The observation that older men suffer from hip fracture at DXA T-scores higher than older women and a proposal of a new low BMD category, osteofrailia, for predicting fracture risk in older men.

The clinical significance of osteoporosis lies in the occurrence of fragility fractures (FFx), and the most relevant fracture site is the hip. The T-score is defined as follows: (BMDpatient-BMDyoung adult mean)/SDyoung adult population, where BMD is bone mineral density and SD is the standard deviation. When the femoral neck (FN) is measured in adult Caucasian women, a cutpoint value of patient BMD of 2.5 SD below the young adult mean BMD results in a prevalence the same as the lifetime risk of hip FFx for Caucasian women. The FN T-score criterion for classifying osteoporosis in older Caucasian men has been provisionally recommended to be - 2.5, but debates remain. Based on a systematic literature review, we noted that older men suffer from hip FFx at a FN T-score approximately 0.5-0.6 higher than older women. While the mean hip FFx FN T-score of around - 2.9 for women lies below - 2.5, the mean hip FF FN T-score of around - 2.33 for men lies above - 2.5. This is likely associated with that older male populations have a higher mean T-score than older female populations. We propose a new category of low BMD status, osteofrailia, for older Caucasian men with T-score ≤ - 2 (T-score ≤ - 2.1 for older Chinese men) who are likely to suffer from hip FFx. The group with T-score ≤ - 2 for older Caucasian men is comparable in prevalence to the group with T-score ≤ - 2.5 for older Caucasian women. However, older men in such category on average have only half the FFx risk as that of older women with osteoporotic T-score.

Supporting companies dealing with asbestos risk: Practical tools for occupational health services, risk prevention specialists, and companies.

Although asbestos has been officially banned in France for over two decades, it remains a major public health and occupational health issue. In 2012, French asbestos regulations became considerably more stringent and complex. Consequently, French Public Works and Building Trades Prevention Organisation (OPPBTP) and occupational health services have been working together for several years to support construction professionals. This support involves information, training and advice. This article presents the range of tools developed by OPPBTP and occupational health services to better understand the asbestos risk as it affects construction companies. These tools and this partnership have demonstrated positive results in confronting risk and in the implementation of suitable means of prevention. They serve the best interests of employees, companies and clients, by combining safeguards to employees' health and worksite performance.

Reference Database for a Novel Binocular Visual Function Perimeter: A Randomized Clinical Trial.

Purpose: To construct a comprehensive reference database (RDB) for a novel binocular automated perimeter. Design: A four-site prospective randomized clinical trial. Subjects and Controls: Three hundred fifty-six healthy subjects without ocular conditions that might affect visual function were categorized into 7 age groups. Methods: Subjects underwent comprehensive ocular examination of both eyes before enrollment. Using the TEMPO/IMOvifa automated perimeter (Topcon Healthcare/CREWT Medical Systems), each subject completed 4 binocular threshold visual field (VF) tests during a single visit: First, practice 24-2 and 10-2 tests were obtained from both eyes. Next, study 24-2 and 10-2 tests were obtained from both eyes. Test order of each sequence was randomized, and the tests were conducted under standard automated perimetry testing conditions: Goldmann stimulus size III, 3183 cd/m2 maximum stimulus intensity, and background intensity of 10 cd/m2, using AIZE-Rapid test strategy. Standard VF reliability indices were assessed. For each subject, 24-2 and 10-2 test results from 1 randomly selected eye were analyzed. Main Outcome Measures: Perimetric threshold sensitivity and reference limits for each test analysis parameter. Results: The ages of the study cohort were widely distributed, with a mean age (standard deviation [SD]) of 52.3 (18.5) years. Sex assignment was 44.0% male and 56.0% female. The majority of subjects self-identified as White (67.4%), followed by Black or African American (13.5%) and Asian (8.7%), with 14.6% self-identified as Hispanic or Latino ethnicity. Mean sensitivity (SD) was 29.1 (1.3) decibels (dB) for the 24-2 and 32.4 (1.0) dB for the 10-2 test. For the 24-2 and 10-2, mean sensitivity (SD) age-related changes averaged -0.06 (0.01) dB and -0.05 (0.01) dB per year, respectively. The normal range of pointwise threshold sensitivity increased with eccentricity and showed asymmetry around the mean, particularly notable in the 24-2 test. Mean (SD) binocular test duration was 3.18 (0.38) minutes (1 minute 35 seconds per eye) for the 24-2 test and 3.58 (0.43) minutes (1 minute 47 seconds per eye) for the 10-2 test. Conclusions: An RDB for the TEMPO/IMOvifa perimeter was established, highlighting the significance of considering both age and stimulus eccentricity in interpreting threshold VF test results. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

RefXAS: an open access database of X-ray absorption spectra.

Under DAPHNE4NFDI, the X-ray absorption spectroscopy (XAS) reference database, RefXAS, has been set up. For this purpose, we developed a method to enable users to submit a raw dataset, with its associated metadata, via a dedicated website for inclusion in the database. Implementation of the database includes an upload of metadata to the scientific catalogue and an upload of files via object storage, with automated query capabilities through a web server and visualization of the data and files. Based on the mode of measurements, quality criteria have been formulated for the automated check of any uploaded data. In the present work, the significant metadata fields for reusability, as well as reproducibility of results (FAIR data principles), are discussed. Quality criteria for the data uploaded to the database have been formulated and assessed. Moreover, the usability and interoperability of available XAS data/file formats have been explored. The first version of the RefXAS database prototype is presented, which features a human verification procedure, currently being tested with a new user interface designed specifically for curators; a user-friendly landing page; a full list of datasets; advanced search capabilities; a streamlined upload process; and, finally, a server-side automatic authentication and (meta-) data storage via MongoDB, PostgreSQL and (data-) files via relevant APIs.

Enhancing metabarcoding efficiency and ecological insights through integrated taxonomy and DNA reference barcoding: A case study on beach meiofauna.

Molecular techniques like metabarcoding, while promising for exploring diversity of communities, are often impeded by the lack of reference DNA sequences available for taxonomic annotation. Our study explores the benefits of combining targeted DNA barcoding and morphological taxonomy to improve metabarcoding efficiency, using beach meiofauna as a case study. Beaches are globally important ecosystems and are inhabited by meiofauna, microscopic animals living in the interstitial space between the sand grains, which play a key role in coastal biodiversity and ecosystem dynamics. However, research on meiofauna faces challenges due to limited taxonomic expertise and sparse sampling. We generated 775 new cytochrome c oxidase I DNA barcodes from meiofauna specimens collected along the Netherlands' west coast and combined them with the NCBI GenBank database. We analysed alpha and beta diversity in 561 metabarcoding samples from 24 North Sea beaches, a region extensively studied for meiofauna, using both the enriched reference database and the NCBI database without the additional reference barcodes. Our results show a 2.5-fold increase in sequence annotation and a doubling of species-level Operational Taxonomic Units (OTUs) identification when annotating the metabarcoding data with the enhanced database. Additionally, our analyses revealed a bell-shaped curve of OTU richness across the intertidal zone, aligning more closely with morphological analysis patterns, and more defined community dissimilarity patterns between supralittoral and intertidal sites. Our research highlights the importance of expanding molecular reference databases and combining morphological taxonomy with molecular techniques for biodiversity assessments, ultimately improving our understanding of coastal ecosystems.

Applying MALDI-TOF MS to resolve morphologic and genetic similarities between two Dermacentor tick species of public health importance.

Hard ticks (Acari: Ixodidae) have been historically identified by morphological methods which require highly specialized expertise and more recently by DNA-based molecular assays that involve high costs. Although both approaches provide complementary data for tick identification, each method has limitations which restrict their use on large-scale settings such as regional or national tick surveillance programs. To overcome those obstacles, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been introduced as a cost-efficient method for the identification of various organisms, as it balances performance, speed, and high data output. Here we describe the use of this technology to validate the distinction of two closely related Dermacentor tick species based on the development of the first nationwide MALDI-TOF MS reference database described to date. The dataset obtained from this protein-based approach confirms that tick specimens collected from United States regions west of the Rocky Mountains and identified previously as Dermacentor variabilis are the recently described species, Dermacentor similis. Therefore, we propose that this integrative taxonomic tool can facilitate vector and vector-borne pathogen surveillance programs in the United States and elsewhere.

A Comparison of Machine Learning Approaches for predicting Hepatotoxicity potential using Chemical Structure and Targeted Transcriptomic Data.

Animal toxicity testing is time and resource intensive, making it difficult to keep pace with the number of substances requiring assessment. Machine learning (ML) models that use chemical structure information and high-throughput experimental data can be helpful in predicting potential toxicity . However, much of the toxicity data used to train ML models is biased with an unequal balance of positives and negatives primarily since substances selected for in vivo testing are expected to elicit some toxicity effect. To investigate the impact this bias had on predictive performance, various sampling approaches were used to balance in vivo toxicity data as part of a supervised ML workflow to predict hepatotoxicity outcomes from chemical structure and/or targeted transcriptomic data. From the chronic, subchronic, developmental, multigenerational reproductive, and subacute repeat-dose testing toxicity outcomes with a minimum of 50 positive and 50 negative substances, 18 different study-toxicity outcome combinations were evaluated in up to 7 ML models. These included Artificial Neural Networks, Random Forests, Bernouilli Naïve Bayes, Gradient Boosting, and Support Vector classification algorithms which were compared with a local approach, Generalised Read-Across (GenRA), a similarity-weighted k-Nearest Neighbour (k-NN) method. The mean CV F1 performance for unbalanced data across all classifiers and descriptors for chronic liver effects was 0.735 (0.0395 SD). Mean CV F1 performance dropped to 0.639 (0.073 SD) with over-sampling approaches though the poorer performance of KNN approaches in some cases contributed to the observed decrease (mean CV F1 performance excluding KNN was 0.697 (0.072 SD)). With under-sampling approaches, the mean CV F1 was 0.523 (0.083 SD). For developmental liver effects, the mean CV F1 performance was much lower with 0.089 (0.111 SD) for unbalanced approaches and 0.149 (0.084 SD) for under-sampling. Over-sampling approaches led to an increase in mean CV F1 performance (0.234, (0.107 SD)) for developmental liver toxicity. Model performance was found to be dependent on dataset, model type, balancing approach and feature selection. Accordingly tailoring ML workflows for predicting toxicity should consider class imbalance and rely on simpler classifiers first.

Environmental DNA metabarcoding reflects spatiotemporal fish community shifts in the Scheldt estuary.

Estuarine ecosystems face increasing anthropogenic pressures, necessitating effective monitoring methods to mitigate their impacts on the biodiversity they harbour. The use of environmental DNA (eDNA) based detection methods is increasingly recognized as a promising tool to complement other, potentially invasive monitoring techniques. Integrating such eDNA analyses into monitoring frameworks for large ecosystems is still challenging and requires a deeper understanding of the scale and resolution at which eDNA patterns may offer insights in species presence and community composition space and time. The Scheldt estuary, characterized by its diverse habitats and complex currents, is one of the largest Western European tidal river systems. Until now, it remains challenging to obtain accurate information on fish communities living in and migrating through this ecosystem, consequently confining our knowledge to specific locations. To explore the potential of eDNA based monitoring, we simultaneously combine stow net fishing with eDNA metabarcoding, to assess spatiotemporal shifts in the Scheldt estuary's fish communities. In total, we detected 71 fish species in the estuary using eDNA metabarcoding, partly overlapping with historic fish community data gathered at the different study locations and in contrast to only 42 species using stow net fishing during the same survey period. Community compositions found by both detection methods varied among sampling locations, driven by a clear correlation to the salinity gradient. Limited effects of sampling depth and tide were observed on the eDNA metabarcoding data, allowing a significant reduction of the eDNA sampling effort for future eDNA fish monitoring campaigns in this study system. Our results further demonstrate that seasonal shifts in fish species occurrence can be detected using eDNA metabarcoding. Combining eDNA metabarcoding and stow net fishing further enhances our understanding of this vital waterway's diverse fish populations, allowing a higher resolution and more efficient monitoring strategy.

Development of a defined approach for eye hazard identification of solid chemicals according to the three UN GHS categories.

Currently there are two OECD-adopted defined approaches (DA) for eye hazard identification of non-surfactant liquids (OECD TG 467). The current study aimed to develop a DA for eye hazard identification of solid chemicals according to the three UN GHS categories (Cat.1, Cat. 2, No Cat.): the DAS. The DAS combines two test methods described in OECD TG 437 and TG 492. The DAS was developed based on in-depth statistical analysis of a database on solids containing in vitro and historically curated in vivo Draize eye test data. The performance of the DAS was assessed by comparing the predictions with the classification based on in vivo Draize eye test data, on the one hand, and with the performance criteria established by the OECD expert group, on the other hand. In a first tier of the DAS, the SkinEthic™ HCE EIT method (TG 492) is used to distinguish No Cat. from classified substances. For classified substances, the BCOP LLBO method (TG 437) is used to identify Cat. 1, and the remaining solids are predicted Cat. 2. In summary, 77.4% Cat. 1 (N=31), 52.3% Cat. 2 (N=18), and 70.0% of No Cat. (N=60) solids were correctly identified compared to the classification based on the Draize eye test. The percentage of correct predictions met the minimum OECD performance values of 75% Cat. 1, 50% Cat. 2, and 70% No Cat., and the percentage of mispredictions was below the established maximum values. Therefore, inclusion of the DAS in OECD TG 467 has been achieved.

Defined approaches combine information from different non-animal testing methods in a specific way and interpret the results according to a fixed procedure. Such defined approaches are already available as full replacements of animal testing to assess the eye hazard of liquid chemicals (OECD Test Guideline 467). This study used two OECD-adopted in vitro methods, based on human cells and corneas from cattle, to create a defined approach that can be used for solid chemicals. The performance of the procedure was assessed against data from previous animal tests for 109 solid chemicals. The results have already led to this defined approach being adopted by the OECD TGs programme for inclusion in TG 467. With the adoption of the new defined approach, non-animal human relevant strategies are now available for eye hazard assessment of liquids and solids, reducing the need for animal testing.

Environmental DNA: The next chapter.

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

MetaZooGene Atlas and Database: Reference Sequences for Marine Ecosystems.

The MetaZooGene Atlas and Database (MZGdb; https://metazoogene.org/mzgdb/ ) is an open-access data and metadata portal synchronized with the NCBI GenBank and BOLD data repositories. The MZGdb includes sequences for genes used for the classification and identification of marine organisms based on DNA barcoding and metabarcoding. The focus of the MZGdb is biodiversity of marine ecosystems, including phytoplankton and microbes, zooplankton and invertebrates, fish, and other marine vertebrates (pinnipeds, cetaceans, and sea turtles). DNA sequences currently included are mitochondrial cytochrome oxidase I (COI), 12S, and 16S rRNA, and nuclear 18S and 28S rRNA. The MZGdb provides data and mapping tools for assembling and downloading compilations of reference sequence data that are specific to selected genes, taxonomic groups, and/or ocean regions. An additional feature of the MZGdb is the Atlas which summarizes data coverage and proportional completeness based on statistics of species with available sequences versus species commonly found in each ocean region.This chapter is a collaborative effort of the Scientific Committee for Ocean Research (SCOR) Working Group WG157: MetaZooGene: Toward a new global view of marine zooplankton biodiversity based on DNA metabarcoding and reference DNA sequence databases ( https://metazoogene.org ).

Tapping the Full Potential of Infrared Spectroscopy for the Analysis of Technical Lignins.

We present an approach to overcome the challenges associated with the increasing demand of high-throughput characterization of technical lignins, a key resource in emerging bioeconomies. Our approach offers a resort from the lack of direct, simple, and low-cost analytical techniques for lignin characterization by employing multivariate calibration models based on infrared (IR) spectroscopy to predict structural properties of lignins (i. e., functionality, molar mass). By leveraging a comprehensive database of over 500 well-characterized technical lignin samples - a factor of 10 larger than previously used sets - our chemometric models achieved high levels of quality and statistical confidence for the determination of different functional group contents (RMSEPs of 4-16 %). However, the statistical moments of the molar mass distribution are still best determined by size-exclusion chromatography. Analyses of over 500 technical lignins offered also a great opportunity to provide information on the general variability in kraft lignins and lignosulfonates (from different origins). Overall, the effected savings in analysis time (>7 h), resources, and required sample mass combined with non-destructiveness of the measurement satisfy key demands for efficient high-throughput lignin analyses. Finally, we discuss the advantages, disadvantages, and limitations of our approach, along with critical insights into the associated chemical-analytical and spectroscopic challenges.

An In-House Developed Probiotics Database E-Reference Information for Healthcare Professionals.

Currently available references provide evidence on efficacy of probiotics strains but exclude product-specific information, making it challenging for healthcare professionals (HCPs) to provide suitable probiotic recommendations to consumers. This study describes the development and evaluation of an online probiotics e-reference database to assist HCPs in delivering evidence-based recommendations on probiotics to consumers. The database currently consists of 556 clinical studies collated through PubMed literature search, 753 probiotic products from multiple retail stores in Singapore and 5708 unique product-study links. Users can search for probiotics based on indication, product or strain. Based on a pilot evaluation by 25 pharmacists practising in hospital and retail settings, 84% agreed that the database helped in assessing the efficacy of probiotic products. All (100%) found the database easy to navigate and most (96%) would continue to use the database as an evidence-based e-reference for probiotic information.

East Asians' T-scores for the diagnosis of osteoporosis should be calculated using ethnicity- and gender-specific BMD reference ranges: justifications.

The 2013 ISCD consensus recommended a Caucasian female reference database for T-score calculation in men, which says "A uniform Caucasian (non-race adjusted) female reference database should be used to calculate T-scores for men of all ethnic groups." However, this statement was recommended for the US population, and no position was taken with respect to BMD reference data or ethnicity matching outside of the USA. In East Asia, currently, a Japanese BMD reference database is universally adopted in Japan for clinical DXA diagnosis, while both local BMD and Caucasian BMD reference databases are in use in Mainland China, South Korea, Taiwan, and Singapore. In this article, we argue that an ethnicity- and gender-specific BMD database should be used for T-score calculations for East Asians, and we list the justifications why we advocate so. Use of a Caucasian BMD reference database leads to systematically lower T-scores for East Asians and an overestimation of the prevalence of osteoporosis. Using a female BMD reference database to calculate T-scores for male patients leads to higher T-score values and an underestimation of the prevalence of osteoporosis. Epidemiological evidence does not support using a female BMD reference database to calculate T-scores for men. We also note that BMD reference databases collected in Asia should be critically evaluated for their quality.

taxalogue: a toolkit to create comprehensive CO1 reference databases.

Background: Taxonomic identification through DNA barcodes gained considerable traction through the invention of next-generation sequencing and DNA metabarcoding. Metabarcoding allows for the simultaneous identification of thousands of organisms from bulk samples with high taxonomic resolution. However, reliable identifications can only be achieved with comprehensive and curated reference databases. Therefore, custom reference databases are often created to meet the needs of specific research questions. Due to taxonomic inconsistencies, formatting issues, and technical difficulties, building a custom reference database requires tremendous effort. Here, we present taxalogue, an easy-to-use software for creating comprehensive and customized reference databases that provide clean and taxonomically harmonized records. In combination with extensive geographical filtering options, taxalogue opens up new possibilities for generating and testing evolutionary hypotheses. Methods: taxalogue collects DNA sequences from several online sources and combines them into a reference database. Taxonomic incongruencies between the different data sources can be harmonized according to available taxonomies. Dereplication and various filtering options are available regarding sequence quality or metadata information. taxalogue is implemented in the open-source Ruby programming language, and the source code is available at https://github.com/nwnoll/taxalogue. We benchmark four reference databases by sequence identity against eight queries from different localities and trapping devices. Subsamples from each reference database were used to compare how well another one is covered. Results: taxalogue produces reference databases with the best coverage at high identities for most tested queries, enabling more accurate, reliable predictions with higher certainty than the other benchmarked reference databases. Additionally, the performance of taxalogue is more consistent while providing good coverage for a variety of habitats, regions, and sampling methods. taxalogue simplifies the creation of reference databases and makes the process reproducible and transparent. Multiple available output formats for commonly used downstream applications facilitate the easy adoption of taxalogue in many different software pipelines. The resulting reference databases improve the taxonomic classification accuracy through high coverage of the query sequences at high identities.

Closing the Gap in Proteomic Identification of Histoplasma capsulatum: A Case Report and Review of Literature.

Histoplasmosis is a globally distributed systemic infection caused by the dimorphic fungus Histoplasma capsulatum (H. capsulatum). This fungus can cause a wide spectrum of clinical manifestations, and the diagnosis of progressive disseminated histoplasmosis is often a challenge for clinicians. Although microscopy and culture remain the gold standard diagnostic tests for Histoplasma identification, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) has emerged as a method of microbial identification suitable for the confirmation of dimorphic fungi. However, to our knowledge, there are no entries for H. capsulatum spectra in most commercial databases. In this review, we describe the case of disseminated histoplasmosis in a patient living with HIV admitted to our university hospital that we failed to identify by the MALDI-TOF method due to the limited reference spectrum of the instrument database. Furthermore, we highlight the utility of molecular approaches, such as conventional polymerase chain reaction (PCR) and DNA sequencing, as alternative confirmatory tests to MALDI-TOF technology for identifying H. capsulatum from positive cultures. An overview of current evidence and limitations of MALDI-TOF-based characterization of H. capsulatum is also presented.

Rare phylotypes in stone, stool, and urine microbiomes are associated with urinary stone disease.

Introduction: In complex microbial communities, the importance of microbial species at very low abundance levels and their prevalence for overall community structure and function is increasingly being recognized. Clinical microbiome studies on urinary stone disease (USD) have indicated that both the gut and urinary tract microbiota are associated with the onset of the disease and that kidney stones them-selves harbor a complex, yet consistent and viable, microbiome. However, how rare phylotypes contribute to this association remains unclear. Delineating the contribution of rare and common phylotypes to urinary stone disease is important for the development of bacteriotherapies to promote urologic health. Methods: The objectives of the current report were to conduct a metaanalysis of 16S rRNA datasets derived from the kidney stone, stool, and urine samples of participants with or without urinary stone disease. To delineate the impact of rare and common phylotypes, metaanalyses were conducted by first separating rare and common taxa determined by both the frequency and abundance of amplicon sequence variants. Results: Consistent with previous analyses, we found that gut, upper urinary, and lower urinary tract microbiomes were all unique. Rare phylotypes comprised the majority of species observed in all sample types, with kidney stones exhibiting the greatest bias toward rarity, followed by urine and stool. Both rare and common fractions contributed significantly to the differences observed between sample types and health disparity. Furthermore, the rare and common fractions were taxonomically unique across all sample types. A total of 222 and 320 unique rare phylotypes from urine and stool samples were found to be significantly associated with USD. A co-occurrence correlation analysis revealed that rare phylotypes are most important for microbiome structure in stones, followed by urine and stool. Discussion: Collectively, the results indicate that rare phylotypes may be important for the pathophysiology of USD, particularly in the kidney stone matrix, which is inherently a very low microbial biomass niche that can have implications for the diagnosis and treatment of kidney stones. Further studies are needed to investigate the functional significance of rare phylotypes in kidney stone pathogenesis.

Evaluation of different 16S rRNA gene hypervariable regions and reference databases for profiling engineered microbiota structure and functional guilds in a swine wastewater treatment plant.

High-throughput 16S rRNA gene amplicon sequencing technology is widely applied for environmental microbiota structure analysis to derive knowledge that informs microbiome-based surveillance and oriented bioengineering. However, it remains elusive how the selection of 16S rRNA gene hypervariable regions and reference databases affects microbiota diversity and structure profiling. This study systematically evaluated the fitness of different frequently used reference databases (i.e. SILVA 138 SSU, GTDB bact120_r207, Greengenes 13_5 and MiDAS 4.8) and primers of 16S rRNA gene in microbiota profiling of anaerobic digestion and activated sludge collected from a full-scale swine wastewater treatment plant (WWTP). The comparative results showed that MiDAS 4.8 achieved the highest levels of taxonomic diversity and species-level assignment rate. For whichever sample groups, microbiota richness captured by different primers decreased in the following order: V4 > V4-V5 > V3-V4 > V6-V8/V1-V3. Using primer-bias-free metagenomic data results as the judging standard, V4 region also best characterized microbiota structure and well represented typical functional guilds (e.g. methanogens, ammonium oxidizers and denitrifiers), while V6-V8 regions largely overestimated the archaeal methanogens (mainly Methanosarcina) by over 30 times. Therefore, MiDAS 4.8 database and V4 region are recommended for best simultaneous analysis of bacterial and archaeal community diversity and structure of the examined swine WWTP.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach.

BACKGROUND: The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq. RESULTS: In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2. CONCLUSIONS: A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Human Metabolome Reference Database in a Biracial Cohort across the Adult Lifespan.

As one of the OMICS in systems biology, metabolomics defines the metabolome and simultaneously quantifies numerous metabolites that are final or intermediate products and effectors of upstream biological processes. Metabolomics provides accurate information that helps determine the physiological steady state and biochemical changes during the aging process. To date, reference values of metabolites across the adult lifespan, especially among ethnicity groups, are lacking. The "normal" reference values according to age, sex, and race allow the characterization of whether an individual or a group deviates metabolically from normal aging, encompass a fundamental element in any study aimed at understanding mechanisms at the interface between aging and diseases. In this study, we established a metabolomics reference database from 20-100 years of age from a biracial sample of community-dwelling healthy men and women and examined metabolite associations with age, sex, and race. Reference values from well-selected healthy individuals can contribute to clinical decision-making processes of metabolic or related diseases.