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Next-generation DNA sequencing (NGS) has progressed enormously over the past decade, transforming genomic analysis and opening up many new opportunities for applications in clinical microbiology laboratories. The impact of NGS on microbiology has been revolutionary, with new microbial genomic sequences being generated daily, leading to the development of large databases of genomes and gene sequences. The ability to analyze microbial communities without culturing organisms has created the ever-growing field of metagenomics and microbiome analysis and has generated significant new insights into the relation between host and microbe. The medical literature contains many examples of how this new technology can be used for infectious disease diagnostics and pathogen analysis. The implementation of NGS in medical practice has been a slow process due to various challenges such as clinical trials, lack of applicable regulatory guidelines, and the adaptation of the technology to the clinical environment. In April 2015, the American Academy of Microbiology (AAM) convened a colloquium to begin to define these issues, and in this document, we present some of the concepts that were generated from these discussions.

In this IDSA policy paper, we review the current diagnostic landscape, including unmet needs and emerging technologies, and assess the challenges to the development and clinical integration of improved tests. To fulfill the promise of emerging diagnostics, IDSA presents recommendations that address a host of identified barriers. Achieving these goals will require the engagement and coordination of a number of stakeholders, including Congress, funding and regulatory bodies, public health agencies, the diagnostics industry, healthcare systems, professional societies, and individual clinicians.

Recent advancements in next-generation sequencing (NGS) have provided the foundation for modern studies into the composition of microbial communities. The use of these NGS methods allows for the detection and identification of (‘difficult-to-culture’) microorganisms using a culture-independent strategy. In the field of routine clinical diagnostics however, the application of NGS is currently limited to microbial strain typing for epidemiological purposes only, even though the implementation of NGS for microbial community analysis may yield clinically important information. This lack of NGS implementation is due to many different factors, including issues relating to NGS method standardization and result reproducibility. In this review article, the authors provide a general introduction to the most widely used NGS methods currently available (i.e., targeted amplicon sequencing and shotgun metagenomics) and the strengths and weaknesses of each method is discussed. The focus of the publication then shifts toward 16S rRNA gene NGS methods, which are currently the most cost-effective and widely used NGS methods for research purposes, and are therefore more likely to be successfully implemented into routine clinical diagnostics in the short term. In this respect, the experimental pitfalls and biases created at each step of the 16S rRNA gene NGS workflow are explained, as well as their potential solutions. Finally, a novel diagnostic microbiota profiling platform (‘MYcrobiota’) is introduced, which was developed by the authors by taking into consideration the pitfalls, biases, and solutions explained in this article. The development of the MYcrobiota, and future NGS methodologies, will help pave the way toward the successful implementation of NGS methodologies into routine clinical diagnostics.

Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

The rapid high-throughput detection of foodborne pathogens is essential in controlling food safety. In this study, a 10-channel up-converting phosphor technology-based lateral flow (TC-UPT-LF) assay was established for the rapid and simultaneous detection of 10 epidemic foodborne pathogens. Ten different single-target UPT-LF strips were developed and integrated into one TC-UPT-LF disc with optimization. Without enrichment the TC-UPT-LF assay had a detection sensitivity of 10 4  CFU mL −1 or 10 5  CFU mL −1 for each pathogen, and after sample enrichment it was 10 CFU/0.6 mg. The assay also showed good linearity, allowing quantitative detection, with a linear fitting coefficient of determination (R 2 ) of 0.916–0.998. The 10 detection channels did not cross-react, so multiple targets could be specifically detected. When 279 real food samples were tested, the assay was highly consistent (100%) with culture-based methods. The results for 110 food samples artificially contaminated with single or multiple targets showed a high detection rate (≥80%) for most target bacteria. Overall, the TC-UPT-LF assay allows the rapid, quantitative, and simultaneous detection of 10 kinds of foodborne pathogens within 20 min, and is especially suitable for the rapid detection and surveillance of foodborne pathogens in food and water.

Background There is a pressing need to understand better the extent and distribution of antimicrobial resistance on a global scale, to inform development of effective interventions. Collation of datasets for meta-analysis, mathematical modelling and temporo-spatial analysis is hampered by the considerable variability in clinical sampling, variable quality in laboratory practice and inconsistencies in antimicrobial susceptibility testing and reporting. Methods The Microbiology Investigation Criteria for Reporting Objectively (MICRO) checklist was developed by an international working group of clinical and laboratory microbiologists, infectious disease physicians, epidemiologists and mathematical modellers. Results In keeping with the STROBE checklist, but applicable to all study designs, MICRO defines items to be included in reports of studies involving human clinical microbiology data. It provides a concise and comprehensive reference for clinicians, researchers, reviewers and journals working on, critically appraising, and publishing clinical microbiology datasets. Conclusions Implementation of the MICRO checklist will enhance the quality and scientific reporting of clinical microbiology data, increasing data utility and comparability to improve surveillance, grade data quality, facilitate meta-analyses and inform policy and interventions from local to global levels.

Background Pathogen identification is essential in sepsis and septic shock. Metagenomic next-generation sequencing (mNGS) is a novel pathogen detection method with several advantages over traditional tests. However, the consistency between mNGS and traditional pathogen tests requires further investigation. Objectives We aimed to assess the consistency between mNGS and traditional pathogen tests and to identify the factors influencing this consistency. Methods This systematic review and meta-analysis involved a comprehensive search of mNGS and traditional pathogen tests in PubMed, Embase, Scopus, Web of Science, and the Cochrane Library. Data from included studies were extracted, and kappa consistency between mNGS and traditional tests was calculated. Study quality was evaluated using the QUADAS-2 tool. Results The search identified 415 studies, of which 27 were included in the analysis, involving 4112 individuals. Meta-analysis showed a pooled consistency of 0.319 ± 0.013 ( p  < 0.001), indicating a moderate relationship. In terms of sample type, cerebrospinal fluid showed the highest pooled kappa consistency at 0.500 ± 0.029 ( p  < 0.001). Immunocompromised patients had a lower pooled kappa consistency of 0.294 ± 0.014 ( p  < 0.001) compared to 0.321 ± 0.028 ( p  < 0.001) in immunocompetent patients. Positive percent agreement of mNGS was 83.63% over traditional microbiological test, and negative percent agreement was 54.59%. Conclusion This review demonstrates a moderate relationship between mNGS and traditional pathogen tests, indicating a complex relationship between these two methods. Sterile samples show higher consistency than non-sterile samples. Immune function deficiency may reduce the consistency between mNGS and traditional tests. Further research is needed on the use of mNGS in sepsis and septic shock.

Humans suffer from infections caused by single species or more complex polymicrobial communities. Identification of infectious bacteria commonly employs microbiological culture, which depends upon the in vitro propagation and isolation of viable organisms. In contrast, detection of bacterial DNA using next generation sequencing (NGS) allows culture-independent microbial profiling, potentially providing important new insights into the microbiota in clinical specimens. NGS 16S rRNA gene sequencing (NGS16S) was compared with culture using (a) synthetic polymicrobial samples for which the identity and abundance of organisms present were precisely defined and (b) primary clinical specimens. Complex mixtures of at least 20 organisms were well resolved by NGS16S with excellent reproducibility. In mixed bacterial suspensions (10 total genomes), we observed linear detection of a target organism over a 4-log concentration range (500-3 × 10 genomes). NGS16S analysis more accurately recapitulated the known composition of synthetic samples than standard microbiological culture using nonselective media, which distorted the relative abundance of organisms and frequently failed to identify low-abundance pathogens. However, extended quantitative culture using selective media for each of the component species recovered the expected organisms at the proper abundance, validating NGS16S results. In an analysis of sputa from cystic fibrosis patients, NGS16S identified more clinically relevant pathogens than standard culture. Biases in standard, nonselective microbiological culture lead to a distorted characterization of polymicrobial mixtures. NGS16S demonstrates enhanced reproducibility, quantification, and classification accuracy compared with standard culture, providing a more comprehensive, accurate, and culture-free analysis of clinical specimens.

Bacterial persisters are phenotypic variants that survive antibiotic treatment in a dormant state and can be formed by multiple pathways. We recently proposed that the second messenger (p)ppGpp drives Escherichia coli persister formation through protease Lon and activation of toxin-antitoxin (TA) modules. This model found considerable support among researchers studying persisters but also generated controversy as part of recent debates in the field. In this study, we therefore used our previous work as a model to critically examine common experimental procedures to understand and overcome the inconsistencies often observed between results of different laboratories. Our results show that seemingly simple antibiotic killing assays are very sensitive to variations in culture conditions and bacterial growth phase. Additionally, we found that some assay conditions cause the killing of antibiotic-tolerant persisters via induction of cryptic prophages. Similarly, the inadvertent infection of mutant strains with bacteriophage ϕ80, a notorious laboratory contaminant, apparently caused several of the phenotypes that we reported in our previous studies. We therefore reconstructed all infected mutants and probed the validity of our model of persister formation in a refined assay setup that uses robust culture conditions and unravels the dynamics of persister cells through all bacterial growth stages. Our results confirm the importance of (p)ppGpp and Lon but no longer support a role of TA modules in E. coli persister formation under unstressed conditions. We anticipate that the results and approaches reported in our study will lay the ground for future work in the field. IMPORTANCE The recalcitrance of antibiotic-tolerant persister cells is thought to cause relapsing infections and antibiotic treatment failure in various clinical setups. Previous studies identified multiple genetic pathways involved in persister formation but also revealed reproducibility problems that sparked controversies about adequate tools to study persister cells. In this study, we unraveled how typical antibiotic killing assays often fail to capture the biology of persisters and instead give widely differing results based on poorly controlled experimental parameters and artifacts caused by cryptic as well as contaminant prophages. We therefore established a new, robust assay that enabled us to follow the dynamics of persister cells through all growth stages of bacterial cultures without distortions by bacteriophages. This system also favored adequate comparisons of mutant strains with aberrant growth phenotypes. We anticipate that our results will contribute to a robust, common basis for future studies on the formation and eradication of antibiotic-tolerant persisters. The recalcitrance of antibiotic-tolerant persister cells is thought to cause relapsing infections and antibiotic treatment failure in various clinical setups. Previous studies identified multiple genetic pathways involved in persister formation but also revealed reproducibility problems that sparked controversies about adequate tools to study persister cells. In this study, we unraveled how typical antibiotic killing assays often fail to capture the biology of persisters and instead give widely differing results based on poorly controlled experimental parameters and artifacts caused by cryptic as well as contaminant prophages. We therefore established a new, robust assay that enabled us to follow the dynamics of persister cells through all growth stages of bacterial cultures without distortions by bacteriophages. This system also favored adequate comparisons of mutant strains with aberrant growth phenotypes. We anticipate that our results will contribute to a robust, common basis for future studies on the formation and eradication of antibiotic-tolerant persisters.

Optimal clinical decision-making depends on identification of clinically relevant organisms present in a sample. Standard microbiological culture may fail to identify unusual or fastidious organisms and can misrepresent relative abundance of sample constituents. Culture-independent methods have improved our ability to deconvolute polymicrobial patient samples. We used next-generation 16S rRNA gene sequencing (NGS16S) to determine how often cultivatable organisms in complex polymicrobial samples are not reported by standard culture. Twenty consecutive bronchoalveolar lavage (BAL) samples were plated to standard and additional media; bacteria were identified by NGS16S analysis of DNA extracted directly from samples or from washed culture plates. 96% of organisms identified were cultivable, but only 21% were reported by standard culture, indicating that standard work-up provides an incomplete assessment of microbial constituents. Direct NGS16S correlated well with standard culture, identifying the same predominant organism in 50% of samples. When predominant organisms differed, NGS16S most often detected anaerobes, whose growth is unsupported by standard culture conditions for this specimen. NGS16S i dentified more organisms per sample and allowed identification of fastidious organisms, while culture was better at capturing organisms when bacterial load was low, and allowed incidental recovery of non-bacterial pathogens. Molecular and culture-based methods together detect more organisms than either method alone.