Strategies to maximize heterologous protein expression in Escherichia coli with minimal cost

Automation and miniaturization are key issues of high-throughput research projects in the post-genomic era. The implementation of robotics and parallelization has enabled researchers to process large numbers of protein targets for structural studies in a short time with reasonable cost efficiency. However, the cost of implementing the robotics and parallelization often prohibit their use in the traditional academic laboratory. Fortunately, multiple groups have made significant efforts to minimize the cost of heterologous protein expression for the production of protein samples in quantities suitable for high resolution structural studies. In this review, we describe recent efforts to continue to minimize the cost for the parallel processing of multiple protein targets and focus on those materials and strategies that are highly suitable for the traditional academic laboratory.     

The utility of low-density genotyping for imputation in the Thoroughbred horse

Background

Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem.

Results

Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money.

Conclusions

Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy.     

Prey selection by coral-feeding butterflyfishes: strategies to maximize the profit

Synopsis Factors that structure preferences among food corals were examined for the obligate coral-feeding butterflyfishChaetodon multicinctus. In the field, fish show a simple repetitious pattern of foraging composed of (1) pre-encounter search for coral colonies, and (2) post-encounter inspection/orientation, bite, and consumption of polyps. Rose coral,Pocillopora meandrina, and the massive coral,Porites lobata, were taken in higher proportions than their percentage substrate cover, while finger coral,Porites compressa, was taken in lower proportion. Paired presentations of coral colonies in the lab gave similar results:Poc. meandrina was preferred overPor. lobata which was preferred overPor. compressa. Poc. meandrina tissue had the highest energy content, lowest handling time, and highest profitability. Energy content did not differ amongPorites tissues, but handling time was greater and more inspective eye movements were made while foraging on the branched finger coral,Por. compressa. Experimental manipulation of coral colony morphology indicate preferences amongPorites are most likely structured by handling costs. Predictions of a simple prey-choice foraging model are supported in theC. multicinctus system if abundance of the branched coralPor. compressa is estimated as that available to fishes rather than percentage substrate cover. The relative size and abundance of stinging nematocysts are also consistent with observed foraging patterns in the field, but await immunological confirmation. Coral-feeding butterflyfishes offer unique opportunities to test models of foraging ecology in reef fishes, and the direction of future studies is suggested.     

Analyses and comparison of accuracy of different genotype imputation methods

The power of genetic association analyses is often compromised by missing genotypic data which contributes to lack of significant findings, e.g., in in silico replication studies. One solution is to impute untyped SNPs from typed flanking markers, based on known linkage disequilibrium (LD) relationships. Several imputation methods are available and their usefulness in association studies has been demonstrated, but factors affecting their relative performance in accuracy have not been systematically investigated. Therefore, we investigated and compared the performance of five popular genotype imputation methods, MACH, IMPUTE, fastPHASE, PLINK and Beagle, to assess and compare the effects of factors that affect imputation accuracy rates (ARs). Our results showed that a stronger LD and a lower MAF for an untyped marker produced better ARs for all the five methods. We also observed that a greater number of haplotypes in the reference sample resulted in higher ARs for MACH, IMPUTE, PLINK and Beagle, but had little influence on the ARs for fastPHASE. In general, MACH and IMPUTE produced similar results and these two methods consistently outperformed fastPHASE, PLINK and Beagle. Our study is helpful in guiding application of imputation methods in association analyses when genotype data are missing.     

Nutrigonometry II: Experimental strategies to maximize nutritional information in multidimensional performance landscapes

Animals regulate their nutrient consumption to maximize the expression of fitness traits with competing nutritional needs (“nutritional trade‐offs”). Nutritional trade‐offs have been studied using a response surface modeling approach known as the Geometric Framework for nutrition (GF). Current experimental design in GF studies does not explore the entire area of the nutritional space resulting in performance landscapes that may be incomplete. This hampers our ability to understand the properties of the performance landscape (e.g., peak shape) from which meaningful biological insights can be obtained. Here, I tested alternative experimental designs to explore the full range of the performance landscape in GF studies. I compared the performance of the standard GF design strategy with three alternatives: hexagonal, square, and random points grid strategies with respect to their accuracy in reconstructing baseline performance landscapes from a landmark GF dataset. I showed that standard GF design did not reconstruct the properties of baseline performance landscape appropriately particularly for traits that respond strongly to the interaction between nutrients. Moreover, the peak estimates in the reconstructed performance landscape using standard GF design were accurate in terms of the nutrient ratio but incomplete in terms of peak shape. All other grid designs provided more accurate reconstructions of the baseline performance landscape while also providing accurate estimates of nutrient ratio and peak shape. Thus, alternative experimental designs can maximize information from performance landscapes in GF studies, enabling reliable biological insights into nutritional trade‐offs and physiological limits within and across species.     

Evaluation of alternative strategies to optimize ketorolac transdermal delivery

In the present study, 2 alternative strategies to optimize ketorolac transdermal delivery, namely, prodrugs (polyoxyethylene glycol ester derivatives, I–IV) and nanostructured lipid carriers (NLC) were investigated. The synthesized prodrugs were chemically stable and easily degraded to the parent drug in human plasma. Ketorolac-loaded NLC with high drug content could be successfully prepared. The obtained products formulated into gels showed a different trend of drug permeation through human stratum corneum and epidermis. Particularly, skin permeation of ester prodrugs was significantly enhanced, apart from ester IV, compared with ketorolac, while the results of drug release from NLC outlined that these carriers were ineffective in increasing ketorolac percutaneous absorption owing to a higher degree of mutual interaction between the drug and carrier lipid matrix. Polyoxyethylene glycol esterification confirmed to be a suitable approach to enhance ketorolac transdermal delivery, while NLC seemed more appropriate for sustained release owing to the possible formation of a drug reservoir into the skin. Published: August 4, 2006     

An alternative genotyping method using dye-labeled universal primer to reduce unspecific amplifications

We proposed a modification the procedure of genotyping based in labeled universal primer and tailed primer. In the standard protocol, three primers are used in the same PCR reaction, a forward primer with tail added at the 5′ end of the identical sequence to labeled universal primer with dye-fluorescent and a reverse primer. Unfortunately, the choice of a labeled primer characterized by a large number of complementary sequences in target genomes (which is more probable in larger genomes) result in unspecific amplifications (false positive) can cause absence or decrease amplification of the locus of interest and also false interpretation of the analysis. However, identification of possible homologies between the primer chosen for labelling and the genome is rarely possible from the available DNA data bases. In our approach, cycling is interrupted for the addition of the labeled primer only during the final cycles, thus minimizing unspecific amplification and competition between primers, resulting in the more fidelity amplification of the target regions.     

A comparison between SNaPshot, pyrosequencing, and biplex invader SNP genotyping methods: accuracy, cost, and throughput

Three methods of Single Nucleotide Polymorphism (SNP) detection: SNaPshot, Pyrosequencing and Biplex Invader, with two different chemistries were investigated to compare, (1) accuracy, (2) ease of use, (3) throughput capability, and (4) cost. We genotyped 192 human DNA samples across 24 SNPs (minor allele frequencies above 30%), of which seven SNPs were genotyped with all three methods. We show that the Biplex Invader genotyping method was found to be the most accurate and easiest to use with lowest cost, although Pyrosequencing provided similar results at a low cost. With little optimization, the accuracy of the SNaPshot method was also comparable to these two methods with a higher cost, if only singleplex reactions are used.     

Multi-generational imputation of single nucleotide polymorphism marker genotypes and accuracy of genomic selection

Availability of high-density single nucleotide polymorphism (SNP) genotyping platforms provided unprecedented opportunities to enhance breeding programmes in livestock, poultry and plant species, and to better understand the genetic basis of complex traits. Using this genomic information, genomic breeding values (GEBVs), which are more accurate than conventional breeding values. The superiority of genomic selection is possible only when high-density SNP panels are used to track genes and QTLs affecting the trait. Unfortunately, even with the continuous decrease in genotyping costs, only a small fraction of the population has been genotyped with these high-density panels. It is often the case that a larger portion of the population is genotyped with low-density and low-cost SNP panels and then imputed to a higher density. Accuracy of SNP genotype imputation tends to be high when minimum requirements are met. Nevertheless, a certain rate of genotype imputation errors is unavoidable. Thus, it is reasonable to assume that the accuracy of GEBVs will be affected by imputation errors; especially, their cumulative effects over time. To evaluate the impact of multi-generational selection on the accuracy of SNP genotypes imputation and the reliability of resulting GEBVs, a simulation was carried out under varying updating of the reference population, distance between the reference and testing sets, and the approach used for the estimation of GEBVs. Using fixed reference populations, imputation accuracy decayed by about 0.5% per generation. In fact, after 25 generations, the accuracy was only 7% lower than the first generation. When the reference population was updated by either 1% or 5% of the top animals in the previous generations, decay of imputation accuracy was substantially reduced. These results indicate that low-density panels are useful, especially when the generational interval between reference and testing population is small. As the generational interval increases, the imputation accuracies decay, although not at an alarming rate. In absence of updating of the reference population, accuracy of GEBVs decays substantially in one or two generations at the rate of 20% to 25% per generation. When the reference population is updated by 1% or 5% every generation, the decay in accuracy was 8% to 11% after seven generations using true and imputed genotypes. These results indicate that imputed genotypes provide a viable alternative, even after several generations, as long the reference and training populations are appropriately updated to reflect the genetic change in the population.     

A comparison of strategies for selecting breeding pairs to maximize genetic diversity retention in managed populations

Captive breeding programs aim to maintain populations that are demographically self-sustaining and genetically healthy. It has been well documented that the best way for managed breeding programs to retain gene diversity (GD) and limit inbreeding is to select breeding pairs that minimize a population's average kinship. We used a series of computer simulations to test 4 methods of minimizing average kinship across a variety of scenarios with varying generation lengths, mortality rates, reproductive rates, and rates of breeding pair success. "Static MK Selection" and "Dynamic MK Selection" are 2 methods for iteratively selecting genetically underrepresented individuals for breeding, whereas "Ranked MK Selection" and "Simultaneous MK Selection" are 2 methods for concurrently selecting the group of breeding individuals that produce offspring with the lowest average kinship. For populations with discrete generations (24 tested scenarios), we found that the Simultaneous and Ranked MK Selection methods were generally the best, nearly equivalent methods for selecting breeding pairs that retained GD and limited inbreeding. For populations with overlapping generations (198 tested scenarios), we found that Dynamic MK Selection was the most robust method for selecting breeding pairs. We used these results to provide guidelines for identifying which method of minimizing average kinship was most appropriate for various breeding program scenarios.     

Plants use alternative strategies to utilize nonexchangeable potassium in minerals

Plant species differ in their capacity to use nonexchangeable potassium (NEK) in soils. In this study two typical plants with high K use efficiency, ryegrass and grain amaranth, were compared with regard to their capacity to use K from five K-bearing minerals. Biomass relative yield and K uptake data indicated that ryegrass was much more efficient than grain amaranth at using NEK in minerals. Root exudates of grain amaranth collected under hydroponic culture contained considerable amounts of oxalic and citric acids, while these acids were not detected in ryegrass root exudates. Compared with grain amaranth, the kinetic parameters of K uptake by ryegrass roots were characterized by a significantly higher K uptake rate (V_max) and a significantly lower C_min, the minimum external K concentration at which K is taken up. The dynamic release of NEK from minerals in various solutions showed that the release rate of NEK was largely K-concentration dependent and some thresholds of K concentration prevented further NEK release from minerals. The K thresholds were related to mineral type and increased in the presence of Ca²⁺ or Na⁺ in solutions. The positive effect of H⁺ (20 mmol L^?1) on NEK release was also mainly attributed to elevating the thresholds of K concentration, rather than to the effects of weathering. The results indicated that the main mechanism by which plant species efficiently use NEK in minerals was to the capacity of plants to absorb K at low concentrations. The lower the C_min for the root K uptake, the higher the expected NEK use efficiency of the plant.     

An evaluation of sequencing coverage and genotyping strategies to assess neutral and adaptive diversity

Whole genome sequences (WGS) greatly increase our ability to precisely infer population genetic parameters, demographic processes, and selection signatures. However, WGS may still be not affordable for a representative number of individuals/populations. In this context, our goal was to assess the efficiency of several SNP genotyping strategies by testing their ability to accurately estimate parameters describing neutral diversity and to detect signatures of selection. We analysed 110 WGS at 12× coverage for four different species, i.e., sheep, goats and their wild counterparts. From these data we generated 946 data sets corresponding to random panels of 1K to 5M variants, commercial SNP chips and exome capture, for sample sizes of five to 48 individuals. We also extracted low‐coverage genome resequencing of 1×, 2× and 5× by randomly subsampling reads from the 12× resequencing data. Globally, 5K to 10K random variants were enough for an accurate estimation of genome diversity. Conversely, commercial panels and exome capture displayed strong ascertainment biases. Besides the characterization of neutral diversity, the detection of the signature of selection and the accurate estimation of linkage disequilibrium (LD) required high‐density panels of at least 1M variants. Finally, genotype likelihoods increased the quality of variant calling from low coverage resequencing but proportions of incorrect genotypes remained substantial, especially for heterozygote sites. Whole genome resequencing coverage of at least 5× appeared to be necessary for accurate assessment of genomic variations. These results have implications for studies seeking to deploy low‐density SNP collections or genome scans across genetically diverse populations/species showing similar genetic characteristics and patterns of LD decay for a wide variety of purposes.     

How initiation factors maximize the accuracy of tRNA selection in initiation of bacterial protein synthesis

During initiation of bacterial protein synthesis, messenger RNA and fMet-tRNAfMet bind to the 30S ribosomal subunit together with initiation factors IF1, IF2, and IF3. Docking of the 30S preinitiation complex to the 50S ribosomal subunit results in a peptidyl-transfer competent 70S ribosome. Initiation with an elongator tRNA may lead to frameshift and an aberrant N-terminal sequence in the nascent protein. We show how the occurrence of initiation errors is minimized by (1) recognition of the formyl group by the synergistic action of IF2 and IF1, (2) uniform destabilization of the binding of all tRNAs to the 30S subunit by IF3, and (3) an optimal distance between the Shine-Dalgarno sequence and the initiator codon. We suggest why IF1 is essential for E. coli, discuss the role of the G-C base pairs in the anticodon stem of some tRNAs, and clarify gene expression changes with varying IF3 concentration in the living cell.     

Comparison of genotype imputation strategies using a combined reference panel for chicken population

Using whole-genome sequence (WGS) data are supposed to be optimal for genome-wide association studies and genomic predictions. However, sequencing thousands of individuals of interest is expensive. Imputation from single nucleotide polymorphisms panels to WGS data is an attractive approach to obtain highly reliable WGS data at low cost. Here, we conducted a genotype imputation study with a combined reference panel in yellow-feather dwarf broiler population. The combined reference panel was assembled by sequencing 24 key individuals of a yellow-feather dwarf broiler population (internal reference panel) and WGS data from 311 chickens in public databases (external reference panel). Three scenarios were investigated to determine how different factors affect the accuracy of imputation from 600 K array data to WGS data, including: genotype imputation with internal, external and combined reference panels; the number of internal reference individuals in the combined reference panel; and different reference sizes and selection strategies of an external reference panel. Results showed that imputation accuracy from 600 K to WGS data were 0.834±0.012, 0.920±0.007 and 0.982±0.003 for the internal, external and combined reference panels, respectively. Increasing the reference size from 50 to 250 improved the accuracy of genotype imputation from 0.848 to 0.974 for the combined reference panel and from 0.647 to 0.917 for the external reference panel. The selection strategies for the external reference panel had no impact on the accuracy of imputation using the combined reference panel. However, if only an external reference panel with reference size >50 was used, the selection strategy of minimizing the average distance to the closest leaf had the greatest imputation accuracy compared with other methods. Generally, using a combined reference panel provided greater imputation accuracy, especially for low-frequency variants. In conclusion, the optimal imputation strategy with a combined reference panel should comprehensively consider genetic diversity of the study population, availability and properties of external reference panels, sequencing and computing costs, and frequency of imputed variants. This work sheds light on how to design and execute genotype imputation with a combined external reference panel in a livestock population.     

Simulated long-term vegetation response to alternative stocking strategies in savanna rangelands

Increasing cover by woody vegetation, prevalent in semiarid savanna rangelands throughout the world, is a degrading process attributed to the grazing impact as a major causal factor. We studied grazing effects on savanna vegetation dynamics under alternative stocking strategies with a spatially explicit grid-based simulation model grounded in Kalahari (southern Africa) ecology. Plant life histories were modeled for the three major life forms: perennial grasses, shrubs, annuals. We conducted simulation experiments over a range of livestock utilization intensities for three alternative scenarios of small scale grazing heterogeneity, and two alternative strategies: fixed stocking versus adaptive stocking tracking herbage production. Additionally, the impact of the duration of the management planning horizon was studied, by comparing community response and mean stocking rates after 20 and 50 years. Results confirmed a threshold behavior of shrub cover increase: at low, subcritical utilization intensity little change occurred; when utilization intensity exceeded a threshold, shrub cover increased drastically. For both stocking strategies, thresholds were highly sensitive to grazing heterogeneity. At a given critical utilization intensity, the long term effect of grazing depended on the level of grazing heterogeneity: whereas under low heterogeneity, shrub cover remained unchanged, a large increase occurred under highly heterogeneous grazing. Hence, information on spatial grazing heterogeneity is crucial for correct assessment of the impact of livestock grazing on vegetation dynamics, and thus for the assessment of management strategies. Except for the least heterogeneous grazing scenario, adaptive stocking allowed a more intensive utilization of the range without inflating the risk of shrub cover increase. A destabilizing feedback between rainfall and herbage utilization was identified as the major cause for the worse performance of fixed compared to adaptive stocking, which lacks this feedback. Given the usually high grazing heterogeneity in semiarid rangelands, adaptive stocking provides a management option for increasing herbage utilization and thus returns of livestock produce without increasing degradation risks.