ProbRank: An efficient DNA database search method for complex mixtures per a quantitative likelihood ratio model.

Searching a DNA Database with a DNA profile from an evidentiary trace can provide investigative leads in a forensic case. Various searching approaches exist such as conventional methods based on matching alleles or more advanced methods computing likelihood ratios (LR) while considering drop-in and drop-out. Here we examine the potential of using a quantitative LR model (EuroForMix model incorporated in ProbRank method) that takes peak heights into account in comparison to a qualitative LR model (LRmix model implemented in SmartRank method). Both methods present DNA database candidates in order of decreasing LR. Especially regarding minor contributors in complex mixtures, the method using the quantitative model outperforms the method using the qualitative model in terms of sensitivity and specificity as more true donors and less adventitious matches are retrieved. ProbRank is to be implemented in DNAStatistX and is sufficiently fast for daily use.

A novel l-leucine 5-hydroxylase from Nostoc piscinale unravels unexpected sulfoxidation activity toward l-methionine.

Hydroxy amino acids are produced by Fe(II)/αKG-dependent dioxygenases and used widely as medicinal intermediates for chemical synthesis. A novel l-leucine 5-hydroxylase gene from Nostoc piscinale (NpLDO) was cloned into pET28a (+), pColdI and pQE-80 L plasmids. Using a two-step purification process (Ni-affinity chromatography and gel filtration), highly purified recombinant NpLDO was obtained. Recombinant NpLDO displayed unexpectedly high sulfoxidation activity toward l-methionine. The reaction products were analyzed by high-performance liquid chromatography. Sequence alignment analysis implied that residues of His150, His236 and Asp152 constitute the catalytic triad of NpLDO, which is completely conserved in the Fe(II)/αKG-dependent dioxygenase superfamily. Biochemical data showed that NpLDO catalyzed regio- and stereoselective hydroxylation of l-leucine and sulfoxidation of l-methionine with Fe(II) and l-ascorbic acid as cofactor, and αKG as cosubstrate, respectively.

Determining the number of contributors to DNA mixtures in the low-template regime: Exploring the impacts of sampling and detection effects.

The interpretation of DNA evidence may rely upon the assumption that the forensic short tandem repeat (STR) profile is composed of multiple genotypes, or partial genotypes, originating from n contributors. In cases where the number of contributors (NOC) is in dispute, it may be justifiable to compute likelihood ratios that utilize different NOC parameters in the numerator and denominator, or present different likelihoods separately. Therefore, in this work, we evaluate the impact of allele dropout on estimating the NOC for simulated mixtures with up to six contributors in the presence or absence of a major contributor. These simulations demonstrate that in the presence of dropout, or with the application of an analytical threshold (AT), estimating the NOC using counting methods was unreliable for mixtures containing one or more minor contributors present at low levels. The number of misidentifications was only slightly reduced when we expand the number of STR loci from 16 to 21. In many of the simulations tested herein, the minimum and actual NOC differed by more than two, suggesting that low-template, high-order mixtures with allele counts fewer than six may be originating from as many as four-, five-, or six-persons. Thus, there is justification for the use of differing or multiple assumptions on the NOC when computing the weight of DNA evidence for low-template mixtures, particularly when the peak heights are in the vicinity of the signal threshold or allele counting methods are the mechanism by which the NOC is assessed.

Protein charge determination and implications for interactions in cell extracts.

Decades of dilute-solution studies have revealed the influence of charged residues on protein stability, solubility and stickiness. Similar characterizations are now required in physiological solutions to understand the effect of charge on protein behavior under native conditions. Toward this end, we used free boundary and native gel electrophoresis to explore the charge of cytochrome c in buffer and in Escherichia coli extracts. We find that the charge of cytochrome c was ∼2-fold lower than predicted from primary structure analysis. Cytochrome c charge was tuned by sulfate binding and was rendered anionic in E. coli extracts due to interactions with macroanions. Mutants in which three or four cationic residues were replaced with glutamate were charge-neutral and "inert" in extracts. A comparison of the interaction propensities of cytochrome c and the mutants emphasizes the role of negative charge in stabilizing physiological environments. Charge-charge repulsion and preferential hydration appear to prevent aggregation. The implications for molecular organization in vivo are discussed.

CEESIt: A computational tool for the interpretation of STR mixtures.

In forensic DNA interpretation, the likelihood ratio (LR) is often used to convey the strength of a match. Expanding on binary and semi-continuous methods that do not use all of the quantitative data contained in an electropherogram, fully continuous methods to calculate the LR have been created. These fully continuous methods utilize all of the information captured in the electropherogram, including the peak heights. Recently, methods that calculate the distribution of the LR using semi-continuous methods have also been developed. The LR distribution has been proposed as a way of studying the robustness of the LR, which varies depending on the probabilistic model used for its calculation. For example, the LR distribution can be used to calculate the p-value, which is the probability that a randomly chosen individual results in a LR greater than the LR obtained from the person-of-interest (POI). Hence, the p-value is a statistic that is different from, but related to, the LR; and it may be interpreted as the false positive rate resulting from a binary hypothesis test between the prosecution and defense hypotheses. Here, we present CEESIt, a method that combines the twin features of a fully continuous model to calculate the LR and its distribution, conditioned on the defense hypothesis, along with an associated p-value. CEESIt incorporates dropout, noise and stutter (reverse and forward) in its calculation. As calibration data, CEESIt uses single source samples with known genotypes and calculates a LR for a specified POI on a question sample, along with the LR distribution and a p-value. The method was tested on 303 files representing 1-, 2- and 3-person samples injected using three injection times containing between 0.016 and 1 ng of template DNA. Our data allows us to evaluate changes in the LR and p-value with respect to the complexity of the sample and to facilitate discussions regarding complex DNA mixture interpretation. We observed that the amount of template DNA from the contributor impacted the LR--small LRs resulted from contributors with low template masses. Moreover, as expected, we observed a decrease of p-values as the LR increased. A p-value of 10(-9) or lower was achieved in all the cases where the LR was greater than 10(8). We tested the repeatability of CEESIt by running all samples in duplicate and found the results to be repeatable.

An assessment of the information content of likelihood ratios derived from complex mixtures.

With the increasing sensitivity of DNA typing methodologies, as well as increasing awareness by law enforcement of the perceived capabilities of DNA typing, complex mixtures consisting of DNA from two or more contributors are increasingly being encountered. However, insufficient research has been conducted to characterize the ability to distinguish a true contributor (TC) from a known non-contributor (KNC) in these complex samples, and under what specific conditions. In order to investigate this question, sets of six 15-locus Caucasian genotype profiles were simulated and used to create mixtures containing 2-5 contributors. Likelihood ratios were computed for various situations, including varying numbers of contributors and unknowns in the evidence profile, as well as comparisons of the evidence profile to TCs and KNCs. This work was intended to illustrate the best-case scenario, in which all alleles from the TC were detected in the simulated evidence samples. Therefore the possibility of drop-out was not modeled in this study. The computer program DNAMIX was then used to compute LRs comparing the evidence profile to TCs and KNCs. This resulted in 140,000 LRs for each of the two scenarios. These complex mixture simulations show that, even when all alleles are detected (i.e. no drop-out), TCs can generate LRs less than 1 across a 15-locus profile. However, this outcome was rare, 7 of 140,000 replicates (0.005%), and associated only with mixtures comprising 5 contributors in which the numerator hypothesis includes one or more unknown contributors. For KNCs, LRs were found to be greater than 1 in a small number of replicates (75 of 140,000 replicates, or 0.05%). These replicates were limited to 4 and 5 person mixtures with 1 or more unknowns in the numerator. Only 5 of these 75 replicates (0.004%) yielded an LR greater than 1,000. Thus, overall, these results imply that the weight of evidence that can be derived from complex mixtures containing up to 5 contributors, under a scenario in which no drop-out is required to explain any of the contributors, is remarkably high. This is a useful benchmark result on top of which to layer the effects of additional factors, such as drop-out, peak height, and other variables.

Familial searching on DNA mixtures with dropout.

Familial searching, the act of searching a database for a relative of an unknown individual whose DNA profile has been obtained, is usually restricted to cases where the DNA profile of that person has been unambiguously determined. Therefore, it is normally applied only with a good quality single source profile as starting point. In this article we investigate the performance of the method if applied to mixtures with and without allelic dropout, when likelihood ratios are computed with a semi-continuous (binary) model. We show that mixtures with dropout do not necessarily perform worse than mixtures without, especially if some separation between the donors is possible due to their different dropout probabilities. The familial searching true and false positive rates of mixed profiles on 15 loci are in some cases better than those of single source profiles on 10 loci. Thus, the information loss due to the fact that the person of interest's DNA has been mixed with that of other, and is affected by dropout, can be less than the loss of information corresponding to having 5 fewer loci available for a single source trace. Profiles typed on 10 autosomal loci are often involved in familial searching casework since many databases, including the Dutch one, in part consist of such profiles. Therefore, from this point of view, there seems to be no objection to extend familial searching to mixed or degraded profiles.

Distinguishing between donors and their relatives in complex DNA mixtures with binary models.

While likelihood ratio calculations were until the recent past limited to the evaluation of mixtures in which all alleles of all donors are present in the DNA mixture profile, more recent methods are able to deal with allelic dropout and drop-in. This opens up the possibility to obtain likelihood ratios for mixtures where this was not previously possible, but it also means that a full match between the alleged contributor and the crime stain is no longer necessary. We investigate in this article what the consequences are for relatives of the actual donors, because they typically share more alleles with the true donor than an unrelated individual. We do this with a semi-continuous binary approach, where the likelihood ratios are based on the observed alleles and the dropout probabilities for each donor, but not on the peak heights themselves. These models are widespread in the forensic community. Since in many cases a simple model is used where a uniform dropout probability is assumed for all (or for all unknown) contributors, we explore the extent to which this alters the false positive probabilities for relatives of donors, compared to what would have been obtained with the correct probabilities of dropout for each donor.

A cost-effective polyphosphate-based metabolism fuels an all E. coli cell-free expression system.

A new cost-effective metabolism providing an ATP-regeneration system for cell-free protein synthesis is presented. Hexametaphosphate, a polyphosphate molecule, is used as phosphate donor together with maltodextrin, a polysaccharide used as carbon source to stimulate glycolysis. Remarkably, addition of enzymes is not required for this metabolism, which is carried out by endogenous catalysts present in the Escherichia coli crude extract. This new ATP regeneration system allows efficient recycling of inorganic phosphate, a strong inhibitor of protein synthesis. We show that up to 1.34-1.65mg/mL of active reporter protein is synthesized in batch-mode reaction after 5h of incubation. Unlike typical hybrid in vitro protein synthesis systems based on bacteriophage transcription, expression is carried out through E. coli promoters using only the endogenous transcription-translation molecular machineries provided by the extract. We demonstrate that traditional expensive energy regeneration systems, such as creatine phosphate, phosphoenolpyruvate or phosphoglycerate, can be replaced by a cost-effective metabolic scheme suitable for cell-free protein synthesis applications. Our work also shows that cell-free systems are useful platforms for metabolic engineering.

Complex DNA mixture analysis in a forensic context: evaluating the probative value using a likelihood ratio model.

The interpretation of mixed DNA profiles obtained from low template DNA samples has proven to be a particularly difficult task in forensic casework. Newly developed likelihood ratio (LR) models that account for PCR-related stochastic effects, such as allelic drop-out, drop-in and stutters, have enabled the analysis of complex cases that would otherwise have been reported as inconclusive. In such samples, there are uncertainties about the number of contributors, and the correct sets of propositions to consider. Using experimental samples, where the genotypes of the donors are known, we evaluated the feasibility and the relevance of the interpretation of high order mixtures, of three, four and five donors. The relative risks of analyzing high order mixtures of three, four, and five donors, were established by comparison of a 'gold standard' LR, to the LR that would be obtained in casework. The 'gold standard' LR is the ideal LR: since the genotypes and number of contributors are known, it follows that the parameters needed to compute the LR can be determined per contributor. The 'casework LR' was calculated as used in standard practice, where unknown donors are assumed; the parameters were estimated from the available data. Both LRs were calculated using the basic standard model, also termed the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim. We show how our results furthered the understanding of the relevance of analyzing high order mixtures in a forensic context. Limitations are highlighted, and it is illustrated how our study serves as a guide to implement likelihood ratio interpretation of complex DNA profiles in forensic casework.

Proteome informatics research group (iPRG)_2012: a study on detecting modified peptides in a complex mixture.

The proteome informatics research group of the Association of Biomolecular Resource Facilities conducted a study to assess the community's ability to detect and characterize peptides bearing a range of biologically occurring post-translational modifications when present in a complex peptide background. A data set derived from a mixture of synthetic peptides with biologically occurring modifications combined with a yeast whole cell lysate as background was distributed to a large group of researchers and their results were collectively analyzed. The results from the twenty-four participants, who represented a broad spectrum of experience levels with this type of data analysis, produced several important observations. First, there is significantly more variability in the ability to assess whether a results is significant than there is to determine the correct answer. Second, labile post-translational modifications, particularly tyrosine sulfation, present a challenge for most researchers. Finally, for modification site localization there are many tools being employed, but researchers are currently unsure of the reliability of the results these programs are producing.

Molecular detection of invasive species in heterogeneous mixtures using a microfluidic carbon nanotube platform.

Screening methods to prevent introductions of invasive species are critical for the protection of environmental and economic benefits provided by native species and uninvaded ecosystems. Coastal ecosystems worldwide remain vulnerable to damage from aquatic species introductions, particularly via ballast water discharge from ships. Because current ballast management practices are not completely effective, rapid and sensitive screening methods are needed for on-site testing of ships in transit. Here, we describe a detection technology based on a microfluidic chip containing DNA oligonucleotide functionalized carbon nanotubes. We demonstrate the efficacy of the chip using three ballast-transported species either established (Dreissena bugensis) or of potential threat (Eriocheir sinensis and Limnoperna fortuneii) to the Laurentian Great Lakes. With further refinement for on-board application, the technology could lead to real-time ballast water screening to improve ship-specific management and control decisions.

A PMMA microfluidic droplet platform for in vitro protein expression using crude E. coli S30 extract.

Droplet based microfluidics are promising new tools for biological and chemical assays. In this paper, a high throughput and high sensitivity microfluidic droplet platform is described for in vitro protein expression using crude Escherichia coli S30 extract. A flow-focusing polymethylmethacrylate (PMMA) microchip was designed and integrated with different functions involving droplet generation, storage, separation and detection. The material used for the chip is superior to the previously tested polydimethylsiloxane (PDMS) due to its mechanical and chemical properties. Droplet formation characteristics such as size and generation rate are investigated systematically. The effect of surfactants Abil EM90 and Span80 in the oil phase on droplet formation and optical detection is also studied. The performance of the system is demonstrated by the high throughput and stable droplet generation and ultralow detection limit. The robustness of the system is also demonstrated by the successful synthesis of a green fluorescent protein (GFP) using E. coli S30 extract as a source of RNA translation reagents.

Unknown biological mixtures evaluation using STR analytical quantification.

Allelic quantification of STRs, where the presence of three or more alleles represents mixtures, provides a novel method to identify mixtures from unknown biological sources. The allelic stutters resulting in slightly different repeat containing products during fragment amplification can be mistaken for true alleles complicating a simple approach to mixture analysis. An algorithm based on the array of estimated stutters from known samples was developed and tuned to maximize the identification of true non-mixtures through the analysis of three pentanucleotide STRs. Laboratory simulated scenarios of needle sharing generated 58 mixture and 38 non-mixture samples that were blinded for determining the number of alleles. Through developing and applying an algorithm that additively estimates stuttering around the two highest peaks, mixtures and non-mixtures were characterized with sensitivity of 77.5, 82.7 and 58% while maintaining the high specificity of 100, 97.4 and 100 for the W, X, and Z STRs individually. When all three STRs were used collectively, the resulting sensitivity and specificity was 91.4 and 97.4%, respectively. The newly validated approach of using multiple STRs as highly informative biomarkers in unknown sample mixture analyses has potential applications in genetics, forensic science, and epidemiological studies.

Molecular characterisation of SALMFamide neuropeptides in sea urchins.

The SALMFamides are a family of neuropeptides found in species belonging to the phylum Echinodermata. Members of this family have been identified in starfish (class Asteroidea) and in sea cucumbers (class Holothuroidea) but not in other echinoderms. Our aim here was to characterise SALMFamide neuropeptides in sea urchins (class Echinoidea). Radioimmunoassays for the starfish SALMFamides S1 and S2 were used to test for related peptides in whole-body acetone extracts of the sea urchin Echinus esculentus. Fractionation of extracts using high performance liquid chromatography (HPLC) revealed several peaks of SALMFamide-like immunoreactivity, with two S2-like immunoreactive peaks (3 and 4) being the most prominent. However, peak 4 could not be purified to homogeneity and although peak 3 was purified, only a partial sequence (MRYH) could be obtained. An alternative strategy for identification of echinoid SALMFamides was provided by sequencing the genome of the sea urchin Strongylocentrotus purpuratus. Analysis of whole-genome shotgun sequence data using the Basic Local Alignment Search Tool (BLAST) identified a contig (347664) that contains a coding region for seven putative SALMFamide neuropeptides (PPVTTRSKFTFamide, DAYSAFSFamide, GMSAFSFamide, AQPSFAFamide, GLMPSFAFamide, PHGGSAFVFamide and GDLAFAFamide), which we have named SpurS1-SpurS7, respectively. Three of these peptides (SpurS1-3) have the C-terminal sequences TFamide or SFamide, which are identical or similar to the C-terminal region of the starfish SALMFamide S2. This may explain the occurrence of several S2-like immunoreactive peptides in extracts of Echinus esculentus. Detailed analysis of the sequence of contig 347664 indicated that the SALMFamide gene in Strongylocentrotus purpuratus comprises two exons, with the first exon encoding a signal peptide sequence and the second exon encoding SpurS1-SpurS7. Characterisation of this gene is important because it is the first echinoderm neuropeptide precursor sequence to be identified and, more specifically, it provides our first insight into the structure and organisation of a SALMFamide gene in an echinoderm. In particular, it has revealed a hitherto unknown complexity in the diversity of SALMFamide neuropeptides that may occur in an echinoderm species because all previous studies, which relied on peptide purification and sequencing, revealed only two SALMFamide neuropeptides in each species examined. It now remains to be established whether or not the occurrence of more than two SALMFamides in Strongylocentrotus purpuratus is a feature that is peculiar to this species and to echinoids in general or is more widespread across the phylum Echinodermata. Identification of SpurS1-SpurS7 provides the basis for comparative analysis of the physiological actions of these peptides in sea urchins and for exploitation of the sea urchin genome sequence to identify the receptor(s) that mediate effects of SALMFamides in echinoderms.

Crude extracts of bacterially expressed dsRNA can be used to protect plants against virus infections.

BACKGROUND: Double-stranded RNA (dsRNA) is a potent initiator of gene silencing in a diverse group of organisms that includes plants, Caenorhabditis elegans, Drosophila and mammals. We have previously shown and patented that mechanical inoculation of in vitro-transcribed dsRNA derived from viral sequences specifically prevents virus infection in plants. The approach required the in vitro synthesis of large amounts of RNA involving high cost and considerable labour. RESULTS: We have developed an in vivo expression system to produce large amounts of virus-derived dsRNAs in bacteria, with a view to providing a practical control of virus diseases in plants. Partially purified bacterial dsRNAs promoted specific interference with the infection in plants by two viruses belonging to the tobamovirus and potyvirus groups. Furthermore, we have demonstrated that easy to obtain, crude extracts of bacterially expressed dsRNAs are equally effective protecting plants against virus infections when sprayed onto plant surfaces by a simple procedure. Virus infectivity was significantly abolished when plants were sprayed with French Press lysates several days before virus inoculation. CONCLUSION: Our approach provides an alternative to genetic transformation of plant species with dsRNA-expressing constructs capable to interfere with plant viruses. The main advantage of this mode of dsRNA production is its simplicity and its extremely low cost compared with the requirements for regenerating transgenic plants. This approach provides a reliable and potential tool, not only for plant protection against virus diseases, but also for the study of gene silencing mechanisms in plant virus infections.