In this study, we have evaluated the performance characteristics (host-specificity and -sensitivity) of four human wastewater-associated Escherichia coli (E. coli) genetic markers (H8, H12, H14, and ...H24) in 10 target (human) and nontarget (cat, cattle, deer, dog, emu, goat, horse, kangaroo, and possum) host groups in Southeast Queensland, Australia. The overall host-sensitivity values of the tested markers in human wastewater samples were 1.0 (all human wastewater samples contained the E. coli genetic markers). The overall host-specificity values of these markers to differentiate between human and animal host groups were 0.94, 0.85, 0.72, and 0.57 for H8, H12, H24, and H14, respectively. Based on the higher host-specificity values, H8 and H12 markers were chosen for a validation environmental study. The prevalence of the H8 and H12 markers was determined among human wastewater E. coli isolates collected from a wastewater treatment plant (WWTP). Among the 97 isolates tested, 44 (45%) and 14 (14%) were positive for the H8 and H12 markers, respectively. A total of 307 E. coli isolates were tested from environmental water samples collected in Brisbane, of which 7% and 20% were also positive for the H8 and H12 markers, respectively. Based on our results, we recommend that these markers could be useful when it is important to identify the source(s) of E. coli (whether they originated from human wastewater or not) in environmental waters.
The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized ...medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.
Since sewage is a hotspot for antibiotic resistance genes (ARGs), the identification of ARGs in environmental waters impacted by sewage, and their correlation to fecal indicators, is necessary to ...implement management strategies. In this study, sewage treatment plant (STP) influent samples were collected and analyzed using quantitative polymerase chain reaction (qPCR) to investigate the abundance and correlations between sewage-associated markers (i.e.,
Bacteroides
HF183,
Lachnospiraceae
Lachno3, crAssphage) and ARGs indicating resistance to nine antibiotics (belonging to aminoglycosides, beta-lactams, sulfonamides, macrolides, and tetracyclines). All ARGs, except
bla
VIM
, and sewage-associated marker genes were always detected in untreated sewage, and
ermF
and
sul1
were detected in the greatest abundances.
intl1
was also highly abundant in untreated sewage samples. Significant correlations were identified between sewage-associated marker genes, ARGs and the
intl1
in untreated sewage (τ = 0.488,
p
= 0.0125). Of the three sewage-associated marker genes, the BIO-ENV procedure identified that HF183 alone best maximized correlations to ARGs and
intl1
(τ = 0.590). Additionally, grab samples were collected from peri-urban and urban sites along the Brisbane River system during base and stormflow conditions, and analyzed for
Escherichia coli
, ARGs, the
intl1
, and sewage-associated marker genes using quantitative polymerase chain reaction (qPCR). Significant correlations were identified between
E. coli
, ARGs, and
intl1
(τ = 0.0893,
p
= 0.0032), as well as with sewage-associated marker genes in water samples from the Brisbane River system (τ = 0.3229,
p
= 0.0001). Of the sewage-associated marker genes and
E. coli
, the BIO-ENV procedure identified that crAssphage alone maximized correlations with ARGs and
intl1
in river samples (τ = 0.4148). Significant differences in
E. coli
, ARGs,
intl1
, and sewage-associated marker genes, and by flow condition (i.e., base vs. storm), and site types (peri-urban vs. urban) combined were identified (
R
= 0.3668,
p
= 0.0001), where percent dissimilarities between the multi-factorial groups ranged between 20.8 and 11.2%. Results from this study suggest increased levels of certain ARGs and sewage-associated marker genes in stormflow river water samples compared to base flow conditions.
E. coli
, HF183 and crAssphage may serve as potential indicators of sewage-derived ARGs under stormflow conditions, and this merits further investigation. Data presented in this study will be valuable to water quality managers to understand the links between sewage pollution and ARGs in urban environments.
A multi-omics approach was applied to an urban river system (the Brisbane River (BR), Queensland, Australia) in order to investigate surface water quality and characterize the bacterial population ...with respect to water contaminants. To do this, bacterial metagenomic amplicon-sequencing using Illumina next-generation sequencing (NGS) of the V5-V6 hypervariable regions of the 16S rRNA gene and untargeted community metabolomics using gas chromatography coupled with mass spectrometry (GC-MS) were utilized. The multi-omics data, in combination with fecal indicator bacteria (FIB) counts, trace metal concentrations (by inductively coupled plasma mass spectrometry (ICP-MS)) and in-situ water quality measurements collected from various locations along the BR were then used to assess the health of the river ecosystem. Sites sampled represented the transition from less affected (upstream) to polluted (downstream) environments along the BR. Chemometric analysis of the combined datasets indicated a clear separation between the sampled environments.
and
were common key factors for differentiation of pristine waters. Increased sugar alcohol and short-chain fatty acid production was observed by
and
that are known to form biofilms in urban polluted and brackish waters. Results from this study indicate that a multi-omics approach enables a deep understanding of the health of an aquatic ecosystem, providing insight into the bacterial diversity present and the metabolic output of the population when exposed to environmental contaminants.
Stormwater harvesting and reuse in the urban environment is emerging as an alternative water source, despite human pathogens in the stormwater may represent a hazard to public health. This study ...presents the results of 1-year monitoring to evaluate the quality of stormwater obtained in a high-income neighborhood in Rio de Janeiro for a set of microbiological parameters as total coliforms,
Escherichia coli
(
E. coli
), human adenovirus (HAdV), human JC polyomavirus (JCPyV), Group A rotavirus (RVA), and norovirus GI and GII. Forty-eight stormwater samples obtained from two multiplex units presented total coliforms and
E. coli
in 91.7% (
n
= 44) and 58.3% (
n
= 28) of samples, while HAdV and JCPyV were detected in 20.8% (
n
= 10) and 12.5% (
n
= 6), respectively. Viral quantification ranged from 10
3
to 10
4
genomic copies/liter (GC/L) for HAdV and from 10
1
to 10
4
GC/L for JCPyV. Neither RVA nor norovirus GI and GII was detected. Fifteen out of sixteen (93.8%) samples containing viruses were compliant as per fecal indicator bacteria (FIB) according to Brazilian standards for rainwater reuse and US EPA Guidelines for Water Reuse, suggesting that viruses monitoring should complement the study of bacterial indicators.
A quantitative PCR（q PCR） assay was used to quantify Ancylostoma caninum ova in wastewater and sludge samples.We estimated the average gene copy numbers for a single ovum using a mixed population of ...ova.The average gene copy numbers derived from the mixed population were used to estimate numbers of hookworm ova in A.caninum seeded and unseeded wastewater and sludge samples.The newly developed qP CR assay estimated an average of3.7 × 10~3 gene copies per ovum,which was then validated by seeding known numbers of hookworm ova into treated wastewater.The qP CR estimated an average of（1.1 ± 0.1）,（8.6 ± 2.9）and（67.3 ± 10.4） ova for treated wastewater that was seeded with（1 ± 0）,（10 ± 2） and（100 ± 21）ova,respectively.The further application of the q PCR assay for the quantification of A.caninum ova was determined by seeding a known numbers of ova into the wastewater matrices.The qP CR results indicated that 50%,90% and 67% of treated wastewater（1 L）,raw wastewater（1 L）and sludge（~4 g） samples had variable numbers of A.caninum gene copies.After conversion of the q PCR estimated gene copy numbers to ova for treated wastewater,raw wastewater,and sludge samples,had an average of 0.02,1.24 and 67 ova,respectively.The result of this study indicated that qP CR can be used for the quantification of hookworm ova from wastewater and sludge samples;however,caution is advised in interpreting qP CR generated data for health risk assessment.
Despite the global push for a circular water and nutrient economy, the United States still lags in recycling and reusing valuable waste streams. The reuse of waste streams could result in more ...sustainable agricultural practices by reducing water withdrawals in stressed environments and nutrient inputs to eutrophication-impacted ecosystems. However, microbial risks are a key barrier to reuse. We identify research and regulatory gaps through a systematic review of quantitative microbial risk assessments (QMRAs) and regulations for biosolids, manure, and human source-separated urine. We propose a cohesive path forward to improve upon existing QMRA approaches, to combine QMRA with other risk frameworks, and to develop integrated monitoring and control strategies by incorporating molecular biology tools. The application of a farm-to-fork risk-based approach that considers the combined use of waste streams is needed to develop comprehensive best management practices, treatment recommendations, and microbial quality criteria that promote food safety while advancing agricultural sustainability.
PDF
