Biospectroscopic fingerprinting phytotoxicity towards environmental monitoring for food security and contaminated site remediation.

Human activities have resulted in severe environmental pollution since the industrial revolution. Phytotoxicity-based environmental monitoring is well known due to its sedentary nature, abundance, and sensitivity to environmental changes, which are essential preconditions to avoiding potential environmental and ecological risks. However, conventional morphological and physiological methods for phytotoxicity assessment mainly focus on descriptive determination rather than mechanism analysis and face challenges of labour and time-consumption, lack of standardized protocol and difficulties in data interpretation. Molecular-based tests could reveal the toxicity mechanisms but fail in real-time and in-situ monitoring because of their endpoint manner and destructive operation in collecting cellular components. Herein, we systematically propose and lay out a biospectroscopic tool (e.g., infrared and Raman spectroscopy) coupled with multivariate data analysis as a relatively non-destructive and high-throughput approach to quantitatively measure phytotoxicity levels and qualitatively profile phytotoxicity mechanisms by classifying spectral fingerprints of biomolecules in plant tissues in response to environmental stresses. With established databases and multivariate analysis, this biospectroscopic fingerprinting approach allows ultrafast, in situ and on-site diagnosis of phytotoxicity. Overall, the proposed protocol and validation of biospectroscopic fingerprinting phytotoxicity can distinguish the representative biomarkers and interrogate the relevant mechanisms to quantify the stresses of interest, e.g., environmental pollutants. This state-of-the-art concept and design broaden the knowledge of phytotoxicity assessment, advance novel implementations of phytotoxicity assay, and offer vast potential for long-term field phytotoxicity monitoring trials in situ.

Synergistic/antagonistic toxicity characterization and source-apportionment of heavy metals and organophosphorus pesticides by the biospectroscopy-bioreporter-coupling approach.

Many anthropogenic chemicals are manufactured and eventually enter the surrounding environment, threatening food security and human health. Considering the additive or synergistic effects of pollutant mixtures, there is an expanding need for rapid, cost-effective and field-portable screening methods in environmental monitoring. This study used a recently developed biospectroscopy-bioreporter-coupling (BBC) approach to investigate the binary toxicity of Ag(I), Cr(VI) and four organophosphorus pesticides (dichlorvos, parathion, omethoate and monocrotophos). Ag(I) and Cr(VI) altered the toxicity mechanisms of pesticides, explained by the synergistic or antagonistic effect of Ag/Cr-induced cytotoxicity and pesticide-induced genotoxicity. The discriminating Raman spectral peaks associated with organophosphorus pesticides were 1585 and 1682 cm-1, but 750, 1004, 1306 and 1131 cm-1 were found in heavy metal and pesticide mixtures. More spectral alterations were related to pesticides rather than Ag(I) or Cr(VI), hinting at the dominant toxicity mechanisms of pesticides in mixtures. Ag(I) supplement significantly increased the levels of reactive oxygen species induced by organophosphorus pesticides, attributing to the increased permeability of cell membrane and entrance of toxic substances into the cells by the oligodynamic actions. This study lends deeper insights into the interactions between microbes and pollutant mixtures, offering clues to assess the cocktail effects of multiple pollutants comprehensively.

Toxicity Characterization of Environment-Related Pollutants Using a Biospectroscopy-Bioreporter-Coupling Approach: Potential for Real-World Toxicity Determination and Source Apportionment of Multiple Pollutants.

Exposure to environmental pollutants occurs ubiquitously and poses many risks to human health and the ecosystem. Although many analytical methods have been developed to assess such jeopardies, the circumstances applying these means are restricted to linking the toxicities to compositions in the pollutant mixtures. The present study proposes a novel analytical approach, namely, biospectroscopy-bioreporter-coupling (BBC), to quantify and apportion the toxicities of metal ions and organic pollutants. Using a toxicity bioreporter ADPWH_recA and Raman spectroscopy, both bioluminescent signals and spectral alterations had similar dosage- and time-response behavior to the toxic compounds, validating the possibility of coupling these two methods from practical aspects. Raman spectral alterations successfully distinguished the biomarkers for different toxicity mechanisms of individual pollutants, such as ring breathing mode of DNA/RNA bases (1373 cm-1) by Cr, reactive oxygen species-induced peaks of proteins (1243 cm-1), collagen (813 cm-1), and lipids (1255 cm-1) by most metal ions, and indicative fingerprints of organic toxins. The support vector machine model had a satisfactory performance in distinguishing and apportioning toxicities of individual toxins from all input data, achieving a sensitivity of 88.54% and a specificity of 97.80%. This work set a preliminary database for Raman spectral alterations of whole-cell bioreporter response to multiple pollutants. It proved the state-of-the-art concept that the BBC approach is feasible to rapidly quantify and precisely apportion toxicities of numerous pollutant mixtures.

In Vitro Diagnosis and Visualization of Cerebral Ischemia/Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning.

Ischemic stroke is a major cause of mortality with complicated pathophysiological mechanisms, and hematoxylin and eosin (HE) staining is a histochemical diagnosis technique heavily relying on subjective observation. In this study, we developed a noninvasive assay using Raman spectroscopy for in vitro diagnosis and visualization of cerebral ischemia/reperfusion injury and protective effects of ferulic acid. By establishing a middle cerebral artery occlusion (MCAO) model in Sprague-Dawley male rats, we found effective interventions by ferulic acid using the neurological function score and HE staining. Raman spectra of neuronal and neuroglial cells exhibited significant intensity changes of protein, nucleotide, lipid, and carbohydrate at 780, 814, 1002, 1012, 1176, 1224, 1402, 1520, 1586, 1614, and 1752 cm-1. Cluster vector analysis highlighted the alterations at 1002, 1080, 1298, 1430, 1478, 1508, 1586, and 1676 cm-1. To evaluate the levels of neuron injury and intervention performance, a random forest model was developed on Raman spectral data and achieved satisfactory accuracy (0.9846), sensitivity (0.9679-0.9932), and specificity (0.9945-0.9989), ranking peaks around 1002 cm-1 as key fingerprint for classification. Spectral phenylalanine-to-tryptophan ratio was the biomarker to visualize neuronal injury and intervention performance of ferulic acid with a resolution of 1 µm. Our results unravel the biochemical changes in neuronal cells with cerebral ischemia/reperfusion injury and ferulic acid treatment, and prove Raman spectroscopy coupled with machine learning as a power tool to classify neuron viability and evaluate the intervention performance in pharmacological research.

Response of soil microbial communities to petroleum hydrocarbons at a multi-contaminated industrial site in Lanzhou, China.

Total petroleum hydrocarbon (TPH) contamination poses threats to ecological systems and human health. Many studies have reported its negative impacts on soil microbes, but limited information is known about microbial change and response to multiple TPH contamination events. In this study, we investigated TPH contamination level, microbial community structure and functional genes at a multi-contaminated industrial site in Lanzhou, where a benzene spill accident caused the drinking water crisis in 2014. TPHs distribution in soils and groundwater indicated multiple TPH contamination events in history, and identified the spill location where high TPH level (6549 mg kg-1) and high ratio of low-molecular-weight TPHs (>80%) were observed. In contrast, TPH level was moderate (349 mg kg-1) and the proportion of low-molecular-weight TPHs was 44% in soils with a long TPH contamination history. After the spill accident, soil bacterial communities became significant diverse (p = 0.047), but the dominant microbes remained the same as Pseudomonadaceae and Comamonadaceae. The abundance of hydrocarbon-degradation related genes increased by 10-1000 folds at the site where the spill accident occurred in multi-contaminated areas and was significantly related to 2-ring PAHs. Such changes of microbial community and hydrocarbon-degradation related genes together indicated the resilience of soil indigenous microbes toward multiple contamination events. Our results proved the significant change of bacterial community and huge shift of hydrocarbon-degradation related genes after the spill accident (multiple contamination events), and provided a deep insight into microbial response at industrial sites with a long period of contamination history.

In-vitro toxicity assessment of Eucalyptus robusta Smith extracts via whole-cell bioreporter.

Eucalyptus is widely planted in China for wood industries, and there are increasing concerns about its ecotoxicity in the environment. This study explored the in-vitro toxicity of Eucalyptus extracts by assessing the impacts of water-soluble and dimethylsulfoxide (DMSO)-soluble fractions via a whole-cell bioreporter, Acinetobacter baylyi ADPWH_recA. Compounds identified in Eucalyptus extracts included one tannin, two phenolic acids, four terpenoids, four glycosides, and five flavonoids. The leaf extracts contained more biological-active components than barks and roots. Genotoxicity induced by Eucalyptus extracts was mainly associated with water extracts (e.g., flavonoids, phenolic acids) instead of DMSO extracts. The significant cytotoxicity was explained by programmed cell death (PCD), suggested by the results of propidium iodide (PI) and 2',7'-dichlorofluorescein-diacetate (DCFH-DA) assays. Generally, water-soluble fractions contributed more toxicities than DMSO-soluble fractions, particularly at high concentrations. A robust linear regression was built between the compromised toxicity and PCD index (Compromised toxicity = -2.192 × PCD index + 2.219; R2 = 0.8886), suggesting a PCD-dependent compromised toxicity which was greatly underestimated. Our results implied non-neglectable ecotoxicological risks of Eucalyptus extracts, hinting at the possible magnified ecological impacts of its large-scale plantation and the potential adverse outcomes to the surrounding ecosystems.

Toxicity assessment and microbial response to soil antibiotic exposure: differences between individual and mixed antibiotics.

Increasing amounts of antibiotics are introduced into soils, raising great concerns on their ecotoxicological impacts on the soil environment. This work investigated the individual and joint toxicity of three antibiotics, tetracycline (TC), sulfonamide (SD) and erythromycin (EM) via a whole-cell bioreporter assay. TC, SD and EM in aqueous solution demonstrated cytotoxicity, whilst soil exposure showed genotoxicity, indicating that soil particles possibly affected the bioavailability of antibiotics. Toxicity of soils exposed to TC, SD and EM changed over time, demonstrating cytotoxic effects within 14-d exposure and genotoxic effects after 30 days. Joint toxicity of TC, SD and EM in soils instead showed cytotoxicity, suggesting a synergetic effect. High-throughput sequencing suggested that the soil microbial response to individual antibiotics and their mixtures showed a different pattern. Soil microbial community composition was more sensitive to TC, in which the abundance of Pseudomonas, Pirellula, Subdivision3_genera_incertae_sedis and Gemmata varied significantly. Microbial community functions were significantly shifted by EM amendments, including signal transduction mechanisms, cytoskeleton, cell wall/membrane/envelope biogenesis, transcription, chromatin structure and dynamics, and carbohydrate transport and metabolism. This work contributes to a better understanding of the ecological effects and potential risks of individual and joint antibiotics on the soil environment.

Characterization and identification of microplastics using Raman spectroscopy coupled with multivariate analysis.

The manufacture and use of plastic products have resulted in the release and spread of a massive amount of microplastics. Identifying and quantifying microplastics is challenging due to their small size and complicated composition. Although vibrational spectroscopy has been applied to analyze microplastics, its reliability and throughput are limited by the challenges to distinguish the pending alterations manually and the lack of a spectra-based automated microplastic classification model. The present study applied Raman spectroscopy coupled with multivariate analysis to develop a new and robust analytical method to comprehensively interrogate the spectral profiles of seven microplastic references and real microplastic samples post-exposure to environmental stresses. Besides identifying unique Raman peaks of individual microplastics, their whole spectra were separated by principal component analysis (PCA) and linear discriminant analysis (LDA). Support vector machine (SVM) classification achieved an accuracy rate of over 98% for polypropylene, polyethylene terephthalate, polyvinyl chloride, polycarbonate, polyamide, and over 70% for high-density polyethylene and low-density polyethylene. Real microplastic samples from the breakdown of snack boxes, mineral water bottles, juice bottles, and medicine vials were also matched to their chemical components by SVM with an overall sensitivity, specificity, and accuracy of 98.1%, 99.4%, and 99.1%, respectively. Additionally, post-exposure to environmental stressors, 1D PCA-LDA score plots could still distinguish microplastic type, and the developed SVM classification achieved an accuracy of 96.75% in the real-world scenario. These findings prove Raman spectroscopy coupled with multivariate analysis as an ideal tool to distinguish the types and environmental exposure of microplastics, demonstrating great potential for microplastic automatic detection.

Controllable Design and Preparation of Hollow Carbon-Based Nanotubes for Asymmetric Supercapacitors and Capacitive Deionization.

Carbon-based materials are important desirable materials in areas such as supercapacitors and capacitive deionization. However, traditional commercial materials are heterogeneous and prone to agglomeration in nanoscale and have structural limitation of electrochemical and desalination performance due to poor transport channels and low capacitance of prepared electrodes. Here, we introduce the facile strategy for controllable preparation of two types of hollow carbon-based nanotubes (HCTs) with amorphous mesoporous structures, which are synthesized by employing a MnO2 linear template method and calcination of polymer precursors. The porous N-doped HCT (NHCT) shows a specific capacitance of 412.6 F g-1 (1 A g-1), with 77.3% rate capability (20 A g-1). The fabricated asymmetric MnO2//NHCT supercapacitor displays the energy density of 55.8 Wh kg-1 at a power density of 803.9 W kg-1. Furthermore, two typical MnO2//HCT and MnO2//NHCT devices both show the selective desalination performance of sulfate, and the MnO2//NHCT device possesses a high deionization value of 11.37 mg g-1 (500 mg L-1 Na2SO4). These fabricated hollow carbon-based architectures with functional characteristics promise potential applications in energy and environmental related fields.

Interrogating cadmium and lead biosorption mechanisms by Simplicillium chinense via infrared spectroscopy.

Fungi-associated phytoremediation is an environmentally friendly and cost-efficient approach to remove potential toxic elements (PTEs) from contaminated soils. Many fungal strains have been reported to possess PTE-biosorption behaviour which benefits phytoremediation performance. Nevertheless, most studies are limited in rich or defined medium, far away from the real-world scenarios where nutrients are deficient. Understanding fungal PTE-biosorption performance and influential factors in soil environment can expand their application potential and is urgently needed. This study applied attenuated total reflection Fourier-transform infrared (ATR-FTIR) coupled with phenotypic microarrays to study the biospectral alterations of a fungal strain Simplicillium chinense QD10 and explore the mechanisms of Cd and Pb biosorption. Both Cd and Pb were efficiently adsorbed by S. chinense QD10 cultivated with 48 different carbon sources and the biosorption efficiency achieved >90%. As the first study using spectroscopic tools to analyse PTE-biosorption by fungal cells in a high-throughput manner, our results indicated that spectral biomarkers associated with phosphor-lipids and proteins (1745 cm-1, 1456 cm-1 and 1396 cm-1) were significantly correlated with Cd biosorption, suggesting the cell wall components of S. chinense QD10 as the primary interactive targets. In contrast, there was no any spectral biomarker associated with Pb biosorption. Addtionally, adsorption isotherms evidenced a Langmuir model for Cd biosorption but a Freundlich model for Pb biosorption. Accordingly, Pb and Cd biosorption by S. chinense QD10 followed discriminating mechanisms, specific adsorption on cell membrane for Cd and unspecific extracellular precipitation for Pb. This work lends new insights into the mechanisms of PTE-biosorption via IR spectrochemical tools, which provide more comprehensive clues for biosorption behaviour with a nondestructive and high-throughput manner solving the traditional technical barrier regarding the real-world scenarios.

Spectrochemical identification of kanamycin resistance genes in artificial microbial communities using Clover-assay.

Persistent abuse and overuse of antibiotics induces a widespread bloom of antibiotic resistance genes (ARGs) and the emergence of superbugs. A method designed to rapidly quantify ARGs in real-world scenarios is urgently needed. Here, we present an orthogonal test of heavy water and kanamycin exposure, namely, a "clover-assay", to reveal the capability of state-of-the-art Raman microspectroscopy to identify ARGs within microbial communities. This assay successfully recognizes the discriminating spectral alterations from two genetically identical strains that differ only in terms of the expression of one kanamycin resistance gene. In addition to the previously reported Raman shift at carbon-deuterium vibration bands (2,040-2,300 cm-1), we identify two new peak shifts (970-990 cm-1) and (1,110-1,130 cm-1) associated with deuterium labelling. Notably, the spectral alterations from 1,110-1,130 cm-1 strongly correlate with kanamycin exposure. By introducing dispersion index (DI) and clover assay index (CAI) as indicators, this assay is able to quantify the abundance of kanamycin resistance genes within artificial microbiotas. Based on our results, the biospectral clover assay is a powerful tool for the in situ interrogation of the occurrence of ARGs within microbial communities, which displays great potential to eliminate the need for culture protocols in the future. Due to the non-destructive and non-intrusive features, this approach may therefore potentially be able to diagnose horizontal gene transfer (HGT) in real time.

Unraveling uncultivable pesticide degraders via stable isotope probing (SIP).

Uncultivable microorganisms account for over 99% of all species on earth, playing essential roles in ecological processes such as carbon/nitrogen cycle and chemical mineralization. Their functions remain unclear in ecosystems and natural habitats, requiring cutting-edge biotechnologies for a deeper understanding. Stable isotope probing (SIP) incorporates isotope-labeled elements, e.g. 13 C, 18 O or 15 N, into the cellular components of active microorganisms, serving as a powerful tool to link phylogenetic identities to their ecological functions in situ. Pesticides raise increasing attention for their persistence in the environment, leading to severe damage and risks to the ecosystem and human health. Cultivation and metagenomics help to identify either cultivable pesticide degraders or potential pesticide metabolisms within microbial communities, from various environmental media including the soil, groundwater, activated sludge, plant rhizosphere, etc. However, the application of SIP in characterizing pesticide degraders is limited, leaving considerable space in understanding the natural pesticide mineralization process. In this review, we try to comprehensively summarize the fundamental principles, successful cases and technical protocols of SIP in unraveling functional-yet-uncultivable pesticide degraders, by raising its shining lights and shadows. Particularly, this study provides deeper insights into various feasible isotope-labeled substrates in SIP studies, including pesticides, pesticide metabolites, and similar compounds. Coupled with other techniques, such as next-generation sequencing, nanoscale secondary ion mass spectrometry (NanoSIMS), single cell genomics, magnetic-nanoparticle-mediated isolation (MMI) and compound-specific isotope analysis (CSIA), SIP will significantly broaden our understanding of pesticide biodegradation process in situ.

Spectrochemical analyses of growth phase-related bacterial responses to low (environmentally-relevant) concentrations of tetracycline and nanoparticulate silver.

Exposure to environmental insults generally occurs at low levels, making it challenging to measure bacterial responses to such interactions. Additionally, microbial behaviour and phenotype varies in differing bacterial types or growth phases, likely giving rise to growth- or species-specific responses to environmental stimuli. The present study applied a spectrochemical tool, infrared (IR) spectral interrogation coupled with multivariate analysis, to investigate the growth- and species-specific responses of two bacterial strains, Gram-negative Pseudomonas fluorescens and Gram-positive Mycobacterium vanbaalenii, to low concentrations of tetracycline, nanoparticulate silver (AgNP) or mixtures thereof. Results indicate the tendency for tetracycline-induced biospectral alterations to occur in outer-cellular components, e.g., phospholipids or proteins, while AgNPs-induced changes are mainly associated with proteins (∼964 cm-1, ∼1485 cm-1, ∼1550 cm-1, ∼1650 cm-1). The primary altered targets are correlated with bacterial membranes or outer-cellular components. Furthermore, significant lipid changes at 1705-1750 cm-1 were only present in P. fluorescens cells compared to M. vanbaalenii, owing to differences in cell wall structure between Gram-positive and -negative bacteria. This study also found distinct biospectral alterations in non-log phase compared to log phase, confirming bacterial growth-dependent responses to environmental exposures. It implies that previous studies on log phase only may underestimate the impacts from exposures of interest in situ, where bacteria stay in different growth stages. Our work proves the feasibility of biospectroscopy in determining bacterial responses to low-level environmental exposures in a fast and efficient manner, revealing sufficient biochemical information continuously through growth phases. As a nondestructive approach, biospectroscopy may provide deeper insights into the actual and in situ interactions between microbes and environmental stimuli, regardless of the exposure level, growth phase, or bacterial types.

Infrared Spectroscopy Coupled with a Dispersion Model for Quantifying the Real-Time Dynamics of Kanamycin Resistance in Artificial Microbiota.

Overusage of antibiotics leads to the widespread induction of antibiotic-resistance genes (ARGs). Developing an approach to allow real-time monitoring and fast prediction of ARGs dynamics in clinical or environmental samples has become an urgent matter. Vibrational spectroscopy is potentially an ideal technique toward the characterization of the microbial composition of microbiota as it is nondestructive, high-throughput, and label-free. Herein, we employed attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectroscopy and developed a spectrochemical tool to quantify the static and dynamic composition of kanamycin resistance in artificial microbiota to evaluate microbial antibiotic resistance. Second-order differentiation was introduced in identifying the spectral biomarkers, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was used for the multivariate analysis of the entire spectral features employed. The calculated results of the mathematical dispersion model coupled with PCA-LDA showed high similarity to the designed microbiota structure, with no significant difference (P > 0.05) in the static treatments. Moreover, our model successfully predicted the dynamics of kanamycin resistance within artificial microbiota under kanamycin pressures. This work lends new insights into the potential role of spectrochemical analyses in investigating the existence and trends of antibiotic resistance in microbiota.

Fingerprinting microbiomes towards screening for microbial antibiotic resistance.

There is an increasing need to investigate microbiomes in their entirety in a variety of contexts ranging from environmental to human health scenarios. This requirement is becoming increasingly important with the emergence of antibiotic resistance. In general, more conventional approaches are too expensive and/or time-consuming and often predicated on prior knowledge of the microorganisms one wishes to study. Herein, we propose the use of biospectroscopy tools as relatively high-throughput, non-destructive approaches to profile microbiomes under study. Fourier-transform infrared (FTIR) or Raman spectroscopy both generate fingerprint spectra of biological material and such spectra can readily be subsequently classed according to biochemical changes in the microbiota, such as emergence of antibiotic resistance. FTIR spectroscopy techniques generally can only be applied to desiccated material whereas Raman approaches can be applied to more hydrated samples. The ability to readily fingerprint microbiomes could lend itself to new approaches in determining microbial behaviours and emergence of antibiotic resistance.