Performance assessment of the Bruker Biotyper MALDI-TOF MS for the identification of difficult-to-identify viridans group streptococci.

Differentiating Streptococcus pneumoniae among nonpneumococcal viridans group streptococci (VGS) is challenging in conventional laboratories. Therefore, we aimed to evaluate the performance of the latest Bruker Biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) system in identifying VGS by comparing the results to those of the specific gene sequencing approach. Clinical isolates were initially identified using the BD Phoenix system to identify Streptococcus species. The optochin test was used to distinguish nonpneumococcal VGS from S. pneumoniae. The species of individual reference strains and clinical isolates were determined by comparing the sequences of the 16S rDNA, gyrB, sodA, groESL, or coaE genes with those in the GenBank sequence databases. We evaluated the performance of the Bruker Biotyper MALDI-TOF MS in VGS identification using two different machines with three databases. We collected a total of 103 nonpneumococcal VGS and 29 S. pneumoniae blood isolates at a medical center in northern Taiwan. Among these isolates, only seven could not be identified at the species level by the specific gene sequencing approach. We found that none of the nonpneumococcal VGS isolates were misidentified as pneumococci by the latest Biotyper system, and vice versa. However, certain strains, especially those in the mitis and bovis groups, could still not be correctly identified. The latest Bruker Biotyper 4.1 (DB_10833) showed significant improvement in identifying VGS strains. However, a specific gene sequencing test is still needed to precisely differentiate the species of strains in the mitis and bovis groups.

Development of a database and standardized approach for rpoB sequence-based subtyping and identification of aerobic spore-forming Bacillales.

Aerobic spore-forming Bacillales are a highly diverse and ubiquitous group that includes organisms that cause foodborne illnesses and food spoilage. Classical microbiological and biochemical identification of members of the order Bacillales represents a challenge due to the diversity of organisms in this group as well as the fact that the phenotypic-based taxonomic assignment of some named species in this group is not consistent with their phylogenomic characteristics. DNA-sequencing-based tools, on the other hand, can be fast and cost-effective, and can provide for a more reliable identification and characterization of Bacillales isolates. In comparison to 16S rDNA, rpoB was shown to better discriminate between Bacillales isolates and to allow for improved taxonomic assignment to the species level. However, the lack of a publicly accessible rpoB database, as well as the lack of standardized protocols for rpoB-based typing and strain identification, is a major challenge. Here, we report (i) the curation of a DNA sequence database for rpoB-based subtype classification of Bacillales isolates; (ii) the development of standardized protocols for generating rpoB sequence data, and a scheme for rpoB-based initial taxonomic identification of Bacillales isolates at the species level; and (iii) the integration of the database in a publicly accessible online platform that allows for the analysis of rpoB sequence data from uncharacterized Bacillales isolates. Specifically, we curated a database of DNA sequences for a 632-nt internal variable region within the rpoB gene from representative Bacillales reference type strains and a large number of isolates that we have previously isolated and characterized through multiple projects. As of May 21, 2021, the rpoB database contained more than 8350 rpoB sequences representing 1902 distinct rpoB allelic types that can be classified into 160 different genera. The database also includes 1129 rpoB sequences for representative Bacillales reference type strains as available on May 21, 2021 in the NCBI database. The rpoB database is integrated into the online Food Microbe Tracker platform (www.foodmicrobetracker.com) and can be queried using the integrated BLAST tool to initially subtype and taxonomically identify aerobic and facultative anaerobic spore-formers. While whole-genome sequencing is increasingly used in bacterial taxonomy, the rpoB sequence-based identification scheme described here provides a valuable tool as it allows for rapid and cost-effective initial isolate characterization, which can help to identify and characterize foodborne pathogens and food spoilage bacteria. In addition, the database and primers described here can also be adopted for metagenomics approaches that include rpoB as a target, improving discriminatory power and identification over what can be achieved using 16S rDNA as a target.

The case for "investigate all": Assessing the cost-effectiveness of investigating no CODIS hit cases in a sexual assault kit initiative.

An increasing number of US jurisdictions have begun to submit their previously untested sexual assault kits (SAKs) for DNA testing. However, best practices for what should happen after testing are not well established. Should all cases be investigated regardless of the testing outcome or only those that returned a DNA hit? We examine an early-adopter jurisdiction that has completed testing and investigating all 5165 previously never tested kits. We explore and compare the criminal justice outcomes and cost-effectiveness of investigating: all cases, those with CODIS hits, and those without CODIS hits. Findings indicate the SAK initiative produced a cost savings to the community: $26.48 million ($5127 p/kit) after the inclusion of tangible and intangible costs of future sexual assaults averted through convictions, of which $9.99 million ($1934 p/kit) was from also investigating no CODIS hit cases. When considering only the costs to law enforcement, investigating all cases cost $12,000 p/additional conviction. Findings also illustrate the cost-effectiveness of investigating no CODIS hits cases and support an "investigate all" approach. This study enhances our understanding of the economic value of what comes after testing kits and investigating cases and provides a framework for jurisdictions for prioritizing resources and maximizing outcomes from testing.

NDRindex: a method for the quality assessment of single-cell RNA-Seq preprocessing data.

BACKGROUND: Single-cell RNA sequencing can be used to fairly determine cell types, which is beneficial to the medical field, especially the many recent studies on COVID-19. Generally, single-cell RNA data analysis pipelines include data normalization, size reduction, and unsupervised clustering. However, different normalization and size reduction methods will significantly affect the results of clustering and cell type enrichment analysis. Choices of preprocessing paths is crucial in scRNA-Seq data mining, because a proper preprocessing path can extract more important information from complex raw data and lead to more accurate clustering results. RESULTS: We proposed a method called NDRindex (Normalization and Dimensionality Reduction index) to evaluate data quality of outcomes of normalization and dimensionality reduction methods. The method includes a function to calculate the degree of data aggregation, which is the key to measuring data quality before clustering. For the five single-cell RNA sequence datasets we tested, the results proved the efficacy and accuracy of our index. CONCLUSIONS: This method we introduce focuses on filling the blanks in the selection of preprocessing paths, and the result proves its effectiveness and accuracy. Our research provides useful indicators for the evaluation of RNA-Seq data.

Assessment of transcriptional importance of cell line-specific features based on GTRD and FANTOM5 data.

Creating a complete picture of the regulation of transcription seems to be an urgent task of modern biology. Regulation of transcription is a complex process carried out by transcription factors (TFs) and auxiliary proteins. Over the past decade, ChIP-Seq has become the most common experimental technology studying genome-wide interactions between TFs and DNA. We assessed the transcriptional significance of cell line-specific features using regression analysis of ChIP-Seq datasets from the GTRD database and transcriptional start site (TSS) activities from the FANTOM5 expression atlas. For this purpose, we initially generated a large number of features that were defined as the presence or absence of TFs in different promoter regions around TSSs. Using feature selection and regression analysis, we identified sets of the most important TFs that affect expression activity of TSSs in human cell lines such as HepG2, K562 and HEK293. We demonstrated that some TFs can be classified as repressors and activators depending on their location relative to TSS.

Deep learning predicts short non-coding RNA functions from only raw sequence data.

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information. Here we show that RNA function can be predicted with good accuracy from a lightweight representation of sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations. Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep.

The archives are half-empty: an assessment of the availability of microbial community sequencing data.

As DNA sequencing has become more popular, the public genetic repositories where sequences are archived have experienced explosive growth. These repositories now hold invaluable collections of sequences, e.g., for microbial ecology, but whether these data are reusable has not been evaluated. We assessed the availability and state of 16S rRNA gene amplicon sequences archived in public genetic repositories (SRA, EBI, and DDJ). We screened 26,927 publications in 17 microbiology journals, identifying 2015 16S rRNA gene sequencing studies. Of these, 7.2% had not made their data public at the time of analysis. Among a subset of 635 studies sequencing the same gene region, 40.3% contained data which was not available or not reusable, and an additional 25.5% contained faults in data formatting or data labeling, creating obstacles for data reuse. Our study reveals gaps in data availability, identifies major contributors to data loss, and offers suggestions for improving data archiving practices.

A cost-effectiveness analysis of the number of samples to collect and test from a sexual assault.

Although the backlog of untested sexual assault kits in the United States is starting to be addressed, many municipalities are opting for selective testing of samples within a kit, where only the most probative samples are tested. We use data from the San Francisco Police Department Criminalistics Laboratory, which tests all samples but also collects information on the samples flagged by sexual assault forensic examiners as most probative, to build a standard machine learning model that predicts (based on covariates gleaned from sexual assault kit questionnaires) which samples are most probative. This model is embedded within an optimization framework that selects which samples to test from each kit to maximize the Combined DNA Index System (CODIS) yield (i.e., the number of kits that generate at least one DNA profile for the criminal DNA database) subject to a budget constraint. Our analysis predicts that, relative to a policy that tests only the samples deemed probative by the sexual assault forensic examiners, the proposed policy increases the CODIS yield by 45.4% without increasing the cost. Full testing of all samples has a slightly lower cost-effectiveness than the selective policy based on forensic examiners, but more than doubles the yield. In over half of the sexual assaults, a sample was not collected during the forensic medical exam from the body location deemed most probative by the machine learning model. Our results suggest that electronic forensic records coupled with machine learning and optimization models could enhance the effectiveness of criminal investigations of sexual assaults.

Evolving public views on the value of one's DNA and expectations for genomic database governance: Results from a national survey.

We report results from a large survey of public attitudes regarding genomic database governance. Prior surveys focused on the context of academic-sponsored biobanks, framing data provision as altruistic donation; our survey is designed to reflect four growing trends: genomic databases are found across many sectors; they are used for more than academic biomedical research; their value is reflected in corporate transactions; and additional related privacy risks are coming to light. To examine how attitudes may evolve in response to these trends, we provided survey respondents with information from mainstream media coverage of them. We then found only 11.7% of respondents willing to altruistically donate their data, versus 50.6% willing to provide data if financially compensated, and 37.8% unwilling to provide data regardless of compensation. Because providing one's genomic data is sometimes bundled with receipt of a personalized genomic report, we also asked respondents what price they would be willing to pay for a personalized report. Subtracting that response value from one's expected compensation for providing data (if any) yields a net expected payment. For the altruistic donors, median net expected payment was -$75 (i.e. they expected to pay $75 for the bundle). For respondents wanting compensation for their data, however, median net expected payment was +$95 (i.e. they expected to receive $95). When asked about different genomic database governance policies, most respondents preferred options that allowed them more control over their data. In particular, they favored policies restricting data sharing or reuse unless permission is specifically granted by the individual. Policy preferences were also relatively consistent regardless of the sector in which the genomic database was located. Together these findings offer a forward-looking window on individual preferences that can be useful for institutions of all types as they develop governance approaches in this area of large-scale data sharing.

Regulatory perspectives on next-generation sequencing and complementary diagnostics in Japan.

INTRODUCTION: The 'one biomarker/one drug' scenario is unsustainable because cancer is a complex disorder that involves a number of molecular defects. In the past decade, major technological advances have lowered the overall cost and increased the efficiency of next-generation sequencing (NGS). AREAS COVERED: We review recent regulations on NGS and complementary diagnostics in Japan, mainly focusing on high-quality studies that utilized these new diagnostic modalities and were published within the last 5 years. We highlight significant changes in regulation, and explain the direction of efforts to translate the results of NGS and complementary diagnostics into clinical practice. EXPERT OPINION: NGS holds a number of advantages over conventional companion and complementary diagnostics that enable simultaneous analyzes of multiple cancer genes to detect actionable mutations. Parallel technological developments and regulatory changes have led to the rapid adoption of NGS into clinical practice. NGS-based genomic data have been leveraged to better understand the characteristics of a disease that affects its patient's response to a given therapy. As NGS-based tests become more widespread, however, Japanese authorities will face significant challenges particularly with respect to the complexity of genomic data, which will have to be managed if NGS is to benefit patients.

Results of the 2018 Rapid DNA Maturity Assessment.

Three commercially available integrated rapid DNA instruments were tested as a part of a rapid DNA maturity assessment in July of 2018. The assessment was conducted with sets of blinded single-source reference samples provided to participants for testing on the individual rapid platforms within their laboratories. The data were returned to the National Institute of Standards and Technology (NIST) for review and analysis. Both FBI-defined automated review (Rapid DNA Analysis) and manual review (Modified Rapid DNA Analysis) of the datasets were conducted to assess the success of genotyping the 20 Combined DNA Index System (CODIS) core STR loci and full profiles generated by the instruments. Genotype results from the multiple platforms, participating laboratories, and STR typing chemistries were combined into a single analysis. The Rapid DNA Analysis resulted in a success rate of 80% for full profiles (85% for the 20 CODIS core loci) with automated analysis. Modified Rapid DNA Analysis resulted in a success rate of 90% for both the CODIS 20 core loci and full profiles (all attempted loci per chemistry). An analysis of the peak height ratios demonstrated that 95% of all heterozygous alleles were above 59% heterozygote balance. For base-pair sizing precision, the precision was below the standard 0.5 bp deviation for both the ANDE 6C System and the RapidHIT 200.

Assessment of genetic polymorphism at 20 autosomal STR loci in scheduled caste population of Himachal Pradesh.

In this study, we evaluated the genetic diversity indices and forensic parameters of scheduled caste population of Himachal Pradesh, India, at 20 autosomal STR loci. Altogether, 233 alleles were observed with an average of 11.65 ± 0.88 alleles per locus. In exception of locus D13S317, no loci deviated from Hardy Weinberg equilibrium. Locus Penta E was found to be the most polymorphic and discriminative loci. The combined power of discrimination and the combined power of exclusion were 1 and 0.999. Further, we established the phylogenetic relationship between the scheduled caste population of Himachal Pradesh and 14 other populations of India. We found 20 autosomal STR loci used in the present study were polymorphic and can be used in population genetic studies and forensic related case works.

FQStat: a parallel architecture for very high-speed assessment of sequencing quality metrics.

BACKGROUND: High throughput DNA/RNA sequencing has revolutionized biological and clinical research. Sequencing is widely used, and generates very large amounts of data, mainly due to reduced cost and advanced technologies. Quickly assessing the quality of giga-to-tera base levels of sequencing data has become a routine but important task. Identification and elimination of low-quality sequence data is crucial for reliability of downstream analysis results. There is a need for a high-speed tool that uses optimized parallel programming for batch processing and simply gauges the quality of sequencing data from multiple datasets independent of any other processing steps. RESULTS: FQStat is a stand-alone, platform-independent software tool that assesses the quality of FASTQ files using parallel programming. Based on the machine architecture and input data, FQStat automatically determines the number of cores and the amount of memory to be allocated per file for optimum performance. Our results indicate that in a core-limited case, core assignment overhead exceeds the benefit of additional cores. In a core-unlimited case, there is a saturation point reached in performance by increasingly assigning additional cores per file. We also show that memory allocation per file has a lower priority in performance when compared to the allocation of cores. FQStat's output is summarized in HTML web page, tab-delimited text file, and high-resolution image formats. FQStat calculates and plots read count, read length, quality score, and high-quality base statistics. FQStat identifies and marks low-quality sequencing data to suggest removal from downstream analysis. We applied FQStat on real sequencing data to optimize performance and to demonstrate its capabilities. We also compared FQStat's performance to similar quality control (QC) tools that utilize parallel programming and attained improvements in run time. CONCLUSIONS: FQStat is a user-friendly tool with a graphical interface that employs a parallel programming architecture and automatically optimizes its performance to generate quality control statistics for sequencing data. Unlike existing tools, these statistics are calculated for multiple datasets and separately at the "lane," "sample," and "experiment" level to identify subsets of the samples with low quality, thereby preventing the loss of complete samples when reliable data can still be obtained.

Assessment of the functional impact on the pre-mRNA splicing process of 28 nucleotide variants associated with Pompe disease in GAA exon 2 and their recovery using antisense technology.

Glycogen storage disease II (GSDII), also called Pompe disease, is an autosomal recessive inherited disease caused by a defect in glycogen metabolism due to the deficiency of the enzyme acid alpha-glucosidase (GAA) responsible for its degradation. So far, more than 500 sequence variants of the GAA gene have been reported but their possible involvement on the pre-messenger RNA splicing mechanism has not been extensively studied. In this work, we have investigated, by an in vitro functional assay, all putative splicing variants within GAA exon 2 and flanking introns. Our results show that many variants falling in the canonical splice site or the exon can induce GAA exon 2 skipping. In these cases, therefore, therapeutic strategies aimed at restoring protein folding of partially active mutated GAA proteins might not be sufficient. Regarding this issue, we have tested the effect of antisense oligonucleotides (AMOs) that were previously shown capable of rescuing splicing misregulation caused by the common c.-32-13T>G variant associated with the childhood/adult phenotype of GSDII. Interestingly, our results show that these AMOs are also quite effective in rescuing the splicing impairment of several exonic splicing variants, thus widening the potential use of these effectors for GSDII treatment.

Molecular characterization of liver fluke intermediate host lymnaeids (Gastropoda: Pulmonata) snails from selected regions of Okavango Delta of Botswana, KwaZulu-Natal and Mpumalanga provinces of South Africa.

Lymnaeidae snail species are known to be intermediate hosts of human and livestock helminths parasites, especially Fasciola species. Identification of these species and their geographical distribution is important to better understand the epidemiology of the disease. Significant diversity has been observed in the shell morphology of snails from the Lymnaeidae family and the systematics within this family is still unclear, especially when the anatomical traits among various species have been found to be homogeneous. Although there are records of lymnaeid species of southern Africa based on shell morphology and controversial anatomical traits, there is paucity of information on the molecular identification and phylogenetic relationships of the different taxa. Therefore, this study aimed at identifying populations of Lymnaeidae snails from selected sites of the Okavango Delta (OKD) in Botswana, and sites located in the KwaZulu-Natal (KZN) and Mpumalanga (MP) provinces of South Africa using molecular techniques. Lymnaeidae snails were collected from 8 locations from the Okavango delta in Botswana, 9 from KZN and one from MP provinces and were identified based on phylogenetic analysis of the internal transcribed spacer (ITS-2). Analyses based on the ITS-2 marker identified the presence of a well-supported Radix clade containing Radix auricularia, R. natalensis and R. rubiginosa, which were not well resolved. Experimental samples from the OKD and KZN present in this clade were referable to these species. An unidentified experimental taxon from the OKD formed a well-supported sister clade to the Radix clade, although it was not possible to identify it. Galba truncatula was well supported in a sister relationship to a well-supported Pseudosuccinea columella clade which included samples from MP and KZN provinces of South Africa. We observed that P. columella shared the same habitats with R. natalensis and R. auricularia in KZN. Our study contributes new knowledge on the Lymnaeidae species present in Southern Africa and their phylogenetic relationships. The study further identifies the species which are likely to co-exist in the same environment and this information will be of use to those designing control programs for fasciolosis. This is the first study reporting the presence of R. auricularia in the OKD of Botswana and KZN province of South Africa.

Assessment of Genetic Diversity of HTLV-1 ORF-I Sequences Collected from Patients with Different Clinical Profiles.

The human T cell lymphotropic virus type 1 (HTLV-1) infects 5 to 10 million individuals and remains without specific treatment. This retrovirus genome is composed of the genes gag, pol, env, and a region known as pX. This region contains four open reading frames (ORFs) that encode specific proteins. The ORF-I produces the protein p12 and its cleavage product, p8. In this study, we analyzed the genetic diversity of 32 ORF-I sequences from patients with different clinical profiles. Seven amino acid changes with frequency over 5% were identified: G29S, P34L, L55F, F61L, S63P, F78L, and S91P. The identification of regions where the posttranslational sites were identified showed a high identity among the sequences and the amino acid changes exclusive of specific clinical profile were found in less than 5% of the samples. We compare the findings with 2.406 sequences available in GenBank. The low overall genetic diversity found suggested that this region could be used in the HTLV-1 vaccine development.

Assessment of BOLD and GenBank - Their accuracy and reliability for the identification of biological materials.

Taxonomic identification of biological materials can be achieved through DNA barcoding, where an unknown "barcode" sequence is compared to a reference database. In many disciplines, obtaining accurate taxonomic identifications can be imperative (e.g., evolutionary biology, food regulatory compliance, forensics). The Barcode of Life DataSystems (BOLD) and GenBank are the main public repositories of DNA barcode sequences. In this study, an assessment of the accuracy and reliability of sequences in these databases was performed. To achieve this, 1) curated reference materials for plants, macro-fungi and insects were obtained from national collections, 2) relevant barcode sequences (rbcL, matK, trnH-psbA, ITS and COI) from these reference samples were generated and used for searching against both databases, and 3) optimal search parameters were determined that ensure the best match to the known species in either database. While GenBank outperformed BOLD for species-level identification of insect taxa (53% and 35%, respectively), both databases performed comparably for plants and macro-fungi (~81% and ~57%, respectively). Results illustrated that using a multi-locus barcode approach increased identification success. This study outlines the utility of the BLAST search tool in GenBank and the BOLD identification engine for taxonomic identifications and identifies some precautions needed when using public sequence repositories in applied scientific disciplines.

Automated assessment of biological database assertions using the scientific literature.

BACKGROUND: The large biological databases such as GenBank contain vast numbers of records, the content of which is substantively based on external resources, including published literature. Manual curation is used to establish whether the literature and the records are indeed consistent. We explore in this paper an automated method for assessing the consistency of biological assertions, to assist biocurators, which we call BARC, Biocuration tool for Assessment of Relation Consistency. In this method a biological assertion is represented as a relation between two objects (for example, a gene and a disease); we then use our novel set-based relevance algorithm SaBRA to retrieve pertinent literature, and apply a classifier to estimate the likelihood that this relation (assertion) is correct. RESULTS: Our experiments on assessing gene-disease relations and protein-protein interactions using the PubMed Central collection show that BARC can be effective at assisting curators to perform data cleansing. Specifically, the results obtained showed that BARC substantially outperforms the best baselines, with an improvement of F-measure of 3.5% and 13%, respectively, on gene-disease relations and protein-protein interactions. We have additionally carried out a feature analysis that showed that all feature types are informative, as are all fields of the documents. CONCLUSIONS: BARC provides a clear benefit for the biocuration community, as there are no prior automated tools for identifying inconsistent assertions in large-scale biological databases.