A new set of DIP‐SNP markers for detection of unbalanced and degraded DNA mixtures

Unbalanced and degraded mixtures (UDM) are frequently encountered during forensic DNA analysis. For example, forensic DNA units regularly encounter DNA mixture signal where the DNA signal from the alleged offender is masked or swamped by high quantities of DNA from the victim. Our previous data presented a new kind of DNA markers that composed of a deletion/insertion polymorphism (DIP) and a SNP and we termed this new kind of microhaplotypes DIP‐SNP (combination of DIP and SNP). Since such markers could be designed short enough for degraded DNA amplification, we hypothesized that DIP‐SNP markers are applicable for typing of UDM. In this study, we developed a new set of DIP‐SNPs with short amplicons which were complement to our prior developed system. The multiplex PCR and SNaPshot assay were established for 20 DIP‐SNPs in a Chinese Han population. The DIP‐SNPs were capable of detecting the minor contributor's allele in home‐made DNA mixture with sensitivities from 1:100 to 1:1000 with a total of 1 –10 ng input DNA. Moreover, this system successfully typed the degraded DNA whether it came from the single source or mixture samples. In Chinese population, the system showed an average informative value of 0.293 and combined informative value of 0.998363862. Our results demonstrated that DIP‐SNPs may serve as a valuable tool in detection of UDM in forensic medicine.     

Development of a novel forensic STR multiplex for ancestry analysis and extended identity testing

There is growing interest in developing additional DNA typing techniques to provide better investigative leads in forensic analysis. These include inference of genetic ancestry and prediction of common physical characteristics of DNA donors. To date, forensic ancestry analysis has centered on population‐divergent SNPs but these binary loci cannot reliably detect DNA mixtures, common in forensic samples. Furthermore, STR genotypes, forming the principal DNA profiling system, are not routinely combined with forensic SNPs to strengthen frequency data available for ancestry inference. We report development of a 12‐STR multiplex composed of ancestry informative marker STRs (AIM‐STRs) selected from 434 tetranucleotide repeat loci. We adapted our online Bayesian classifier for AIM‐SNPs: Snipper, to handle multiallele STR data using frequency‐based training sets. We assessed the ability of the 12‐plex AIM‐STRs to differentiate CEPH Human Genome Diversity Panel populations, plus their informativeness combined with established forensic STRs and AIM‐SNPs. We found combining STRs and SNPs improves the success rate of ancestry assignments while providing a reliable mixture detection system lacking from SNP analysis alone. As the 12 STRs generally show a broad range of alleles in all populations, they provide highly informative supplementary STRs for extended relationship testing and identification of missing persons with incomplete reference pedigrees. Lastly, mixed marker approaches (combining STRs with binary loci) for simple ancestry inference tests beyond forensic analysis bring advantages and we discuss the genotyping options available.     

A wavelet‐PCA method saves high mass resolution information in data treatment of SIMS molecular depth profiles

A detailed depth characterization of multilayered polymeric systems is a very attractive topic. Currently, the use of cluster primary ion beams in time‐of‐flight secondary ion mass spectrometry allows molecular depth profiling of organic and polymeric materials. Because typical raw data may contain thousands of peaks, the amount of information to manage grows rapidly and widely, so that data reduction techniques become indispensable in order to extract the most significant information from the given dataset. Here, we show how the wavelet‐based signal processing technique can be applied to the compression of the giant raw data acquired during time‐of‐flight secondary ion mass spectrometry molecular depth‐profiling experiments. We tested the approach on data acquired by analyzing a model sample consisting of polyelectrolyte‐based multilayers spin‐cast on silicon. Numerous wavelet mother functions and several compression levels were investigated. We propose some estimators of the filtering quality in order to find the highest ‘safe’ approximation value in terms of peaks area modification, signal to noise ratio, and mass resolution retention. The compression procedure allowed to obtain a dataset straightforwardly ‘manageable’ without any peak‐picking procedure or detailed peak integration. Moreover, we show that multivariate analysis, namely, principal component analysis, can be successfully combined to the results of the wavelet‐filtering, providing a simple and reliable method for extracting the relevant information from raw datasets. Copyright © 2016 John Wiley & Sons, Ltd.     

Automated detection and removal of capillary electrophoresis artifacts due to spectral overlap

While DNA detection using capillary electrophoresis has enabled improvements in both resolution and throughput, the use of CE – particularly with multiple dye channels – can introduce artifacts that can complicate analyses. Undetected pull‐up artifacts can pose a challenge to investigators, especially in low‐level samples, while partial pull‐up peaks can distort peak height balance within a locus and impact the downstream likelihood ratio. Current methods for addressing pull‐up are typically manually implemented. This study presents an effective alternative: a series of mathematical models, created using symbolic regression achieved through genetic programming. The models estimate the amount of pull‐up expected in a peak from a true allele for a given dye‐dye relationship and instrument type. This leads to the removal of artifactual pull‐up peaks and peak height corrections when pull‐up is present within true alleles. When models are used in conjunction with a dynamic threshold, pull‐up peaks were automatically detected and removed with an accuracy rate of 96.1%. The removal of partial pull‐up from true allele peaks led to a more accurate heterozygote balance for the affected locus. These models have been optimized for use with any analytical threshold and can be implemented by any lab using a 3100 or 3500 instrument series.     

Non‐hybridization single nucleotide polymorphism detection and genotyping assay through direct discrimination of single base mutation by capillary electrophoretic separation of single‐stranded DNA

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.     

Pattern-based algorithm for peptide sequencing from tandem high energy collision-induced dissociation mass spectra

A new strategy is reported for extracting complete and partial sequence information from collision-induced dissociation (CID) spectra of peptides, CID spectra are obtained from high energy CID of peptide molecular ions on a four-sector tandem mass spectrometer with an electro-optically coupled microchannel array detector, A peak detection routine reduces the spectrum to a list of peak masses and peak heights, which is then used for sequencing, The sequencing algorithm was designed to use spectral data to generate sequence fits directly rather than to use data to test the fit of series of sequence guesses. The peptide sequencing algorithm uses a pattern based on the polymeric nature of peptides to classify spectral peaks into sets that are related in a sequence-independent manner, It then establishes sequence relationships among these sets, Peak detection from raw data takes 10–20 s, with sequence generation requiring an additional 10–60 s on a Sun 3/60 workstation, The program is written in the C language to run on a Unix platform. The principal advantages of our method are in the speed of analysis and the potential for identifying modified or rare amino acids. The algorithm was designed to permit real-time sequencing but awaits hardware modifications to allow real-time access to CID spectra.     

Graphene Doped Mn2O3 Nanofibers as a Facile Electroanalytical DNA Point Mutation Detection Platform for Early Diagnosis of Breast/Ovarian Cancer

This paper demonstrates a simple, label‐free detection methodology for detecting single point DNA mutations. Single point mutation detection is a key enabler for diagnosis and prevention of several genetic disorders that manifest into cancers. Specifically for this purpose, herein, an electrochemical biosensor utilizing electrospun graphene doped manganese III oxide nanofibers (GMnO) is developed. The charge transfer resistance offered by GMnO is extremely sensitive to the localized change in the conductivity. This sensitivity, attributed to the low band gap of Mn₂O₃ and high charge transfer kinetics of graphene, is explored in the proposed mutation detection platform. As a proof of concept, ultrasensitive detection of BRCA1 gene specific point mutation is demonstrated. The target specific single stranded probe DNA is immobilized onto GMnO modified glassy carbon working electrodes via chemisorption. Post target‐DNA hybridization, differential pulse voltammetry is employed to facilitate detection of targeted point mutation, wherein, difference in peak currents is used to distinguish the target DNA as normal or mutant. Efficiency of the proposed method is evaluated against a target concentration ranging from 10 pM−1 μM. With respect to the mutated target DNA, the LoD of the proposed device is found to be 0.8±0.069 pM. The proposed approach can be extended for detecting any mutation/hybridization of interest by simply adapting an appropriate functionalization protocol.     

Sample stacking capillary electrophoretic microdevice for highly sensitive mini Y short tandem repeat genotyping

Lab‐on‐a‐chip provides an ideal platform for short tandem repeat (STR) genotyping due to its intrinsic low sample consumption, rapid analysis, and high‐throughput capability. One of the challenges, however, in the forensic human identification on the microdevice is the detection sensitivity derived from the nanoliter volume sample handling. To overcome such a sensitivity issue, here we developed a sample stacking CE microdevice for mini Y STR genotyping. The mini Y STR includes redesigned primer sequences to generate smaller‐sized PCR amplicons to enhance the PCR efficiency and the success rate for a low copy number and degraded DNA. The mini Y STR amplicons occupied in the 5‐ and 10‐mm stacking microchannels are preconcentrated efficiently in a defined narrow region through the optimized sample stacking CE scheme, resulting in more than tenfold improved fluorescence peak intensities compared with that of a conventional cross‐injection microcapillary electrophoresis method. Such signal enhancement allows us to successfully analyze the Y STR typing with only 25 pg of male genomic DNA, with high background of female genomic DNA, and with highly degraded male genomic DNA. The combination of the mini Y STR system with the novel sample stacking CE microdevice provides the highly sensitive Y STR typing on a chip, making it promising to perform high‐performance on‐site forensic human identification.     

A comparison of the effects of PCR inhibition in quantitative PCR and forensic STR analysis

In this paper we compare the effects of three representative PCR inhibitors using quantitative PCR (qPCR) and multiplex STR amplification in order to determine the effect of inhibitor concentration on allele dropout and to develop better ways to interpret forensic DNA data. We have used humic acid, collagen and calcium phosphate at different concentrations to evaluate the profiles of alleles inhibited in these amplifications. These data were correlated with previously obtained results from quantitative PCR including melt curve effects, efficiency changes and cycle threshold (Ct) values. Overall, the data show that there are two competing processes that result from PCR inhibition. The first process is a general loss of larger alleles. This appears to occur with all inhibitors. The second process is more sequence specific and occurs when the inhibitor binds DNA, altering the cycle threshold and the melt curve. This sequence-specific inhibition results in patterns of allele loss that occur in addition to the overall loss of larger alleles. The data demonstrate the applicability of utilizing real-time PCR results to predict the presence of certain types of PCR inhibition in STR analysis.     

Ultrahighly Sensitive Homogeneous Detection of DNA and MicroRNA by Using Single‐Silver‐Nanoparticle Counting

DNA and RNA analysis is of high importance for clinical diagnoses, forensic analysis, and basic studies in the biological and biomedical fields. In this paper, we report the ultrahighly sensitive homogeneous detection of DNA and microRNA by using a novel single‐silver‐nanoparticle counting (SSNPC) technique. The principle of SSNPC is based on the photon‐burst counting of single silver nanoparticles (Ag NPs) in a highly focused laser beam (about 0.5 fL detection volume) due to Brownian motion and the strong resonance Rayleigh scattering of single Ag NPs. We first investigated the performance of the SSNPC system and then developed an ultrasensitive homogeneous detection method for DNA and microRNA based on this single‐nanoparticle technique. Sandwich nucleic acid hybridization models were utilized in the assays. In the hybridization process, when two Ag‐NP–oligonucleotide conjugates were mixed in a sample containing DNA (or microRNA) targets, the binding of the targets caused the Ag NPs to form dimers (or oligomers), which led to a reduction in the photon‐burst counts. The SSNPC method was used to measure the change in the photon‐burst counts. The relationship between the change of the photon‐burst counts and the target concentration showed a good linearity. This method was used for the assay of sequence‐specific DNA fragments and microRNAs. The detection limits were at about the 1 fM level, which is 2–5 orders of magnitude more sensitive than current homogeneous methods.     

Developing a new nonbinary SNP fluorescent multiplex detection system for forensic application in China

Nonbinary single‐nucleotide polymorphisms (SNPs) are potential forensic genetic markers because their discrimination power is greater than that of normal binary SNPs, and that they can detect highly degraded samples. We previously developed a nonbinary SNP multiplex typing assay. In this study, we selected additional 20 nonbinary SNPs from the NCBI SNP database and verified them through pyrosequencing. These 20 nonbinary SNPs were analyzed using the fluorescent‐labeled SNaPshot multiplex SNP typing method. The allele frequencies and genetic parameters of these 20 nonbinary SNPs were determined among 314 unrelated individuals from Han populations from China. The total power of discrimination was 0.9999999999994, and the cumulative probability of exclusion was 0.9986. Moreover, the result of the combination of this 20 nonbinary SNP assay with the 20 nonbinary SNP assay we previously developed demonstrated that the cumulative probability of exclusion of the 40 nonbinary SNPs was 0.999991 and that no significant linkage disequilibrium was observed in all 40 nonbinary SNPs. Thus, we concluded that this new system consisting of new 20 nonbinary SNPs could provide highly informative polymorphic data which would be further used in forensic application and would serve as a potentially valuable supplement to forensic DNA analysis.     

An automatic peak finding method for LC‐MS data using Gaussian second derivative filtering

A highly automated procedure for localising and characterising peaks in the chromatographic time domain of LC‐MS data has been developed. The work was initiated by an identified need to facilitate the detection and tracking of chromatographic peaks during method development for the analysis of impurities in pharmaceutical products. The algorithm is mainly based on a digital filter for which the settings are automatically adapted to the data set under study. The procedure was evaluated for synthetic data sets with various S/N levels, peak widths and baseline properties. It was found that even for the worst case tested with S/N=10 and a high variability in the baseline, 94% of the simulated analytical peaks could be detected without producing any false‐positive identifications. Furthermore, the number of correctly estimated peak heights and peak widths falling within a 10% error of the true values were 94 and 91%, respectively. For experimental data sets, peak height, and width estimations were more difficult, but the processed reconstructions showed an excellent agreement with the analytical signals of the raw data, and also a clearly improved visualisation in total ion‐ and base‐peak chromatograms.     

Cross-talk filtering in four dye fluorescence-based DNA sequencing

We have addressed two important issues of nonlinear cross-talk and baseline adjustment in DNA data processing. An important aspect in the processing of the four-dye fluorescence-based data is the cross-talk filtering. Typically, a matrix M, which is a function of the fluorophores and the fluorescence detection system, is used in the multicomponent analysis. In this deconvolution process the matrix is applied directly to the raw signal, on a linear cross-talk assumption. This necessitates the signal to be aligned to the baseline before the filter is applied. The various techniques used for aligning the raw data have the negative effect of adding distortion to the signal. An algorithm for cross-talk removal is presented in this paper. The algorithm uses the intensity difference of the signal rather than the actual value itself, thus making the cross-talk removal possible before the base line adjustment. In addition, a supplementary filtering step is proposed in order to account for the nonlinear nature of the cross-talk. This second step is based on a matrix T that accounts for the correlation of each of the signals with the other three. The overall result is a more precise presentation of the DNA data and less information loss through filtering.     

Easy sample treatment for the determination of enrofloxacin and ciprofloxacin residues in raw bovine milk by capillary electrophoresis

An easy, selective, and sensitive method has been developed for the determination of enrofloxacin (ENR) and its main active metabolite, ciprofloxacin (CIP), in raw bovine milk using CE with UV detection at 268 nm. Milk samples were prepared by a clean‐up/extraction procedure based on protein precipitation with hydrochloride acid followed by being defatted by centrifugation and SPE using a hydrophilic‐lipophilic balance cartridge. Optimum separation was obtained using a 50 mM phosphoric acid at pH 8.4 and the total electrophoretic run time was 6 min. Sample preparation by this method yielded clean extracts with quantitative and consistent mean recoveries from 89 to 97% for CIP and from 93 to 98% for ENR. LODs obtained were lower to the maximum residue limits for these fluoroquinolones. The precision of the ensuing method is acceptable; thus, the RSD for peak area and migration time was less than 8.5 and 0.5% for CIP and 9.9 and 0.9% for ENR, respectively. The results showed that the proposed method was efficient showing good recoveries, sensitivity, and precision for the studied compounds and could be satisfactorily applied in routine analysis for the monitoring of ENR and CIP residues in milk, due to its ruggedness and feasibility demonstrated.     

Copy number variants calling for single cell sequencing data by multi-constrained optimization

Variations in DNA copy number carry important information on genome evolution and regulation of DNA replication in cancer cells. The rapid development of single-cell sequencing technology allows one to explore gene expression heterogeneity among single-cells, thus providing important cancer cell evolution information. Single-cell DNA/RNA sequencing data usually have low genome coverage, which requires an extra step of amplification to accumulate enough samples. However, such amplification will introduce large bias and makes bioinformatics analysis challenging. Accurately modeling the distribution of sequencing data and effectively suppressing the bias influence is the key to success variations analysis.Recent advances demonstrate the technical noises by amplification are more likely to follow negative binomial distribution, a special case of Poisson distribution. Thus, we tackle the problem CNV detection by formulating it into a quadratic optimization problem involving two constraints, in which the underling signals are corrupted by Poisson distributed noises. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signals from single-cell sequencing data are anticipated to fit the CNVs patterns more accurately. An efficient numerical solution based on the classical alternating direction minimization method (ADMM) is tailored to solve the proposed model. We demonstrate the advantages of the proposed method using both synthetic and empirical single-cell sequencing data. Our experimental results demonstrate that the proposed method achieves excellent performance and high promise of success with single-cell sequencing data.     

High‐throughput metabolic stability studies in drug discovery by orthogonal acceleration time‐of‐flight (OATOF) with analogue‐to‐digital signal capture (ADC)

Screening assays capable of performing quantitative analysis on hundreds of compounds per week are used to measure metabolic stability during early drug discovery. Modern orthogonal acceleration time‐of‐flight (OATOF) mass spectrometers equipped with analogue‐to‐digital signal capture (ADC) now offer performance levels suitable for many applications normally supported by triple quadruple instruments operated in multiple reaction monitoring (MRM) mode. Herein the merits of MRM and OATOF with ADC detection are compared for more than 1000 compounds screened in rat and/or cryopreserved human hepatocytes over a period of 3 months. Statistical comparison of a structurally diverse subset indicated good agreement for the two detection methods. The overall success rate was higher using OATOF detection and data acquisition time was reduced by around 20%. Targeted metabolites of diazepam were detected in samples from a CLint determination performed at 1 µM. Data acquisition by positive and negative ion mode switching can be achieved on high‐performance liquid chromatography (HPLC) peak widths as narrow as 0.2 min (at base), thus enabling a more comprehensive first pass analysis with fast HPLC gradients. Unfortunately, most existing OATOF instruments lack the software tools necessary to rapidly convert the huge amounts of raw data into quantified results. Software with functionality similar to open access triple quadrupole systems is needed for OATOF to truly compete in a high‐throughput screening environment. Copyright © 2010 John Wiley & Sons, Ltd.     

MALDI‐TOF mass spectrometry for the monitoring of she‐donkey's milk contamination or adulteration

Donkey's milk (DM), representing a safe and alternative food in both IgE‐mediated and non‐IgE‐mediated cow's milk protein allergy, can be categorized as precious pharma‐food. Moreover, an economically relevant interest for the use of DM in cosmetology is also developing. The detection of adulterations and contaminations of DM is a matter of fundamental importance from both an economic and allergenic standpoint, and, to this aim, fast and efficient analytical approaches to assess the authenticity of this precious nutrient are desirable. Here, a rapid matrix‐assisted laser desorption/ionization‐time‐of‐flight mass spectrometry (MALDI‐TOF MS)‐based method aimed to the detection of bovine or caprine milk in raw DM is reported. The presence of the extraneous milks was revealed by monitoring the protein profiles of the most abundant whey proteins, α‐lactalbumin (α‐LA) and β‐lactoglobulin, used as molecular markers. The possibility of obtaining a quantitative analysis of the level of cow or goat milk in DM based on the MALDI‐TOF peak areas of α‐LAs was also explored. The results showed that the experimental quantitative values were in good agreement with the real composition of each mixture. As pretreatment of the milk samples is not required, and owing to the speed and the high sensitivity of MALDI‐MS, the protocol here reported could represent a reliable method for routine analyses aimed to assess the absence of contamination in raw fresh DM samples. Copyright © 2013 John Wiley & Sons, Ltd.     

Usefulness of microchip electrophoresis for the analysis of mitochondrial DNA in forensic and ancient DNA studies

We evaluate the usefulness of a commercially available microchip CE (MCE) device in different genetic identification studies performed with mitochondrial DNA (mtDNA) targets, including the haplotype analysis of HVR1 and HVR2 and the study of interspecies diversity of cytochrome b (Cyt b) and 16S ribosomal RNA (16S rRNA) mitochondrial genes in forensic and ancient DNA samples. The MCE commercial system tested in this study proved to be a fast and sensitive detection method of length heteroplasmy in cytosine stretches produced by 16 189T>C transitions in HVR1 and by 309.1 and 309.2 C-insertions in HVR2. Moreover, the quantitative analysis of PCR amplicons performed by LIF allowed normalizing the amplicon input in the sequencing reactions, improving the overall quality of sequence data. These quantitative data in combination with the quantification of genomic mtDNA by real-time PCR has been successfully used to evaluate the PCR efficiency and detection limit of full sequencing methods of different mtDNA targets. The quantification of amplicons also provided a method for the rapid evaluation of PCR efficiency of multiplex-PCR versus singleplex-PCR to amplify short HV1 amplicons (around 100 bp) from severely degraded ancient DNA samples. The combination of human-specific (Cyt b) and universal (16S rRNA) mtDNA primer sets in a single PCR reaction followed by MCE detection offers a very rapid and simple screening test to differentiate between human and nonhuman hair forensic samples. This method was also very efficient with degraded DNA templates from forensic hair and bone samples, because of its applicability to detect small amplicon sizes. Future possibilities of MCE in forensic DNA typing, including nuclear STRs and SNP profiling are suggested.     

Multi‐scale Gaussian/Haar wavelet strategies coupled with sub‐window factor analysis for an accurate alignment in nontargeted metabolic profiling to enhance herbal origin discrimination capability

Metabolic dataset can provide an overview of different herbal origin, which is conducted by some statistical procedures. Such results often deviate to a certain degree, due to peaks shifts in chromatographic signals. In order to solve this problem, an improved algorithm of combining sub‐window factor analysis with the mass spectrum information is proposed. The algorithm uses a peak detection approach derived either from multi‐scale Gaussian function or Haar wavelet to locate the peaks with different application scope; the candidate drift points at each peak are estimated by Fast Fourier transform cross correlation; Specifically, the best drift points at each candidate peaks are confirmed by sub‐window factor analysis and mass spectrum information in nontargeted metabolic profiling. Finally, the peak regions were aligned against a reference chromatogram, and the non‐peak regions were used linear interpolation. The chromatographic signals of 30 Bupleurum samples were aligned as an illustration of this algorithm, and they could be well distinguished using some statistical procedures. The result demonstrates that the presented method is stronger than other mass‐spectra based algorithms, when facing the alignment of some co‐eluted peaks.     

Detecting and aligning peaks in mass spectrometry data with applications to MALDI

In this paper, we address the peak detection and alignment problem in the analysis of mass spectrometry data. To deal with the peak redundancy problem existing in the MALDI data acquired in the reflectron mode, we propose to use the amplitude modulation technique in peak detection. The alignment of two peak sets is formulated as a non-rigid registration problem and is solved using a robust point matching (RPM) approach. To align multiple peak sets, we first use a super set method to find a common peak set among all peak sets as a standard and then align all peak sets to the standard using the robust point matching approach in a sequential manner (i.e. We align only one peak set to the standard each time, thus reducing the multiple peak set alignment problem to a simpler two peak set alignment problem). Experimental results from a study of ovarian cancer data set show that the quantitative cross-correlation coefficients among technical replicates are increased after peak alignment. Additional comparisons also demonstrate that our method has a similar performance as the hierarchical clustering method, although the implementations of these methods are different.