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Continuous probabilistic genotyping (PG) systems are becoming the default method for calculating likelihood ratios (LRs) for competing propositions about DNA mixtures. Calculation of the LR relies on numerical methods and simultaneous probabilistic simulations of multiple variables rather than on analytical solutions alone. Some also require modelling of individual laboratory processes that give rise to electropherogram artefacts and peak height variance. For these reasons, it has been argued that any LR produced by continuous PG is unique and cannot be compared with another. We challenge this assumption and demonstrate that there are a set of conditions defining specific DNA mixtures which can produce an aspirational LR and thereby provide a measure of reproducibility for DNA profiling systems incorporating PG. Such DNA mixtures could serve as the basis for inter-laboratory comparisons, even when different STR amplification kits are employed. We propose a procedure for an inter-laboratory comparison consistent with these conditions.

Current analysis of forensic DNA stains relies on the probabilistic interpretation of bulk-processed samples that represent mixed profiles consisting of an unknown number of potentially partial representations of each contributor. Single-cell methods, in contrast, offer a solution to the forensic DNA mixture problem by incorporating a step that separates cells before extraction. A forensically relevant single-cell pipeline relies on efficient direct-to-PCR extractions that are compatible with standard down- stream forensic reagents. Here we demonstrate the feasibility of implementing single-cell pipelines into the forensic process by exploring four metrics of electropherogram (EPG) signal quality—i.e., allele detection rates, peak heights, peak height ratios, and peak height balance across low- to high-molecular-weight short tandem repeat (STR) markers—obtained with four direct-to-PCR extraction treatments and a common post-PCR laboratory procedure. Each treatment was used to extract DNA from 102 single buccal cells, whereupon the amplification reagents were immediately added to the tube and the DNA was amplified/injected using post-PCR conditions known to elicit a limit of detection (LoD) of one DNA molecule. The results show that most cells, regardless of extraction treatment, rendered EPGs with at least a 50% true positive allele detection rate and that allele drop-out was not cell independent. Statistical tests demonstrated that extraction treatments significantly impacted all metrics of EPG quality, where the Arcturus® PicoPure™ extraction method resulted in the lowest median allele drop-out rate, highest median average peak height, highest median average peak height ratio, and least negative median values of EPG sloping for GlobalFiler™ STR loci amplified at half volume. We, therefore, conclude the feasibility of implementing single-cell pipelines for casework purposes and demonstrate that inferential systems assuming cell independence will not be appropriate in the probabilistic interpretation of a collection of single-cell EPGs.

Background: Monoclonal protein (M-protein) concentrations are measured by serum protein electrophoresis (SPE). Two methods are used for demarcating the M-protein area in the electropherogram: perpendicular drop (PD) and tangent skimming (TS). The aim of this study was to compare both methods and to establish which is the most accurate and precise. Methods: We studied 24 sera containing M-protein (5-44 g/L). The systematic error (SE) was evaluated in a dilution series of 12 sera. Within-day, between-day, and interobserver variability were assessed. SPE was performed by capillary and agarose gel electrophoresis. M-protein concentrations were measured using both cutoff methods. Results: The PD method shows a constant SE ranged 1.00-2.27 g/L, while constant SE for TS is ranged - 0.30-- 0.57 g/L. None of the cutoff methods or electrophoretic methods showed a proportional SE, with the exception of the TS method in capillary electrophoresis for beta-migrating M-protein. The PD method was more precise than the TS method in all three estimates of imprecision. An increased CV for concentrations < 10 g/L in between-day imprecision was observed with the TS method. Interobserver imprecision was greater for M-protein concentrations < 17 g/L for both cutoff methods (14.85%, 26.42% respectively). Conclusions: Despite being less precise, the TS method provides a more accurate measurement of M-protein concentration.

Fluorescent microspheres (FMs) are widely employed in diagnostics and life sciences research; here, we investigated the effect of capillary coating, polymer concentration, electric field strength, and sample concentration on the separation performance of 1.0 μm FMs in hydroxyethyl cellulose (HEC) by capillary electrophoresis (CE). Results showed that (1) capillary coating could enhance the fluorescence signal. (2) For HEC with the same molecular weight, the higher HEC concentration is, the later the first peak appears in the electropherogram. (3) When FMs are diluted, increasing the electric field strength can enhance the migration speed and reduce the aggregation of FMs. (4) The number of FMs calculated is close to the theoretical value when it is diluted 10,000 times. The optimum conditions for CE were as follows: 6 cm/8 cm of effective length and total length of the coated capillary, 0.3% HEC (1300 k), and 300 V/cm of electric field strength. Such a study is helpful for the development of a FM counting system. Graphical abstract.

A simple and robust ultra-small four-color-fluorescence detection system was developed by integrating its components, namely, a four-capillary array, an injection-molded-plastic four-lens array, a four-dichroic-mirror array, and a CMOS sensor, as one device. The developed system was applied to a high-dynamic-range capillary-array electrophoresis (HiDy CE) to quantify a rare EGFR mutant (MT) of exon 19 deletion in a large excess of EGFR wild type (WT). Samples with serially diluted MT and constant-concentration WT were co-amplified by competitive PCR and subjected to HiDy CE. The MT peak in each electropherogram was then compared to the WT peak. As a result, MT was quantified with high-sensitivity (LOD of 0.004% MT/WT) and four-orders-of-magnitude dynamic range (0.01-100% MT/WT) by HiDy CE. Moreover, compared with existing methods, HiDy CE achieves higher speed, higher sample throughput, and lower consumable cost per sample. It has therefore great potential to be used in clinical practice.

The significant demands for single nucleotide polymorphism detection and genotyping assays have grown. Most common assays are based on the recognition of the target sequence by the hybridization with its specific probe having the complementary sequence of the target. Herein, a simple, label-free, and economical non-hybridization assay was developed for single nucleotide polymorphism detection and genotyping, based on the direct discrimination of single base mutation by simple capillary electrophoresis separation for single-stranded DNA in an acidic electrophoretic buffer solution containing urea. Capillary electrophoresis separation of single-base sequential isomers of DNA was achieved due to charge differences resulting from the different protonation properties of the DNA bases. Single nucleotide polymorphism detection and genotyping were achieved by discriminating the electropherogram pattern change, that is, peak number in the electropherogram, obtained by the proposed method. The successful practical application of the proposed method was demonstrated through single nucleotide polymorphism detection and genotyping on a known gene region of 84-mer, in which guanine to adenine single-base mutation is commonly observed, using a human hair sample in combination with genomic DNA extraction, polymerase chain reaction amplification, DNA purification from polymerase chain reaction products, and capillary electrophoresis separation.

An electrokinetically pumped sheath-flow nanoelectrospray interface provides an efficient means of transferring ions from a capillary electrophoresis system into a mass spectrometer. To characterize its performance, we analyzed angiotensin solutions prepared in a background of 0.25 mg/mL of a BSA tryptic digest. Calibration curves were prepared from 10 zeptomole (10(−21) mol) to 10 femtomole (10(−14) mol) of angiotensin injected into the capillary. A parallel reaction monitoring approach was used; MS1 was set to m/z = 523.8 ± 2, and fragment ion signals at 263.1389 (y(2+)) and 784.4095 (b(6+)) were used to generate selected ion electropherograms. Calibration curves based on peak areas were linear (log-log slope of 0.94 for the y(2+) fragment and 0.98 for the b(6+) fragment). We then injected 1-zmol (600 copies) of angiotensin in the BSA background using a 10-μm ID separation capillary. Triplicate analyses consistently produced co-migrating peaks for the two fragment ions. The b(6+) electropherogram showed no background signal, whereas the y(2+) electropherogram showed a few noise spikes that were smaller than the peak maximum. Bienayme-Tchebycheff inequality was used to estimate detection limits of 230 ymol (140 ions) injected into the separation capillary. To the best of our knowledge, these electropherograms present the smallest number of molecules detected using mass spectrometry coupled with a separation.

DNA profiles are generated in forensic biology laboratories around the world. It is possible that these profiles are assessed by two independent people in order for the profiles to be ‘read’. Recent work has been carried out to develop a neural network model to classify fluorescence in a DNA profile electropherogram and potentially replace one, or both human readers. The ability to use neural networks for this function has been programmed into the software FaSTR™ DNA, which has been validated for use in at least one laboratory in Australia. The work that previously developed a neural network system had a number of limitations, specifically it was computer intensive, did not make the best use of available data, and consequently the performance of this model was sub-optimal in some conditions (particularly for low-intensity peaks). In the current work a new neural network model is developed that makes various improvements on the old model, by using convolutional layers, a multi-head architecture and data augmentation. Results indicate that an improved performance can be expected for low-intensity profiles.

This study shows that the upper limit of binding (stability) constants determined by mobility shift affinity capillary electrophoresis can be increased from 104 to 106 -109 L/mol if the lowest possible analyte concentration in samples is used (for example, the concentration that gives electrophoretic peaks with a signal-to-noise ratio of 10) and the effective electrophoretic mobility of the analyte is calculated via the parameter a1 of the Haarhoff-Van der Linde function. The equation to calculate the boundary values of binding constants for 1:1 complexes was derived for the case when the constants cannot be calculated in the usual way. These values are obtained from the inequality: the difference between the ionic mobility of the analyte-ligand complex and the effective electrophoretic mobility of the analyte determined at the lowest ligand concentration in the background electrolyte at which the analyte appears as an undistorted peak in electropherograms is less than or equal to the absolute error in mobility measurements. The application of the equation was illustrated by the example of electrophoretic data for a complex between betulin 3,28-diphthalate and (2-hydroxypropyl)-γ-cyclodextrin. An algorithm to determine the binding constants for strong complexation by mobility shift affinity capillary electrophoresis was suggested.

Although insect exuviae-based genetics is challenging, it can be a valuable method for obtaining reliable DNA resources by non-invasive sampling. This approach is especially effective when the target species is endangered/endemic or when sampling the adult is difficult. One example is cicadas, which during molt leave their exoskeletons on tree trunks, making them easily collectable. While cicada exuviae-derived DNA has previously been employed for mitochondrial DNA sequencing, this study aimed to develop a reliable method for the PCR amplification of nuclear microsatellite loci from cicada exuviae derived DNA for application in molecular ecology, conservation and population genetics. Five different PCR amplification protocols were performed, and the fragment patterns compared with those obtained using DNA extracted from adult individuals. Moreover, the relationship between the freshness of the exuviae and genotyping success was evaluated. TaKaRa LA Taq provided the best performance in the PCR amplification of DNA isolated from cicada exuviae and the electropherogram showed a clear fragment pattern that was equivalent to that obtained from the DNA extracted from the adult individual. This result suggests that cicada exuviae-derived DNA can be amplified by PCR and that multiple independent loci of nuclear DNA microsatellite markers can be easily genotyped. This study demonstrates that fresh cicada exuviae provide high quality DNA, which can be used for microsatellite genotyping. The methods developed in this study are applicable not only for cicada but other insect species for which exuviae are available. Thus, this study can make a significant contribution to insect sciences.

CE–MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility‐scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE–MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self‐contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV‐Vis absorption‐like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data.

The conventional capillary electrophoresis (CE) genotyping workflow used in forensic DNA laboratories is composed of two processes: measurement and interpretation. The outcome of the measurement process is an electropherogram (EPG). The outcome of the interpretation process is a strength of evidence statement often reported in the form of a likelihood ratio (LR) which typically requires probabilistic genotyping software (PGS). An LR system is defined as the entire pipeline of the measurement and interpretation processes where PGS is a piece of the whole LR system. To gain understanding on how two LR systems perform, a total of 154 two-person mixture, 147 three-person mixture, and 127 four-person mixture profiles of varying DNA quality, DNA quantity, and mixture ratios were obtained from the filtered (.CSV) files of the GlobalFiler 29 cycles 15s PROVEDIt dataset and deconvolved in two independently developed fully continuous programs, STRmix v2.6 and EuroForMix v2.1.0. Various parameters were set in each software and LR computations obtained from the two software were based on same/fixed EPG features, same pair of propositions, number of contributors, theta, and population allele frequencies. The ability of each LR system to discriminate between contributor (H1-true) and non-contributor (H2-true) scenarios was evaluated qualitatively and quantitatively. Differences in the numeric LR values and their corresponding verbal classifications between the two LR systems were compared. The magnitude of the differences in the assigned LRs and the potential explanations for the observed differences greater than or equal to 3 on the log10 scale were described. Cases of LR < 1 for H1-true tests and LR > 1 for H2-true tests were also discussed. Our intent is to demonstrate the value of using a publicly available ground truth known mixture dataset to assess discrimination performance of any LR system and show the steps used to investigate and understand similarities and differences between different LR systems. We share our observations with the forensic community and describe how examining more than one PGS with similar discrimination power can be beneficial, help analysts compare interpretation especially with low-template profiles or minor contributor cases, and be a potential additional diagnostic check even if software in use does contain certain diagnostic statistics as part of the output.HighlightsThe use of two different Likelihood Ratio (LR) systems to assign LRs is discussed.H1-true and H2-true tests are performed using STRmix and EuroForMix and a large set of PROVEDIt mixture profiles.Assessment of discrimination performance of two LR systems using ROC plots, scatter plots, and relative frequency histograms.The ability of the two LR systems to discriminate between contributors and non-contributors are statistically indistinguishable for the data that we considered.Potential reasons for the differences in LR values between the two LR systems that are ≥ 3 on the log10 scale are investigated and discussed.Contributors with LRs < 1 and non-contributors with LRs > 1 generated from each LR system are discussed.

Dear Editor A recent publication [1] has claimed to address criticism of probabilistic genotyping by the President’s Council of Advisors on Science and Technology (PCAST) report [2] and addendum [3]. PCAST considered probabilistic genotyping to have “foundational validity … under limited circumstances (specifically, a three-person mixture in which the minor contributor constitutes at least 20 percent of the DNA in the mixture), but that substantially more evidence is needed to establish foundational validity across broader settings” [2]. For more than three contributors and/or for mixtures with minor contributors constituting less than 20% of the DNA, PCAST recommends “the creation and dissemination … of large collections of hundreds of DNA profiles created from known mixtures” [2]. Bright et al. [1] draw upon guidelines for testing reliability and validity of probabilistic genotyping published by The Scientific Working Group on DNA Analysis Methods (SWGDAM) [4] and the International Society for Forensic Genetics (ISFG) [5] to produce an internal validation of continuous probabilistic genotyping using STRmix™ on electropherogram (epg) outputs provided by multiple laboratories. Their study extends an internal validation performed only in the FBI Laboratory at Quantico, Virginia (USA) [6]. We believe that the publication by Bright et al. [1] is a valuable first step in the direction of establishing a foundational validity for mixture interpretation using probabilistic software, as recommended by the PCAST report. We hope that our suggestions would help to better address this issue.

An ‘Autologous Blood Transfusion’ (ABT) is the reinjection of blood previously taken from an athlete to increase its oxygen transport capabilities. Despite the World Anti-Doping Agency's ban on such practices, ABT abuse continues. Autologous blood doping (ABD) is challenging to detect because of the similarities between an individual's doped and undoped blood. Recently, Harrison et al. reported that high-speed capillary electrophoresis may identify ABD. In their work, first order derivatives of the electropherograms were used to identify doping. However, this method suffered from false negatives due to the subjective nature of the analysis. Here, we provide an informatics analysis of the data from this study, contrasting the results of traditional statistical methods and less traditional mathematical techniques. First, three well-known multivariate statistical tools: cluster analysis, principal component analysis (PCA), and partial least squares (PLS) are applied to develop calibrations and/or group electropherograms of undoped (0%) and doped (5% and 10%) blood samples. (These doping levels were chosen due to the low physiological effect of doping below 5%, with 10% corresponding to the approximate ‘gain’ derived from the transfusion of a single unit of blood into an adult.) Different preprocessing and variable selection methods were considered. Due to variation in the electropherograms and the limited sample size, these methods were inadequate. We next considered four less commonly used mathematical/informatics tools: pattern recognition entropy (PRE), the Euclidean distance between vectors, a peak fitting/integration method, and the second moment (SM). Each of these techniques showed some ability to differentiate between the 0, 5, and 10% doped samples. We then evaluated the prediction capabilities of inverse least squares (ILS) models based on these summary statistics. An ILS calibration based on PRE, the Euclidean distance, and peak fitting/integration proved more successful than the PLS model at predicting levels of blood doping from the corresponding electropherograms; the ILS model distinguished between doped (5% and 10%) and undoped (0%) blood. This methodology may be applicable to other challenging informatics problems like determining risk factors for genetically linked diseases, robust pattern finding in peak-like data such as ChIP-seq, or other genomic sequencing for understanding the 3D genome.

CE application in aptamer selection (CE-SELEX) shows more advantages than other selection methods. In this study, an online reaction based single-step CE (ssCE) mode was employed for fast obtaining protein-ssDNA complex. Using human thrombin (H-Thr) and its aptamer Apt29 as models, we accomplished the procedures of mixing, reaction, separation, detection and complex collection in single step online process, which took about 10 min to obtain the H-Thr/Apt29 complex. Important factors, affecting the aptamer and H-Thr interaction (buffer, ratio of aptamer and H-Thr amount), and complex separation and collection (voltage and temperature) were discussed. Later, the online reaction of H-Thr with an 80 nt ssDNA library was realized under optimized conditions, and the H-Thr/ssDNA complex was collected and subjected to PCR. By analyzing the PCR product through capillary gel electrophoresis, the resulting approximative 80 nt DNA length validated the ssDNA sequence in complex. To confirm the availability of ssCE mode, two ssDNA libraries with different lengths (56 nt and 82 nt ssDNA) and three proteins (platelet derived growth factor, PDGF-BB; lactoferrin protein, LF; and single-strand DNA binding protein, SSB) were utilized. Their complex peaks were also observed in electropherograms as expected. Additionally, the online incubation of ssDNA and H-Thr was achieved by stopping the separation voltage for some time when ssDNA passed the H-Thr zone. Our results show the ssCE mode has apparent merits of saving time and sample cost for aptamer selection against protein targets.

Interlaboratory studies are a type of collaborative exercise in which many laboratories are presented with the same set of data to interpret, and the results they produce are examined to get a "big picture" view of the effectiveness and accuracy of analytical protocols used across participating laboratories. In 2005 and again in 2013, the Applied Genetics Group of the National Institute of Standards and Technology (NIST) conducted interlaboratory studies involving DNA mixture interpretation. In the 2005 NIST MIX05 study, 69 laboratories interpreted data in the form of electropherograms of two-person DNA mixtures representing four different mock sexual assault cases with different contributor ratios. In the 2013 NIST MIX13 study,108 laboratories interpreted electropherogram data for five different case scenarios involving two, three, or four contributors, with some of the contributors potentially related. This paper describes the design of these studies, the variations observed among laboratory results, and lessons learned.

Although forensic DNA testing is well established, some experts disagree with the interpretation and statistical significance of test results obtained from very small samples. This article discusses the problems regarding the use of the low copy number (LCN) technique as well as the value that can be derived from such an analysis. It focuses on the problematic results that can arise from using very small samples for forensic DNA identification. Since this kind of analysis is based on low amounts of DNA samples (between 100 picograms and 200 picograms in South Africa) that are amplified by using more than the normal 28 cycles to create larger samples for analysis, the reliability of the analysis has been questioned. The amplification process, known as the Polymerase Chain Reaction (PCR), is associated with risks such as stochastic effects and contamination that could make interpretation of the results difficult for the defence. While standard operating laboratory protocols could prevent contamination and although the electropherograms could aid the detection of contamination, it is highly problematic for the defence counsel to ascertain whether these procedures were indeed strictly followed. Drawing on foreign jurisprudence, this article considers the risks and key controversies and explains what lawyers need to know, in order to be able to recognise controversial results that could stem from using the LCN DNA technique for forensic DNA identification. The conclusions thus drawn may be of particular relevance to the South African context, as no reported case law exists in which the issues relating to the use of LCN DNA have yet come to the fore.

Complex DNA mixtures are challenging to interpret and require computational tools that aid in that interpretation. Recently, several computational methods that estimate the number of contributors (NOC) to a sample have been developed. Unlike analogous tools that interpret profiles and report LRs, NOC tools vary widely in their operational principle where some are Bayesian and others are machine learning tools. Conjunctionally, NOC tools may return a single n estimate, or a distribution on n. This vast array of constructs, coupled with a gap in standardized methods by which to validate NOC systems, warrants an exploration into the measures by which differing NOC systems might be tested for operations. In the current paper, we use two exemplar NOC systems: a probabilistic system named NOCIt, which renders an a posteriori probability (APP) distribution on the number of contributors given an electropherogram and an artificial neural network (ANN). NOCIt is a continuous Bayesian inference system incorporating models of peak height, degradation, differential degradation, forward and reverse stutter, noise and allelic drop-out while considering allele frequencies in a reference population. The ANN is also a continuous method, taking all the same features (barring degradation) into account. Unlike its Bayesian counterpart, it demands substantively more data to parameterize, requiring synthetic data. We explore each system’s performance by conducting tests on 214 PROVEDIt mixtures where the limit of detection was 1-copy of DNA. We found that after a lengthy training period of approximately 24 h, the ANN’s evaluation process was very fast and perfectly repeatable. In contrast, NOCIt only took a few minutes to train but took tens of minutes to complete each sample and was less repeatable. In addition, it rendered a probability distribution that was more sensitive and specific, affording a reasonable method by which to report all reasonable n that explain the evidence for a given sample. Whatever the method, by acknowledging the inherent differences between NOC systems, we demonstrate that validation constructs will necessarily be guided by the needs of the forensic domain and be dependent upon whether the laboratory seeks to assign a single n or range of n.

A novel method for Sanger DNA sequencing, as part of a compact and inexpensive DNA sequencer, using the RGB image sensor of a digital color camera was developed. Since the RGB image sensor can only detect up to three colors (wavelength bands), while Sanger DNA sequencing is required to detect four or more colors in order to quantify fluorescence of four different fluorophores in a mixed state during capillary electrophoresis, it is difficult to perform Sanger DNA sequencing using an RGB image sensor. Moreover, due to the spectral response of an RGB image sensor, fluorescence of the four fluorophores is detected only on the red and green channels, that is, not on the blue channel. To address the above-described issues, a two-color electropherogram was obtained by capillary electrophoresis of a sequencing sample and reproduced by best local fittings of two-color single peaks of the four fluorophores in chronological order. The fitted single peaks of the four fluorophores respectively give fluorescence intensities of the four fluorophores. That is, the two-color electropherogram is converted to a four-fluorophore electropherogram. The proposed Sanger-DNA-sequencing method was applied to a model sequencing sample, and the DNA sequence of 69-144 bases of the sample was accurately determined. This result is the first successful quantification of four or more fluorophores in a mixed state by using an RGB image sensor.

The reproducibility in migration time is essential in the use of capillary electrophoresis to identify components in a complex sample or compare constituent differences for different botanical drug samples. A powerful one-marker technology for correcting migration time was proposed in this paper. This technology is practically simple compared with the multi-marker technologies developed in literature, due to only one marker required. Paeoniae Radix which is a crude drug used in many traditional prescriptions in China and Japan was selected as an example to verify the effectiveness of the powerful one-marker technology in analyzing complex botanical samples. Relative standard deviations in migration times treated with the powerful one-marker technology were below 0.5% for Paeoniae Radix analyzed during three different days. The technology was successfully applied to classify Paeoniae Radix from nine different growing regions. Based on their corrected electropherograms, Paeoniae Radix was classified into three groups which were in agreement with their real origins.

As a fast, high-performance and cost-effective separation technique, capillary electrophoresis (CE) is applicable to the screening and diagnosis of diseases such as thalassemia. However, it is often not preferred due to its unrepeatable and/or irreproducible migration times. Herein, we propose a stable version of CE that uses migration charge density instead of the migration time to plot the electropherogram. The peak position is now independent of the applied voltage or current and the capillary geometry and is also insensitive to temperature. Its applicability was demonstrated in the quantitative analysis of human hemoglobin. On a laboratory-built device, with a running buffer simply consisting of 3.0 M acetic acid and 0.1% (w/v) hydroxyethyl cellulose, it allows a direct injection of whole blood samples and all the concerned globin chains, α, β, Aγ and Gγ can be well separated in 15 minutes. The resolution of α/β, β/Aγ, and Aγ/Gγ reached 4.4, 3.1 and 5.3, respectively. The intra- and inter-day precisions for the peak position based on the migration charge densities were below 0.6%. Its diagnostic applicability was validated in the analysis of several real blood samples from newborns, children and adults, and its capacity was demonstrated to screen and define the type of thalassemia.

Capillary electrophoresis often causes unrepeatable peak migration times in the electropherogram due to changes of electroosmosis, yet in some cases this separation technique does not have a replacement alternative. Some attempts to overcome this issue have been performed introducing internal standards into the sample and compensating peak shifting in time. However, existing vector calculation-based methods are computationally intensive for portable instrumentation and usually limited to post-processing applications with 1 or 2 markers. In this work, an original approach of compensating peak migration time shift via signal discretization period correction is proposed. Using the proposed method, the number of reference points or markers that are used for compensation is extended. This method is effective in compensating migration time of peaks in real samples, where high sample injection volumes are used. Using 4 reference peaks in compensation, the method was capable of reducing the relative standard deviation of migration time of the peaks in the electropherograms more than 15 times. Corrected signal discretization periods indicated very high correlations with recorded separation currents, what can be perspective developing an adaptive peak migration time compensation method in capillary electrophoresis.

Capillary electrophoresis coupled to mass spectrometry (CE-MS) is increasingly gaining momentum as an analytical tool in metabolomics, thanks to its ability to ob- tain information about the most polar elements in biological samples. This has been helped by improvements in peak robustness by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step towards the use of CE- MS for untargeted metabolomics data, the authors previously developed and introduced the ROMANCE software, with the purpose of automating mobilogram generation for large untargeted datasets while offering a simple and self-contained user interface. In natural continuation ROMANCE has been upgraded to its v2 to read other types of data (targeted MS data and 2D UV-like electropherograms), offer more flexibility in the transformation parameters (including field ramping delays and the use of sec- ondary markers), more measurement conditions (depending on detection and ionization modes), and most importantly tackle the issue of quantitative CE-MS. To prepare the ground for such an upgrade, we present a review of the current theoretical framework with regards to peak reproducibility and quantification, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. We then present the new version of the software, and validate it experimentally. We contrast the multiple marker mobility transfor- mations with previous results, finding increased precision, and finally we showcase an application to actual untargeted metabolomics data.

Dynamic pH barrage junction focusing in CE enables effective signal enhancement, quantitative capture efficiencies, and straightforward optimization. The method is a technical variant of dynamic pH junction focusing. CE separation with dynamic pH barrage junction focusing is compatible with both optical and mass spectrometric detection. We developed a CE-MS/MS method using hydrophilic polyethyleneimine-coated capillaries and validated it for the qualitative analysis of amino acids, peptides, and tryptic peptides of digested monoclonal antibodies. The S/N of extracted ion electropherograms of zwitterionic analytes were enhanced by approximately two orders of magnitude with a tradeoff of a shortened separation window. Online focusing improved the MS signal intensity of a diluted antibody digest, enabling more precursor ions to be analyzed with subsequent tandem mass spectrometric identification. It also broadened the concentration range of protein digest samples for which adequate sequence coverage data can be obtained. With only 0.9 ng of digested infliximab sample loaded into the capillary, 76% and 100% sequence coverage was realized for antibody heavy and light chains, respectively, after online focusing. Full coverage was achieved with 9 ng of injected digest.

A micro-capillary electrophoresis (μCE) system is one of the widely adopted techniques in the molecular diagnostics and DNA sequencing due to the benefits of high resolution, rapid analysis, and low reagent consumption, but due to the requirements of bulky high-power suppliers and an expensive laser-induced fluorescence detector module, the conventional set-up of μCE system is not adequate for point-of-care (POC) molecular diagnostics. In this study, we constructed a miniaturized and integrated μCE system which can be manipulated by a smartphone. The smartphone not only powers two boost converters and an excited laser, but also controls the relay for the power switch. Moreover, the complementary metal-oxide-semiconductor (CMOS) camera of the smartphone was used for detecting the fluorescence signal of amplicons amplified with reverse transcription-polymerase chain reaction (RT-PCR). We also developed a web-based application so that the raw data of the recorded fluorescence intensity versus the running time can display typical capillary electropherograms on the smartphone. The total size of the hand-held μCE system was 9.6 cm [Width] × 22 cm [Length] × 15.5 cm [Height], and the weight was ∼1 kg, which is suitable for POC DNA testing. In the integrated smartphone-associated μCE system, we could accurately analyze two genes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), namely N gene and S gene along with two bracket ladders in 6 min to identify SARS-CoV-2. Such an advanced μCE platform can be applied for a variety of on-site molecular diagnostics fields with user-friendliness.

Identification of semen and then spermatozoa is essential to verify that sexual activity has occurred in alleged cases of sexual assault. Microscopic examination commonly used for spermatozoa identification is however time-consuming and can often lead to false-negative results for samples with deformed and, or, limited number of spermatozoa. To address this limitation, we report on a novel 3-plex MSRE-PCR (methylation-sensitive restriction enzyme-PCR) assay to specifically identify spermatozoa. This assay is comprised of 3 markers: a digestive control marker (DC), sperm-specific marker (SP), and Y chromosome marker (SRY). A total of 214 samples from 10 body fluids or tissues were analyzed. Specificity testing showed that all the normal semen samples were unambiguously identified as being sperm-positive, and no other body fluid (or tissues) showed a sperm-specific signal in the electropherogram. Testing for sensitivity showed that 0.1 ng of DNA from a semen extract was sufficient to identify the presence of spermatozoa by this assay. Mixture analyses illustrated the sensitivity of the assay when the vaginal/semen DNA ratio (80/0.1) was under 800 or the menstrual blood/semen DNA ratio (5/0.1) was under 50, the trace amounts (approximately 0.1 ng) of DNA from semen can still be identified by this 3-plex MSRE-PCR assay. This assay was also applied to the identification of 31 non-probative forensic samples from 18 sexual assault cases. The case studies showed that the 3-plex MSRE-PCR assay was an improvement in the sensitivity of spermatozoa detection.

Capillary electrophoresis provides a rapid, cost-effective platform for enzyme and substrate characterization. The high resolution achievable by capillary electrophoresis enables the analysis of substrates and products that are indistinguishable by spectroscopic techniques alone, while the small volume requirement enables analysis of enzymes or substrates in limited supply. Furthermore, the compatibility of capillary electrophoresis with various detectors makes it suitable for KM determinations ranging from nanomolar to millimolar concentrations. Capillary electrophoresis fundamentals are discussed with an emphasis on the separation mechanisms relevant to evaluate sets of substrate and product that are charged, neutral, and even chiral. The basic principles of Michaelis-Menten determinations are reviewed and the process of translating capillary electrophoresis electropherograms into a Michaelis-Menten curve is outlined. The conditions that must be optimized in order to couple off-line and on-line enzyme reactions with capillary electrophoresis separations, such as incubation time, buffer pH and ionic strength, and temperature, are examined to provide insight into how the techniques can be best utilized. The application of capillary electrophoresis to quantify enzyme inhibition, in the form of KI or IC50 is detailed. The concept and implementation of the immobilized enzyme reactor is described as a means to increase enzyme stability and reusability, as well as a powerful tool for screening enzyme substrates and inhibitors. Emerging techniques focused on applying capillary electrophoresis as a rapid assay to obtain structural identification or sequence information about a substrate and in-line digestions of peptides and proteins coupled to mass spectrometry analyses are highlighted.

One of the main problems of the remote complex sample analysis instrumentation is that such systems are susceptible to temperature fluctuations. Temperature regulation is energetically ineffective, and it is not used in most of the field portable analytical systems. Separations performed in a changing temperature environment provide electropherograms with considerable baseline fluctuations, resulting in significant errors in detection and integration of the peaks. This paper describes electropherogram baseline compensation that is suitable for the capillary electrophoresis-contactless conductivity detection analytical method. The baseline compensation utilizes linear or polynomial data processing methods, and can be programmed in-line using simple microcontroller, or on-line and off-line in data acquisition software. This method is targeted for field portable and autonomous analytical systems that are utilized in a fluctuating environment.

Current models for single source and mixture samples, and probabilistic genotyping software based on them used for analysing STR electropherogram data, assume simple probability distributions, such as the gamma distribution, to model the allelic peak height variability given the initial amount of DNA prior to PCR amplification. Here we illustrate how amplicon number distributions, for a model of the process of sample DNA collection and PCR amplification, may be efficiently computed by evaluating probability generating functions using discrete Fourier transforms.

We report the first successful implementation of a multiplexing method on a standard capillary electrophoresis system with UV detection that is independent of additional hardware. This was achieved using the Hadamard transform approach and employing vial exchange and voltage suspensions for translation of pseudorandom binary sequence elements into sample and background electrolyte injections of a capillary zone electrophoresis separation. Sequences exceeding peak capacity of the capillary were subdivided into shorter subsequences measured successively and realigned afterward based on EOF marker or analyte peaks. This way, we realized and deconvoluted modulation sequences as long as 8-bit (255 injections) for two systems containing either AMP or a mixture of the nucleotides (A,C,G,U)MP resulting in electropherograms of considerably improved signal-to-noise ratio. We achieved factors of intensity enhancement of around 6.9 and 5.2, respectively (theoretical maximum 8.0). This contribution, further, presents experimental and simulation studies on the effects on zones during injection and separation when experiencing voltage suspensions. Besides analysis of EOF behavior and influence of diffusion dispersion, we also provide data on the significance of specific electrophoretic errors such as peak position shift, inconsistent sample injection, and peak broadening on the quality of the inverse Hadamard transform. Moreover, the application of our approach to the practical analysis of a milk sample is described. The results demonstrate the applicability of multiplexing on unmodified standard CE instrumentation and establish a new suitable methodology to enhance the low sensitivity of on-column UV detection in capillary electrophoresis.

This paper presents for the first time the use of an inkjet 3D printing to develop a chip for capillary gel electrophoresis. The designing of the chip is preceded by investigations into surface roughness and the geometrical properties of the printed microchannels, which are important considerations for the separation process. The optical properties of the building material are also determined to confirm whether fluorescence detection is possible. It is found that the printing orientation of the microchannels plays a crucial role in the proper operation of the separation process. A description of the successful separation of a 50–800 bp DNA ladder, which was achieved with fluorescence detection at the end of separation microchannel, is given. Based on electropherograms, the number of theoretical separation plates is calculated (max. 70,000) and compared with data from the literature. Finally, some conclusions and observations on the design of the chip are given in order to improve its configuration in the future toward modular configuration.

In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

Capillary electrophoresis connected to electrospray ionization mass spectrometry is a promising combination to analyze complex biological samples. The use of sheathless electrospray ionization interfaces, such as a porous nanoelectrospray capillary emitter, requires the application of forward flow (either by pressure or electroosmosis) to maintain the electrospray process. The analysis of solute molecules with strong negative charges (e.g., aminopyrenetrisulfonate labeled glycans) necessitates a reversed-polarity capillary electrophoresis separation mode, in which case the electroosmotic flow is counter current, thus pressure assistance is necessary. In this study, we compared the effect of forced convection with and without counter electroosmotic flow on the resulting separation efficiency in capillary electrophoresis based on flow profile simulations by computational fluid dynamics technique and by actual experiments. The efficiencies of the detected peaks were calculated from the resulting electropherograms and found approximately 950 000 plates/m for electrophoresis with counter electroosmotic flow, 20 000 plates/m with pressure only (such as would be in open tubular liquid chromatography), and 480 000 plates/m for electrophoresis with simultaneous counter electroosmotic flow and forward pressure assistance, which validates the simulation data.

The NISTmAb is a monoclonal antibody Reference Material from the National Institute of Standards and Technology; it is a class-representative IgG1κ intended serve as a pre-competitive platform for harmonization and technology development in the biopharmaceutical industry. The publication series of which this paper is a part describes NIST’s overall control strategy to ensure NISTmAb quality and availability over its lifecycle. In this paper, the development and qualification of methods for monitoring NISTmAb charge heterogeneity are described. Capillary zone electrophoresis (CZE) and capillary isoelectric focusing (CIEF) assays were optimized and evaluated as candidate assays for NISTmAb quality control. CIEF was found to be suitable as a structural characterization assay yielding information on the apparent pI of the NISTmAb. CZE was found to be better suited for routine monitoring of NISTmAb charge heterogeneity and was qualified for this purpose. This paper is intended to provide relevant details of NIST’s charge heterogeneity control strategy to facilitate implementation of the NISTmAb as a test molecule in the end user’s laboratory. Graphical AbstractRepresentative capillary zone electropherogram of the NIST monoclonal antibody (NISTmAb). The NISTmAb is a publicly available research tool intended to facilitate advancement of biopharmaceutical analytics. Electronic supplementary material The online version of this article (10.1007/s00216-017-0816-6) contains supplementary material, which is available to authorized users.

Interest in DNA analysis using short tandem repeats (STR) as finger printing tools in forensic medicine has gained tremendous application, as expression of these nuclear factors have enhanced forensic examination. Here we used this Biochemical characterization after conventional extraction process, polymerase chain reaction (PCR), gel electrophoresiss and a sequencer to distinguish and resolve parental dispute. The differential migration of labeled DNA fragments which attains excitation energy with a laser elicits fluorescent light of different wavelength depending on the dye used. A data collection software (Genemapper) collects raw data (spectrograph) and converts it to an electropherogram that is interpreted. By comparing the DNA profiles, inclusion and exclusion criteria were elucidated to resolve disputes. The inherent discriminating power of STRs used in analysis enhances resolution of cell mixtures, genetic aberration, substantiation of tissue origin and provides genetic distinction which is a robust and reliable approach in resolving parental disputes.

In recent years, analytical glycomics gained a significant role due to the rapidly increasing number of glycoproteins introduced as biopharmaceuticals. One of the frequently used methods for the analysis of complex carbohydrates is capillary electrophoresis with laser induced fluorescent detection (CE-LIF). CE-LIF is a high resolution separation technique with excellent sensitivity capable of discriminating between closely related positional and linkage carbohydrate isomers. Individual glycan structures corresponding to the separated peaks in an electropherogram are identified according to their glucose unit (GU) values by mining the built in database. This tutorial introduces the practical use of the GUcal application, a recently developed glycoinformatics tool, which automatically calculates GU values for all sample components of interest in an electropherogram using either the bracketing standard approach or the recently published triple internal standard method. Furthermore, a worked example demonstrates the way glycan structural elucidation of human immunoglobulin G is processed with the help of this simple and rapid GU value calculation application. Significance Biopharmaceuticals have seen something of tremendous development in recent years, which governs the parallel blooming of analytical glycomics. One of the frequently used methods for the analysis of complex carbohydrates is capillary electrophoresis with laser induced fluorescent detection (CE-LIF). CE-LIF is a high resolution separation technique with excellent sensitivity capable of discriminating between closely related positional and linkage carbohydrate isomers. While CE instrumentation is well developed, the related bioinformatics tools are lagging behind. According to our best knowledge, this is the first tutorial paper on the recently disseminated GUcal application, which automatically calculates GU values for all sample components of interest in an electropherogram using either the bracketing standard approach or the new triple internal standard method. On the top the step-by-step instruction how to use the application, the paper includes a worked example demonstrates the way glycan structure elucidation of human immunoglobulin G is processed with the help of the simple and rapid GU value calculation of this new application. After very short training period, the software can be used readily for cutting-edge glycomics of exploratory research or high-throughput routine analysis.

Forensic DNA laboratories process database reference samples on FTA® cards or buccal swabs, which commonly contain adequate amounts of quality DNA resulting in full STR profiles and high first-pass rates. However, some reference samples and many forensic casework samples are exposed to a variety of insults that may lead to low quantities of DNA, DNA degradation, DNA mixtures, and/or PCR inhibition, posing a challenge to downstream genotyping success. The inclusion of multiple amplification targets and internal PCR controls (IPCs) in DNA quantification kits, and quality sensors within STR amplification kits can aid in the accurate interpretation of sample/profile quality, and guide more efficient rework strategies when needed. In order to assess the effectiveness of these quality systems we subjected database-type samples (buccal swabs and blood or saliva on FTA® cards), mock casework samples (low-template, degraded, inhibited, DNA mixtures), and authentic post-coital samples to various challenging conditions. Concordance between the quality flags in the Investigator® Quantiplex® Pro RGQ kit (QIAGEN), the QS markers in QIAGEN's Investigator® 24plex QS kit, and overall STR profile quality was evaluated for all casework-type samples. To assess the value of the QS markers in the Investigator® 24plex QS and GO! STR kits, samples with partial or failed STR profiles were reworked based on the quality of the electropherogram first with the QS markers redacted, and second in conjunction with the QS markers. Results from each of the rework approaches were compared to determine which strategy, if any, improved the STR profile quality and the number of reportable alleles. The QS markers in the 24plex STR kits correctly confirmed sample quality in 99.9% of databasing samples and 98% of mock casework samples. Quality flags during DNA quantification were concordant with downstream STR profiles for the majority (77%) of the mock casework samples. Additionally, when samples with partial STR profiles were reworked, more loci were obtained for 80% of the samples regardless of the rework strategy used. However, the most notable improvement in STR completeness was observed in inhibited samples that were reworked based on the information provided by the STR quality sensors, with an average increase of 56% reportable alleles.

A procedure is developed for the determination of meat proteins by two-dimensional electrophoresis (2D). The procedure is intended for the quantitative determination of muscle proteins in samples of meat raw materials by a complex of proteomic technologies, including 2D-electrophoresis in a polyacrylamide gel and computer densitometry of the recorded electropherograms.

It is demonstrated that the use of pressure extends the possibilities of capillary zone electrophoresis in studying aggregative states of substances, ensuring the detection of the presence of several types of aggregates with different electrophoretic mobilities. The electropherograms of chitosan 2-hydroxybutoxypropylcarbamate (CHBPC) in citrate solutions with pH 3.1, 4.5, and 5.8 indicate the dependence of aggregation on pH. A comparison of the data for CHBPC obtained by capillary zone electrophoresis, static light scattering, and scanning electron microscopy revealed a relationship between the electrophoretic mobility and sizes of aggregates, varying from 140 nm to several micrometers. The size of aggregates can be estimated by hydrodynamic contribution to their mobility. The effectiveness of the use of CHBPC for the dynamic modification of capillaries is shown.

Marijuana (Cannabis sativa L.) is a plant cultivated and trafficked worldwide as a source of fiber (hemp), medicine, and intoxicant. The development of a validated method using molecular techniques such as short tandem repeats (STRs) could serve as an intelligence tool to link multiple cases by means of genetic individualization or association of cannabis samples. For this purpose, a 13 loci STR multiplex method was developed, optimized, and validated according to relevant ISFG and SWGDAM guidelines. The STR multiplex consists of 13 previously described C. sativa STR loci: ANUCS501, 9269, 4910, 5159, ANUCS305, 9043, B05, 1528, 3735, CS1, D02, C11, and H06. A sequenced allelic ladder consisting of 56 alleles was designed to accurately genotype 101 C. sativa samples from three seizures provided by a U.S. Customs and Border Protection crime lab. Using an optimal range of DNA (0.5–1.0 ng), validation studies revealed well-balanced electropherograms (inter-locus balance range: 0.500–1.296), relatively balanced heterozygous peaks (mean peak height ratio of 0.83 across all loci) with minimal artifacts and stutter ratio (mean stutter of 0.021 across all loci). This multi-locus system is relatively sensitive (0.13 ng of template DNA) with a combined power of discrimination of 1 in 55 million. The 13 STR panel was found to be species specific for C. sativa; however, non-specific peaks were produced with Humulus lupulus. The results of this research demonstrate the robustness and applicability of this 13 loci STR system for forensic DNA profiling of marijuana samples.

In this work, we present a novel probabilistic peak detection algorithm based on a Bayesian framework for forensic DNA analysis. The proposed method aims at an exhaustive use of raw electropherogram data from a laser-induced fluorescence multi-CE system. As the raw data are informative up to a single data point, the conventional threshold-based approaches discard relevant forensic information early in the data analysis pipeline. Our proposed method assigns a posterior probability reflecting the data point's relevance with respect to peak detection criteria. Peaks of low intensity generated from a truly existing allele can thus constitute evidential value instead of fully discarding them and contemplating a potential allele drop-out. This way of working utilizes the information available within each individual data point and thus avoids making early (binary) decisions on the data analysis that can lead to error propagation. The proposed method was tested and compared to the application of a set threshold as is current practice in forensic STR DNA profiling. The new method was found to yield a significant improvement in the number of alleles identified, regardless of the peak heights and deviation from Gaussian shape.

The most commonly applied method of fluorescence detection for on-chip gel electrophoresis is finish line detection in epifluorescence configuration using highly sensitive photodiode or a cooled scientific camera as a photodetector. In this paper we aim to confirm that a simple optical configuration based on a limited number of components and a low-cost, non-cooled CCD matrix detector combined with software image processing makes possible very sensitive fluorescence detection for high resolution for on-chip gel electrophoresis. The position and dimensions of software defined detection areas (so called regions of interest) have been identified as the main factors influencing detection properties. Several parameters which typify electropherograms (including signal-to-noise ratio and full width at half maximum of the peaks) have been studied. Finally, the developed detection unit was used in the separation of a DNA ladder with a theoretical number of over 600,000 of separation plates. Thus, the applicability of the detection unit has been confirmed.

Motivation Mutations (or Single Nucleotide Variants) in folded RiboNucleic Acid structures that cause local or global conformational change are riboSNitches. Predicting riboSNitches is challenging, as it requires making two, albeit related, structure predictions. The data most often used to experimentally validate riboSNitch predictions is Selective 2′ Hydroxyl Acylation by Primer Extension, or SHAPE. Experimentally establishing a riboSNitch requires the quantitative comparison of two SHAPE traces: wild-type (WT) and mutant. Historically, SHAPE data was collected on electropherograms and change in structure was evaluated by ‘gel gazing.’ SHAPE data is now routinely collected with next generation sequencing and/or capillary sequencers. We aim to establish a classifier capable of simulating human ‘gazing’ by identifying features of the SHAPE profile that human experts agree ‘looks’ like a riboSNitch. Results We find strong quantitative agreement between experts when RNA scientists ‘gaze’ at SHAPE data and identify riboSNitches. We identify dynamic time warping and seven other features predictive of the human consensus. The classSNitch classifier reported here accurately reproduces human consensus for 167 mutant/WT comparisons with an Area Under the Curve (AUC) above 0.8. When we analyze 2019 mutant traces for 17 different RNAs, we find that features of the WT SHAPE reactivity allow us to improve thermodynamic structure predictions of riboSNitches. This is significant, as accurate RNA structural analysis and prediction is likely to become an important aspect of precision medicine. Availability and Implementation The classSNitch R package is freely available at http://classsnitch.r-forge.r-project.org. Supplementary information Supplementary data are available at Bioinformatics online.

Short tandem repeat (STR) profiling from DNA samples has long been the bedrock of human identification. The laboratory process is composed of multiple procedures that include quantification, sample dilution, PCR, electrophoresis, and fragment analysis. The end product is a short tandem repeat electropherogram comprised of signal from allele, artifacts, and instrument noise. In order to optimize or alter laboratory protocols, a large number of validation samples must be created at significant expense. As a tool to support that process and to enable the exploration of complex scenarios without costly sample creation, a mechanistic stochastic model that incorporates each of the aforementioned processing features is described herein. The model allows rapid in silico simulation of electropherograms from multicontributor samples and enables detailed investigations of involved scenarios. An implementation of the model that is parameterized by extensive laboratory data is publically available. To illustrate its utility, the model was employed in order to evaluate the effects of sample dilutions, injection time, and cycle number on peak height, and the nature of stutter ratios at low template. We verify the model's findings by comparison with experimentally generated data.

In this work, we describe a method for the identification, separation, and detection of engineered nanoparticles (NPs) using capillary electrophoresis inductively coupled plasma-mass spectrometry in single particle mode (CE-SP-ICP-MS). Benefits of this method compared to conventional techniques include the fact that complex NPs mixtures are characterized on a particle-by-particle basis, separated with acceptable resolution, and in much shorter time. Information on particle number, particle mean size, size distribution, and elemental composition is obtained and visualized in three-dimensional single-particle electropherograms for the first time. The successful detection and characterization of single 10 nm-sized AuNPs with ICP-MS is demonstrated. Based on these results we believe that this method will become an important tool in high-throughput analysis, fractionation analysis, and in situ particle characterization.

Acupuncture sample injection is a simple method to deliver well-defined nanoliter-scale sample plugs in PDMS microfluidic channels. This acupuncture injection method in microchip CE has several advantages, including minimization of sample consumption, the capability of serial injections of different sample solutions into the same microchannel, and the capability of injecting sample plugs into any desired position of a microchannel. Herein, we demonstrate that the simple and cost-effective acupuncture sample injection method can be used for PDMS microchip-based field amplified sample stacking in the most simplified straight channel by applying a single potential. We achieved the increase in electropherogram signals for the case of sample stacking. Furthermore, we present that microchip CGE of ΦX174 DNA-HaeⅢ digest can be performed with the acupuncture injection method on a glass microchip while minimizing sample loss and voltage control hardware.

Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells us about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. A technique that lends itself well to such a task of classification in the face of vast amounts of data is the use of artificial neural networks. These networks, inspired by the workings of the human brain, have been increasingly successful in analysing large datasets, performing medical diagnoses, identifying handwriting, playing games, or recognising images. In this work we demonstrate the use of an artificial neural network which we train to 'read' electropherograms and show that it can generalise to unseen profiles.

At NFC the internally developed software for DNA analysis, SlimDna is used. It is complementary to the LIMS and keeps track of samples, sample batches, instrument files and generated data. The system communicates with the LIMS, instruments and other software. SlimDna includes four modules (Analysis, Control, Administration and Frequency calculation) and covers the entire analysis process from DNA extraction to reporting approved STR profiles to the LIMS. SlimDna is built with Microsoft Internet Information Services (IIS) as application server and the user interface consists of Windows clients. For data storage MySQL is used. The software has been implemented in different packages, STR typing being the latest. The system has streamlined the STR typing by providing, among other functions, automated evaluation of STR profiles, databases for observed variant alleles as well as tracking and logging of negative and positive controls. STR electropherograms from analysis of crime scene samples (around 30 000 per year) are evaluated by SlimDna according to set rules concerning for example stutter ratio, heterozygote balance and number of alleles per marker in order to define the profile as a single source genotype or a mixture. The SlimDna output is compared to a manual evaluation before the results are reported to the LIMS. This process saves nearly one minute hands-on time per sample compared to the previous Excel-based solution. For reference samples, SlimDna evaluates the majority (55%) of the samples without manual revision. SlimDna’s automated interpretation has proven to be very accurate and will soon replace more of the manual revisions. In the near future, we aim to develop SlimDna further, with for example a mixture module supporting the reporting officers in analysis.

Sanger sequencing is an indispensable technique for mitochondrial ancestry studies. However, it is a time consuming process that requires several resources to obtain high quality electropherograms. To optimize the efficiency of DNA analysis, we used real-time PCR (qPCR) to evaluate Sanger sequencing reaction performance before capillary electrophoresis. qPCR was performed to amplify Mitochondrial Control Region (CR). We determined that final PCR product quantification can be done using qPCR final fluorescence instead of visualization in agarose gel. Real-time sequencing reactions were done using BigDye Terminator v3.1 and SYBR Safe (Invitrogen); in addition, a dissociation curve step from 65 °C to 95 °C was added at the end of the thermal cycler protocol. The sequencing qPCR products were purified and run in a 3130 Genetic Analyzer (Applied Biosystems). The results demonstrated that fluorescence at 65 °C during the dissociation curve was directly related with DNA quantity in the sequencing qPCR reaction. Furthermore, samples that presented higher fluorescence at 65 °C generated better quality electropherograms. We suggest that electropherogram quality prediction before capillary electrophoresis is possible using sequencing qPCR. In this way, it is possible to increase workflow efficiency in laboratory procedures and identify errors during samples processing.