Background High-throughput sequencing provides a powerful window into the structural and functional profiling of microbial communities, but it is unable to characterize only the viable portion of microbial communities at scale. There is as yet not one best solution to this problem. Previous studies have established viability assessments using propidium monoazide (PMA) treatment coupled with downstream molecular profiling (e.g., qPCR or sequencing). While these studies have met with moderate success, most of them focused on the resulting “viable” communities without systematic evaluations of the technique. Here, we present our work to rigorously benchmark “PMA-seq” (PMA treatment followed by 16S rRNA gene amplicon sequencing) for viability assessment in synthetic and realistic microbial communities. Results PMA-seq was able to successfully reconstruct simple synthetic communities comprising viable/heat-killed Escherichia coli and Streptococcus sanguinis. However, in realistically complex communities (computer screens, computer mice, soil, and human saliva) with E. coli spike-in controls, PMA-seq did not accurately quantify viability (even relative to variability in amplicon sequencing), with its performance largely affected by community properties such as initial biomass, sample types, and compositional diversity. We then applied this technique to environmental swabs from the Boston subway system. Several taxa differed significantly after PMA treatment, while not all microorganisms responded consistently. To elucidate the “PMA-responsive” microbes, we compared our results with previous PMA-based studies and found that PMA responsiveness varied widely when microbes were sourced from different ecosystems but were reproducible within similar environments across studies. Conclusions This study provides a comprehensive evaluation of PMA-seq exploring its quantitative potential in synthetic and complex microbial communities, where the technique was effective for semi-quantitative purposes in simple synthetic communities but provided only qualitative assessments in realistically complex community samples.
Since the advent of soap, personal hygiene practices have revolved around removal, sterilization, and disinfection—both of visible soil and microscopic organisms—for a myriad of cultural, aesthetic, or health‐related reasons. Cleaning methods and products vary widely in their recommended use, effectiveness, risk to users or building occupants, environmental sustainability, and ecological impact. Advancements in science and technology have facilitated in‐depth analyses of the indoor microbiome, and studies in this field suggest that the traditional “scorched‐earth cleaning” mentality—that surfaces must be completely sterilized and prevent microbial establishment—may contribute to long‐term human health consequences. Moreover, the materials, products, activities, and microbial communities indoors all contribute to, or remove, chemical species to the indoor environment. This review examines the effects of cleaning with respect to the interaction of chemistry, indoor microbiology, and human health.
Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.
Anaerobic oxidation of methane (AOM) coupled to nitrite reduction (AOM-NIR) is ecologically significant for mitigating the methane-induced greenhouse effect. The microbes responsible for this reaction, NC10 bacteria, have been widely detected in diverse ecosystems. However, some defects were discovered in the commonly used NC10-specific primers, 202F and qP1F. In the present work, the primers were redesigned and improved to overcome the defects found in the previous primers. A new nested PCR method was developed using the improved primers to amplify 16S ribosomal RNA (rRNA) genes from NC10 bacteria. In the new nested PCR method, the qP1mF/1492R and 1051F/qP2R primer sets were used in the first and second rounds, respectively. The PCR products were sequenced, and more operational taxonomic units (OTUs) of the NC10 phylum were obtained using the new primers compared to the previous primers. The sensitivity of the new nested PCR was tested by the serial dilution method, and the limit of detection was approximately 10(3) copies g(-1) dry sed. for the environmental samples compared to approximately 10(5) copies g(-1) dry sed. by the previous method. Finally, the improved primer, qP1mF, was used in quantitative PCR (qPCR) to determine the abundance of NC10 bacteria, and the results agreed well with the activity of AOM-NIR measured by isotope tracer experiments. The improved primers are able to amplify NC10 16S rRNA genes more efficiently than the previous primers and useful to explore the microbial community of the NC10 phylum in different systems.
Background Characterization of microbial activity is essential to the understanding of the basic biology of microbial communities, as the function of a microbiome is defined by its biochemically active (“viable”) community members. Current sequence-based technologies can rarely differentiate microbial activity, due to their inability to distinguish live and dead sourced DNA. As a result, our understanding of microbial community structures and the potential mechanisms of transmission between humans and our surrounding environments remains incomplete. As a potential solution, 16S rRNA transcript-based amplicon sequencing (16S-RNA-seq) has been proposed as a reliable methodology to characterize the active components of a microbiome, but its efficacy has not been evaluated systematically. Here, we present our work to benchmark RNA-based amplicon sequencing for activity assessment in synthetic and environmentally sourced microbial communities. Results In synthetic mixtures of living and heat-killed Escherichia coli and Streptococcus sanguinis, 16S-RNA-seq successfully reconstructed the active compositions of the communities. However, in the realistic environmental samples, no significant compositional differences were observed in RNA (“actively transcribed — active”) vs. DNA (“whole” communities) spiked with E. coli controls, suggesting that this methodology is not appropriate for activity assessment in complex communities. The results were slightly different when validated in environmental samples of similar origins (i.e., from Boston subway systems), where samples were differentiated both by environment type as well as by library type, though compositional dissimilarities between DNA and RNA samples remained low (Bray–Curtis distance median: 0.34–0.49). To improve the interpretation of 16S-RNA-seq results, we compared our results with previous studies and found that 16S-RNA-seq suggests taxon-wise viability trends (i.e., specific taxa are universally more or less likely to be viable compared to others) in samples of similar origins. Conclusions This study provides a comprehensive evaluation of 16S-RNA-seq for viability assessment in synthetic and complex microbial communities. The results found that while 16S-RNA-seq was able to semi-quantify microbial viability in relatively simple communities, it only suggests a taxon-dependent “relative” viability in realistic communities.
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