QMRA of beach water by Nanopore sequencing-based viability-metagenomics absolute quantification

Empowering protein single-molecule sequencing: nanopore technology toward sensing gene sequences

The investigation of proteins at the single-molecule level is urgent to reveal the relationship between their structure and function. Unlike traditional techniques for attaining the overall average effect of group systems, nanopore sensing mode can provide information on the characteristics of proteins at the single-molecule level. Assisting with the intensity, frequency, and period of current changes, nanopore sequencing technology is rapidly advancing due to its merits, including fast readout, high accuracy, low cost, and portability. In particular, the single-molecule nanopore sequencing mode enables in-depth studies of DNA-protein interactions, protein conformation, DNA sequencing, and microbial assay, including genome sequencing of new species. This review summarizes the sensing mechanisms of nanopore sequencing technology in DNA damage, DNA methylation, RNA sequencing, and protein post-translational modifications and unfolding, covering both biological and solid-state nanopores. Due to these significant advantages, nanopore sequencing provides new insights into complex biological processes and enables more precise real-time monitoring of molecular changes. Its applications extend to clinical diagnostics, environmental monitoring, food safety, and forensic analysis. Moreover, the review outlines the present challenges faced by nanopore sequencing patterns, such as the choice of raw reagents and the design of special construction, offering a deep understanding of nanoporous single-molecule sensing toward protein sequence information and structure prediction.

Evaluating Quantitative Metagenomics for Environmental Monitoring of Antibiotic Resistance and Establishing Detection Limits

Metagenomics holds promise as a comprehensive, nontargeted tool for environmental monitoring. However, one key limitation is that the quantitative capacity of metagenomics is not well-defined. Here, we demonstrated a quantitative metagenomic technique and benchmarked the approach for wastewater-based surveillance of antibiotic resistance genes. To assess the variability of low-abundance oligonucleotide detection across sample matrices, we spiked DNA reference standards (meta sequins) into replicate wastewater DNA extracts at logarithmically decreasing mass-to-mass percentages (m/m%). Meta sequin ladders exhibited strong linearity at input concentrations as low as 2 × 10-3 m/m% (R2 > 0.95), with little to no reference length or GC bias. At a mean sequencing depth of 94 Gb, the limits of quantification (LoQ) and detection were calculated to be 1.3 × 103 and 1 gene copy per μL DNA extract, respectively. In wastewater influent, activated sludge, and secondary effluent samples, 27.3, 47.7, and 44.3% of detected genes were ≤LoQ, respectively. Volumetric gene concentrations and log removal values were statistically equivalent between quantitative metagenomics and ddPCR for 16S rRNA, intI1, sul1, CTX-M-1, and vanA. The quantitative metagenomics benchmark here is a key step toward establishing metagenomics for high-throughput, nontargeted, and quantitative environmental monitoring.

Species-resolved profiling of antibiotic resistance genes in complex metagenomes through long-read overlapping with Argo

Environmental surveillance of antibiotic resistance genes (ARGs) is critical for understanding and mitigating the spread of antimicrobial resistance. Current short-read-based ARG profiling methods are limited in their ability to provide detailed host information, which is indispensable for tracking the transmission and assessing the risk of ARGs. Here, we present Argo, a novel approach that leverages long-read overlapping to rapidly identify and quantify ARGs in complex environmental metagenomes at the species level. Argo significantly enhances the resolution of ARG detection by assigning taxonomic labels collectively to clusters of reads, rather than to individual reads. By benchmarking the performance in host identification using simulation, we confirm the advantage of long-read overlapping over existing metagenomic profiling strategies in terms of accuracy. Using sequenced mock communities with varying quality scores and read lengths, along with a global fecal dataset comprising 329 human and non-human primate samples, we demonstrate Argo's capability to deliver comprehensive and species-resolved ARG profiles in real settings.

Relic DNA obscures bacterial diversity and interactions in ballast tank sediment

The dark and anoxic environment of ballast tank sediment (BTS) harbors substantial amounts of relic DNA, yet its impact on microbial diversity estimates in BTS management remains poorly understood. This study employed propidium monoazide (PMA) treatment to eliminate relic DNA and used 16S amplicon high-throughput sequencing to characterize both total and viable bacteria. Our findings revealed that relic DNA is abundant in BTS. When removed, it led to variable reductions in species richness, which fluctuated from a 3.15% increase to a 37.52% decrease. Additionally, 6.27%-15.79% of OTUs were absent in the PMA-treated samples. These findings indicate that relic DNA has diverse effects on microbial diversity estimates. Moreover, relic DNA removal altered the relative abundances of a wide range of taxa, thereby facilitating the detection of rare taxa. Furthermore, the absence of relic DNA resulted in an overestimation of co-occurrence network size, complexity, and competitiveness, which could lead to misinterpretations of community assembly processes. In conclusion, our findings indicate that relic DNA obscures microbial diversity estimates and risk assessments in BTS, highlighting the critical need for monitoring viable bacteria in ballast sediment management.

The quest for environmental analytical microbiology: absolute quantitative microbiome using cellular internal standards

BACKGROUND

High-throughput sequencing has revolutionized environmental microbiome research, providing both quantitative and qualitative insights into nucleic acid targets in the environment. The resulting microbial composition (community structure) data are essential for environmental analytical microbiology, enabling characterization of community dynamics and assessing microbial pollutants for the development of intervention strategies. However, the relative abundances derived from sequencing impede comparisons across samples and studies.

RESULTS

This review systematically summarizes various absolute quantification (AQ) methods and their applications to obtain the absolute abundance of microbial cells and genetic elements. By critically comparing the strengths and limitations of AQ methods, we advocate the use of cellular internal standard-based high-throughput sequencing as an appropriate AQ approach for studying environmental microbiome originated from samples of complex matrices and high heterogeneity. To minimize ambiguity and facilitate cross-study comparisons, we outline essential reporting elements for technical considerations, and provide a checklist as a reference for environmental microbiome research.

CONCLUSIONS

In summary, we propose absolute microbiome quantification using cellular internal standards for environmental analytical microbiology, and we anticipate that this approach will greatly benefit future studies. Video Abstract.

Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes

Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.

Two-year Monitoring of Microbiological Water Quality in Small Water Supply Systems: Implications for Microbial Risk Management

Small water supply systems (SWSSs) are often more vulnerable to waterborne disease outbreaks. In Japan, many SWSSs operate without regulation under the Waterworks Law, yet there is limited investigation into microbial contamination and the associated health risks. In this study, the microbiological water quality of four SWSSs that utilize mountain streams as water sources and do not install water treatment facilities were monitored for over 2 years. In investigated SWSSs, the mean heterotrophic plate counts were below 350 CFU/mL, and the total bacterial loads (16S rDNA concentration) ranged from 4.71 to 5.35 log10 copies/mL. The results also showed the consistent presence of fecal indicator bacteria (FIB), i.e., Escherichia coli and Clostridium perfringens, suggesting the potential of fecal pollution. E. coli was then utilized as an indicator to assess the health risk posed by E. coli O157:H7 and Campylobacter jejuni. The results indicated that the estimated mean annual risk of infection and disability-adjusted life years (DALYs) exceeded acceptable levels in all SWSSs for the two reference pathogens. To ensure microbial water safety, implementing appropriate water treatment facilities with an estimated mean required reduction of 5-6 log10 was necessary. This study highlighted the potential microbial contamination and health risk level in SWSSs that utilize mountain streams as water sources, even though the water sources were almost not affected by human activities. Furthermore, this study would also be helpful in supporting risk-based water management to ensure a safe water supply in SWSSs.

A mica filter enables bacterial enrichment from large volumes of natural water for sensitive monitoring of pathogens by nanopore sequencing

Nanopore sequencing is extremely promising for the high-throughput detection of pathogenic bacteria in natural water; these bacteria may be transmitted to humans and cause waterborne infectious diseases. However, the concentration of pathogenic bacteria in natural water is too low to be detected directly by nanopore sequencing. Herein, we developed a mica filter to enrich over 85% of bacteria from > 10 L of natural water in 100 min, which led to a 102-fold improvement in the assay limits of the MinION sequencer for assessing pathogenic bacteria. Correspondingly, the sequencing time of S. Typhi detection at a concentration as low as 105 CFU/L was reduced from traditional 48 h to 3 h. The bacterial adsorption followed pseudo-first-order kinetics and the successful adsorption of bacteria to the mica filter was confirmed by scanning electron microscopy and Fourier infrared spectroscopy et al. The mica filter remained applicable to a range of water samples whose quality parameters were within the EPA standard limits for freshwater water. The mica filter is thus an effective tool for the sensitive and rapid monitoring of pathogenic bacteria by nanopore sequencing, which can provide timely alerts for waterborne transmission events.

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

Antibiotic resistance genes associated with size-segregated bioaerosols from wastewater treatment plants: A review

The antibiotic-resistant pollution in size-segregated bioaerosols from wastewater treatment plants (WWTPs) is of increasing concern due to its public health risks, but an elaborate review is still lacking. This work overviewed the profile, mobility, pathogenic hosts, source, and risks of antibiotic resistance genes (ARGs) in size-segregated bioaerosols from WWTPs. The dominant ARG type in size-segregated bioaerosols from WWTPs was multidrug resistance genes. Treatment units that equipped with mechanical facilities and aeration devices, such as grilles, grit chambers, biochemical reaction tanks, and sludge treatment units, were the primary sources of bioaerosol antibiotic resistome in WWTPs. Higher enrichment of antibiotic resistome in particulate matter with an aerodynamic diameter of <2.5 μm, was found along the upwind-downwind-WWTPs gradient. Only a small portion of ARGs in inhalable bioaerosols from WWTPs were flanked by mobile genetic elements. The pathogens with multiple drug resistance had been found in size-segregated bioaerosols from WWTPs. Different ARGs or antibiotic resistant bacteria have different aerosolization potential associated with bioaerosols from various treatment processes. The validation of pathogenic antibiotic resistance bacteria, deeper investigation of ARG mobility, emission mechanism of antibiotic resistome, and development of treatment technologies, should be systematically considered in future.

Application of high-throughput sequencing technologies and analytical tools for pathogen detection in urban water systems: Progress and future perspectives

The ubiquitous presence of pathogenic microorganisms, such as viruses, bacteria, fungi, and protozoa, in urban water systems poses a significant risk to public health. The emergence of infectious waterborne diseases mediated by urban water systems has become one of the leading global causes of mortality. However, the detection and monitoring of these pathogenic microorganisms have been limited by the complexity and diversity in the environmental samples. Conventional methods were restricted by long assay time, high benchmarks of identification, and narrow application sceneries. Novel technologies, such as high-throughput sequencing technologies, enable potentially full-spectrum detection of trace pathogenic microorganisms in complex environmental matrices. This review discusses the current state of high-throughput sequencing technologies for identifying pathogenic microorganisms in urban water systems with a concise summary. Furthermore, future perspectives in pathogen research emphasize the need for detection methods with high accuracy and sensitivity, the establishment of precise detection standards and procedures, and the significance of bioinformatics software and platforms. We have compiled a list of pathogens analysis software/platforms/databases that boast robust engines and high accuracy for preference. We highlight the significance of analyses by combining targeted and non-targeted sequencing technologies, short and long reads technologies, sequencing technologies, and bioinformatic tools in pursuing upgraded biosafety in urban water systems.

Roadmap to tackle antibiotic resistance in the environment under the One Health framework

Antibiotic resistance has been recognized as a major challenge worldwide for humans. "One Health" has been recognized as a key concept for containment of antibiotic resistance. Under the framework, the role of the environment in the development of antibiotic resistance genes (ARGs) has become increasingly obvious. Despite numerous efforts, response to antibiotic resistance is considered to be inadequate, which is probably due to the lack of a clear roadmap. Here, we propose a "One Health" roadmap to combat antibiotic resistance in the environment through (1) understanding environmental resistome. The environmental gene pool has long been recognized as the single largest reservoir of both known and novel ARGs. (2) Standardizing ARG quantification. Systematic joint efforts based on standardized quantification are urgently needed to understand the true tempospatial profiles of the environmental resistome. (3) Identifying mechanisms of resistome development. Horizontal gene transfer and co-selection have been recognized as the two main mechanisms contributing to the environmental resistome. (4) Establishing a risk-assessment framework. The first critical step for large-scale cost-effective targeted ARG management in the environment is the risk assessment to identify the priority ARGs for control. (5) Formulating regulatory standards. By correlating the environmental ARG profile with public health, we may identify the indicator ARGs that can be integrated into current environmental quality standards. (6) Developing control strategies. Systematic analysis of available control technologies is required to identify the most feasible ones to curtail the spread of ARGs in the environment. The proposed roadmap under the "One Health" framework provides a guide to tackle antibiotic resistance in the environment.