Draft versus finished sequence data for DNA and protein diagnostic signature development

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10(−3)–10(−5) (∼8× coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of ∼1% (3× to 6× coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures

LAVA: An Open-Source Approach To Designing LAMP (Loop-Mediated Isothermal Amplification) DNA Signatures

<p>Abstract</p> <p>Background</p> <p>We developed an extendable open-source Loop-mediated isothermal AMPlification (LAMP) signature design program called LAVA (LAMP Assay Versatile Analysis). LAVA was created in response to limitations of existing LAMP signature programs.</p> <p>Results</p> <p>LAVA identifies combinations of six primer regions for basic LAMP signatures, or combinations of eight primer regions for LAMP signatures with loop primers, which can be used as LAMP signatures. The identified primers are conserved among target organism sequences. Primer combinations are optimized based on lengths, melting temperatures, and spacing among primer sites. We compare LAMP signature candidates for <it>Staphylococcus aureus </it>created both by LAVA and by PrimerExplorer. We also include signatures from a sample run targeting all strains of <it>Mycobacterium tuberculosis</it>.</p> <p>Conclusions</p> <p>We have designed and demonstrated new software for identifying signature candidates appropriate for LAMP assays. The software is available for download at <url>http://lava-dna.googlecode.com/</url>.</p

Draft versus finished sequence data for DNA and protein diagnostic signature development

Abstract Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop highquality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors, or NNs) to sequence. We use SAP to assess whether draft data is sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high quality draft with error rates of 10 -3 -10 -5 (~8x coverage) of target organisms is suitable for DNA signature prediction. Low quality draft with error rates of ~1% (3x to 6x coverage) of target isolates is inadequate for DNA signature prediction, although low quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high quality draft of target and low quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures. 3 Introduction Draft sequencing requires that the order of base pairs in cloned fragments of a genome be determined usually at least 4 times (4x depth of coverage) at each position for a minimum degree of draft accuracy. This information is assembled into contigs, or fragments of the genome that cannot be joined further due to lack of sequence information across gaps between the contigs. To generate high-quality draft, usually about 8x coverage is optimal (1). Finished sequence, without gaps or ambiguous base calls, usually requires 8x to 10x coverage, along with additional analyses, often manual, to orient the contigs relative to one another and to close the gaps between them in a process called finishing. In fact, it has been stated that &quot;the defining distinction of draft sequencing is the avoidance of significant human intervention&quot; (1), although there are computational tools that may also be capable of automated finishing in some circumstances (2). While some tabulate the cost differential between high quality draft versus finished sequences to be 3-to 4-fold, and the speed differential to be over 10-fold (1), others state that the cost differential is a more modest 1.3-to 1.5-fold (3). In either case, draft sequencing is cheaper and faster. Experts have debated whether finished sequencing is always necessary, considering the higher costs (1,3,4). Thus, here we set out to determine whether draft sequence data is adequate for the computational prediction of DNA and protein diagnostic signatures. By a &quot;signature&quot; we mean a short region of sequence that is sufficient to uniquely identify an organism down to the species level, without false negatives due to strain variation or false positives due to cross reaction with close phylogenetic relatives. In addition, for DNA signatures, we require that the signature be suitable for a TaqMan reaction (e.g. composed of two primers and a probe of the desired T m &apos;s). Limited funds and facilities in which to sequence biothreat pathogens mean that decision makers must choose wisely which and how many organisms to sequence. Money and time saved as a result of draft rather than finished sequencing enables more target organisms, more isolates of the target, and more NN&apos;s of the target to be sequenced. However, if draft data does not facilitate the generation of high quality signatures for detection, the tradeoff of quantity over quality will not be worth it. We used the Sequencing Analysis Pipeline (SAP) (5,6) to compare the value of finished sequence, real draft sequence, and simulated draft sequence of different qualities for the computational prediction of DNA and protein signatures for pathogen detection/diagnostics. Marburg and variola viruses were used as model organisms for these analyses, due to the availability of multiple genomes for these organisms. We hope that variola may serve as a guide for making predictions about bacteria, in which the genomes are substantially larger, and thus the cost of sequencing is much higher than for viruses. Variola was selected as the best available surrogate for bacteria at the time we began these analyses because: 1) it is double-stranded DNA 2) it has a relatively low mutation rate, more like bacteria than like the RNA or shorter DNA viruses that have higher mutation rates and thus higher levels of variation 3) it is very long for a virus, albeit shorter than a bacterial genom

Factorial validity of the Toronto Alexithymia Scale (TAS-20) in clinical samples: A critical examination of the literature and a psychometric study in anorexia nervosa

There is extensive use of the 20-item Toronto Alexithymia Scale (TAS-20) in research and clinical practice in anorexia nervosa (AN), though it is not empirically established in this population. This study aims to examine the factorial validity of the TAS-20 in a Portuguese AN sample (N = 125), testing four different models (ranging from 1 to 4 factors) that were identified in critical examination of existing factor analytic studies. Results of confirmatory factor analysis (CFA) suggested that the three-factor solution, measuring difficulty identifying (DIF) and describing feelings (DDF), and externally oriented thinking (EOT), was the best fitting model. The quality of measurement improves if two EOT items (16 and 18) are eliminated. Internal consistency of EOT was low and decreased with age. The results provide support for the factorial validity of the TAS-20 in AN. Nevertheless, the measurement of EOT requires some caution and may be problematic in AN adolescents.Center for Psychology at the University of Porto, Portuguese Science Foundation (FCT UID/PSI/00050/2013) and EU FEDER through COMPETE 2020 program (POCI-01-0145-FEDER-007294info:eu-repo/semantics/acceptedVersio

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Sequencing Needs for Viral Diagnostics

We built a system to guide decisions regarding the amount of genomic sequencing required to develop diagnostic DNA signatures, which are short sequences that are sufficient to uniquely identify a viral species. We used our existing DNA diagnostic signature prediction pipeline, which selects regions of a target species genome that are conserved among strains of the target (for reliability, to prevent false negatives) and unique relative to other species (for specificity, to avoid false positives). We performed simulations, based on existing sequence data, to assess the number of genome sequences of a target species and of close phylogenetic relatives (near neighbors) that are required to predict diagnostic signature regions that are conserved among strains of the target species and unique relative to other bacterial and viral species. For DNA viruses such as variola (smallpox), three target genomes provide sufficient guidance for selecting species-wide signatures. Three near-neighbor genomes are critical for species specificity. In contrast, most RNA viruses require four target genomes and no near-neighbor genomes, since lack of conservation among strains is more limiting than uniqueness. Severe acute respiratory syndrome and Ebola Zaire are exceptional, as additional target genomes currently do not improve predictions, but near-neighbor sequences are urgently needed. Our results also indicate that double-stranded DNA viruses are more conserved among strains than are RNA viruses, since in most cases there was at least one conserved signature candidate for the DNA viruses and zero conserved signature candidates for the RNA viruses

The relationship between acquired knowledge in medical school and the level of knowledge on standard precautions among medical students of De La Salle Health Sciences Institute, A.Y. 2016-2017

The cross-sectional study was conducted at the College of Medicine, De La Salle Health Sciences Institute (DLSHSI). Ninety-eight (98) medical students selected by stratified random sampling were chosen as respondents. Data was collected using a self-administered questionnaire and was analysed using t-test, Analysis of Variance, and standard deviation. Findings showed that the level of knowledge on standard precautions among medical students was generally inadequate with knowledge mean score of 28.1 out of 36 points. Only 32% of the students demonstrated adequate level of knowledge. Majority of the participants reported that medical curriculum (42%) and pre-medical courses (40%) were 2 substantial sources for knowledge about standard precautions. Administration of statistical tests revealed the following: 1) there was no significant difference in the level of participants\u27 knowledge in relation to exposure to lectures and trainings about standard precautions in medical school; 2) a significant difference was observed in the level of participants\u27 knowledge in relation to their pre-medical course, between health science and non-health sciences; and 3) there was no evidence that there is an association between acquired knowledge in medical school and the level of knowledge on standard precautions among medical students of DLSHSI, A.Y. 2016-2017. Therefore, their suboptimal level of knowledge did not reflect the impact of current teaching methods provided for them. It can also be said that in general, medical students are not ready enough for exposure in dealing with patients in preventing and controlling infections in clinical practices based on the level of their knowledge on standard precautions