Improved yield and accuracy for DNA extraction in microbiome studies with variation in microbial biomass

Comprehensive identification of pathogenic microbes and antimicrobial resistance genes in food products using nanopore sequencing-based metagenomics

Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Given the limitations of conventional culture-based approaches, which are limited in scope and time-consuming, metagenomic sequencing of food products emerges as a promising solution. This method provides a fast and comprehensive way to detect the presence of pathogenic microbes and antimicrobial resistance genes (ARGs). Notably, nanopore long-read sequencing provides more accurate bacterial taxonomic classification in comparison to short-read sequencing. Here, we revealed the impact of food types and attributes (origin, retail place, and food processing methods) on microbial communities and the AMR profile using nanopore metagenomic sequencing. We analyzed a total of 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. Clostridium botulinum, Acinetobacter baumannii, and Vibrio parahaemolyticus were identified as the top three foodborne pathogens in raw meat and sashimi. Importantly, even with low pathogen abundance, higher percentages of samples containing carbapenem and cephalosporin resistance genes were identified in chicken and RTE vegetables, respectively. In parallel, our results demonstrated that fresh, peeled, and minced foods exhibited higher levels of pathogenic bacteria. In conclusion, this comprehensive study offers invaluable data that can contribute to food safety assessments and serve as a basis for quality indicators.

Impact of cell lysis treatment before saliva metagenomic DNA extraction on the oral microbiome and the associated resistome

OBJECTIVES

The human oral microbiome, a complex ecosystem linked to oral and systemic health, harbors a diverse array of microbial populations, including antimicrobial resistance genes (ARGs). As a critical component of the One Health approach to tackle antibiotic resistance, comprehending the oral resistome's composition and diversity is imperative. The objective of this study was to investigate the impact of chemical cell lysis treatment using MetaPolyzyme on the detectability of the oral microbiome, resistome, and DNA quality and quantity.

MATERIALS AND METHODS

Saliva samples were collected from five healthy individuals, and each of the samples was subjected to DNA extraction with and without the treatment with MetaPolyzyme. Through metagenomic sequencing, we analyzed, assessed, and compared the microbial composition, resistome, and DNA characteristics between both groups of extracted DNA.

RESULTS

Our study revealed that MetaPolyzyme treatment led to significant shifts in the detectability of microbial composition, favoring Gram-positive bacteria, notably Streptococcus, over Gram-negative counterparts. Moreover, the MetaPolyzyme treatment also resulted in a distinct change in ARG distribution. This shift was characterized by an elevated proportion of ARGs linked to fluoroquinolones and efflux pumps, coupled with a reduction in the prevalence of tetracycline and β-lactam resistance genes when compared with the nontreated group. Alpha diversity analysis demonstrated altered species and ARG distribution without affecting overall diversity, while beta diversity analysis confirmed significant differences in the taxonomical composition and oral resistome between treated and nontreated groups.

CONCLUSIONS

These findings underscore the critical role of cell lysis treatment in optimizing oral metagenomic studies and enhance our understanding of the oral resistome's dynamics in the context of antimicrobial resistance.

Development of a multiplex droplet digital PCR assay for simultaneous detection and quantification of Escherichia coli, E. marmotae, and E. ruysiae in water samples

Escherichia coli are widely used by water quality managers as Fecal Indicator Bacteria, but current quantification methods do not differentiate them from benign, environmental Escherichia species such as E. marmotae (formerly named cryptic clade V) or E. ruysiae (cryptic clades III and IV). Reliable and specific techniques for their identification are required to avoid confounding microbial water quality assessments. To address this, a multiplex droplet digital PCR (ddPCR) assay targeting lipB (E. coli and E. ruysiae) and bglC (E. marmotae) was designed. The ddPCR performance was assessed using in silico analysis; genomic DNA from 40 local, international, and reference strains of target and non-target coliforms; and spiked water samples in a range relevant to water quality managers (1 to 1000 cells/100 mL). Results were compared to an analogous quantitative PCR (qPCR) and the Colilert method. Both PCR assays showed excellent sensitivity with a limit of detection of 0.05 pg/μL and 0.005 pg/μl for ddPCR and qPCR respectively, and of quantification of 0.5 pg/μL of genomic DNA. The ddPCR allowed differentiation and quantification of three Escherichia species per run by amplitude multiplexing and showed a high concordance with concentrations measured by Colilert once proportional bias was accounted for. In silico specificity testing underlined the possibility to further detect and distinguish Escherichia cryptic clade VI. Finally, the applicability of the ddPCR was successfully tested on environmental water samples where E. marmotae and E. ruysiae potentially confound E. coli counts based on the Most Probable Number method, highlighting the utility of this novel ddPCR as an efficient and rapid discriminatory test to improve water quality assessments.

Alternative amplicon-PCR protocol for maximizing bacterial and fungal sequencing in low-biomass samples

Determining bacterial and fungal communities from low-biomass samples remains a challenge for high-throughput sequencing. Due to the low microbial load and host contamination, some sites, including the female upper reproductive tract and the lower respiratory tract, were even considered sterile until recent years. Despite efforts to improve sampling and DNA isolation protocols, some samples provide insufficient microbial DNA input for library preparation and sequencing. Herein, we propose an alternative amplicon-PCR protocol to be used in bacterial and fungal sequencing in low-biomass samples, targeting 16S-rDNA and the internal transcribed spacer region (ITS), respectively. Similar to a nested-PCR, we performed two sequential PCR reactions to maximise the target amplicon. We compared metagenomic results from the original Illumina protocol (Protocol 1 - P1) and the alternative one (Protocol 2 - P2), using a mock community and clinical samples with different microbial loads. Our findings showed no significant differences in data generated by P1 and P2, indicating that the second amplification round does not bias the microbiota diversity rates. Thus, the alternative protocol can be applied for low-biomass samples when the original protocol results in spurious output, preventing library preparation and sequencing.

Pragmatic Considerations When Extracting DNA for Metagenomics Analyses of Clinical Samples

Microbiome analyses are essential for understanding microorganism composition and diversity, but interpretation is often challenging due to biological and technical variables. DNA extraction is a critical step that can significantly bias results, particularly in samples containing a high abundance of challenging-to-lyse microorganisms. Taking into consideration the distinctive microenvironments observed in different bodily locations, our study sought to assess the extent of bias introduced by suboptimal bead-beating during DNA extraction across diverse clinical sample types. The question was whether complex targeted extraction methods are always necessary for reliable taxonomic abundance estimation through amplicon sequencing or if simpler alternatives are effective for some sample types. Hence, for four different clinical sample types (stool, cervical swab, skin swab, and hospital surface swab samples), we compared the results achieved from extracting targeted manual protocols routinely used in our research lab for each sample type with automated protocols specifically not designed for that purpose. Unsurprisingly, we found that for the stool samples, manual extraction protocols with vigorous bead-beating were necessary in order to avoid erroneous taxa proportions on all investigated taxonomic levels and, in particular, false under- or overrepresentation of important genera such as Blautia, Faecalibacterium, and Parabacteroides. However, interestingly, we found that the skin and cervical swab samples had similar results with all tested protocols. Our results suggest that the level of practical automation largely depends on the expected microenvironment, with skin and cervical swabs being much easier to process than stool samples. Prudent consideration is necessary when extending the conclusions of this study to applications beyond rough estimations of taxonomic abundance.

An improved workflow for accurate and robust healthcare environmental surveillance using metagenomics

BACKGROUND

Effective surveillance of microbial communities in the healthcare environment is increasingly important in infection prevention. Metagenomics-based techniques are promising due to their untargeted nature but are currently challenged by several limitations: (1) they are not powerful enough to extract valid signals out of the background noise for low-biomass samples, (2) they do not distinguish between viable and nonviable organisms, and (3) they do not reveal the microbial load quantitatively. An additional practical challenge towards a robust pipeline is the inability to efficiently allocate sequencing resources a priori. Assessment of sequencing depth is generally practiced post hoc, if at all, for most microbiome studies, regardless of the sample type. This practice is inefficient at best, and at worst, poor sequencing depth jeopardizes the interpretation of study results. To address these challenges, we present a workflow for metagenomics-based environmental surveillance that is appropriate for low-biomass samples, distinguishes viability, is quantitative, and estimates sequencing resources.

RESULTS

The workflow was developed using a representative microbiome sample, which was created by aggregating 120 surface swabs collected from a medical intensive care unit. Upon evaluating and optimizing techniques as well as developing new modules, we recommend best practices and introduce a well-structured workflow. We recommend adopting liquid-liquid extraction to improve DNA yield and only incorporating whole-cell filtration when the nonbacterial proportion is large. We suggest including propidium monoazide treatment coupled with internal standards and absolute abundance profiling for viability assessment and involving cultivation when demanding comprehensive profiling. We further recommend integrating internal standards for quantification and additionally qPCR when we expect poor taxonomic classification. We also introduce a machine learning-based model to predict required sequencing effort from accessible sample features. The model helps make full use of sequencing resources and achieve desired outcomes. Video Abstract CONCLUSIONS: This workflow will contribute to more accurate and robust environmental surveillance and infection prevention. Lessons gained from this study will also benefit the continuing development of methods in relevant fields.

DNA extraction leads to bias in bacterial quantification by qPCR

Quantitative PCR (qPCR) has become a widely used technique for bacterial quantification. The affordability, ease of experimental design, reproducibility, and robustness of qPCR experiments contribute to its success. The establishment of guidelines for minimum information for publication of qPCR experiments, now more than 10 years ago, aimed to mitigate the publication of contradictory data. Unfortunately, there are still a significant number of recent research articles that do not consider the main pitfalls of qPCR for quantification of biological samples, which undoubtedly leads to biased experimental conclusions. qPCR experiments have two main issues that need to be properly tackled: those related to the extraction and purification of genomic DNA and those related to the thermal amplification process. This mini-review provides an updated literature survey that critically analyzes the following key aspects of bacterial quantification by qPCR: (i) the normalization of qPCR results by using exogenous controls, (ii) the construction of adequate calibration curves, and (iii) the determination of qPCR reaction efficiency. It is primarily focused on original papers published last year, where qPCR was applied to quantify bacterial species in different types of biological samples, including multi-species biofilms, human fluids, and water and soil samples. KEY POINTS: • qPCR is a widely used technique used for absolute bacterial quantification. • Recently published papers lack proper qPCR methodologies. • Not including proper qPCR controls significantly affect experimental conclusions.

Modulation of the porcine intestinal microbiota in the course of Ascaris suum infection

Background

The porcine roundworm Ascaris suum impairs feed conversion and weight gain, but its effects on intestinal microbiota remain largely unexplored.

Methods

Modulation of the intestinal microbiota was assessed in pigs that were infected once with 10,000 A. suum eggs and pigs that received a trickle infection (1000 eggs/day over 10 days), compared with a non-infected control group. Six pigs each were sacrificed per group at days 21, 35 and 49 post-infection (p.i.). Faecal samples taken weekly until slaughter and ingesta samples from different intestinal compartments were subjected to next-generation sequencing of the bacterial 16S rRNA gene.

Results

The results revealed marked differences between the single- and the trickle-infected group. Single infection caused a remarkable but transient decrease in microbial diversity in the caecum, which was not observed in the trickle-infected group. However, an increase in short-chain fatty acid-producing genera in the caecum on day 21 p.i., which shifted to a decrease on day 35 p.i., was common to both groups, possibly related to changes in excretory–secretory products following the parasite’s final moult. Faecal microbial interaction networks were more similar between the single-infected and control group than the trickle-infected group. In addition, a lower degree of similarity over time indicated that A. suum trickle infection prevented microbiota stabilization.

Conclusions

These different patterns may have important implications regarding the comparability of experimental infections with natural scenarios characterized by continuous exposure, and should be confirmed by further studies.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05535-w.

Inferring Species Compositions of Complex Fungal Communities from Long- and Short-Read Sequence Data

Our study is unique in that it provides an in-depth comparative study of a real-life complex fungal community analyzed with multiple long- and short-read sequencing approaches. These technologies and their application are currently of great interest to diverse biologists as they seek to characterize the community compositions of microbiomes.

ddPCR allows 16S rRNA gene amplicon sequencing of very small DNA amounts from low-biomass samples

BACKGROUND

One limiting factor of short amplicon 16S rRNA gene sequencing approaches is the use of low DNA amounts in the amplicon generation step. Especially for low-biomass samples, insufficient or even commonly undetectable DNA amounts can limit or prohibit further analysis in standard protocols.

RESULTS

Using a newly established protocol, very low DNA input amounts were found sufficient for reliable detection of bacteria using 16S rRNA gene sequencing compared to standard protocols. The improved protocol includes an optimized amplification strategy by using a digital droplet PCR. We demonstrate how PCR products are generated even when using very low concentrated DNA, unable to be detected by using a Qubit. Importantly, the use of different 16S rRNA gene primers had a greater effect on the resulting taxonomical profiles compared to using high or very low initial DNA amounts.

CONCLUSION

Our improved protocol takes advantage of ddPCR and allows faithful amplification of very low amounts of template. With this, samples of low bacterial biomass become comparable to those with high amounts of bacteria, since the first and most biasing steps are the same. Besides, it is imperative to state DNA concentrations and volumes used and to include negative controls indicating possible shifts in taxonomical profiles. Despite this, results produced by using different primer pairs cannot be easily compared.

A Simple, Cost-Effective, and Automation-Friendly Direct PCR Approach for Bacterial Community Analysis

Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S rRNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary for analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased based on the types of species present. Direct PCR method is a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, including both Gram-positive and Gram-negative species, ZymoBIOMICS microbial community standards, and groundwater. By comparing direct PCR methods with DNeasy Blood and Tissue Kits for microbial isolates and DNeasy PowerSoil Kits for microbial communities, we found that a specific variant of the direct PCR method exhibits an overall efficiency comparable to that of the conventional DNeasy PowerSoil protocol in the circumstances we tested. We also found that the method showed higher efficiency for extracting gDNA from the Gram-negative strains compared to DNeasy Blood and Tissue protocol. This direct PCR method is 1,600 times less expensive ($0.34 for 96 samples) and 10 times simpler (15 min hands-on time for 96 samples) than the DNeasy PowerSoil protocol. The direct PCR method can also be fully automated and is compatible with small-volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis.

IMPORTANCE Understanding bacterial interactions and assembly in complex microbial communities using 16S rRNA sequencing normally requires a large experimental load. However, the current DNA extraction methods, including cell disruption and genomic DNA purification, are normally biased, costly, time-consuming, labor-intensive, and not amenable to miniaturization by droplets or 1,536-well plates due to the significant DNA loss during the purification step for tiny-volume and low-cell-density samples. A direct PCR method could potentially solve these problems. In this study, we developed a direct PCR method which exhibits similar efficiency as the widely used method, the DNeasy PowerSoil protocol, while being 1,600 times less expensive and 10 times faster to execute. This simple, cost-effective, and automation-friendly direct-PCR-based 16S rRNA sequencing method allows us to study the dynamics, microbial interaction, and assembly of various microbial communities in a high-throughput fashion.

Identifying biases and their potential solutions in human microbiome studies

Advances in DNA sequencing technology have vastly improved the ability of researchers to explore the microbial inhabitants of the human body. Unfortunately, while these studies have uncovered the importance of these microbial communities to our health, they often do not result in similar findings. One possible reason for the disagreement in these results is due to the multitude of systemic biases that are introduced during sequence-based microbiome studies. These biases begin with sample collection and continue to be introduced throughout the entire experiment leading to an observed community that is significantly altered from the true underlying microbial composition. In this review, we will highlight the various steps in typical sequence-based human microbiome studies where significant bias can be introduced, and we will review the current efforts within the field that aim to reduce the impact of these biases. Video abstract.

Respiratory Bacteria Stabilize and Promote Airborne Transmission of Influenza A Virus

Influenza A virus (IAV) is a major pathogen of the human respiratory tract, where the virus coexists and interacts with bacterial populations comprising the respiratory tract microbiome. Synergies between IAV and respiratory bacterial pathogens promote enhanced inflammation and disease burden that exacerbate morbidity and mortality. We demonstrate that direct interactions between IAV and encapsulated bacteria commonly found in the respiratory tract promote environmental stability and infectivity of IAV. Antibiotic-mediated depletion of the respiratory bacterial flora abrogated IAV transmission in ferret models, indicating that these virus-bacterium interactions are operative for airborne transmission of IAV. Restoring IAV airborne transmission in antibiotic-treated ferrets by coinfection with Streptococcus pneumoniae confirmed a role for specific members of the bacterial respiratory community in promoting IAV transmission. These results implicate a role for the bacterial respiratory flora in promoting airborne transmission of IAV.IMPORTANCE Infection with influenza A virus (IAV), especially when complicated with a secondary bacterial infection, is a leading cause of global mortality and morbidity. Gaining a greater understanding of the transmission dynamics of IAV is important during seasonal IAV epidemics and in the event of a pandemic. Direct bacterium-virus interactions are a recently appreciated aspect of infectious disease biology. Direct interactions between IAV and specific bacterial species of the human upper respiratory tract were found to promote the stability and infectivity of IAV during desiccation stress. Viral environmental stability is an important aspect during transmission, suggesting a potential role for bacterial respiratory communities in IAV transmission. Airborne transmission of IAV was abrogated upon depletion of nasal bacterial flora with topical antibiotics. This defect could be functionally complemented by S. pneumoniae coinfection. These data suggest that bacterial coinfection may be an underappreciated aspect of IAV transmission dynamics.

Thermus thermophilus DNA can be used as internal control for process monitoring of clinical metagenomic next-generation sequencing of urine samples

INTRODUCTION

Metagenomics is increasingly considered for clinical diagnostics. In order for this technology to become integrated in the clinical microbiology laboratory, process controls are required. Molecular diagnostic tests typically integrate an internal control (IC) to detect potential sources of variation and technical failure. However, few studies report on the integration of an IC in metagenomics.

AIM

We aimed to develop an easy-to-use IC method for the process control of library preparation and sequencing applied to metagenomics in clinical microbiology diagnostics using Thermus thermophilus DNA.

METHODOLOGY

DNA was extracted from urine samples and sequenced on the Ion Torrent Proton in the absence and presence of incremental concentrations (0.5-2-5%) of IC. Between aliquots of each sample, we compared the IC relative abundance (RA), and after in silico subtraction of IC reads, analysed microbial composition and the RA of pathogens. The optimal IC concentration was defined as the lowest concentration still detectable in all samples with the smallest impact on the microbial composition.

RESULTS

The RA of IC correlated linearly with the spiked IC concentration (r² = 0.99). IC added in a concentration of 0.5% of the total DNA concentration was detectable in all sample aliquots, regardless of human-bacterial DNA proportion, and after in silico removal gave the smallest difference in RA of pathogens compared to the sample aliquot sequenced in the absence of IC. The microbial composition in the presence and absence of IC was highly similar after in silico removal of IC reads (median BC-dissimilarity per sample: 0.059), provided samples had a mean of >10,000 bacterial reads.

CONCLUSION

T. thermophilus DNA at a percentage of 0.5% of the total DNA concentration was successfully applied for the process control of metagenomics of urine samples. We demonstrated negligible alterations in sample microbial composition after in silico subtraction of IC reads. This approach contributes toward implementation of metagenomics in the clinical microbiology laboratory.

Validating DNA Extraction Protocols for Bentonite Clay

Bentonite clay is an integral component of the engineered barrier system of deep geological repositories (DGRs) that are planned for the long-term storage of high-level radioactive waste. Although nucleic acid extraction and analysis can provide powerful qualitative and quantitative data reflecting the presence, abundance, and functional potential of microorganisms within DGR materials, extraction of microbial DNA from bentonite clay is challenging due to the low biomass and adsorption of nucleic acids to the charged clay matrix. In this study, we used quantitative PCR, gel fingerprinting, and high-throughput sequencing of 16S rRNA gene amplicons to assess DNA extraction efficiency from natural MX-80 bentonite and the same material "spiked" with Escherichia coli genomic DNA. Extraction protocols were tested without additives and with casein and phosphate as blocking agents. Although we demonstrate improved DNA recovery by blocking agents at relatively high DNA spiking concentrations, at relatively low spiking concentrations, we detected a high proportion of contaminant nucleic acids from blocking agents that masked sample-specific microbial profile data. Because bacterial genomic DNA associated with casein preparations was insufficiently removed by UV treatment, casein is not recommended as an additive for DNA extractions from low-biomass samples. Instead, we recommend a kit-based extraction protocol for bentonite clay without additional blocking agents, as tested here and validated with multiple MX-80 bentonite samples, ensuring relatively high DNA recoveries with minimal contamination.IMPORTANCE Extraction of microbial DNA from MX-80 bentonite is challenging due to low biomass and adsorption of nucleic acid molecules to the charged clay matrix. Blocking agents improve DNA recovery, but their impact on microbial community profiles from low-biomass samples has not been characterized well. In this study, we evaluated the effect of casein and phosphate as blocking agents for quantitative recovery of nucleic acids from MX-80 bentonite. Our data justify a simplified framework for analyzing microbial community DNA associated with swelling MX-80 bentonite samples within the context of a deep geological repository for used nuclear fuel. This study is among the first to demonstrate successful extraction of DNA from Wyoming MX-80 bentonite.