A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System

Beale, David J.; Karpe, Avinash V.; Ahmed, Warish; Cook, Stephen; Morrison, Paul D.; Staley, Christopher; Sadowsky, Michael J.; Palombo, Enzo A.

doi:10.3390/ijerph14030303

Cited by 64 publications

(33 citation statements)

References 58 publications

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“…Statistically significant discrimination between the control and spiked samples was obtained at 24 h of incubation for L. monocytogenes (Figure 2), 12 h for E. coli O157:H7 (Figure 3) and 18 h for S. enterica (Figure 4). The Q 2 value for all PLS-DA models were above 90% which is indicative of a model that reasonably fits the data and has a good predictive capability (>70%) (Beale et al, 2017).…”

Section: Resultsmentioning

confidence: 96%

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

et al. 2018

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Considering the short shelf-life of certain food products such as red meat, there is a need for rapid and cost-effective methods for pathogen detection. Routine pathogen testing in food laboratories mostly relies on conventional microbiological methods which involve the use of multiple selective culture media and long incubation periods, often taking up to 7 days for confirmed identifications. The current study investigated the application of omics-based approaches, proteomics using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) and metabolomics using gas chromatography-mass spectrometry (GC-MS), for detection of three red meat pathogens – Listeria monocytogenes, Salmonella enterica and Escherichia coli O157:H7. Species-level identification was achieved within 18 h for S. enterica and E. coli O157:H7 and 30 h for L. monocytogenes using MALDI-ToF MS analysis. For the metabolomics approach, metabolites were extracted directly from selective enrichment broth samples containing spiked meat samples (obviating the need for culturing on solid media) and data obtained using GC-MS were analyzed using chemometric methods. Putative biomarkers relating to L. monocytogenes, S. enterica and E. coli O157:H7 were observed within 24, 18, and 12 h, respectively, of inoculating meat samples. Many of the identified metabolites were sugars, fatty acids, amino acids, nucleosides and organic acids. Secondary metabolites such as cadaverine, hydroxymelatonin and 3,4-dihydroxymadelic acid were also observed. The results obtained in this study will assist in the future development of rapid diagnostic tests for these important foodborne pathogens.

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Section: Resultsmentioning

confidence: 96%

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

et al. 2018

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“…Their presence in the top seven classes also indicates that these classes may be thriving here because of the abundance of hydrocarbons contamination. Beale et al 36] using a community multi-omics approach towards the assessment of surface water quality in an Urban River system reported similar top 10 orders to include Actinomycetes, Rhodospirillales, Bukholderiales, Sphingobacteriales, Alteromonadales, Cyanobacteria family II, Flavobacteriales Planctomycetales, Acidimicrobiales and Rhizobiales. These orders were well represented in our findings apart from Cyanobacteria family II.…”

Section: Discussionmentioning

confidence: 99%

Microbiological Examination and Physicochemical Analysis of Estuary Water Used as a Point of Source Drinking Water

Edet

Antai

Brooks

et al. 2018

IJPR

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Introduction: Access to potable water is a fundamental human right. However, this is hardly the case in the rural areas of oil producing communities of the Niger Delta. Aim of Study: The primary aim of this study was therefore to evaluate the physicochemical and microbiological qualities of estuary water used as potable water. Method: Estuary water samples were collected from Eastern Obolo community in Akwa Ibom State, Niger Delta, Nigeria and analysed for physiochemical using standard techniques, and microbiological parameters using standard cultural and metagenomics techniques. Replicate data from microbiological and physicochemical analyses were analyzed using analysis of variance (ANOVA) while bioinformatic analyses were done using Vecton NTI suite 9 (InforMax, Inc.), NCBI-BLAST-2.2.24 and CLC bio Genomics workbench v7.5.1. IJPR, 1(1): 1-13, 2018; Article no.IJPR.41432 2 Results: Physicochemical analysis showed that the levels of metals such as chromium, nickel, zinc and iron and as well as turbidity were significantly higher than acceptable standards. Bacterial counts ranged from 0.64 to 1.00 (x 10 5 ) cfu/ml. Fungal counts ranged from 2.00 to 4.00 (x 10 2 ) cfu/ml. Esherichia coli, Citrobacter, Bacillus, Micrococcus, Pseudomonas and Flavobacterium, Shigella, Salmonella and Vibrio species were isolated using cultural means. Total coliforms counts were higher in location E6 which was closest to the community. Metagenomics analysis gave a total of six kingdoms namely bacteria, unknown, protozoa, archae, plantae and fungi in decreasing order of read counts. Furthermore, it revealed a total of 16 phyla, 24 classes, 38 orders, 39 families and 209 species of bacteria. Some pathogens not captured by cultural means such as Clostridium species, Vibrio alginolyticus, Vibrio neresis, Staphylococcus kloosii, Corynebacterium diptheriae, and uncultured species such as uncultured Helicobacter were all captured by metagenomics. Conclusion: Although, cultural methods used in this study were able to capture water borne disease pathogens, metagenomics captured much more kingdoms and species. Where possible, both techniques should be used in the microbiological examination of water samples. Original Research Article

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“…A metabolome is the total metabolites in an organism and the study of the metabolite profile of a cell within a given condition is called metabolomics (Beale et al, 2017). A cell produces a range of primary and secondary metabolites when subjected to external stress which has enabled us to understand and analyze the effect of environmental conditions on the metabolome of organisms (Malla et al, 2018).…”

Section: Metabolomicsmentioning

confidence: 99%

Microbial Biodiversity and Bioremediation Assessment Through Omics Approaches

Chandran

Meena

Sharma

2020

Front. Environ. Chem.

130

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Industrialization, population burst, and changing lifestyles have resulted in the genesis of non-degradable pollutants languishing the environment and human health. Biological approaches using microorganisms are gaining importance as an eco-friendly and cost-effective substitute to mitigate the pollution load. Microorganisms can survive in a divergent environment and produce metabolites that can degrade and transform pollutants making it possible to revive contaminated sites naturally. Modern omics technologies like metagenomics, transcriptomics, proteomics, etc. have been used nowadays design strategies to study ecology and diversity of microorganisms and their application in environmental monitoring and bioremediation. The present article will focus on the omics techniques reportedly used in environmental monitoring to tackle the pollution load.

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A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System

Cited by 64 publications

References 58 publications

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

Microbiological Examination and Physicochemical Analysis of Estuary Water Used as a Point of Source Drinking Water

Microbial Biodiversity and Bioremediation Assessment Through Omics Approaches

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