 rpm over 300 s, and the latency at which the animal fell recorded. Animals were tested three times a day for three consecutive days, and performance was averaged for each day and collapsed across days .l-DOPA. As a control, a second cohort was given equivalent volumes of saline. Animals performed rotarod testing 60 min after l-DOPA administration. Each animal's performance was normalized to the previous day's performance.Rats were administered with 10 mg/kg benzerazide, i.p. followed 30 min later with 25 mg/kg, i.p. Animals were placed in the base of a T-maze, consisting of a start arm and two identical goal arms, surrounded by a 10 cm high wall. Each trial consisted of a sample run followed by a choice run. During the sample run, the rat was allowed a choice of one of the two goal arms. Once the animal had chosen, it was held in that goal arm for 30 s. The animal was then immediately returned to the start arm and given another free choice of either goal arm. Whether or not the animal alternated, its choice was recorded, along with the time taken for the animal to make its choice on the second run . AnimalsBehavioural data are expressed as means ± SEM. Analyses were performed using SPSS Statistics 20 (IBM).Supplementary Material, Table S1) followed by a biotinylated secondary antibody which was subsequently incubated in avidin–biotin–peroxidase complex and stained using diaminobenzidine. Stained sections were counterstained using haematoxylin, dehydrated and mounted. Protein extraction and Western analysis were performed as previously described in  and the chemiluminescent ECL+ kit . Bands were quantified using ImageJ software. Data were analysed using one-way ANOVA and Bonferroni post hoc analysis using SPSS Statistics 20 (IBM).For immunohistochemistry, animals were transcardially perfused with phosphate buffer (pH 7.4) followed by 4% paraformaldehyde. Brains were subsequently cryoprotected in 30% sucrose and sliced at 35 µm (or 50 µm for stereology) using a freezing microtome. For peroxidase-immunohistochemistry, sections were incubated overnight with primary antibodies . Cells were counted using a Zeiss Imager M2 light microscope at 40× magnification using a randomly placed counting frame of 50 × 50 µm on a sample grid of 160 × 160 µm. A 22 µm optical dissector with ± 2 µm guard zones was used. Subregions of the SNc  were determined for counting using the Paxinos and Watson Rat Brain Atlas  and a Millar Voltammeter . The scanning voltage was a triangular waveform (−0.7 to +1.3 V range versus Ag/AgCl) at a scan rate of 800 V/s and sampling frequency of 8 Hz. Electrodes were positioned in brain slices to a depth of 100 μm. Amine release was evoked locally by a surface, concentric bipolar Pt/Ir electrode  placed ∼150 μm away from the carbon-fibre microelectrode. Stimulus pulses were generated out-of-phase with FCV scans and were applied at the lowest current that generated maximal dopamine release with a single stimulus pulse in wild-type animals . [DA]o was monitored and quantified in dorsal and ventral striatum. The evoked current signal was confirmed as dopamine by comparing the peak potentials for oxidation and reduction currents with those of dopamine in calibration media . Electrodes were calibrated in 1–2 µM dopamine following experiments in all experimental media. FCV experiments assessed [DA]o evoked by discrete stimuli in the dorsal striatum  and ventral striatum . Recording sites classed as dorsal were from dorsomedial and dorsolateral striatum, whereas those classed as ventral were from ventromedial striatum and nucleus accumbens core  were prepared using a vibratome (Leica VT 1200S) in ice-cold HEPES-buffered artificial cerebrospinal fluid containing: 120 mm NaCl, 5 meviously ,51–53. [00 µm wern, is the number of observations. Anaesthesia was induced with 4% isofluorane , and maintained with urethane , with ketamine  and xylazine  supplements given as required. Anaesthesia was monitored during experiments using the electrocorticogram (see below) and by testing reflexes to a cutaneous pinch or gentle corneal stimulation. Wound margins were infiltrated with the local anaesthetic bubivacaine  and corneal dehydration was prevented with application of Hypromellose eye drops  and eye ointment . Protocols for electrophysiology were similar to those previously described (in situ resistance 10–25 MΩ) filled with saline solution (0.5 M NaCl) and Neurobiotin (Nb) . Electrode signals were amplified (10×) through the active bridge circuitry of an Axoprobe-1A amplifier (Molecular Devices Corp). Single-units were recorded after alternating current coupling, amplification , and standard bandpass filtering . A Humbug (Quest Scientific) was used to eliminate mains noise at 50 Hz. Spikes were several millivolts in amplitude and showed an initial positive deflection. To avoid possible sampling bias, generous online criteria were applied to guide recordings (spike duration threshold-to-trough for bandpass-filtered spikes of >0.8 ms and firing rates < 20 Hz)  and male 16- to 22-months-old rats  in accordance with the Animals (Scientific Procedures) Act of 1986 (United Kingdom). All experiments and subsequent analyses were performed blind to genotype. The sample size, escribed : Animalsescribed  and was < 20 Hz) .Following recording, single neurons were labelled with Nb using the juxtacellular method ,55 to alTissue processing was similar to that previously used to identify recorded and labelled cells in mice : fixed bn = 82). Putative single-unit activity was isolated using template matching, principal component analysis and supervised clustering within Spike2. Firing regularity was calculated using CV2 (P < 0.05 to reject). If data failed normality tests, a Mann–Whitney U-test was used . Significance for all statistical tests was set at P < 0.05.All biopotentials were digitized online using a Power 1401 analogue-digital converter (Cambridge Electronic Design) and acquired using Spike2 software . Because the firing pattern of dopaminergic neurons within the SNc can vary with the brain state , only unsing CV2  which cosing CV2 , a statit-test, one/two-way ANOVA with Bonferroni or Tukey HSD post hoc tests, t-test, Mann–Whitney). Where appropriate, data were transformed (square-rooted) so as to comply with parametric testing, where this was done the data has been presented as non-transformed for the ease of the reader. Separate cohorts of G2019S, R1441C and non-transgenic littermates, and of hWT and non-transgenic littermates, were generated and underwent in-depth phenotyping. Where transgenic animals showed a significant difference from non-transgenic littermate controls in performance on the rotarod and in the spontaneous alternation tests the data were combined, and the performance of the three transgenic lines (G2019S v R1441C v hWT) could be directly compared, as the respective nTG control groups did not differ statistically from each other. For completeness, the original non-combined data are represented in Supplementary Material, Figure S3.Data are expressed as mean ± SEM. Appropriate tests are used , and the Medical Research Council (MRC) UK . M.S. and R.W. hold a Joan Pitts-Tucker/Moritz studentship; A.K. and D.P. hold MRC studentships and D.M.B. held a Wellcome Trust Senior Research Fellowship. Funding to pay the Open Access publication charges for this article was provided by the Charity Open Access Fund.The work was supported by M.S., J.A.-A., D.P., A.K., S.T., N.C.-R., J.P.B., P.J.M., S.J.C., P.D.D., and R.W.-M. designed research; M.S., J.A.-A., D.P., A.K., R.E., S.T., T.D., N.C.-R., K.B., R.W., M.C. and P.D.D. performed research; M.S., D.P., A.K., S.T., N.C.-R., R.W., D.M.B. and P.D.D. analysed data; M.S., S.T., N.C.-R., P.D.D. and R.W.-M. wrote the paper.


Escherichia coli (E. coli). The lysis gene is regulated by a synthetic genetic lysis circuit, using an inducer-regulated promoter-RBS component. To make the design more easily, it is necessary to provide a systematic approach for a genetic lysis circuit to achieve control of cell population density.Cell population control allows for the maintenance of a specific cell population density. In this study, we use lysis gene BBa_K117000 from the Registry of Standard Biological Parts, formed by MIT, to lyse Firstly, the lytic ability of the constructed genetic lysis circuit is described by the relationship between the promoter-RBS components and inducer concentration in a steady state model. Then, three types of promoter-RBS libraries are established. Finally, according to design specifications, a systematic design approach is proposed to provide synthetic biologists with a prescribed I/O response by selecting proper promoter-RBS component set in combination with suitable inducer concentrations, within a feasible range.This study provides an important systematic design method for the development of next-generation synthetic gene circuits, from component library construction to genetic circuit assembly. In future, when libraries are more complete, more precise cell density control can be achieved. Bacillus subtilis delays sporulation under nutrient-limited conditions by killing non-sporulating siblings and feeding on the dead cells to support spore formation [Cell population control is a method of regulating cell density to maintain a self-sustaining population. Self-regulating mechanisms of cell population control have existed in nature for a long time. For example, the spore-forming bacterium ormation . Colicinormation . Recentlormation . Howevere or t can be used to the disrupt E. coli cells [e and t, respectively. Gene e encodes a lysozyme, Gpe; gene t encodes a holin, Gpt. The expression of gene e weakens E. coli cell wall but does not lead to cell disruption, while the expression of gene t enables to induce cell lysis. Another example of a lytic protein is colicin E7 (ColE7), which is encoded by E. coli. Expression of ColE7 is regulated by an SOS response operon. The SOS response operon is composed of the ceaE7, ceiE7 and celE7 genes, the products of which are ColE7, ImE7 and LysE7, respectively [Naturally occurring lytic systems have the ability to trigger host cell lysis with specific proteins under certain circumstances, such as in the presence of antibiotics or competitors, or under conditions of amino-acid starvation. Some species of bacteria and bacteriophage have lytic protein that induces cell lysis. For example, expression of cloned T4 phage genes li cells . Lysis bectively . ColE7 cectively .E. coli that have antibiotic-like activity against closely related bacteria [E. coli. In this study, lysis protein expression level in the genetic lysis circuit relies on tunable genetic components and inducer concentrations. The degree of cell lysis could therefore be fine-tuned by changing external inducer signals. Different inducer concentrations could result in different fates of the cells, for example severe death, modulated death, or slow growth. To make the design more easily, the lytic ability of the constructed genetic lysis circuit is described by the relationship between the promoter-RBS components and inducer concentrations in a steady state model. According to user-oriented specifications, the genetic lysis circuit can be constructed via selecting adequate promoter-RBS components in combination with a feasible range of inducer concentrations. In general, it requires long computation times when component libraries become large. Hence, a genetic algorithm (GA) search method is proposed to save time in evaluating and selecting promoter-RBS components.Lysis protein is able to activate the outer membrane phospholipase A (OMPLA), which allows colicin to cross the cell envelope and enter into the medium. Colicins are plasmid-encoded bacteriocins produced by bacteria ,13. RelebcsA, bcsB, bcsC, and bcsD is required for bacterial cellulose synthesis (bcs) in Acetobacter xylinum [This study provides an important systematic design method for the development of next-generation synthetic biology, from component library construction to genetic circuit assembly. When libraries are more complete, more precise cell density control for genetic lysis circuit can be achieved. The mechanism of cell lysis can be used to release useful macromolecules that cannot pass through cell membranes ,14. For  xylinum . The expThe contributions of this paper are threefold: (1) Based on promoter-RBS kinetic strengths, we establish three kinds of promoter-RBS libraries. (2) Inducible promoter-RBS components are used to construct genetic lysis circuits with different lytic abilities for cell population control. (3) The proposed GA-based systematic searching method could provide synthetic biologists with a useful tool to design synthetic genetic lysis circuits.I1 and I2. In Figure xr1. The protein xr1represses the downstream promoter and reduces expression of the lysis gene. The inducer I1 can bind to the repressor protein and prevent binding to the promoter operon, enhancing expression of the lysis gene. In Figure xa1. The protein xa1, however, needs to form a complex with the inducer I2. The complex constitutes a quorum sensing mechanism. When this complex accumulates, it activates the downstream promoter and enhances expression of the lysis gene.Two type of synthetic genetic lysis circuits are shown in Figure Before we introduce the dynamic model of a genetic lysis circuit, a normal equation for cell growth, without the lysis protein, is as follows:N and max Ndenote cell population density (O.D. 600) and maximum cell population density, respectively, and k denotes the dilution rate due to cell growth. Since our study utilizes the lysis protein to regulate cell population density, the relationship between cell density and the concentration of the lysis protein can be described in the following equation:where 1 xand N γdenote the concentration of the lysis protein and the lysis rate of the lysis protein, respectively. Under normal growth conditions, cells do not suffer from the toxicity of the lysis protein. We used the endogenous gene (BBa_K117000) encoded in E. coli to control cell population density. The lysis protein can activate OMPLA to cause cell lysis and reduce cell density [1 xis the negative regulator of cell population density. Because lysis ability is related to the concentration of lysis protein 1 xand the toxicity N γof the lysis protein, we construct a dynamic model of the genetic lysis circuit to regulate the concentration of lysis protein 1x, and thus lysis ability.where  density ,13. FromP, in which u Pand 1 Pdenote the maximum and minimum promoter-RBS strengths, respectively, TF denotes transcription factor concentration, and I denotes inducer concentration. This function describes the biochemical aspect of the transcription and translation process. The details of the function  can be found in Additional file To construct the dynamic model, promoter-RBS regulation must be introduced. We first define the promoter-RBS regulation function PPu, P, TF, I, PPu, P, TF, I, i, j) denote the th iconstitutive promoter-RBS component and the th jrepressor-regulated promoter-RBS component, respectively. Pc1  denotes the promoter-RBS regulation activity of the first stage of the constitutive promoter-RBS components. u,i Pdenotes the maximum promoter-RBS strength of the th iconstitutive promoter-RBS component. Pr2 denotes the promoter-RBS regulation activity of the second stage of the repressor-regulated components. u,j Pand i,j Pdenote the maximum and minimum promoter-RBS strengths of the th jrepressor-regulated promoter-RBS component, respectively. I1 denotes the concentration, and xr1 denotes the concentration of the repressor. Kr2 and nr2 denote the binding affinity and binding cooperativity between the repressor KI1 denotes the dissociation rate between the inducer I1 and the repressor xr1. N γis the lysis rate of the lysis protein. ω1(t) and ω2(t) denote cellular noise in the transcriptional and translational processes, respectively. Finally, ω3(t) denotes cellular noise in the cell population density.where  and the protein degradation rate γxr1, in combination with the dilution rate k. The repressor protein xr1 binds to the second stage of repressor-regulated components and reduces the regulation activity Pr2 . The inducer I1 can remove the inhibitory effect of the repressor and increase the regulation activity Pr2 . Similarly, the change in concentration of lysis protein xl2 is due to the difference between the protein generation rate Pr2  and the protein degradation rate γxl2, in combination with the dilution rate k. Cell population density is regulated by the concentration of lysis protein xl2. Lytic ability is therefore controlled by the regulation activity Pr2, and the four regulated factors Pu,j, Pi,j, xr1, and I1 can be used to control cell population density by selecting appropriate promoter-RBS components and inducer concentrations.From equation (3), the change in concentration of repressor protein The only difference between Figures i, m) denote the th iconstitutive promoter-RBS component and the th mactivator-regulated promoter-RBS component, respectively. I2 denotes the concentration of the inducer, xa1 denotes the concentration of the activator protein, and Ka2 and na2 denote the binding affinity and the binding cooperativity between activator KI2 denotes the dissociation rate between inducer I2 and activator xa1.where  and (4) are equal to zero. The steady-state concentrations for the genetic lysis circuit with repressor-regulated promoter-RBS component in Figure i, i =v1, 2, with a zero mean and variance of iσ2, denotes cellular noise for both the transcriptional and translational gene expression processes in the steady state. v3 denotes cellular noise in cell population density in the steady state. In (5) and (6), the steady state population density SS Nchanges depending on inducer concentration, constitutive promoter-RBS components, repressor-regulated components, and activator-regulated promoter-RBS components, i.e. i = 1,...,C, j = 1,...,R or i = 1,...,C, m = 1,...,A. In this study, we select values for these components from promoter-RBS libraries  and (6) must be taken into consideration. For example, the kinetic parameters of the promoter-RBS components including the processes of transcription and translation, the degradation rates of regulatory proteins, dilution rates of the cells, and the lysis rates of the lysis proteins, are all stochastically uncertain volution . These aPu,i, ΔPu,j, ΔPl,j, ΔPu,m, ΔPl,m, Δγxr1 Δγxa1, Δγxl2, ΔγN, and Δk denote the standard deviations of the corresponding stochastic parameters, and in(t), i = 1,2,3 denote Gaussian noise, have zero mean and unit variance, and account for random fluctuation sources. Thus, ΔPu,i, ΔPu,j, ΔPl,j, ΔPu,m, ΔPl,m, Δγxr1, Δγxa1, Δγxl2, ΔγN, and Δk denote the deterministic aspects of parameter variation, and ni(t), i = 1,2,3 denote the random fluctuation sources. The kinetic parameters in the steady state model in equations (5) and (6) are replaced by the parameter perturbations shown in (7) for robust design of the genetic circuit. These parameter fluctuations must be considered in the design procedure so that the synthetic genetic circuit can tolerate fluctuations in vivo [where Δ in vivo .The purpose of our design is to construct a genetic lysis circuit by selecting a set of suitable promoter-RBS components from the corresponding libraries in combination with a feasible range of inducer concentrations, to achieve optimal tracking of a desired I/O response. To achieve this, the following design specifications are needed:refN(I) of the genetic lysis circuit.- Desired I/O response - Well-characterized promoter-RBS component libraries and a feasible range of inducer concentrations.in vivo.- Standard derivations of parameter fluctuations and environmental disturbances to be tolerated SS Nin equations (5) and (6) and the desired reference steady state cell population density ref Nas follows:- A cost function between the steady state cell population density S denotes the set of promoter-RBS components i and j (or i and m) selected from the corresponding component libraries, i.e. S =  for constitutive promoter-RBS components and repressor-regulated promoter-RBS components in (5), and S =  for constitutive promoter-RBS components and activator-regulated promoter-RBS components in (6). The inducer concentration I for I1 is S =  and I2 is S = .where refN(I) under intrinsic parameter fluctuations and environmental disturbances. Although the cost function can be minimized by traditional conventional search methods, the combination of promoter-RBS components with inducer concentrations to minimize J will require long computation times as well as trial-and-error experimentation when component libraries become large. Hence, the more effective and efficient genetic algorithm (GA) search method is proposed to save time in evaluating and selecting promoter-RBS components. Since genetic algorithm searches for the optimal solution, on basis of the maximum fitness, which is inversely proportional to the minimum error in (8), we need to define the fitness function as followsIf the cost function in equation (8) is minimized by choosing the most appropriate set of components in combination with a feasible range of inducer concentrations under design specifications, the cell population density of a engineered genetic lysis circuit will optimally match the specified steady state cell population density Therefore,E. coli.- Choose a species for cell population density control. In this study, we used - Provide user-defined design specifications for the genetic lysis circuit.S of promoter-RBS components and inducer concentrations.- Select an initial set F in equation (9) for each set S of promoter-RBS components and inducer concentrations.- Calculate the fitness function S using GA operators such as reproduction, crossover, and mutation.- Create an offspring set - Make copies of possible solutions, on basis of their fitness.- Swap values between two possible solutions.- Randomly alter the value in a possible solution.S obtained by natural selection. Stop when the design goal is achieved or an acceptable solution is obtained. Otherwise, create the next generation and return to step 5.- Calculate the cost value of the new set i Cfrom Additional file m Afrom Additional file i Cfor producing regulatory protein, LuxR. The second stage involves an activator-regulated promoter-RBS component m Afor driving the expression of the lysis protein. The external inducer AHL is used to regulate the lysis activity. The desired population response refN(I) to different inducer concentrations described as follows:For the convenience of description and explanation, as shown in Figure in vivo are given byNote that the standard deviations of parameter fluctuations that are supposed to be tolerated v1 and v2, for transcription and translation processes, and v3 for cell population density, are all Gaussian, with zero mean and unit variance. In order to efficiently solve the constrained optimal matching design problem of the genetic lysis circuit, a GA-based library search method is employed to search a set S from corresponding libraries in Additional file as well as the environmental noise parameters C6 and L2A. The desired response is shown in Figure Then, to minimize the cost function 13), the adequate promoter-RBS components from the corresponding libraries are found to be , the adeIn this study, we focus on the design of synthetic genetic lysis circuit to achieve density control of cell population. A mathematical model is introduced to describe the dynamic and steady state regulatory behavior of the genetic lysis circuit. From the steady state mathematical models in (5) or (6), we find that if we want to control cell population density, we need to control lysis ability, which is related to transcriptional and translational processes. The promoter allows the RNA-polymerase molecules to latch onto a DNA strand and initialize the transcription of a downstream gene into mRNA, and the RBS allows the ribosome to bind and translate the mRNA. Hence, in this study, the promoter combined with the RBS is viewed as a genetic component for regulating lytic ability.For convenient measurement of promoter-RBS components, we use GFP as a reporter to identify characterizations of promoter-RBS components. We can therefore use the parameters identified in Additional file E. coli. Through the control of different expression levels of repressor-regulated or activator-regulated promoter-RBS components, a simple genetic lysis circuit can regulate cell death. This bottom-up design approach can potentially be extended to other complicated processes involving programmed cell death, which could help us to understand systematic phenomena that have always existed in nature.The precise control of cell population density with protein release is useful in medicine to cure disease, becauseThe construction procedure for cell population density control is very important for engineering a more complex synthetic genetic lysis circuit. We characterize the genetic circuit and provide the desired cell population density beforehand. Using GA, we search for an appropriate set of promoter-RBS components in combinations with a feasible range of inducer concentrations to achieve the desired cell population density. The GA provides a useful tool in the construction of genetic lysis circuit for control of cell population density. In future, when libraries are more complete, more effective and efficient design methods for synthetic genetic lysis circuits may aid developments in drug discovery, metabolic control, and therapeutic treatment.In this study, we engineer a genetic lysis circuit to control cell population density. Inducible promoter-RBS components are used to construct genetic lysis circuits with different lytic abilities for cell population control. Moreover, we provide four design specifications for cell population density control, allowing designers to select proper promoter-RBS components from libraries for the synthetic genetic lysis circuits. The design problem can be transformed by selecting proper promoter-RBS components in combination with a feasible range of inducer concentrations to achieve a desired I/O response. The proposed GA-based systematic searching methodology could provide synthetic biologists with a useful tool to design synthetic genetic lysis circuits. From the experimental results, we find that the data are close to the prescribed cell densities. Therefore, we believe that the proposed user-oriented design method for cell population density control will provide a useful guide in the rapidly growing field of synthetic biology.The authors declare that they have no competing interests.CYH developed the method, performed the analysis, evaluated the results, and wrote the manuscript. TCY participated in the method development and helped to draft the manuscript. LJL and RHH performed the experiments. BSC conceived of the study, provided essential guidance and revised the manuscript. All authors read and approved the final manuscript.Supplementary appendixClick here for file


In this study, neostigmine-loaded electrospun nanofibers were prepared and then their efficacy and duration of analgesic action were studied after epidural administration in rats by repeated tail flick and formalin tests.The neostigmine poly vinyl alcohol (PVA) nanofibers were fabricated by electrospinning methods. The nanofibers (1 mg) were injected into the lumbar epidural space (L5-L6) of rats (n = 6). Cerebrospinal fluid samples of rats were collected 1, 5 and 24 hours after injection and then were sampled once weekly for 4 weeks. Free-neostigmine concentration was measured in the samples spectrophotometrically. Rat nociceptive responses were evaluated by repeated tail-flick and formalin tests for 5 weeks after the nanofibers (1 mg) injection. Locomotor activity of rats was measured in the open-field at the same period.The cerebrospinal fluid concentration of free neostigmine reached 5 μg/ml five hours after injection and remained constant until the end of the experiments. The tail-flick latency of treated rats was significantly (p < 0.01) increased and remained constant up to 4 weeks. Pain scores of the rats in both phases of formalin test were significantly (p < 0.01) reduced during the same periods, Epidural injection of the nanofibers had no effect on locomotor activity of rats in an open-field.Our results indicate that the neostigmine nanofibers can provide sustained release of neostigmine for induction of prolonged analgesia after epidural administration. High tissue distribution and penetration of the nanofibers in dorsal horn can increase thermal and chemical analgesia duration without altering locomotor activity in rats for 4 weeks. Recently, researchers have been employing new techniques to improve both the efficacy and duration of analgesic effect of some drugs. Epidural administration of neostigmine could reduce pain in patients with uncontrolled pain . It has in-vitro evaluation of neostigmine release from the nanofibers; (3) assessment of free-neostigmine concentration in the cerebrospinal fluid of rats after the nanofiber injection for 4 weeks; and (4) evaluation of the efficacy and duration of analgesia in thermal and chemical pain model by consecutive tail-flick and formalin test during 5 weeks after the injection of nanofibers.The aims of present study were: (1) fabrication of neostigmine-loaded poly vinyl alcohol (PVA) nanofibers by electrospinning methods; (2) Neostigmine methylsulfate was obtained as a gift sample from the laboratory of Dr. Sayyed Omid Ranaei Syadat, Tehran, Iran. In our experiment, all chemicals were of analytical grade purchased from Sigma-Aldrich.The neostigmine-loaded poly vinyl alcohol nanofibers were prepared according to the procedure of Arecchi et al. . BrieflyThe measurement of AChE inhibitory activity of neostigmine released from the nanofibers was carried out in a vial using spectrophotometric method proposed by Ellman et al. . The perTo determine the encapsulation efficiency, 10 mg of the neostigmine-loaded nanofibers were stored in 1 ml of PBS (pH 7.4). The solution was incubated for 1 min at 37°C. At 5 min intervals, a sample was withdrawn and centrifuged at 16,000 g for 10 min. The precipitated samples were taken and resuspended in 10 ml fresh release medium to keep a complete sink condition and placed back to the shaker. The supernatant solution was retained for HPLC analysis. A mixture of acetonitrile and ammonium acetate (75:25 v/v) was added to the solution after the PBS had been removed. The resulting solution was analyzed using HPLC, in which a C-18 column was used and the mobile phase was delivered at a rate of 1 ml/min. One hundred microliters of sample was injected by an auto-sampler and the column effluent was detected at 248 nm.The surface morphology of the nanofibers was observed by scanning electron microscopy . The free poly vinyl alcohol and neostigmine-loaded nanofibers were placed on a stage and sputter-coated with carbon.Ad libitum. The present study followed the ethical guidelines for investigation of experimental pain in conscious animals as well as the Institutional Animal Ethical Committee of Shahed University, formed under Committee for Purpose of Control and Supervision of Experiments on Animals , approved by the pharmacologic protocols [Adult male Sprague–Dawley rats (200–250 g) were purchased from Razi Institute of Iran. The rats were kept at 22°C, 12 hour night/day cycle, and received tap water and food The experimental groups consisted of six rats. Rats were divided into: (a) control group in which, the rats received epidural injection of 5 μl normal saline solution; (b) sham group in which, the rats were treated with epidural injection of 1 mg poly vinyl alcohol nanofibers and flushed by 5 μl saline solution; (c) neostigmine-loaded nanofiber group in which, the rats were treated with epidural injection of neostigmine-loaded nanofibers (1 mg) and flushed by 5 μl saline solution. Epidural injection was done at L5-L6 intervertebral space.Rats were anesthetized briefly with ether and shaved at the lower back, then placed in the prone position with lower back elevated and flexed ventrally. A lumbar puncture was performed at L5–L6 intervertebral space, perpendicular to the skin, using a 30-gauge needle attached to a 50-μl Hamilton syringe. A catheter of a PE10 polyethylene tube, which was pre-filled with 1 mg neostigmine-loaded nanofibers isolated from 5 μl of saline using a small air bubble, was placed into the needle and advanced 4 cm from the tip of the needle up to the lumber enlargement, which was confirmed by a tail-twitch. The nanofibers were slowly injected and flushed with saline. Three minutes later, the catheter and the needle were respectively removed.Pilot experiments were performed to evaluate the spread of injected solution in the spinal subarachnoid space. Using the same technique and injection volumes described above, the rats received spinal injections of 5 μl methylene blue 1 mg/ml solution. The area of spread of the methylene blue was examined upon animal necropsy 10 min after intrathecal injections. Besides, all intrathecal solutions contained 5% methylene blue and the included data were only from the animals in which intrathecal placement was confirmed postmortem.CSF samples were collected based on procedures described by Haddadi et al. Rats anesthetized by i.p. injection of a mixture of ketamine (80 mg/kg) and xylazine (10 mg/kg) . Then, eNeostigmine concentration in CSF sample of rats (n = 6) was estimated by ultraviolet visible spectrophotometer at 261 nm  [In the present study, two methods were simultaneously used for evaluating anesthetic effect of a single dose of neostigmine-loaded nanofibers against thermal and chemical types of nociceptive stimuli after epidural injection. Some scientists have claimed that the analgesic effect due to the activation of cholinergic mechanisms also depends on the experimental pain model that is utilized for its evaluation .st, 15th and 21st days after epidural injection based on the methods proposed by Kríz et al. [The repeated tail-flick method was used for measuring the analgesic responses of rats after epidural treatment with the neostigmine-loaded nanofibers to a high intensity thermal nociceptive stimulus. Some researchers have also suggested that changes in tail-flick latency may be interpreted in terms of central sensitization and that the repeated tail-flick latency might be considered as a useful marker of chronic nociception . Thus, tz et al. . The aveAM and 5:00 PM. Pain scores were expressed as mean ± SEM. A probability of p < 0.01 was considered significant.The formalin test is usually used for evaluation of anti-nociceptive drugs which are administrated intrathecally against the high intensity of chemical pain stimulus. In order to avoid interaction of both techniques’ effects on the same animals, it is better to evaluate the formalin test at least 7 days after the tail-flick test, because the tail-flick test has no impact on the formalin test results after this period . TherforLocomotor activity was measured using an open field test. The rats were individually placed in one corner of the open field (100 × 100 × 48 cm). Movement of each rat in the field during 15 min of testing session was recorded. After 15 min, the rat was removed to the home cage, and the open field area was cleaned. The total distance and the average velocity of each rat in the field were recorded.The results were expressed as mean ± S.E.M., and statistical significance was evaluated by a two-way repeated measure analysis of variance (ANOVA) followed by Bonferroni tests. The statistical significance criterion  was 0.05. All data calculations and statistical analyses were done by using Prism version 5 .According to the SEM micrograph shown in Figure The percent of AChE inhibition changed with proportions of PVC Figure A and theThe spread of methylene blue dye into the epidural space indicated that the dye was only distributed in lumbar segments of rat spinal cord Figure .Figure 4The time course of neostigmine concentrations in CSF is shown in Figure The epidural administration of neostigmine-loaded nanofibers decreased the pain score significantly (p < 0.001) in early Figure A and latThe duration of analgesia after epidural injection of neostigmine-loaded nanofibers is shown in Figure The mean traveling distance Figure A and theThe results of the present investigation revealed that neostigmine was successfully loaded into the poly vinyl alcohol nanofibers using the electrospinning technique. The SEM images confirmed the incorporation of neostigmine in the nanofibers. As seen in Figure The in vitro study of AChE inhibition after injection of the nanofibers indicated that the neostigmine released from the nanofibers can inhibit AChE effectively and the loading of neostigmine within the nanofibers did not compromise the inherent of AChE inhibitory activity. The results of enzyme activity assay also indicated that the change in the ratio of PVA- neostigmine can influence the amount of neostigmine release and percent of AChE inhibition. Measurement of neostigmine concentrations in cerebrospinal fluid (CSF) has suggested that the profile of the neostigmine release from the loaded nanofibers follows a biphasic pattern characterized by an initial fast release during 5 hours and following sustained release phase. A similar biphasic behavior has also been reported for ethyl cellulose nanofibers fabricated by using electrospinning process . This foThe results of the present study indicated that the thermal pain threshold was increased in rats after single epidural injection of the neostigmine-loaded nanofibers and persisted for as long as 28 days. Consecutive formalin test in rats also showed that the pain scores decreased in both phases and remained stable up to 35 days after injection. The early phase response of the formalin test was considered to be the result of direct effects of formalin on nociceptive fibers. It may be modulated by cholinergic spinal inhibitory interneurons . The latThe high sensitivity of tail flick technique for measurement of pain threshold after manipulation of spinal cholinergic system has been reported . In addiIn support of the present findings it can be said that after being release from nanofibers, the free neostigmine increased the level of endogenous acetylcholine at dorsal horn of spinal cord. Following mechanisms have been proposed to explain the anti-nociception action of acetylcholine at the dorsal horn level. It is shown that acetylcholinesterase inhibition increased acetylcholine level at spinal cord and then it caused (i) the activation of presynaptic nicotinic acetylcholine receptors and decrease in glutamate release from C-fiber terminals in the dorsal horn ; (ii) thIn addition, loading of drugs in nanostructures increased its tissue penetration power , which pComparison of the present findings with previous results ,35 showeIn spite of the free neostigmine side effects on locomotor activity after epidural administration in human , injectiIn this study, electrospun polyvinyl alcohol nanofibers were used as a controlled release matrix for the incorporation of neostigmine. The findings suggested that the nanofibers made from poly vinyl alcohol can easily be loaded with neostigmine. The SEM image confirmed loading of drug in nanofibers. The lumbar epidural administration of the nanofibers can reduce acute and chronic thermal and chemical pain in rats for 5 weeks. Also, its application had no significant effect on locomotor activity of rats.


We have developed a mixture of enzymes and chemicals that completely lyse cyanobacteria. Since the treatment involves only readily-available chemicals and simple proteins that degrade the components of the cyanobacterial cell wall, it can easily be used in high-throughput applications requiring lysis for subsequent intracellular measurements. Our lysis technique consistently enables complete lysis of several different cyanobacterial strains, and we demonstrated that DNA, mRNA, and proteins are preserved in the lysates. Chemical lysis can be superior to existing techniques because of its convenience, reliability, and amenability to a variety of downstream applications.The online version of this article (doi:10.1186/s13036-015-0007-y) contains supplementary material, which is available to authorized users. E. coli [S. cerivisiae [Significant efforts have been directed towards the fundamental goal of using photosynthesis to sustainably produce chemicals and fuels from sunlight and water, usually with either cyanobacteria or algae as hosts . As the E. coli  and 3.6 rivisiae .We believe high-throughput genetic engineering of cyanobacteria will be essential to overcome these limitations and enable the use of photosynthesis to sustainably synthesize chemicals. Applications for high-throughput genetic approaches include screening large libraries of parts  to optimSynechocystis sp. PCC 6803 under the control of a nickel-inducible promoter [Cell lysis to enable intracellular measurements is a fundamental requirement in the strain engineering cycle. It is particularly challenging in cyanobacteria compared to traditional hosts. A recent assessment of several existing methods for cyanobacterial lysis demonstrated effective lysis only by using low-throughput methods such as sonication, mechanical disruption, or lyophilization . A contrpromoter , but thiE. coli and many other commonly engineered organisms. The cyanobacterial cell wall contains a thicker and more highly crosslinked peptidoglycan layer [E. coli have a surface layer (S-layer) composed of polymerized proteins and an exopolysaccharide coating [S-layer of Synechocystis, one of the most widely-used model cyanobacteria, has only recently been characterized in detail [The major obstacle to lysis is the resiliance of the cell wall, which is thicker and more complex in cyanobacteria than in an layer , and cya coating  Fig. 1)E. coli an detail .Fig. 1MiWe sought to develop a simple, one-step chemical process that would degrade each of these barriers systematically. Some reagents for degrading cell wall components are well-established, such as lysozyme for peptidoglycan and detergents to permeabilize membranes. However, since other components of the cyanobacterial cell wall have not been well characterized, we tested a variety of other reagents to ensure all the layers of the cell wall could be breached. Here, we describe the cloning and testing of a novel lysozyme from a cyanobacteria-specific bacteriophage and the development of a chemical treatment to fully lyse cyanobacteria in a high-throughput manner.E. coli.We first tested a lysozyme from a cyanobacteria-specific phage  for its E. coli. Lysis was quantified by measuring the absorbance at 660 nm of chlorophyll released from the cells during the reaction; the “extent of lysis” is plotted in terms of raw absorbance units measured in the supernatant after centrifugation.We initially sought to optimize reaction conditions for cyanobacterial lysis. In these experiments, we compared a chemical lysis process using cyanophage lysozyme to a mechanical lysis procedure using vortexed glass beads as the best established procedure for cyanobacterial lysis. We tested a range of temperatures (4–60 °C), reaction pH values (5.5–9.2), and reaction times (20–180 min). In the initial tests, to achieve any lysis, we had to complement the lysozymes with BugBuster, a commercial lysis reagent which we have previously used with A treatment with lysozyme and BugBuster at 30–42 °C and pH 6–8 for 90 min achieved the best results, although it did not enable complete lysis propanesulfonate (SB3-14) to permeabilize membranes. These detergents were previously found to be particularly beneficial for cell lysis [In addition to lysozyme, we tested cellulases (to break down exopolysaccharide), EDTA (to destabilize the outer membranes), DTT , spermine (which was previously shown to improve the activity of T4 phage lysozyme ), and thll lysis . Furthernate SB3-4 to permSynechocystis  analysis to optimize the concentrations of these four reagents Fig.  and poteSince the requirement for DTT at such a high concentration was particularly interesting, we titrated it separately while keeping the concentrations of the other components constant Fig. . This coSynechococcus sp. PCC 7942, another widely-used model strain, and Synechococcus JA-2-3B′a, a strain isolated from a Yellowstone hot spring [To show the utility of our procedure with additional strains of cyanobacteria, we tested lysis of t spring  Fig. 4)Synechoco+ reductase as an example enzyme, and demonstrated that its activity is preserved in our lysate using a cytochrome c reduction assay [We demonstrated the biological utility of lysates produced with our chemical cocktail in several ways. It is important that a lysis procedure preserve the activity of enzymes in the lysate. We chose ferredoxin-NADPon assay   with β-Mercaptoethanol  and TCEP (a stronger reducing agent than DTT). β-Mercaptoethanol was essentially as effective as DTT. TCEP also effectively contributed to cyanobacterial lysis, but the lysates had a red color instead of the yellow-green color normally seen; this decreased the absorbance measured at 660 nm and suggests that TCEP may reduce other molecules in the lysate, perhaps the pigments , DNA amplification by PCR, and isolation and reverse transcription of mRNA. We quantified lysis by measuring the release of pigments into the lysate; this necessarily means that the pigments were not damaged by the lysis cocktail. For proteins in particular, adsorption onto the large surface area presented by glass beads can be a problem, so a chemical procedure could provide a significant advantage for protein analysis. We note a potential limitation of our procedure in that the high concentration of DTT could break disulfide bonds in proteins.At the scales we have used , we found that chemical lysis was significantly more effective than mechanical disruption with beads. We believe this is because mechanical disruption, especially for cells with such a strong cell wall, requires tremendous force often only provided by specialized equipment such as a BeadBeater homogenizer.We examined a fundamental operation in the strain engineering cycle, cell lysis, from the perspective of the unique cyanobacterial cell wall. As a result, we developed a chemical treatment that fully lyses several strains of cyanobacteria at physiologically relevant conditions and does so more effectively than mechanical disruption with glass beads.Our optimized cocktail consists of T4 lysozyme at 10 μg/mL, the detergents C7Bz0 at 0.2 % w/v and SB3-14 at 2 % w/v, spermine at 400 μM, and DTT at 200 mM. This reliably enabled full lysis of three different cyanobacterial strains.Our lysis procedure uses only chemical components, making it easily adaptible to high-throughput applications, and preserves genomic DNA, mRNA, and enzyme activity for further analysis. We believe this will expand the scope of intracellular measurements that are feasible in cyanobacteria.E. coli strain DH5α, and proteins were expressed in E. coli strain BL-21 (DE3). Plasmids for in vivo expression use a pET21b backbone (Novagen), and plasmids for expression by cell-free protein synthesis use a pY71 backbone [T7 and the ribosome-binding site to allow for modification of the region coding for the 5′ end of the mRNA. In all constructs, the sequence of this region, starting 25 bp upstream of the RBS and extending through the first 15 bp of the coding sequence, was optimized for the mRNA to have a folding energy ΔGf > −1.5 kcal/mol  to minimize inhibition of translation initiation by 5′ secondary structure. Table DNA fragments were joined by Gibson assembly  and propbackbone  modifiedin vivo from BL21 (DE3) strains using IPTG induction. Briefly, 1 L cultures in terrific broth (Invitrogen) supplemented with ampicillin at 100 μg/mL were grown at 37 °C to OD ~1.5 and induced with IPTG at 100 μM. At this point, the temperature was reduced to 25 °C and proteins were expressed overnight. Cultures were harvested by centrifugation at 3000 × g and cells were lysed in a single pass through a high-pressure homogenizer (Avestin) at >18,000 PSI. Debris and insoluble material were removed by centrifugation at 23,000 × g. The soluble supernatant was purified on a streptactin column (IBA Life Sciences) according to the manufacturer’s protocol. After purification, elution fractions were pooled, concentrated ~30 X using a centrifugal filter device , formulated in 20 % sucrose, flash frozen in liquid nitrogen, and stored at − 80 °C. Typical yields were 1 mg of purified protein from 3 (wet) grams of cells.Proteins were expressed Synechocystis sp. PCC 6803 (ATCC 27184) cells grown in BG-11 medium (Sigma) under constant illumination from fluorescent lamps at ~200 μE/m2/s while sparging a mixture of 5 % CO2 in air. Cells were harvested in exponential phase . For lysis experiments, cells were pelleted by centrifugation and resuspended to OD 1.5 in MES buffer at pH 6.2 with lysozyme and either the specified lysis components (see Results) or 1 X BugBuster protein extraction reagent (Novagen). Reactions were conducted in either microcentrifuge tubes ) or deep-well 96-well plates ). Wells in the plate were sealed with a custom PDMS gasket to prevent cross-contamination while shaking. After the reaction, insoluble debris were removed by centrifugation at 10,000 × g for 5 min, and the degree of lysis was quantified by measuring absorbance of the supernatant at 660 nm, corresponding to a chlorophyll absorbance peak. Total lysis was confirmed by the absence of green color in the debris pellets, indicating that all cells had lysed and released their chlorophyll into the supernatant. Mechanical lysis via glass beads  was used as a comparison in many experiments, as this is the current standard for cyanobacterial lysis. In these reactions, beads at 25 % of the reaction volume [Unless otherwise stated, lysis reactions were carried out on n volume  were addTrichoderma viride, Trichoderma reesei, and Aspergillus niger (Sigma) were a kind donation from Lynette Cegelski. Design-of-experiments calculations were done in SPSS (IBM). The orthogonal design function was used to generate the set of experimental conditions, and a univariate general linear model was used to analyze the results.All chemicals were obtained from Sigma-Aldrich. T4 lysozyme was obtained from MClab. Cellulases from


Individual patients show a large variability in albuminuria response to angiotensin receptor blockers (ARB). Identifying novel biomarkers that predict ARB response may help tailor therapy. We aimed to discover and validate a serum metabolite classifier that predicts albuminuria response to ARBs in patients with diabetes mellitus and micro- or macroalbuminuria.2 between a reference model of clinical parameters and a model with clinical parameters and the classifier. The classifier was externally validated in patients with type 1 diabetes and macroalbuminuria (n = 50) treated with losartan 100 mg/day. Molecular process analysis was performed to link metabolites to molecular mechanisms contributing to ARB response.Liquid chromatography-tandem mass spectrometry metabolomics was performed on serum samples. Data from patients with type 2 diabetes and microalbuminuria (n = 49) treated with irbesartan 300 mg/day were used for discovery. LASSO and ridge regression were performed to develop the classifier. Improvement in albuminuria response prediction was assessed by calculating differences in R2 increase from 0.10 to 0.70; p < 0.001). In external validation, median change in UAE was −43 % [Q1–Q35: −63 to −23]. The classifier improved prediction of UAE response to losartan . Specifically ADMA impacting eNOS activity appears to be a relevant factor in ARB response.In discovery, median change in urinary albumin excretion (UAE) was −42 % [Q1–Q3: −69 to −8]. The classifier, consisting of 21 metabolites, was significantly associated with UAE response to irbesartan (p < 0.001) and improved prediction of UAE response on top of the clinical reference model  contains supplementary material, which is available to authorized users. Intervention in the renin-angiotensin-aldosterone system (RAAS) has convincingly shown to delay progression of renal disease in patients with diabetes mellitus with elevated urinary albumin excretion (UAE) in several large trials. However, individual patients show a large variability in long-term renoprotective response, which is linked to a large variability in the short-term response in albuminuria and blood pressure . ConsequBiomarker discovery has advanced significantly over the past years with the use of high-throughput omics screening platforms. Omics profiling has emerged as a research area to expand beyond biomarker discovery to also unravel molecular pathways involved in disease pathophysiology. Integrating these data with clinical data may help give further insights in the underlying molecular mechanisms of drug response variability. Prospective metabolomics studies predicting disease progression in diabetes mellitus are becoming more common –10, but Therefore, the aims of this study were to first discover and validate a serum metabolite classifier that predicts response in albuminuria to angiotensin II receptor blocker (ARB) therapy in patients with diabetes mellitus and micro- or macroalbuminuria, and secondly, to integrate the identified metabolites in a molecular process model capturing disease pathophysiology at the interface of drug mechanism of action to decipher the underlying molecular processes driving albuminuria response to ARB.Serum samples from patients enrolled in two distinct clinical studies conducted at the Steno Diabetes Center , assessing the albuminuria lowering effect of ARBs were used for the present study. Both studies were performed in accordance with the Declaration of Helsinki and approved by the local ethical committee. All patients gave their informed consent.For the discovery cohort, we used data from a crossover clinical study in type 2 diabetes assessing the effect of the ARB irbesartan. This cohort has been previously described . In shor51Cr-EDTA every 6 months.For the external validation cohort, we used data from a clinical study in type 1 diabetes assessing the effect of the ARB losartan. This cohort has been previous described , and incWe expected the treatment effect of irbesartan and losartan on albuminuria to be fully present after 12 or 16 weeks of treatment, respectively. We refer to this as the response period.p180 kit , and categorical variables were reported as number and percentage. The natural log of UAE was used in all regression analysis.Statistical modeling consisted of several steps using a previously described methodology for development of a classifier . First, 2) from the MSEs in order to determine whether the biomarkers significantly improved prediction on top of a model of baseline clinical parameters , systolic blood pressure (SBP), GFR, UAE). The area under the receiver operating characteristics (ROC) curve and integrated discrimination improvement (IDI) index were calculated to assess the discriminatory ability of the serum metabolites for a dichotomous outcome of >30 % decrease in UAE during the response period. This threshold was used based on prior work  OR irbesartan[nm] ≪ or ≫ "losartan"[TIAB] OR losartan[nm] ≪ was performed for identifying publications discussing irbesartan and losartan, respectively. Genes linked to identified publications were extracted from gene2pubmed. For irbesartan, 1471 publications associated to a total of 44 genes and for losartan 8166 publications linked to 101 genes in total were identified. The total set of 125 protein coding genes was used for deriving a mechanism of action molecular model as described in Heinzel et al. . In shorInterference of this ARB mechanism of action molecular model was performed with a previously identified diabetic kidney disease (DKD) molecular model holding 688 protein coding genes in 34 molecular process segments . InterfeMetabolites selected for the classifier were assessed for being part of the DKD molecular model. Metabolite-to-enzyme assignments were identified utilizing the Human Metabolome Database (HMDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Of the 185 metabolites addressed in targeted metabolomics, 114 metabolites could be assigned to at least one enzyme. The respective number for the shortlist of 21 metabolites included in the classifier on drug response is 14. For these 14 metabolites, 9 could be assigned to the molecular model representation of DKD involving 11 assigned enzymes.Baseline characteristics are presented in Table 2/year.In the validation cohort, patients were approximately 47(9) years of age, mostly male (60 %), had a known duration of type 1 diabetes for 33(9) years, and median 24-h UAE was 1211 [Q1–Q3: 598 to 2023] mg/24 h. Median change in UAE was −43 % [Q1–Q3: −23 to −62] over 16 weeks of treatment with losartan 100 mg/day  .In the discovery cohort, the serum metabolites classifier was significantly associated with change in UAE in response to irbesartan 300 mg/day  and significantly improved prediction on top of clinical parameters  .In the validation cohort, the serum metabolite classifier was significantly associated with change in UAE in response to lorsartan 100 mg/day  and significantly improved prediction of change in UAE on top of a panel of clinical parameters . For the dichotomous outcome for GFR change ≤ or >−3.0 mL/min/1.73 m2/year, a significant increase was observed in the area under the ROC curve with the addition of the serum metabolites on top of clinical parameters (ROC increase from 0.71 (95 % CI 0.57 to 0.86) to 0.88 (95 % CI 0.79 to 0.98); p value 0.010).In the validation cohort, for prediction of GFR change after the response period, the combination of the 21 serum metabolites significantly improved prediction on top of clinical parameters  in the discovery study  and validation study .Interference of ARB drug mechanism of action molecular model and the DKD molecular model identifies the enzyme nitric oxide synthase 3 (NOS3). The metabolites included in the classifier were assigned to NOS3 are asymmetric dimethylarginines (ADMA) and citrulline, with ADMA being the most frequently selected metabolite in the LASSO Table . FurtherThis study discovered and externally validated a serum metabolite classifier that significantly improves prediction of albuminuria response to ARBs in patients with diabetes mellitus with micro- or macroalbuminuria on top of traditional clinical risk factors. Metabolites included in the classifier could be assigned to general molecular mechanisms of oxidative stress, inflammation, and fibrosis pathways. Specifically, NOS3 activity appears to be a relevant factor in predicting the albuminuria lowering response to ARBs. Our findings suggest the use of serum metabolites as a tool to tailor albuminuria lowering ARB treatment and illustrate the use of metabolomics to unravel underlying molecular mechanisms of ARB response.Metabolomics, the measurement of exogenous or endogenous small molecules in a sample, is an emerging research area to identify novel biomarkers. The metabolome integrates the biological information of the genome, transcriptome, proteome, and overall enzymatic reactions of an individual, therefore enabling the detection of short and long-term physiological or pathological changes occurring in diseases . MetabolPharmacological blockade of angiotensin II activity by ARBs is currently the most widely used therapeutic option, next to angiotensin converting enzyme inhibitors (ACEi), for treatment of hypertension and albuminuria in diabetes mellitus. Yet, approximately 25 % of patients with diabetes mellitus do not respond in terms of albuminuria lowering to ARBs . The serWe performed a molecular process analysis aiming to further unravel the molecular mechanisms linked to albuminuria response to ARBs in diabetes mellitus. The network approach assumes that individual drug response variability can be in part attributed to individual variability in underlying molecular mechanisms involved in the progression of disease in the light of personalized molecular pathophysiology. Indeed, coupled pathophysiological processes such as oxidative stress, inflammation, and fibrosis appear to drive disease progression, but the individual contribution of each process varies per individual. Drugs on the other hand, address specific targets and thereby interfere in specific disease associated processes. At this level, metabolites, or biomarkers more generally, may help to gain insight to which specific pathophysiological processes are driving disease progression and are targeted by a specific drug’s mode of action . The comA key finding from the molecular process analysis is the relevance of nitric oxide (NO) in ARB response, as illustrated by the direct interference of ARB molecular mechanism of action and DKD molecular model by the enzyme NOS3, and further reflected by the inclusion of ADMA and citrulline in the serum metabolite classifier. ADMA, an endogeneous NO synthase inhibitor, is considered relevant in endothelial dysfunction contributing to extracellular matrix remodeling and being involved in inflammation . IncreasSome metabolites in the classifier could not be directly linked to the ARB mechanism of action molecular model, but were linked to processes driving progression of kidney disease. This indicates that in order to assess drug response, the interplay between disease progression molecular characteristics and specific drug molecular effects should be considered. This notion was further emphasized when testing a different subgroup of metabolites. The subset of seven metabolites being present in the DKD molecular model and being linked with oxidative stress response, inflammation and fibrosis (TGFB and downstream ECM remodeling) next to NOS3 activity significantly improved prediction of albuminuria response. Furthermore, interferences at the process units at the direct drug target together with the bradykinin system and on NFκB/PPARγ indicate involvement of inflammatory processes and lipid metabolism contributing to ARB response. These observations suggest that for assessing drug response, both disease progression status and specific drug molecular effects need to be taken into account. Metabolites of the renin-angiotensin-aldosterone system were not included in the classifier, suggesting that markers of RAAS activity do not predict the response to RAAS inhibition, which is in line with prior studies , 37.Within the validation cohort, we were able to assess GFR change after the initial response period up to the end of follow-up. We observed an improvement in GFR over follow-up in patients who had a >30 % decrease in UAE from baseline, compared to a patients who did not see such a benefit in albuminuria response  patients with diabetes mellitus with polypharmacy. In addition, the relative small sample sizes of the included trials may have decreased the precision of our effect estimates. Unfortunately, a type 2 diabetes validation cohort was not available. We therefore validated the metabolomics classifier in a type 1 diabetes cohort and demonstrated that the classifier was able to predict response to ARB therapy in this population as well. We acknowledge that the disease molecular mechanisms of type 1 diabetes and type 2 diabetes are very different from each other; however, we speculate that in terms of response to albuminuria lowering therapy, the response to treatment and predictors of response may be similar. We showed that the classifier was able to predict the albuminuria response to two different ARBs, but we were unable to assess within this study whether the metabolite classifier would be different in the same patient if that patient were taking a different class of RAAS blockade (such as ACEi). Whether the classifier predicts the response to other interventions in the RAAS has to be analyzed in future studies.In conclusion, we discovered and externally validated a classifier of 21 serum metabolites that significantly improve prediction of albuminuria response to ARBs in diabetes mellitus. Metabolites included in the classifier were assigned to stress/inflammation pathways and downstream consequences of fibrosis and extra cellular matrix remodeling. Specifically, NOS3 activity appears to be a specific factor relevant in ARB response. These results indicate that for assessing drug response, both disease progression status and specific drug molecular effects need to be taken into account. Moreover, the results of this metabolomics study support the growing evidence of using omics tools as a strategy to improve molecular characterization of drug effect and disease pathophysiology. The complementary use of omics platforms, integrated into molecular process models and from there determining biomarker panels, makes implementation of personalized medicine increasingly realistic in clinical practice.


Photosensory receptors have been in the center of vision research and photobiology since the discovery of rhodopsin in 1876 by Franz Boll. However, in the last 10 years the rise of optogenetics has placed them in a broader focus. The majority of these biological light-sensors consist of a protein/pigment complex that alters the activity of a cognate biological effector upon absorption of a photon. With the nowadays available information on the corresponding genes, proteins and the vast access to (meta-) genomic data as well as sophisticated methods in molecular biology and genome engineering the photoreceptor principle of transforming light into biological information is now exploited in many different fields of research.Photosensory receptors therefore not only constitute the backbone of a major methodological breakthrough in cell and neurobiology but also offer bright perspectives for our understanding of dynamic biomolecular processes in general. The possibility to use photons as substrates enables researchers to induce and experimentally monitor biomolecular reactions with up to femtosecond resolution. Combined with techniques capable of molecular resolution such time-resolved experiments not only provide dynamic molecular information on the underlying mechanisms of photosensory and general signal transduction, but also will enable us to identify structure/function relations and design principles of biological sensor/effector complexes. Ultimately, this knowledge will allow us to rationally design novel light-responsive tools with customized properties for application in optogenetics and synthetic biology.This ebook features research articles and reviews covering the most prominent photosensory modules applied in optogenetics, as represented by flavin based photoreceptors (LOV and BLUF), phytochromes and microbial opsins. The articles of this collection showcase state-of-the-art approaches to elucidate the molecular function of such photosensory modules from the initial event of photon absorption to the activation of a downstream effector.Ritter et al. summarize recent advances in time resolved infrared absorption spectroscopy, which allows researchers to visualize structural changes involved in the activation of photosensory proteins by identifying changes in vibrational frequencies of individual chemical bonds. While infrared spectroscopic data may therefore become extremely complex in proteins, larger scale structural transformations like domain rearrangements in photosensor/effector complexes and their dynamics can be more efficiently mapped by discrete distance measurements between interacting paramagnetic centers using pulsed electron paramagnetic spectroscopy as illustrated by Nohr et al. Another elegant way of characterizing functionally relevant differences in signaling-active and inactive protein forms is presented by Lindner et al. Their review summarizes hydrogen/deuterium exchange mass spectrometry that provides information on solvent accessibility and domain flexibility, and thus important mechanistic insights on how protein dynamics determine signal transduction.Song et al.). The chromophore and its dynamic interaction with the protein environment can be studied with extremely high molecular resolution using this technique and allowed the authors to determine aggregation and hydration effects induced by sample preparation on the local structure of the chromophore. Such insights are crucial to critically evaluate experimental results and their functional implications.In their research article, Song and coworkers employ magic angle spinning solid state nuclear magnetic resonance spectroscopy to investigate the molecular and electronic structure of the protein-embedded tetrapyrrole cofactor . They identify two far-red absorbing states in the cyanobacterial phytochrome Cph1 using a combination of steady state Raman spectroscopy, ultrafast time resolved infrared spectroscopy and quantum chemical calculations.Heterogeneity in receptor conformation is a recurring topic both in photoreceptor and signal transduction research and is crucial to understand dark noise of receptor proteins. Chromophore heterogenetity and its relation to signaling is also the focus of the study of Velazquez Escobar et al. on phytochromes  and to simulate molecular structural dynamics of photoreceptor proteins. Bocola et al. employ molecular dynamics simulations to investigate light-induced structural changes in dimeric LOV domains and provide a novel mechanism for the photoactivation of dimeric LOV photoreceptors. Mathes and Götze review the currently available computational studies on the spectroscopic properties and vibrational frequencies of BLUF photoreceptors and explore an alternative mechanism of BLUF photoactivation using quantum chemical calculations.In addition to experimental methods as described in the articles above, computational methods are powerful approaches to calculate spectroscopic properties or molecular dynamics under selected conditions, which may not be accessible experimentally. In this collection computational methods are used to support experimental findings by calculating vibrational frequencies of chromophores  through a VICI grant to JK.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pseudomonas aeruginosa PA01 and Staphylococcus aureus (strain Xen 30) to form biofilms was tested. Nanofibers containing copper particles (Cu-F) were thinner (326 ± 149 nm in diameter), compared to nanofibers without copper . The crystalline structure of the copper particles in Cu-F was confirmed by X-ray diffraction (XRD). Copper crystals were encapsulated, but also attached to the surface of Cu-F, as shown scanning transmission electron microscopy (STEM) and transmission electron microscopy (TEM), respectively. The copper particles had no effect on the thermal degradation and thermal behaviour of Cu-F, as shown by thermogravimetric analysis (TGA) and differential scanning calorimeter (DSC). After 48 h in the presence of Cu-F, biofilm formation by P. aeruginosa PA01 and S. aureus Xen 30 was reduced by 41% and 50%, respectively. Reduction in biofilm formation was ascribed to copper released from the nanofibers. Copper-containing nanofibers may be incorporated into wound dressings.Copper particles were incorporated into nanofibers during the electrospinning of poly-D,L-lactide (PDLLA) and poly(ethylene oxide) (PEO). The ability of the nanofibers to prevent  Copper is an essential metal and is required in small quantities in many metabolic processes , 2. UndePseudomonas aeruginosa, Enterobacter aerogenes, Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), vancomycin-resistant Enterococcus (VRE), Clostridium difficile, Salmonella enterica, Campylobacter jejuni and Escherichia coli 0157:H7, are killed when exposed to the surfaces of copper and copper alloys [In ancient times, copper was used to sterilize water and treat burn, skin and ear infections . Intra-ur alloys –22. CoppExopolysaccharides (EPS) safeguard cells from antibiotics, antimicrobial peptides and harsh environmental conditions , 24. At P. aeruginosa PA01 and a methicillin-resistant S. aureus, strain Xen 30.Silver is well known for its antimicrobial activity and silver nanoparticles (Ag-NPs) incorporated into nanofiber dressings have been used in wound dressings , 27–29. N,N-dimethylformamide (DMF), 3--2,5-diphenyltetrazolium bromide (MTT), Dulbecco’s modified Eagle's medium (DMEM), Hams-F12, fetal bovine serum (FBS), hydrocortisone, insulin, cholera toxin and PenStrep were obtained from Sigma-Aldrich . The LIVE/DEAD® BaclightTM Bacterial Viability kit and FilmTracerTM SYPRO® Ruby Biofilm Matrix Stain were from Thermo Fisher Scientific . All reagents were of analytical grade.Copper powder was supplied by TraceXtec . PDLLA (Mw 75−120 kDa) and PEO (Mw 200 kDa), −1. Initial studies have shown that this was the maximum concentation of copper particles that could be electrospun into nanofibers. Nanofibers were electrospun as described by Heunis et al. [A 24% (w/v) 1:1 combination of PDLLA and PEO, dissolved in DMF, was heated at 40°C to produce a homogenous solution. Copper powder was suspended in the polymer solution to the final concentration of 150 mg mls et al. . PDLLA/PNanofibers were sputter-coated with carbon and their surface morphology visualised by scanning electron microscopy (SEM), using a FEI Nova nanoSEM 230 . A total of 100 image points were measured to determine the average diameter of the nanofibers. ImageJ Software  was used. Transmission electron microscopy (TEM) images were recorded on a Philips Tecnai TF20 (FEI).Copper particles in nanofibers was visualised using a FEI Nova nanoSEM 230 (FEI), equipped with an X/Max Oxford energy-dispersive X-ray (EDX) detector . INCA software  was used to analyse the EDX spectra. Scanning transmission electron microscopy (STEM) images were recorded using the FEI Nova nanoSEM 230, equipped with STEM detector. Physical phases were observed by X-ray diffraction (XRD) using a Bruker AXS D8 Advance X-ray diffractometer , equipped with a Vantec-1 position sensitive detector (Cu-Kα radiation at λ = 1.5406 Å) and operated in locked coupled mode. The X-ray tube was operated at 40 mA and 40 kV. Readings were recorded at a scanning rate of 88 sec/step, with a step size of 0.05° in a 2θ range that extended from 15° to 95°. The thermal stability, melting endotherms and crystallization exotherms of nanofibers were measured by thermogravimetric analyser (TGA) and differential scanning calorimeter (DSC), as described by Ahire et al. .P. aeruginosa PA01 and S. aureus Xen 30 (105 CFU ml–1) were each spread-plated onto Muller-Hinton agar . Sections of 0.5 cm2 copper-containing nanofibers (Cu-F) and nanofibers without copper (CF) were placed on the surface of the spread plates and the plates incubated at 37°C for 24 h. The diameter of growth inhibition zones was measured in millimetres.Active-growing cells of Pseudomonas aeruginosa PA01 and S. aureus Xen 30  were stimulated to form biofilms, as described by Ahire and Dicks [2) were placed in 24 wells of a 96-well plastic round-bottom multidish . Another 24 wells received CF (0.5 cm2). Cell suspensions of P. aeruginosa PA01 and S. aureus Xen 30 were prepared in sterile tryptone soy broth  to 7.3 ± 0.07 log 10 CFU ml–1 and 6.6 ± 0.11 log 10 CFU ml–1, respectively. Two-hundred microliters of the P. aeruginosa PA01 cell suspension was transferred to 12 wells containing Cu-F and 12 wells containing CF. Twelve wells with Cu-F and 12 wells with CF were each inoculated with 200 μl S. aureus Xen 30 cell suspension. Twelve wells without nanofibers were inoculated with 200 μl P. aeruginosa PA01 and another 12 wells with the same volume S. aureus Xen 30. All plates were statically incubated at 37°C for 48 h.nd Dicks , 33. SecAt specific time intervals, nanofibers and planktonic cells were carefully removed from the wells and discarded. The wells were then washed twice with sterile distilled water and air dried. Total biofilm formation was determined by staining the wells with crystal violet , 33. OptSterile PBS, pH 7.3 (100 μl) was added to wells immediately after washing with sterile distilled water. The cells were carefully suspended by using a sterile glass rod, the suspension serially diluted in PBS and plated onto TSA (Biolab). Colonies were counted after 24 h of incubation at 37°C.® BaclightTM Bacterial Viability kit  and FilmTracerTM SYPRO® Ruby Biofilm Matrix Stain (Thermo Fisher Scientific), as recommended by the suppliers. A Carl Zeiss LSM780 confocal microscope  was used to study the stained biofilms. Images were processed by using the ZEN 2011 imaging software (Carl Zeiss).Immediately after washing the cells with sterile distilled water, biofilms were carefully removed from the wells with a sterile pipette tip and transferred to 100 μl sterile PBS (pH 7.3). The biofilms were stained with the LIVE/DEADx and y) and AFM parameters were evaluated using the SPIP 3D image processing 6.3.6 software .Wells that contained biofilms were washed and dried as described elsewhere. After drying, the wells were cut out with a sharp blade and images of the wells taken with a FEI Nova nanoSEM 230 (FEI). The topology of the surfaces was studied using a Nanosurf Easyscan 2 atomic force microscope . The AFM was operated in static force mode, equipped with a CantAI-G cantilever. The P-gain was adjusted to 2800, rotation to 45° and tip voltage to zero. Images were recorded in the range of 10 μm (Sections of Cu-F (10 mg) were each submersed in 1 ml sterile deionized water and incubated at 25°C. The nanofiber mat was transferred to sterile deionized water, every 2 h, for up to 24 h. Release of copper from the nanofiber mats was studied with inductively-coupled plasma mass spectrometry (ICP-MS), using an Agilent 7700 ICP-MS .–1 hydrocortisone, 10 μg ml–1 insulin, 100 ng ml–1 cholera toxin and 1% (v/v) PenStrep. Cells were seeded in 12 × 24-well NEST tissue culture plates  to 8.0 × 104 per well and incubated at 37°C in humidified atmosphere (5% CO2). After 24 h, the medium in wells was replaced with UV-sterilized Cu-F (0.5 cm2), CF (0.5 cm2), and fresh culture media , respectively. The plates were incubated for a further 24 h, after which cell viability was determined using the MTT assay.The cytotoxicity of nanofibers was performed as described by Ahire et al. . BrieflyP value < 0.05 or less was considered statistically significant.All experiments were performed in triplicate. Values are expressed as mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was calculated by using GraphPad Prism . A Copper particles in the PDLLA/PEO solution accelerated a liquid jet towards a grounded collector, due to an increase in conductance. Similar findings were reported with the presence of copper nanoparticles during the spinning of polyurethane nanofibers . This exAnalyses with SEM-energy-dispersive X-ray (EDX) of Cu-F  and coppθ values of 43.12°, 50.10°, 74.0°, and 89.6° recorded with XRD corresponded to (111), (200), (220) and (311) crystal planes  and methicillin resistant S. aureus Xen 30 (inhibition zone diameter: 12 ± 1.5 mm). Nanofibers without copper particles (CF) did not inhibit the growth of the two species and confirmed previous findings [P. aeruginosa PA01 is ascribed to the strain’s natural resistance to copper [2+, is known to oxidise proteins and degrade DNA [P. aeruginosa PA01 and methicillin resistant S. aureus Xen 30 [Copper-containing nanofibers (Cu-F) placed on the surface of plates inhibited the growth of findings , 38, 27.o copper . Resistao copper . The outo copper . Accumulo copper . The oxirade DNA . Similarrade DNA . Silver s Xen 30 .P. aeruginosa PA01 and S. aureus Xen 30 were after 48 h approximately 5% less in the presence of CF, compared to cells grown in the absence of nanofibers  [P. aeruginosa biofilm biomass and a 90% decrease in S. aureus biofilm biomass when treated with Cu-NPs. We did not determine changes in biomass, but recorded a drastic decline in biofilm formation based on crystal violet staining (41% for P. aeruginosa PA01 and 50% S. aureus Xen 30).In a recent study, growth inhibition and biofilm formation of MRSA and (Cu-NPs) , 26. Chr® BaclightTM and FilmTracerTM SYPRO® Ruby Biofilm Matrix Stain showed only few viable cells in the presence of Cu-F  survived exposure to copper-containing fibers, which suggests that the levels of copper released from the nanofibers were highly toxic to cells in tissue culture. Other studies have shown that copper concentrations at these levels have no adverse reaction when applied on human skin [Despite irregularity observed in the shape of the copper particles, they were successfully incorporated into PDLLA and PEO nanofibers and remained in crystal form. The encapsulated copper particles had no effect on the thermal behaviour of the nanofibers, even at an inclusion of 40 wt. %. Biofilm formation by man skin .