In 2024, the US Centers for Disease Control and Prevention (CDC) and National Institute of Standards and Technology (NIST) initiated an interagency collaboration to bolster preparedness in the event of a pandemic scenario due to high pathogenicity avian influenza A(H5N1) clade 2.3.4.4b viruses that had been circulating in North America since 2021. Multiple spillover events into mammalian species, including an outbreak among dairy cattle and a surge in human cases, spurred the development of RNA reference materials to assist with new diagnostics development and validation. With input from CDC on sequences, NIST generated three synthetic RNA materials of A(H5N1) hemagglutinin, neuraminidase, and matrix proteins 1 and 2 gene segments. Here, we describe the development and characterization of these reference materials utilizing droplet digital reverse transcription polymerase chain reaction. Through this collaboration, we were able to rapidly provide quantified, homogeneous, stable, and epidemiologically relevant RNA reference materials to the public to aid new assay development and validation.

The increasing use of metagenomic sequencing (MGS) for microbiome analysis has significantly advanced our understanding of microbial communities and their roles in various biological processes, including human health, environmental cycling, and disease. However, the inherent compositionality of MGS data, where the relative abundance of each taxon depends on the abundance of all other taxa, complicates the measurement of individual taxa and the interpretation of microbiome data. Here, we describe an experimental design that incorporates exogenous internal standards in routine MGS analyses to correct for compositional distortions. A mathematical framework was developed for using the observed internal standard relative abundance to calculate "Scaled Abundances" for native taxa that were (i) independent of sample composition and (ii) directly proportional to actual biological abundances. Through analysis of mock community and human gut microbiome samples, we demonstrate that Scaled Abundances outperformed traditional relative abundance measurements in both precision and accuracy and enabled reliable, quantitative comparisons of individual microbiome taxa across varied sample compositions and across a wide range of taxon abundances. By providing a pathway to accurate taxon quantification, this approach holds significant potential for advancing microbiome research, particularly in clinical and environmental health applications where precise microbial profiling is critical.IMPORTANCEMetagenomic sequencing (MGS) analysis has become central to modern characterizations of microbiome samples. However, the inherent compositionality of these analyses, where the relative abundance of each taxon depends on the abundance of all other taxa, often complicates interpretations of results. We present here an experimental design and corresponding mathematical framework that uses internal standards with routine MGS methods to correct for compositional distortions. We validate this approach for both amplicon and shotgun MGS analysis of mock communities and human gut microbiome (fecal) samples. By using internal standards to remove compositionality, we demonstrate significantly improved measurement accuracy and precision for quantification of taxon abundances. This approach is broadly applicable across a wide range of microbiome research applications.

When profiling the human gut microbiome, technical biases introduced by analytical approaches impede translational research, reducing data reliability and study comparability. Here, through a global study involving 23 labs, we analyzed a wide range of sequencing and bioinformatic approaches for the taxonomic profiling of two well-defined DNA reference reagents (RRs) comprised of 20 common gut bacteria. Through both shotgun and 16S rRNA gene amplicon sequencing, we aimed to isolate sources of bias and understand their impact on microbiome profiling accuracy. Importantly, minimum quality criteria (MQC) were established and are used to evaluate profiling performance. We found that the variability of shotgun sequencing data sets was greater than that of 16S rRNA gene amplicon sequencing and isolated sources of bias in wet and dry lab steps, such as sequencing depth, primer and database choices, rarefaction, and 16S copy number adjustment. This study presents well-defined RRs and MQC to combat technical bias, paving the way for reliable and comparable microbiome research.IMPORTANCEThis benchmark paper highlights the true level of variability in microbiome data across the world and across sectors, underscoring the critical need for the use of WHO International DNA Gut Reference Reagents (RRs) to elevate the quality of data in microbiome research. This global study is the first of its kind, revealing the reality of the bias in the field, comprehensively testing methodologies used by leading laboratories across the world, but also providing avenues for workflow optimization, to accelerate innovation and translational research and move the field forward.

Total and viable microbial cell counts are increasingly important for applications including live biotherapeutic products, food safety, and probiotics. In microbiology, cells are quantified using methods such as colony forming unit (CFU), flow cytometry, and polymerase chain reaction (PCR), but different methods measure different aspects of the cells (measurands), and results may not be directly comparable across methods. In the absence of a ground-truth reference material for cell count, one cannot quantify the accuracy of any cell counting method, which limits method performance assessments and comparisons. Herein, a modified analysis of cell counting methods based on the ISO 20391-2:2019 standard was developed and demonstrated for microbial cell samples diluted over a log-scale range of concentrations. Escherichia coli samples ranging in concentration from ~5 x 105 cells/mL to 2 x 107 cells/mL were quantified using CFU, Coulter principle, fluorescence flow cytometry, and impedance flow cytometry. Quality metrics modified from the ISO standard were calculated for each method and shown to be repeatable across replicate experiments. The quality metrics illustrate large differences in proportionality and variability across methods, with total cell counts in good agreement and viable cell count having more variability. As the ISO standard is meant to guide fit-for-purpose method selection, interpretation of the results and quality metrics can drive method choice and optimization. The framework introduced here will help researchers select fit-for-purpose counting methods for quantification of microbial total and viable cells across a range of applications.

We assessed the analytical performance of metagenomic workflows using NIST Reference Material (RM) 8376 DNA from bacterial pathogens spiked into two simulated clinical samples: cerebrospinal fluid (CSF) and stool. Sequencing and taxonomic classification were used to generate signals for each sample and taxa of interest and to estimate the limit of detection (LOD), the linearity of response, and linear dynamic range. We found that the LODs for taxa spiked into CSF ranged from approximately 100 to 300 copy/mL, with a linearity of 0.96 to 0.99. For stool, the LODs ranged from 10 to 221 kcopy/mL, with a linearity of 0.99 to 1.01. Furthermore, discriminating different E. coli strains proved to be workflow-dependent as only one classifier:database combination of the three tested showed the ability to differentiate the two pathogenic and commensal strains. Surprisingly, when we compared the linear response of the same taxa in the two different sample types, we found those functions to be the same, despite large differences in LODs. This suggests that the "agnostic diagnostic" theory for metagenomics (i.e., any organism can be identified because DNA is the measurand) may apply to different target organisms and different sample types. Because we are using RMs, we were able to generate quantitative analytical performance metrics for each workflow and sample set, enabling relatively rapid workflow screening before employing clinical samples. This makes these RMs a useful tool that will generate data needed to support the translation of metagenomics into regulated use.IMPORTANCEAssessing the analytical performance of metagenomic workflows, especially when developing clinical diagnostics, is foundational for ensuring that the measurements underlying a diagnosis are supported by rigorous characterization. To facilitate the translation of metagenomics into clinical practice, workflows must be tested using control samples designed to probe the analytical limitations (e.g., limit of detection). Spike-ins allow developers to generate fit-for-purpose control samples for initial workflow assessments and inform decisions about further development. However, clinical sample types include a wide range of compositions and concentrations, each presenting different detection challenges. In this work, we demonstrate how spike-ins elucidate workflow performance in two highly dissimilar sample types (stool and CSF), and we provide evidence that detection of individual organisms is unaffected by background sample composition, making detection sample-agnostic within a workflow. These demonstrations and performance insights will facilitate the translation of the technology to the clinic.

The cultivation of low-abundance and fastidious microorganisms remains a critical challenge in microbiology. To overcome this, we developed nanocultures—a microencapsulation platform that enables high-throughput cultivation of microbes under near-native conditions. These nanoliter-sized polymeric microcapsules are generated via droplet microfluidics and provide a mechanically robust yet tunable environment for microbial growth, isolation, and interrogation. By engineering the capsule shell chemistry, we control the mechanical properties to allow on-demand lysis and efficient retrieval of intracellular contents. We assessed three physical disruption methods—osmotic swelling, sonication, and bead beating—to evaluate their performance in releasing viable cells and nucleic acids from nanocultures. Osmotic swelling yielded the highest recovery of both viable microbes and high-integrity nucleic acids, outperforming the other methods. This approach preserves the biological relevance of the cultivated communities while enabling downstream processing for species identification and functional analysis. Nanocultures offer a scalable, high-throughput strategy to culture diverse microbial species in environments that mimic natural habitats. Their mechanical tunability provides precise control over microcapsule lysis and content recovery, positioning them as a powerful tool for microbial discovery, diagnostics, and synthetic ecology.

ABSTRACT The experimental methods employed during metagenomic sequencing analyses of microbiome samples significantly impact the resulting data and typically vary substantially between laboratories. In this study, a full factorial experimental design was used to compare the effects of a select set of methodological choices (sample, operator, lot, extraction kit, variable region, and reference database) on the analysis of biologically diverse stool samples. For each parameter investigated, a main effect was calculated that allowed direct comparison both between methodological choices (bias effects) and between samples (real biological differences). Overall, methodological bias was found to be similar in magnitude to real biological differences while also exhibiting significant variations between individual taxa, even between closely related genera. The quantified method biases were then used to computationally improve the comparability of data sets collected under substantially different protocols. This investigation demonstrates a framework for quantitatively assessing methodological choices that could be routinely performed by individual laboratories to better understand their metagenomic sequencing workflows and to improve the scope of the datasets they produce. IMPORTANCE Method-specific bias is a well-recognized challenge in metagenomic sequencing characterization of microbiome samples, but rigorous bias quantification is challenging. This report details a full factorial exploration of 48 experimental protocols by systematically varying microbiome sample, iterations of material production, laboratory personnel, DNA extraction kit, marker gene selection, and reference databases. Quantification of the biases associated with each parameter revealed similar magnitudes of variation arising from real biological differences and from varied analysis procedures. Furthermore, these measurement biases varied substantially with taxa, even between closely related genera. However, computational correction of method bias using a reference material was demonstrated that significantly harmonized metagenomic sequencing results collected using different analysis protocols.

This work explored the role of natural transformation – a mechanism by which bacteria uptake and express extracellular genes - in driving antibiotic resistance propagation in the human gut microbiome. The model extracellular antibiotic resistance gene (eARG) - a plasmid containing a kanamycin resistance (kanR) gene and a green fluorescence protein (GFP) gene - was dosed into pooled and homogenized human stool and incubated anaerobically. Cellular uptake of the eARG was assessed via droplet digital PCR, the expression of newly acquired genes was assessed by culturing on selective media and fluorescent microscopy, newly resistant isolates were identified by long-read Nanopore sequencing and the impacts on the taxonomy of the gut microbiome was assessed using shotgun Illumina sequencing. Significant gene uptake of both kanR and GFP was quantified in gut microbes, and extent of gene accumulation correlated with background kanamycin levels. Gut microbes dosed with background kanamycin expressed kanamycin resistance acquired by the eARG (as quantified by CFU on kanamycin-containing media). Newly resistant isolates, identified as Enterococcus faecium by long-read sequencing, also expressed green fluorescence acquired from the eARG. Though compositional changes of the kanamycin-resistant subpopulation were observed in the gut microbiome in response to eARG and antibiotic exposure, these changes were not reproducible among replicates and trends in taxonomy due to transformation could not be identified. This comprehensive analysis therefore establishes the significant propagation of antibiotic resistance within the human gut microbiome due to eARG exposure, while evaluating the utility of various measurements in characterizing transformation in a complex microbial community.

Fecal microbiota transplantation (FMT) has been demonstrated to be efficacious in preventing recurrent Clostridioides difficile (C. difficile) infections, and is being investigated for treatment of several other diseases including inflammatory bowel disease, cancer, obesity, liver disease, and diabetes. To speed up the translation of FMT into clinical practice as a safe and standardized therapeutic intervention, additional evidence-based technical and regulatory guidance is needed. To this end in May of 2022, the International Alliance for Biological Standardization (IABS) and the BIOASTER Microbiology Technology Institute hosted a second webinar to discuss key issues still impeding the advancement and standardization of FMT. The goal of this two-day webinar was to provide a forum for scientific experts to share and discuss data and key challenges with one another. Discussion included a focus on the evaluation of safety, efficacy, clinical trial design, reproducibility and accuracy in obtained microbiome measurements and data reporting, and the potential for standardization across these areas. It also focused on increasing the application potential and visibility of FMT beyond treating C. difficile infections.

Reference Material (RM) 8376 is intended for NGS-based measurements quantitative to the chromosome. A unit of RM 8376 consists of 20 components (A-T, 19 bacteria and 1 human) each containing well-characterized DNA in 10 mmol/L Tris-HCl, 1 mmol/L EDTA pH 8 buffer. Each component consists of one skirted 0.5-mL tube containing approximately 100 uL of DNA solution. Each tube is labeled and sealed with a removable screwcap. Here, we have documented the production, analytical methods, and statistical evaluation of realizing this RM.

Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R2) ≥ 0.980. Regardless of qPCR assay, variability in repeated measurements at each dilution level were very low (quantification threshold standard deviations ≤ 0.657) and exhibited a heteroscedastic trend characteristic of qPCR standard curves. The influence of a yeast carrier tRNA added to the standard control material buffer was also investigated. Findings demonstrated that NIST SRM® 2917 functions with all qPCR methods and suggests that the future use of this control material by scientists and water quality managers should help reduce variability in concentration estimates and make results more consistent between laboratories.

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Ma-terial (R) 2917 (NIST SRM (R) 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study in-vestigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 labo-ratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within-and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Standard Reference Material (SRM) 2917 is intended for calibrating qPCR-based assays of fecal indicator bacteria (FIB) for assessing water quality. A unit of SRM 2917 consists of 6?Levels of linearized plasmid DNA. The length of DNA is approximately 4.4 kb; it contains 13 single-copy PCR target regions. The 6 Levels span a log10 dilution series from approximately (5 to 500,000) plasmid copy per uL. Each Level is suspended in 1 TE buffer at pH 8 with approximately 10 ng/uL yeast tRNA. Approximately 0.2 mL of each Level were bottled in 1.5 mL skirted centrifuge vials. In total, approximately 1000 units were generated. The material is both stable and should be stored at 4? C. The production, analytical methods, statistical evaluation, and certified values of this SRM are described herein.