Developmental validation of STRmix™ NGS, a probabilistic genotyping tool for the interpretation of autosomal STRs from forensic profiles generated using NGS.

We describe the developmental validation of the probabilistic genotyping software - STRmix™ NGS - developed for the interpretation of forensic DNA profiles containing autosomal STRs generated using next generation sequencing (NGS) also known as massively parallel sequencing (MPS) technologies. Developmental validation was carried out in accordance with the Scientific Working Group on DNA Analysis Methods (SWGDAM) Guidelines for the Validation of Probabilistic Genotyping Systems and the International Society for Forensic Genetics (ISFG) recommendations and included sensitivity and specificity testing, accuracy, precision, and the interpretation of case-types samples. The results of developmental validation demonstrate the appropriateness of the software for the interpretation of profiles developed using NGS technology.

Validation of a neural network approach for STR typing to replace human reading.

A typical forensic laboratory process for interpreting STR capillary electrophoresis profile data is for two people to independently 'read' the profiles, compare results, and resolve any differences. Recently, work has been conducted to develop a machine learning tool called an artificial neural network (ANN) to carry out the same function as a human profile reader, by classifying areas of fluorescence in the capillary electrophoresis profile raw signal data. The ANN approach has been embedded in commercial software FaSTR™ DNA to read GlobalFiler™ DNA profiles. The ANN feature of FaSTR™ DNA was investigated during validation at Forensic Science South Australia (FSSA) to determine whether one of the human profile readers could be replaced by an ANN reader. FaSTR™ DNA accuracy in detecting allele peaks in reference profiles was 99.7% and was deemed high enough that a one-reader workflow could be implemented into the reference reading workflow at FSSA.

Modeling allelic analyte signals for aSTRs in NGS DNA profiles.

We describe an adaption of Bright et al.'s work modeling peak height variability in CE-DNA profiles to the modeling of allelic aSTR (autosomal short tandem repeats) read counts from NGS-DNA profiles, specifically for profiles generated from the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B. Bright et al.'s model consists of three key components within the estimation of total allelic product-template, locus-specific amplification efficiencies, and degradation. In this work, we investigated the two mass parameters-template and locus-specific amplification efficiencies-and used MLE (maximum likelihood estimation) and MCMC (Markov chain Monte Carlo) methods to obtain point estimates to calculate the total allelic product. The expected read counts for alleles were then calculated after proportioning some of the expected stutter product from the total allelic product. Due to preferential amplicon selection introduced by the sample purification beads, degradation is difficult to model from the aSTR outputs alone. Improved modeling of the locus-specific amplification efficiencies may mask the effects of degradation. Whilst this model could be improved by introducing locus specific variances in addition to locus specific priors, our results demonstrate the suitability of adapting Bright et al.'s allele peak height model for NGS-DNA profiles. This model could be incorporated into continuous probabilistic interpretation approaches for mixed DNA profiles.

Estimating the number of contributors to a DNA profile using decision trees.

The interpretation of DNA profiles typically starts with an assessment of the number of contributors. In the last two decades, several methods have been proposed to assist with this assessment. We describe a relatively simple method using decision trees, that is fast to run and fully transparent to a forensic analyst. We use mixtures from the publicly available PROVEDIt dataset to demonstrate the performance of the method. We show that the performance of the method crucially depends on the performance of filters for stutter and other artefacts. We compare the performance of the decision tree method with other published methods for the same dataset.

Variability and additivity of read counts for aSTRs in NGS DNA profiles.

There has been an increase in the number of laboratories and researchers adopting new sequencing technologies, known as next-generation sequencing (NGS). An understanding of the behaviour of NGS DNA profiles is needed to enable for the development of probabilistic genotyping methods for the interpretation of such profiles. In this work, we investigate NGS analyte signal variation, specifically heterozygous balance and stutter variability from profiles generated using the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B. We also investigate additivity of analyte signals in NGS profiles for overlapping allelic and stutter signals originating from the same or different contributors. We describe models that can be used to inform a continuous method for the interpretation of DNA profiling data.

iStable 2.0: Predicting protein thermal stability changes by integrating various characteristic modules.

Protein mutations can lead to structural changes that affect protein function and result in disease occurrence. In protein engineering, drug design or and optimization industries, mutations are often used to improve protein stability or to change protein properties while maintaining stability. To provide possible candidates for novel protein design, several computational tools for predicting protein stability changes have been developed. Although many prediction tools are available, each tool employs different algorithms and features. This can produce conflicting prediction results that make it difficult for users to decide upon the correct protein design. Therefore, this study proposes an integrated prediction tool, iStable 2.0, which integrates 11 sequence-based and structure-based prediction tools by machine learning and adds protein sequence information as features. Three coding modules are designed for the system, an Online Server Module, a Stand-alone Module and a Sequence Coding Module, to improve the prediction performance of the previous version of the system. The final integrated structure-based classification model has a higher Matthews correlation coefficient than that of the single prediction tool (0.708 vs 0.547, respectively), and the Pearson correlation coefficient of the regression model likewise improves from 0.669 to 0.714. The sequence-based model not only successfully integrates off-the-shelf predictors but also improves the Matthews correlation coefficient of the best single prediction tool by at least 0.161, which is better than the individual structure-based prediction tools. In addition, both the Sequence Coding Module and the Stand-alone Module maintain performance with only a 5% decrease of the Matthews correlation coefficient when the integrated online tools are unavailable. iStable 2.0 is available at http://ncblab.nchu.edu.tw/iStable2.

The interpretation of mixed DNA profiles from a mother, father, and child trio.

We report the interpretation of three-person mixed DNA profiles constructed from DNA from one mother, father, and child trio using the probabilistic genotyping software STRmix™. A total of 40 mixtures were examined, with varying total template and mixture proportions of the three contributors. In addition, mixtures were artificially degraded at four different rates to test the effects of degradation on the interpretation of mother, father and child trios. A total of 560 STRmix™ analyses were undertaken, examining four different interpretation strategies. Reasonable results were only achieved by conditioning on one parent as an assumed donor and applying a user-informed prior to the mixture proportion of both parents. For each of the 40 amplified mixtures, 10,000 non-donors were compared, conditioning on one parent and applying a user-informed prior to the mixture proportion of both parents. This leads to 800,000 non-donor tests.

The sex-specific association between maternal paraben exposure and size at birth.

Parabens are a group of esters of parahydroxybenzoic acid and are utilized as antimicrobial preservatives in the majority of personal care products (PCPs). Epidemiological studies regarding the adverse effects of parabens on fetuses are still limited. The aim of this study was to determine the association between maternal paraben exposure and birth outcomes. One hundred and ninety-nine pregnant women were enrolled, and maternal urine was collected in the third trimester. The urine concentrations of four parabens (methyl (MP), ethyl (EP), propyl (PP), and butyl (BP)) were determined by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Generalized additive model-penalized regression splines and a multivariable regression model were employed to determine the association between paraben exposure levels and birth outcomes. A causal mediation analysis was conducted to determine the mediation effect of oxidative stress on birth outcomes. The geometric means of urinary MP, EP, PP, and BP were 51.79, 1.26, 4.21, and 1.25 µg/g cre., respectively. In the penalized regression splines, sex-specific associations between maternal MP levels and birth outcomes were observed; a downward curvature was observed between the MP level and birth weight, length, head circumference, and thoracic circumference among female newborns. Pregnant women in the group with MP levels above the third quartile had neonates with significantly lower body weight (ß = -215.98 g, p value = 0.02) compared to those in the group with MP levels lower than the third quartile. No significant mediation of oxidative stress was observed between maternal MP exposure and female birth weight. The estimated proportion mediated ranged from -6% to 15%. The negative association between maternal paraben exposure and female birth outcomes in relation to child development should be carefully considered.

Associations between prenatal exposure to bisphenol a and neonatal outcomes in a Taiwanese cohort study: Mediated through oxidative stress?

This study determined whether maternal bisphenol A (BPA) exposure influences birth outcomes through oxidative stress and estimated the daily intake of BPA through breast milk for infants. One hundred and eighty-six pregnant women without pregnancy complications were enrolled and maternal urine was collected in the third trimester. Postnatal breast milk was collected in the first and third months after delivery. Concentrations of BPA were determined through ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Generalized additive model-penalized regression splines and a multivariable regression model were employed to determine the effects of BPA exposure and oxidative stress levels on birth outcomes. A causal mediation analysis was conducted to clarify the mediation effects of oxidative stress due to maternal BPA exposure on birth outcomes. The daily intake of BPA in breast milk was calculated using probabilistic risk assessment methods. The geometric means (geometric standard deviation) of BPA levels for maternal urine and first- and third-month breast milk were 2.19 (2.88) µg/g creatinine., 1.35 (3.53) ng/g, and 3.17 (2.97) ng/g, respectively. No significant mediation existed among maternal BPA exposure, oxidative stress level, and neonatal head circumference. Three percent of 1-monthold babies and 1% of 3-month-old babies exceeded the BPA tolerable daily intake of 4 µg/kg-bw/day proposed by the European Food Safety Authority. This study revealed the BPA exposure profile for pregnant women and infants in northern Taiwan. The marginally significant correlation between maternal BPA exposure and neonatal head circumference should be considered.

Interactive effects of nonylphenol and bisphenol A exposure with oxidative stress on fetal reproductive indices.

Nonylphenol (NP) and/or bisphenol A (BPA) may have reproductive effects. Although the mechanisms of action remain unclear, steroid hormones biosynthesis, hypothalamus pituitary adrenal axis activity, oxidative stress, and crosstalk interaction of NP and BPA mixture and its pathways may play a contributory role. This cross-sectional study examined whether the interactive effects of NP/BPA and oxidative stress biomarkers played a role in reproductive indices (penis length and anogenital distance (AGD)) in 244 mother-fetus pairs. Four biomarkers of oxidative stress, (8-hydroxy-2'-deoxyguanosine (8-OHdG), 8-nitroguanine (8-NO2Gua), 8-iso-prostaglandin F2α (8-isoPF2α), and 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA)) were simultaneously analyzed using the high-performance liquid chromatography-electrospray ionization tandem mass spectrometry method. No significant associations were found between reproductive indices and NP/BPA or oxidative stress biomarkers. Maternal exposure to a mixture of NP and BPA may enhance 8-OHdG. Interactive effects were found in the high 8-isoPF2α group, and prenatal NP exposure was inversely associated with penis length (ß = -3.68 mm; p = 0.01). Similar results were noted among boys who were born to mothers in the high 8-isoPF2α group, in which BPA was inversely associated with penis length (ß = -4.43 mm; p = 0.005). Our findings suggest important implications for prenatal exposure to oxidative stress, as evidenced by the 8-isoPF2α level. Thus, NP and BPA may interact to shape fetal reproductive tract development, particularly in boys. The interactive effects of NP/BPA, oxidative stress, and reproductive indices should be considered.

A fully continuous system of DNA profile evidence evaluation that can utilise STR profile data produced under different conditions within a single analysis.

The introduction of probabilistic DNA interpretation systems has made it possible to evaluate many profiles that previously (under a manual interpretation system) were not. These probabilistic systems have been around for a number of years and it is becoming more common that their use within a laboratory has spanned at least one technology change. This may be a change in laboratory hardware, the DNA profiling kit used, or the manner in which the profile is generated. Up until this point, when replicates DNA profiles are generated, that span a technological change, the ability to utilise all the information in all replicates has been limited or non-existent. In this work we explain and derive the models required to evaluate (what we term) multi-kit analysis problems. We demonstrate the use of the multi-kit feature on a number of scenarios where such an analysis would be desired within a laboratory. Allowing the combination of profiling data that spans a technological change will further increase the amount of DNA profile information produced in a laboratory that can be evaluated.

Membrane protein assembly: two cytoplasmic phosphorylated serine sites of Vpu from HIV-1 affect oligomerization.

Viral protein U (Vpu) encoded by human immunodeficiency virus type 1 (HIV-1) is a short integral membrane protein which is known to self-assemble within the lipid membrane and associate with host factors during the HIV-1 infectivity cycle. In this study, full-length Vpu (M group) from clone NL4-3 was over-expressed in human cells and purified in an oligomeric state. Various single and double mutations were constructed on its phosphorylation sites to mimic different degrees of phosphorylation. Size exclusion chromatography of wild-type Vpu and mutants indicated that the smallest assembly unit of Vpu was a dimer and over time Vpu formed higher oligomers. The rate of oligomerization increased when (i) the degree of phosphorylation at serines 52 and 56 was decreased and (ii) when the ionic strength was increased indicating that the cytoplasmic domain of Vpu affects oligomerization. Coarse-grained molecular dynamic simulations with models of wild-type and mutant Vpu in a hydrated lipid bilayer supported the experimental data in demonstrating that, in addition to a previously known role in downregulation of host factors, the phosphorylation sites of Vpu also modulate oligomerization.

Patch formation of a viral channel forming protein within a lipid membrane--Vpu of HIV-1.

Ion channels and their viral companions are defined by their quaternary structure. The individual sub-units have to assemble into homo- or hetero-oligomers. Using Vpu of HIV-1, a putative viral channel forming protein (VCP), as a test case, the formation of a quaternary structure is monitored using coarse grained molecular dynamics (CGMD) simulations. Full length Vpu is generated by combining the helical transmembrane domain (TMD) with the cytoplasmic domain derived from NMR spectroscopy. Patches of 2 to 6 as well as patches of 16 and 32 Vpu proteins, Vpu-WT, containing unphosphorylated serines 52 and 56 are used to study assembly dynamics. The same patches are simulated for the Vpu double mutant, Vpu-DD, in which the two serines 52 and 56 are replaced by aspartic acid. Serines 52 and 56 in Vpu-WT allow short lived contacts between the cytoplasmic domains. Dimer formation is the first step for long lasting assemblies and is induced by the EYR motif. Roll-over movements allow rearrangement within the dimer. Independent of the number of Vpu proteins, Vpu-DD prefers smaller aggregates than Vpu-WT. In the case of simulation of 4 Vpu-WT proteins a pore-like assembly is directly identified with the TMD Ser-23 pointing towards a putative central pore axis.

Estimating binding free energy of a putative growth factors EGF-VEGF complex - a computational bioanalytical study.

Epidermal growth factor (EGF) and homodimeric vascular endothelial growth factor (VEGF) bind to cell surface receptors. They are responsible for cell growth and angiogenesis, respectively. Docking of the individual proteins as monomeric units using ZDOCK 2.3.2 reveals a partial blocking of the receptor binding site of VEGF by EGF. The receptor binding site of EGF is not affected by VEGF. The calculated binding energy is found to be intermediate between the binding energies calculated for Alzheimer's Aß42 and the barnase/barstar complex.

Degraded RNA transcript stable regions (StaRs) as targets for enhanced forensic RNA body fluid identification.

The detection of messenger RNA (mRNA) using reverse transcriptase PCR (RT-PCR) is becoming common practice for forensic body fluid identification. However, the degraded and scarce nature of RNA from forensic samples mean that mRNA transcripts are not consistently detected or remain undetected in practice. Conventional primer design for RT-PCR (and quantitative RT-PCR) includes targeting primers to span exon-exon boundaries or by having the primers on two separate exons, and satisfying common primer thermodynamic criteria. We have found that the conventional placement of primers is not always optimal for obtaining reproducible results from degraded samples. Using massively parallel sequencing data from degraded body fluids, we designed primers to amplify transcript regions of high read coverage, hence, higher stability, and compared these with primers designed using conventional methodology. Our findings are that primers designed for transcript regions of higher read coverage resulted in vastly improved detection of mRNA transcripts that were not previously detected or were not consistently detected in the same samples using conventional primers. We developed a new concept whereby primers targeted to transcript stable regions (StaRs) are able to consistently and specifically amplify a wide range of RNA biomarkers in various body fluids of varying degradation levels.

Development and Characterization of the Recombinant Human VEGF-EGF Dual-Targeting Fusion Protein as a Drug Delivery System.

The design, preparation, as well as structural and functional characterizations of the recombinant fusion protein hVEGF-EGF as a dual-functional agent that may target both EGFR (R: receptor) and angiogenesis are reported. hVEGF-EGF was found to bind to EGFR more strongly than did EGF, and to bind to VEGFR similarly to VEGF. Mass spectrometry measurements showed that the sites of DTPA (diethylenetriaminepentaacetic acid) conjugated hVEGF-EGF (for radiolabeling) were the same as those of its parent hEGF and hVEGF proteins. All DTPA-conjugated proteins retained similar binding capacities to their respective receptors as compared to their respective parent proteins. In vitro cell binding studies using BAEC (a bovine aortic endothelial cell) and MDA-MB-231 (a human breast cancer) cells expressing both EGFR and VEGFR confirmed similar results. Treating BAEC cells with hVEGF-EGF induced remarkable phosphorylation of EGFR, VEGFR, and their downstream targets ERK1/2. Nevertheless, the radiolabeled (111)In-DTPA-hVEGF-EGF showed cytotoxicity against MDA-MB-231 cells. Pharmacokinetic studies using (111)In-DTPA-hVEGF-EGF in BALB/c nude mice showed that appreciable tracer activities were accumulated in liver and spleen. In all, this study demonstrated that the fusion protein hVEGF-EGF maintained the biological specificity toward both EGFR and VEGFR and may be a potential candidate as a dual-targeting moiety in developing anticancer drugs.

Online open-tubular fractionation scheme coupled with push-pull perfusion sampling for profiling extravasation of gold nanoparticles in a mouse tumor model.

The extravasation of administered nano-drug carriers is a critical process for determining their distributions in target and non-target organs, as well as their pharmaceutical efficacies and side effects. To evaluate the extravasation behavior of gold nanoparticles (AuNPs), currently the most popular drug delivery system, in a mouse tumor model, in this study we employed push-pull perfusion (PPP) as a means of continuously sampling tumor extracellular AuNPs. To facilitate quantification of the extravasated AuNPs through inductively coupled plasma mass spectrometry, we also developed a novel online open-tubular fractionation scheme to allow interference-free determination of the sampled extracellular AuNPs from the coexisting biological matrix. After optimizing the flow-through volume and flow rate of this proposed fractionation scheme, we found that (i) the system's temporal resolution was 7.5h(-1), (ii) the stability presented by the coefficient of variation was less than 10% (6-h continuous measurement), and (iii) the detection limits for the administered AuNPs were in the range 0.057-0.068µgL(-1). Following an intravenous dosage of AuNPs (0.3mgkg(-1) body weight), in vivo acquired profiles indicated that the pegylated AuNPs (PEG-AuNPs) had greater tendency toward extravasating into the tumor extracellular space. We also observed that the accumulation of nanoparticles in the whole tumor tissues was higher for PEG-AuNPs than for non-pegylated ones. Overall, pegylation appears to promote the extravasation and accumulation of AuNPs for nano-drug delivery applications.

Transcriptomic analysis of degraded forensic body fluids.

Massively parallel sequencing (MPS) has facilitated a significant increase in transcriptomic studies in all biological disciplines. However, the analysis of degraded RNA remains a genuine challenge in practice. In forensic science the biological samples encountered are often extensively degraded and of low abundance. RNA from these compromised samples is used for body fluid identification through the detection of body fluid-specific transcripts. Here we demonstrate the sequencing of four forensically relevant body fluids: oral mucosa/saliva (buccal), circulatory blood, menstrual blood and vaginal fluid. RNA was extracted from fresh, two and six week aged samples. Despite the extensive degradation of most body fluids, significant high quality sequencing output (>80% sequence above Q30) was generated. An average of over 80% of reads from all but one sample aligned successfully to the reference human genome. Furthermore, FPKMs (fragments per kilobase of exon per million fragments mapped) generated indicate the accurate detection of known body fluid markers in respective body fluids. Assessment of global gene expression levels over degradation time enabled the characterisation of differential RNA degradation in different body fluids. This study demonstrates the practical application of MPS technology for the accurate analysis of degraded RNA from minimal samples.

Structure based computational assessment of channel properties of assembled ORF-8a from SARS-CoV.

ORF 8a is a short 39 amino acid bitopic membrane protein encoded by severe acute respiratory syndrome causing corona virus (SARS-CoV). It has been identified to increase permeability of the lipid membrane for cations. Permeability is suggested to occur due to the assembly of helical bundles. Computational models of a pentameric assembly of 8a peptides are generated using the first 22 amino acids, which include the transmembrane domain. Low energy structures reveal a hydrophilic pore mantled by residues Thr-8, and -18, Ser-11, Cys-13, and Arg-22. Potential of mean force (PMF) profiles for mono (Na(+) , K(+) , Cl(-) ) and divalent (Ca(2+) ) ions along the pore are calculated. The data support experimental findings of a weak cation selectivity of the channel. Calculations on 8a are compared to data derived for a pentameric bundle consisting of the M2 helices of the bacterial pentameric ligand gated ion channel GLIC (3EHZ). PMF curves of both, bundles 8a and M2, show sigmoidal shaped profiles. In comparison to the data for the M2-GLIC model, data of the 8a bundle show lower amplitude of the PMF values between maximum and minimum and less discrimination amongst ions.