Development of a digital droplet PCR approach for the quantification of soil micro-organisms involved in atmospheric CO2 fixation

Carbon-fixing micro-organisms (CFMs) play a pivotal role in soil carbon cycling, contributing to carbon uptake and sequestration through various metabolic pathways. Despite their importance, accurately quantifying the absolute abundance of these micro-organisms in soils has been challenging. This study used a digital droplet polymerase chain reaction (ddPCR) approach to measure the abundance of key and emerging CFMs pathways in fen and bog soils at different depths, ranging from 0 to 15 cm. We targeted total prokaryotes, oxygenic phototrophs, aerobic anoxygenic phototrophic bacteria and chemoautotrophs, optimizing the conditions to achieve absolute quantification of these genes. Our results revealed that oxygenic phototrophs were the most abundant CFMs, making up 15% of the total prokaryotic abundance. They were followed by chemoautotrophs at 10% and aerobic anoxygenic phototrophic bacteria at 9%. We observed higher gene concentrations in fen than in bog. There were also variations in depth, which differed between fen and bog for all genes. Our findings underscore the abundance of oxygenic phototrophs and chemoautotrophs in peatlands, challenging previous estimates that relied solely on oxygenic phototrophs for microbial carbon dioxide fixation assessments. Incorporating absolute gene quantification is essential for a comprehensive understanding of microbial contributions to soil processes. This approach sheds light on the complex mechanisms of soil functioning in peatlands.

Cyanomethyl Vinyl Ethers Against Naegleria fowleri

Naegleria fowleri is a pathogenic amoeba that causes a fulminant and rapidly progressive disease affecting the central nervous system called primary amoebic meningoencephalitis (PAM). Moreover, the disease is fatal in more than 97% of the reported cases, mostly affecting children and young people after practicing aquatic activities in nontreated fresh and warm water bodies contaminated with these amoebae. Currently, the treatment of primary amoebic meningoencephalitis is based on a combination of different antibiotics and antifungals, which are not entirely effective and lead to numerous side effects. In the recent years, research against PAM is focused on the search of novel, less toxic, and fully effective antiamoebic agents. Previous studies have reported the activity of cyano-substituted molecules in different protozoa. Therefore, the activity of 46 novel synthetic cyanomethyl vinyl ethers (QOET-51 to QOET-96) against two type strains of N. fowleri (ATCC 30808 and ATCC 30215) was determined. The data showed that QOET-51, QOET-59, QOET-64, QOET-67, QOET-72, QOET-77, and QOET-79 were the most active molecules. In fact, the selectivity index (CC₅₀/IC₅₀) was sixfold higher when compared to the activities of the drugs of reference. In addition, the mechanism of action of these compounds was studied, with the aim to demonstrate the induction of a programmed cell death process in N. fowleri.

Application of digital PCR for public health-related water quality monitoring

Digital polymerase chain reaction (dPCR) is emerging as a reliable platform for quantifying microorganisms in the field of water microbiology. This paper reviews the fundamental principles of dPCR and its application for health-related water microbiology. The relevant literature indicates increasing adoption of dPCR for measuring fecal indicator bacteria, microbial source tracking marker genes, and pathogens in various aquatic environments. The adoption of dPCR has accelerated recently due to increasing use for wastewater surveillance of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) - the virus that causes Coronavirus Disease 2019 (COVID-19). The collective experience in the scientific literature indicates that well-optimized dPCR assays can quantify genetic material from microorganisms without the need for a calibration curve and often with superior analytical performance (i.e., greater sensitivity, precision, and reproducibility) than quantitative polymerase chain reaction (qPCR). Nonetheless, dPCR should not be viewed as a panacea for the fundamental uncertainties and limitations associated with measuring microorganisms in water microbiology. With dPCR platforms, the sample analysis cost and processing time are typically greater than qPCR. However, if improved analytical performance (i.e., sensitivity and accuracy) is critical, dPCR can be an alternative option for quantifying microorganisms, including pathogens, in aquatic environments.

ddPCR surpasses classical qPCR technology in quantitating bacteria and fungi in the environment

Quantitative real-time PCR (qPCR) has been widely used in quantifying bacterial and fungal populations in various ecosystems, as well as the fungi to bacteria ratio (F:B ratio). Recently, researchers have begun to apply droplet digital PCR (ddPCR) to this area, however, no study has systematically compared qPCR and ddPCR for quantitating both bacteria and fungi in environmental samples at the same time. Here, we designed probe-primer pair combinations targeting the 16S rRNA gene and Internal Transcribed Spacer (ITS) for the detection of bacteria and fungi respectively, and tested both SYBR Green and TaqMan approaches in qPCR and ddPCR methods for mock communities and in real environmental samples. In mock communities, the quantification results of ddPCR were significantly closer to expected values (P < 0.05), and had smaller coefficients of variations (P < 0.05) than qPCR, suggesting ddPCR was more accurate and repeatable. In environmental samples, ddPCR consistently quantified ITS and 16S rRNA gene concentrations in all four habitats without abnormal overestimation or underestimation, and the F:B ratio obtained by ddPCR was consistent with phospholipid fatty acid analysis. Our results indicated that ddPCR had better precision, repeatability, sensitivity, and stability in bacterial and fungal quantitation than qPCR. Although ddPCR has high cost, complicated processes and restricted detection range, it shows insensitivity to PCR inhibitors and the potential of quantifying long target fragments. We expect that ddPCR, which is complementary to qPCR, will contribute to microbial quantification in environmental monitoring and evaluation.

Integrating Virus Monitoring Strategies for Safe Non-potable Water Reuse

Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, and especially viral pathogen exposure, limit widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling of viral health risks in the context of water reuse. First, we describe the current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We introduce promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies are ready for identifying and implementing viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in more robust assessment of water reuse risk.

Various brain-eating amoebae: the protozoa, the pathogenesis, and the disease

Among various genera of free-living amoebae prevalent in nature, some members are identified as causative agents of human encephalitis, in which Naegleria fowleri followed by Acanthamoeba spp. and Balamuthia mandrillaris have been successively discovered. As the three dominant genera responsible for infections, Acanthamoeba and Balamuthia work as opportunistic pathogens of granulomatous amoebic encephalitis in immunocompetent and immunocompromised individuals, whereas Naegleria induces primary amoebic meningoencephalitis mostly in healthy children and young adults as a more violent and deadly disease. Due to the lack of typical symptoms and laboratory findings, all these amoebic encephalitic diseases are difficult to diagnose. Considering that subsequent therapies are also affected, all these brain infections cause significant mortality worldwide, with more than 90% of the cases being fatal. Along with global warming and population explosion, expanding areas of human and amoebae activity in some regions lead to increased contact, resulting in more serious infections and drawing increased public attention. In this review, we summarize the present information of these pathogenic free-living amoebae, including their phylogeny, classification, biology, and ecology. The mechanisms of pathogenesis, immunology, pathophysiology, clinical manifestations, epidemiology, diagnosis, and therapies are also discussed.

Quantitative Microbial Risk Assessment and Molecular Biology: Paths to Integration

Quantitative microbial risk assessment (QMRA) has now been in use for over 35 years and has formed the basis for developing criteria for ensuring public health related to water, food, and remediation, to name a few areas. The initial data for QMRA (both in exposure assessment and in dose response assessment) came from measurements using assays for viability, such as plate counts, plaque assays, or animal infectivity. With the increasing use of molecular methods for the measurement of microorganisms in the environment, it has become important to assess how to use such data to estimate infectious disease risks. The limitations to the use of such data and needs to resolve the limitations will be addressed.

Removal of fecal indicator bacteria and antibiotic resistant genes in constructed wetlands

Wastewater discharge evidently increased bacterial diversity in the receiving waterbodies. The objective of this study was to evaluate the effectiveness of a constructed wetland in reducing fecal indicator bacteria (FIB) and antibiotic resistant genes (ARGs). We determined the prevalence and attenuation of fecal indicator bacteria including Escherichia coli and enterococci, along with ARGs, and human-associated Bacteroidales (HF183) markers by quantitative polymerase chain reaction (qPCR) method. Three types of water samples (inlet, intermediate, and outlet) from a constructed wetland were collected once a month from May to December in 2013. The overall reduction of E. coli was 50.0% based on culture method. According to the qPCR result, the overall removal rate of E. coli was only 6.7%. Enterococci were found in 62.5% of the wetland samples. HF183 genetic marker was detected in all final effluent samples with concentration ranging from 1.8 to 4.22 log₁₀ gene copies (GC)/100 ml. Of the ARGs tested, erythromycin resistance genes (ermF) were detected in 79.2% of the wetland samples. The class 1 integrase (intI1) was detected in all water samples with concentration ranging from 0.83 to 5.54 log₁₀ GC/100 ml. The overall removal rates of enterococci, HF183, intI1, and ermF were 84.0%, 66.6%, 67.2%, and 13.1%, respectively.