Gene synthesis by integrated polymerase chain assembly and PCR amplification using a high-speed thermocycler

Polymerase chain assembly (PCA) is a technique used to synthesize genes ranging from a few hundred base pairs to many kilobase pairs in length. In traditional PCA, equimolar concentrations of single stranded DNA oligonucleotides are repeatedly hybridized and extended by a polymerase enzyme into longer dsDNA constructs, with relatively few full-length sequences being assembled. Thus, traditional PCA is followed by a second primer-mediated PCR reaction to amplify the desired full-length sequence to useful, detectable quantities. Integration of assembly and primer-mediated amplification steps into a single reaction using a high-speed thermocycler is shown to produce similar results. For the integrated technique, the effects of oligo concentration, primer concentration, and number of oligonucleotides are explored. The technique is successfully demonstrated for the synthesis of two genes encoding EPCR-1 (653 bp) and pUC19 β-lactamase (929 bp) in under 20 min. However, rapid integrated PCA–PCR was found to be problematic when attempted with the TM-1 gene (1509 bp). Partial oligonucleotide sets of TM-1 could be assembled and amplified simultaneously, indicating that the technique may be limited to a maximum number of oligonucleotides due to competitive annealing and competition for primers

Gene synthesis by integrated polymerase chain assembly and PCR amplification using a high-speed thermocycler

Polymerase chain assembly (PCA) is a technique used to synthesize genes ranging from a few hundred base pairs to many kilobase pairs in length. In traditional PCA, equimolar concentrations of single stranded DNA oligonucleotides are repeatedly hybridized and extended by a polymerase enzyme into longer dsDNA constructs, with relatively few full-length sequences being assembled. Thus, traditional PCA is followed by a second primer-mediated PCR reaction to amplify the desired full-length sequence to useful, detectable quantities. Integration of assembly and primer-mediated amplification steps into a single reaction using a high-speed thermocycler is shown to produce similar results. For the integrated technique, the effects of oligo concentration, primer concentration, and number of oligonucleotides are explored. The technique is successfully demonstrated for the synthesis of two genes encoding EPCR-1 (653 bp) and pUC19 β-lactamase (929 bp) in under 20 min. However, rapid integrated PCA–PCR was found to be problematic when attempted with the TM-1 gene (1509 bp). Partial oligonucleotide sets of TM-1 could be assembled and amplified simultaneously, indicating that the technique may be limited to a maximum number of oligonucleotides due to competitive annealing and competition for primers

A Model of Tuberculosis Transmission and Intervention Strategies in an Urban Residential Area

The model herein aims to explore the dynamics of the spread of tuberculosis (TB) in an informal settlement or township. The population is divided into households of various sizes and also based on commuting status. The model dynamics distinguishes between three distinct social patterns: the exposure of commuters during travel, random diurnal interaction and familial exposure at night. Following the general SLIR models, the population is further segmented into susceptible (S), exposed/latently infected (L), active/infectious (I), and recovered (R) individuals. During the daytime, commuters travel on public transport, while non-commuters randomly interact in the community to mimic chance encounters with infectious persons. At night, each family interacts and sleeps together in the home. The risk of exposure to TB is based on the proximity, duration, and frequency of encounters with infectious persons. The model is applied to a hypothetical population to explore the effects of different intervention strategies including vaccination, wearing of masks or scarves during the commute, prophylactic treatment of latent infections and more effective case-finding and treatment. The most important findings of the model are: (1) members of larger families are responsible for more disease transmissions than those from smaller families, (2) daily commutes on public transport provide ideal conditions for transmission of the disease, (3) improved diagnosis and treatment has the greatest impact on the spread of the disease, and (4) detecting TB at the first clinic visit, when patients are still smear negative, is key

A Model of Tuberculosis Transmission and Intervention Strategies in an Urban Residential Area

The model herein aims to explore the dynamics of the spread of tuberculosis (TB) in an informal settlement or township. The population is divided into households of various sizes and also based on commuting status. The model dynamics distinguishes between three distinct social patterns: the exposure of commuters during travel, random diurnal interaction and familial exposure at night. Following the general SLIR models, the population is further segmented into susceptible (S), exposed/latently infected (L), active/infectious (I), and recovered (R) individuals. During the daytime, commuters travel on public transport, while non-commuters randomly interact in the community to mimic chance encounters with infectious persons. At night, each family interacts and sleeps together in the home. The risk of exposure to TB is based on the proximity, duration, and frequency of encounters with infectious persons. The model is applied to a hypothetical population to explore the effects of different intervention strategies including vaccination, wearing of masks or scarves during the commute, prophylactic treatment of latent infections and more effective case-finding and treatment. The most important findings of the model are: (1) members of larger families are responsible for more disease transmissions than those from smaller families, (2) daily commutes on public transport provide ideal conditions for transmission of the disease, (3) improved diagnosis and treatment has the greatest impact on the spread of the disease, and (4) detecting TB at the first clinic visit, when patients are still smear negative, is key

Experimental Validation of a Fundamental Model for PCR Efficiency

Recently a theoretical analysis of PCR efficiency has been published by Booth et al., (2010). The PCR yield is the product of three efficiencies: (i) the annealing efficiency is the fraction of templates that form binary complexes with primers during annealing, (ii)the polymerase binding efficiency is the fraction of binary complexes that bind to polymerase to form ternary complexes and (iii)the elongation efficiency is the fraction of ternary complexes that extend fully. Yield is controlled by the smallest of the three efficiencies and control could shift from one type of efficiency to another over the course of a PCR experiment. Experiments have been designed that are specifically controlled by each one of the efficiencies and the results are consistent with the mathematical model. The experimental data has also been used to quantify six key parameters of the theoretical model. An important application of the fully characterized model is to calculate initial template concentration from real-time PCR data. Given the PCR protocol, the midpoint cycle number (where the template concentration is half that of the final concentration) can be theoretically determined and graphed for a variety of initial DNA concentrations. Real-time results can be used to calculate the midpoint cycle number and consequently the initial DNA concentration, using this graph. The application becomes particularly simple if a conservative PCR protocol is followed where only the annealing efficiency is controlling

Fluoroquinolone Efficacy against Tuberculosis Is Driven by Penetration into Lesions and Activity against Resident Bacterial Populations.

Fluoroquinolones represent the pillar of multidrug-resistant tuberculosis (MDR-TB) treatment, with moxifloxacin, levofloxacin, or gatifloxacin being prescribed to MDR-TB patients. Recently, several clinical trials of "universal" drug regimens, aiming to treat drug-susceptible and drug-resistant TB, have included a fluoroquinolone. In the absence of clinical data comparing their side-by-side efficacies in controlled MDR-TB trials, a pharmacological rationale is needed to guide the selection of the most efficacious fluoroquinolone. The present studies were designed to test the hypothesis that fluoroquinolone concentrations (pharmacokinetics) and activity (pharmacodynamics) at the site of infection are better predictors of efficacy than the plasma concentrations and potency measured in standard growth inhibition assays and are better suited to determinations of whether one of the fluoroquinolones outperforms the others in rabbits with active TB. We first measured the penetration of these fluoroquinolones in lung lesion compartments, and their potency against bacterial populations that reside in each compartment, to compute lesion-centric pharmacokinetic-pharmacodynamic (PK/PD) parameters. PK modeling methods were used to quantify drug penetration from plasma to tissues at human-equivalent doses. On the basis of these metrics, moxifloxacin emerged with a clear advantage, whereas plasma-based PK/PD favored levofloxacin (the ranges of the plasma AUC/MIC ratio [i.e., the area under the concentration-time curve over 24 h in the steady state divided by the MIC] are 46 to 86 for moxifloxacin and 74 to 258 for levofloxacin). A comparative efficacy trial in the rabbit model of active TB demonstrated the superiority of moxifloxacin in reducing bacterial burden at the lesion level and in sterilizing cellular and necrotic lesions. Collectively, these results show that PK/PD data obtained at the site of infection represent an adequate predictor of drug efficacy against TB and constitute the baseline required to explore synergies, antagonism, and drug-drug interactions in fluoroquinolone-containing regimens

Rapid Diagnosis of Tuberculosis in a Peripheral Setting

Tuberculosis is an ancient and worldwide epidemic affecting millions of people in mainly the developing world, killing almost 2 million people in 2008. Current diagnostic techniques are outdated and have proven insufficient to control the disease. Smear microscopy has poor sensitivity and culture is slow to yield results. Modern diagnostic techniques are making great strides in shortening time to result but are restricted by two qualities: 1) prohibitively high costs prevent implementation in resource poor areas, and 2) equipment and technician requirements limit application to centralized laboratories. There exists a divide between new technologies and the people that need them most. Here, a novel epidemiological model of tuberculosis in an urban community confirms the importance of improved diagnostics in lowering prevalence. The model highlights the importance of sensitivity and accessibility. This work presents the development of a nucleic acid amplification test for tuberculosis diagnosis from sputum. The prototype system consists of 1) a sputum processing unit capable of extracting DNA within 5 minutes, and 2) a rapid PCR thermocycler which amplifies Mycobacterium tuberculosis complex specific sequences (IS6110 and IS1081) in under 15 minutes and detects product in real-time. Lysis protocol development was guided by a combined theoretical/experimental analysis of the kinetics of heat lysis of Mycobacterium smegmatis. The analysis revealed the activation energy of lysis (22.1 kcal/mole) and the minimum cell wall damage that result in cell distruction (14-17%). The PCR is capable of amplifying template amounts below smear microscopy concentrations. The test was applied to 58 clinical samples from the Steve Biko Academic Hospital in Pretoria, South Africa. Sensitivity was 95% on smear positive culture positive samples and 70% on smear negative culture positive samples. Specificity was 86%. In summary, the test moves toward an important niche of rapid (less than 30 minutes) and affordable ($5-10) diagnosis in a peripheral setting. Sensitivity of the test is comparable to other available systems, while specificity still needs improvement. However, turnaround times and costs are far below other tests currently being developed

The tri-frame model

The tri-frame model gives mathematical expression to the transcription and translation processes, and considers all three reading frames. RNA polymerases transcribe DNA in single nucleotide increments, but ribosomes translate mRNA in pairings of three (triplets or codons). The set of triplets in the mRNA, starting with the initiation codon (usually AUG) defines the open reading frame (ORF). Since ribosomes do not always translocate three nucleotide positions, two additional reading frames are accessible. The -1RF and the +1RF are triplet pairings of the mRNA which are accessed by shifting one nucleotide position in the 5’ and 3’ directions respectively. Transcription is modeled as a linear operator that maps the initial codons in all three frames into other codon sets to account for possible transcriptional errors. Translational errors (missense errors) originate from misacylation of tRNA’s and misreading of aa-tRNA’s by the ribosome. Translation is modeled as a linear mapping from codons into aa-tRNA species, which includes misreading errors. A final transformation from aa-tRNA species into amino acids provides the probability distributions of possible amino acids into which the codons in all three frames could be translated. An important element of the tri-frame model is the ribosomal occupancy probability. It is a vector in R3 that gives the probability to find the ribosome in the ORF, -1RF or +1RF at each codon position. The sequence of vectors, from the first to the final codon position, gives a history of ribosome frameshifting. The model is powerful: it provides exact expressions for: (1) yield of error-free protein, (2) fraction of prematurely terminated polypeptides, (3) number of transcription errors, (4) number of translation errors and (5) mutations due to frameshifting. The theory is demonstrated for the three genes rpsU, dnaG and rpoD of E. coli which lie on the same operon, as well as for the prfB gene

Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems

Rare events such as genetic mutations or cell-cell interactions are important contributors to dynamics in complex biological systems, eg, in drug-resistant infections. Computational approaches can help analyze rare events that are difficult to study experimentally. However, analyzing the frequency and dynamics of rare events in computational models can also be challenging due to high computational resource demands, especially for high-fidelity stochastic computational models. To facilitate analysis of rare events in complex biological systems, we present a multifidelity analysis approach that uses medium-fidelity analysis (Monte Carlo simulations) and/or low-fidelity analysis (Markov chain models) to analyze high-fidelity stochastic model results. Medium-fidelity analysis can produce large numbers of possible rare event trajectories for a single high-fidelity model simulation. This allows prediction of both rare event dynamics and probability distributions at much lower frequencies than high-fidelity models. Low-fidelity analysis can calculate probability distributions for rare events over time for any frequency by updating the probabilities of the rare event state space after each discrete event of the high-fidelity model. To validate the approach, we apply multifidelity analysis to a high-fidelity model of tuberculosis disease. We validate the method against high-fidelity model results and illustrate the application of multifidelity analysis in predicting rare event trajectories, performing sensitivity analyses and extrapolating predictions to very low frequencies in complex systems. We believe that our approach will complement ongoing efforts to enable accurate prediction of rare event dynamics in high-fidelity computational models

Ribosome kinetics and aa-tRNA competition determine rate and fidelity of peptide synthesis

It is generally accepted that the translation rate depends on the availability of cognate aa-tRNAs. In this study it is shown that the key factor that determines translation rate is the competition between near-cognate and cognate aa-tRNAs. The transport mechanism in the cytoplasm is diffusion, thus the competition between cognate, near-cognate and non-cognate aa-tRNAs to bind to the ribosome is a stochastic process. Two competition measures are introduced; C (i) and R (i) (i = 1, 64) are quotients of the arrival frequencies of near-cognates vs. cognates and noncognates vs. cognates, respectively. Furthermore, the reaction rates of bound cognates differ from those of bound near-cognates. If a near-cognate aa-tRNA binds to the A site of the ribosome, it may be rejected at the anti-codon recognition step or proofreading step or it may be accepted. Regardless of its fate, the near-cognates and non-cognates have caused delays of varying duration to the observed rate of translation. Rate constants have been measured at a temperature of 20 °C by (Gromadski, K.B., Rodnina, M.V., 2004. Kinetic determinants of high-fidelity tRNA discrimination on the ribosome. Mol. Cell 13, 191–200). These rate constants have been re-evaluated at 37 °C, using experimental data at 24.5 °C and 37 °C (Varenne, S., et al., 1984. Translation in a non-uniform process: effect of tRNA availability on the rate of elongation of nascent polypeptide chains. J. Mol. Biol. 180, 549–576). The key results of the study are: (i) the average time (at 37 °C) to add an amino acid, as defined by the ith codon, to the nascent peptide chain is: τ(i) = 9.06 + 1.445 × [10.48C(i) + 0.5R (i)] (in ms); (ii) the misreading frequency is directly proportional to the near-cognate competition, E(i) = 0.0009C(i); (iii) the competition from near-cognates, and not the availability of cognate aa-tRNAs, is the most important factor that determines the translation rate – the four codons with highest near-cognate competition (in the case of E. coli ) are [GCC] \u3e [CGG] \u3e [AGG] \u3e [GGA], which overlap only partially with the rarest codons: [AGG] \u3c [CCA] \u3c [GCC] \u3c [CA C]; (iv) based on the kinetic rates at 37 °C, the average time to insert a cognate amino acid is 9.06 ms and the average delay to process a nearcognate aa-tRNA is 10.45 ms and (vii) the model also provides estimates of the vacancy times of the A site of the ribosome – an important factor in frameshifting