Phenotypic Tracking of Antibiotic Resistance Spread via Transformation from Environment to Clinic by Reverse D2O Single-Cell Raman Probing

Antibiotic resistance genes in aquatic systems: Sources, transmission, and risks

The widespread use of antibiotics has significantly contributed to the spread of antibiotic resistance genes (ARGs), which have become a major challenge to global ecological and public health. Antibiotic resistance not only proliferates in clinical settings but also persists in aquatic systems, where its residues and cross-domain spread pose a dual threat to both ecosystems and human health. ARGs spread rapidly within microbial communities through horizontal gene transfer (HGT) and vertical gene transfer (VGT). Aquatic systems are the key transmission medium. This review summarizes recent studies on the Source-Transport-Sink dynamics of ARGs in aquatic environments, along with their environmental and health risk assessments, with a particular focus on the potential ecotoxicity of ARGs transmission. It also examines the distribution characteristics of ARGs across different regions and the ecological risk assessment methods employed, highlighting the limitations of existing models when addressing the complex behaviors of ARGs. By analyzing the potential hazards of ARGs to aquatic ecosystems and public health, this article aims to provide a scientific foundation for future research and the development of public policies.

Leveraging the microbiome to combat antibiotic resistant gynecological infections

The vaginal resistome can be considered a collection of the resistant determinants in the vaginal microbiome. Here we review the vaginal resistome including the microbes and resistant genes harbored in common gynecological infections, vaginal microbes that participate in horizontal gene transfer, host factors that contribute to the resistome, and common therapies. Finally, we provide perspective on technologies that can be leveraged to study the vaginal resistome and remaining challenges.

Soil warming increases the active antibiotic resistome in the gut of invasive giant African snails

BACKGROUND

Global warming is redrawing the map for invasive species, spotlighting the globally harmful giant African snail as a major ecological disruptor and public health threat. Known for harboring extensive antibiotic resistance genes (ARGs) and human pathogens, it remains uncertain whether global warming exacerbates these associated health risks.

METHODS

We use phenotype-based single-cell Raman with D2O labeling (Raman-D2O) and genotype-based metagenomic sequencing to investigate whether soil warming increases active antibiotic-resistant bacteria (ARBs) in the gut microbiome of giant African snails.

RESULTS

We show a significant increase in beta-lactam phenotypic resistance of active ARBs with rising soil temperatures, mirrored by a surge in beta-lactamase genes such as SHV, TEM, OCH, OKP, and LEN subtypes. Through a correlation analysis between the abundance of phenotypically active ARBs and genotypically ARG-carrying gut microbes, we identify species that contribute to the increased activity of antibiotic resistome under soil warming. Among 299 high-quality ARG-carrying metagenome-assembled genomes (MAGs), we further revealed that the soil warming enhances the abundance of "supercarriers" including human pathogens with multiple ARGs and virulence factors. Furthermore, we identified elevated biosynthetic gene clusters (BGCs) within these ARG-carrying MAGs, with a third encoding at least one BGC. This suggests a link between active ARBs and secondary metabolism, enhancing the environmental adaptability and competitive advantage of these organisms in warmer environments.

CONCLUSIONS

The study underscores the complex interactions between soil warming and antibiotic resistance in the gut microbiome of the giant African snail, highlighting a potential escalation in environmental health risks due to global warming. These findings emphasize the urgent need for integrated environmental and health strategies to manage the rising threat of antibiotic resistance in the context of global climate change. Video Abstract.

Probing metabolism in mouse embryos using Raman spectroscopy and deuterium tags

The use of deuterated compounds is an interesting opportunity to expand the capabilities of Raman spectroscopy to study metabolism in living cells. Different biological objects have different tolerances to different deuterated compounds, and their metabolic chains may differ. Here, we explore the potential of this approach to probe metabolism in early mouse embryos. We investigated the Raman spectra of mouse embryos at different developmental stages cultured with deuterated amino acids, phenylalanine-d8 and leucine-d10, glucose-d7, and D2O. Embryos after in vitro culture with 20 % v/v D2O demonstrate Raman peak at 2186 cm-1 corresponding to newly synthesized proteins. Deuterated amino acids can slow down the development rate in 4-8 cell stage embryos, and deuterated glucose can be used at 2 mM concentration. For blastocyst, it was possible to achieve 75 % fraction of deuterated phenylalanine, when cultured with glucose, the maximal intensity ratio between CD and CH bands was 13.7 %. To demonstrate the capabilities of Raman spectroscopy reinforced by deuterium labeling, we investigated the short-term effect of cryopreservation and revealed that cryopreservation decreases the amount of saccharides in embryos and does not affect the activity of protein de novo synthesis.

Transmission and control strategies of antimicrobial resistance from the environment to the clinic: A holistic review

The environment serves as a significant reservoir of antimicrobial resistance (AMR) microbes and genes and is increasingly recognized as key source of clinical AMR. Modern human activities impose an additional burden on environmental AMR, promoting its transmission to clinical setting and posing a serious threat to human health and welfare. Therefore, a comprehensive review of AMR transmission from the environment to the clinic, along with proposed effective control strategies, is crucial. This review systematically summarized current research on the transmission of environmental AMR to clinical settings. Furthermore, the transmission pathways, horizontal gene transfer (HGT) mechanisms, as well as the influential drivers including triple planetary crisis that may facilitate AMR transfer from environmental species to clinical pathogens are highlighted. In response to the growing trend of AMR transmission, we propose insightful mitigation strategies under the One Health framework, integrating advanced surveillance and tracking technologies, interdisciplinary knowledge, multisectoral interventions, alongside multiple antimicrobial use and stewardship approaches to tacking development and spread of AMR.

Key active mercury methylating microorganisms and their synergistic effects on methylmercury production in paddy soils

Rice contamination with neurotoxic methylmercury (MeHg) from paddy soils is an escalating global concern. Identifying the microorganisms responsible for mercury (Hg) methylation in these soils is essential for controlling Hg contamination in the food chain and mitigating health impacts. Current research often focuses on total Hg-methylating microorganisms, overlooking the contributions of active ones, which can lead to either overestimating or neglecting the specific roles of microorganisms in Hg methylation within paddy soils. In this study, active Hg-methylating microorganisms in paddy soils were identified using a combination of DNA-SIP, Hg isotope labelling, and Hg methylation gene sequencing techniques. Our findings revealed that Geobacter and Anaerolinea are pivotal active Hg-methylating microorganisms across a contamination gradient in paddy soils. Transcriptomic analysis of soils from major rice-producing provinces in China confirmed the widespread and synergistic involvement of these microorganisms. Microbial incubation further validated their interaction significantly enhances Hg methylation, with Me198Hg concentrations increasing 2.8-fold compared to Geobacter alone and 5.2-fold compared to Anaerolinea alone. These findings enhance our understanding of microbial Hg methylation in paddy soils, providing critical insights for accurately predicting soil MeHg load, rice grain MeHg contamination, and human MeHg exposure risks.

Quinolone-mediated metabolic cross-feeding develops aluminium tolerance in soil microbial consortia

Aluminium (Al)-tolerant beneficial bacteria confer resistance to Al toxicity to crops in widely distributed acidic soils. However, the mechanism by which microbial consortia maintain Al tolerance under acid and Al toxicity stress remains unknown. Here, we demonstrate that a soil bacterial consortium composed of Rhodococcus erythropolis and Pseudomonas aeruginosa exhibit greater Al tolerance than either bacterium alone. P. aeruginosa releases the quorum sensing molecule 2-heptyl-1H-quinolin-4-one (HHQ), which is efficiently degraded by R. erythropolis. This degradation reduces population density limitations and further enhances the metabolic activity of P. aeruginosa under Al stress. Moreover, R. erythropolis converts HHQ into tryptophan, promoting the synthesis of peptidoglycan, a key component for cell wall stability, thereby improving the Al tolerance of R. erythropolis. This study reveals a metabolic cross-feeding mechanism that maintains microbial Al tolerance, offering insights for designing synthetic microbial consortia to sustain food security and sustainable agriculture in acidic soil regions.

Proteomic stable isotope probing with an upgraded Sipros algorithm for improved identification and quantification of isotopically labeled proteins

BACKGROUND

Proteomic stable isotope probing (SIP) is used in microbial ecology to trace a non-radioactive isotope from a labeled substrate into de novo synthesized proteins in specific populations that are actively assimilating and metabolizing the substrate in a complex microbial community. The Sipros algorithm is used in proteomic SIP to identify variably labeled proteins and quantify their isotopic enrichment levels (atom%) by performing enrichment-resolved database searching.

RESULTS

In this study, Sipros was upgraded to improve the labeled protein identification, isotopic enrichment quantification, and database searching speed. The new Sipros 4 was compared with the existing Sipros 3, Calisp, and MetaProSIP in terms of the number of identifications and the accuracy and precision of atom% quantification on both the peptide and protein levels using standard E. coli cultures with 1.07 atom%, 2 atom%, 5 atom%, 25 atom%, 50 atom%, and 99 atom% 13C enrichment. Sipros 4 outperformed Calisp and MetaProSIP across all samples, especially in samples with ≥ 5 atom% 13C labeling. The computational speed on Sipros 4 was > 20 times higher than Sipros 3 and was on par with the overall speed of Calisp- and MetaProSIP-based pipelines. Sipros 4 also demonstrated higher sensitivity for the detection of labeled proteins in two 13C-SIP experiments on a real-world soil community. The labeled proteins were used to trace 13C from 13C-methanol and 13C-labeled plant exudates to the consuming soil microorganisms and their newly synthesized proteins.

CONCLUSION

Overall, Sipros 4 improved the quality of the proteomic SIP results and reduced the computational cost of SIP database searching, which will make proteomic SIP more useful and accessible to the border community. Video Abstract.

Starting with screening strains to construct synthetic microbial communities (SynComs) for traditional food fermentation

With the elucidation of community structures and assembly mechanisms in various fermented foods, core communities that significantly influence or guide fermentation have been pinpointed and used for exogenous restructuring into synthetic microbial communities (SynComs). These SynComs simulate ecological systems or function as adjuncts or substitutes in starters, and their efficacy has been widely verified. However, screening and assembly are still the main limiting factors for implementing theoretic SynComs, as desired strains cannot be effectively obtained and integrated. To expand strain screening methods suitable for SynComs in food fermentation, this review summarizes the recent research trends in using SynComs to study community evolution or interaction and improve the quality of food fermentation, as well as the specific process of constructing synthetic communities. The potential for novel screening modalities based on genes, enzymes and metabolites in food microbial screening is discussed, along with the emphasis on strategies to optimize assembly for facilitating the development of synthetic communities.

Integrating Multiple Bacterial Phenotypes and Bayesian Network for Analyzing Health Risks of Pathogens in Plastisphere

Plastic pollution represents a critical threat to soil ecosystems and even humans, as plastics can serve as a habitat for breeding and refuging pathogenic microorganisms against stresses. However, evaluating the health risk of plastispheres is difficult due to the lack of risk factors and quantification model. Here, DNA sequencing, single-cell Raman-D2O labeling, and transformation assay were used to quantify key risk factors of plastisphere, including pathogen abundance, phenotypic resistance to various stresses (antibiotic and pesticide), and ability to acquire antibiotic resistance genes. A Bayesian network model was newly introduced to integrate these three factors and infer their causal relationships. Using this model, the risk of pathogen in the plastisphere is found to be nearly 3 magnitudes higher than that in free-living state. Furthermore, this model exhibits robustness for risk prediction, even in the absence of one factor. Our framework offers a novel and practical approach to assessing the health risk of plastispheres, contributing to the management of plastic-related threats to human health.

Sewage Sludge Promotes the Accumulation of Antibiotic Resistance Genes in Tomato Xylem

Xylem serves as a conduit linking soil to the aboveground plant parts and facilitating the upward movement of microbes into leaves and fruits. Despite this potential, the composition of the xylem microbiome and its associated risks, including antibiotic resistance, are understudied. Here, we cultivated tomatoes and analyzed their xylem sap to assess the microbiome and antibiotic resistance profiles following treatment with sewage sludge. Our findings show that xylem microbes primarily originate from soil, albeit with reduced diversity in comparison to those of their soil microbiomes. Using single-cell Raman spectroscopy coupled with D2O labeling, we detected significantly higher metabolic activity in xylem microbes than in rhizosphere soil, with 87% of xylem microbes active compared to just 36% in the soil. Additionally, xylem was pinpointed as a reservoir for antibiotic resistance genes (ARGs), with their abundance being 2.4-6.9 times higher than in rhizosphere soil. Sludge addition dramatically increased the abundance of ARGs in xylem and also increased their mobility and host pathogenicity. Xylem represents a distinct ecological niche for microbes and is a significant reservoir for ARGs. These results could be used to manage the resistome in crops and improve food safety.

Aerobic Anoxygenic Phototrophic Bacteria in the Marine Environments Revealed by Raman/Fluorescence-Guided Single-Cell Sorting and Targeted Metagenomics

Aerobic anoxygenic phototrophic bacteria (AAPB) contribute profoundly to the global carbon cycle. However, most AAPB in marine environments are uncultured and at low abundance, hampering the recognition of their functions and molecular mechanisms. In this study, we developed a new culture-independent method to identify and sort AAPB using single-cell Raman/fluorescence spectroscopy. Characteristic Raman and fluorescent bands specific to bacteriochlorophyll a (Bchl a) in AAPB were determined by comparing multiple known AAPB with non-AAPB isolates. Using these spectroscopic biomarkers, AAPB in coastal seawater, pelagic seawater, and hydrothermal sediment samples were screened, sorted, and sequenced. 16S rRNA gene analysis and functional gene annotations of sorted cells revealed novel AAPB members and functional genes, including one species belonging to the genus Sphingomonas, two genera affiliated to classes Betaproteobacteria and Gammaproteobacteria, and function genes bchCDIX, pucC2, and pufL related to Bchl a biosynthesis and photosynthetic reaction center assembly. Metagenome-assembled genomes (MAGs) of sorted cells from pelagic seawater and deep-sea hydrothermal sediment belonged to Erythrobacter sanguineus that was considered as an AAPB and genus Sphingomonas, respectively. Moreover, multiple photosynthesis-related genes were annotated in both MAGs, and comparative genomic analysis revealed several exclusive genes involved in amino acid and inorganic ion metabolism and transport. This study employed a new single-cell spectroscopy method to detect AAPB, not only broadening the taxonomic and genetic contents of AAPB in marine environments but also revealing their genetic mechanisms at the single-genomic level.

Raman spectroscopy-based microfluidic platforms: A promising tool for detection of foodborne pathogens in food products

Rapid and sensitive detection of foodborne pathogens in food products is paramount for ensuring food safety and public health. In the ongoing effort to tackle this issue, detection methods are continually researched and upgraded to achieve rapidity, sensitivity, portability, and cost-effectiveness. This review addresses the critical need for improved technique by focusing on Raman spectroscopy-based microfluidic platforms, which have shown potential in revolutionizing the field of foodborne pathogen analysis offering point-of-care diagnosis and multiplex detection. The key problem lies in the persistent threat of compromised food quality and public health due to inadequate pathogen detection. The review elucidates the various trapping strategies employed in a microfluidic platform, including optical trapping, electrical trapping, mechanical trapping, and acoustic trapping for the capture of microbial cells. Subsequently, the review delves into the key aspects of the application of microbial detection in food products, highlighting recent advances and challenges in the field. The integrated technique allows point-of-care application assessment, which is an attractive quality for in-line and real-time detection of foodborne pathogens. However, the application of the technique in food products is limited and requires further research to combat the complexity of the food matrix, reduced costs of production, and ensure real-time use for diverse pathogens. Ultimately, this review aims to propel advancements in microbial detection, thus promoting enhanced food safety through state-of-the-art technologies.

gcPathogen: a comprehensive genomic resource of human pathogens for public health

Here, we present the manually curated Global Catalogue of Pathogens (gcPathogen), an extensive genomic resource designed to facilitate rapid and accurate pathogen analysis, epidemiological exploration and monitoring of antibiotic resistance features and virulence factors. The catalogue seamlessly integrates and analyzes genomic data and associated metadata for human pathogens isolated from infected patients, animal hosts, food and the environment. The pathogen list is supported by evidence from medical or government pathogenic lists and publications. The current version of gcPathogen boasts an impressive collection of 1 164 974 assemblies comprising 986 044 strains from 497 bacterial taxa, 4794 assemblies encompassing 4319 strains from 265 fungal taxa, 89 965 assemblies featuring 13 687 strains from 222 viral taxa, and 646 assemblies including 387 strains from 159 parasitic taxa. Through this database, researchers gain access to a comprehensive 'one-stop shop' that facilitates global, long-term public health surveillance while enabling in-depth analysis of genomes, sequence types, antibiotic resistance genes, virulence factors and mobile genetic elements across different countries, diseases and hosts. To access and explore the data and statistics, an interactive web interface has been developed, which can be accessed at https://nmdc.cn/gcpathogen/. This user-friendly platform allows seamless querying and exploration of the extensive information housed within the gcPathogen database.

Environmental risks of antibiotic resistance genes released from biological laboratories and its control measure

Antibiotic resistance genes (ARGs) are a growing global threat to public health. Biological laboratory wastewater contains large amounts of free ARGs. It is important to assess the risk of free ARGs from biological laboratories and to find appropriate treatments to control their spread. The fate of plasmids in the environment and the effect of different thermal treatments on their persistence activity were tested. The results showed that untreated resistance plasmids could exist in water for more than 24 h (the special 245 bp fragment). Gel electrophoresis and transformation assays showed that the plasmids boiled for 20 min retained 3.65% ± 0.31% transformation activity of the intact plasmids, while autoclaving for 20 min at 121 °C could effectively degrade the plasmids and that NaCl, bovine serum albumin, and EDTA-2Na affected the degradation efficiency of the plasmids during boiling. In the simulated aquatic system, using 10⁶ copy/μL of plasmids after autoclaving, only 10² copies/μL of the fragment after only 1-2 h could be detected. By contrast, boiled plasmids for 20 min were still detectable after plunging them into water for 24 h. These findings suggest that untreated and boiled plasmids can remain in the aquatic environment for a certain time resulting in the risk of disseminating ARGs. However, autoclaving is an effective way of degrading waste free resistance plasmids.

Real-Time Intracellular Analysis of Kanamycin Using Microaptasensors

With the emergence of multidrug-resistant bacteria, infection-related death toll is on the rise. Overuse of antibiotics and their leakage into waterways have transformed the environment into a sink, resulting in bacterial resistance permeating through all tiers of the food cycle. As one of the primary sources of food, fish and fish products such as fish eggs must be studied for their ability to accumulate relevant antibiotics. While the accumulation of these pharmaceuticals has previously been studied, there remains a need to analyze these processes in real time. Electrochemical aptamer-based sensor technology allows for selective, real-time monitoring of small molecules. Herein, we report the first use of miniaturized electrochemical aptamer-based sensors for the analysis of the passive uptake of the aminoglycoside antibiotic, kanamycin, in single salmon eggs. We use pulled platinum microelectrodes and increase the surface area at the electrode tip through dendritic gold deposition. These electrodes showed a 100-fold increase in DNA immobilization on the electrode surface as compared to bare microelectrodes. Additionally, the sensors showed improved stability in complex biological media over an extended period of time when compared to the more widely used macrosensors (r = 1 mm). The sensor range was determined to extend from nanomolar to micromolar concentrations of kanamycin in fish egg lysate and when used in a single salmon egg the μ-aptasensors were able to monitor the passive uptake of kanamycin over time. The accumulation kinetics were simulated using COMSOL Multiphysics software. This research presents the first reported record of passive uptake of a small molecule in a single cell in real-time using electrochemistry.

Surface-enhanced Raman spectroscopy combined with stable isotope probing to assess the metabolic activity of Escherichia coli cells in chicken carcass wash water

Rapid evaluation of the metabolic activity of microorganisms is crucial in the assessment of the disinfection ability of various antimicrobial agents in the food industry. In this study, surface-enhanced Raman spectroscopy combined with isotope probing was employed for the analysis of the disinfection of single bacterial cells in the chicken carcass wash water. The Raman signals from single Escherichia coli O157:H7 cells were enhanced by in situ synthesis of silver nanoparticles. The ΔCD of the cells grown in presence of 0.5% hydrogen peroxide and 50 ppm chlorine was 5.86 ± 1.86% and 5.1 ± 2.3%, respectively, which showed significant reduction compared with cells grown in the absence of disinfecting agents (19.86 ± 2.51%) after 2 h of incubation. The study proved that the proposed method had the potential to assess the metabolic activity of microorganisms in other food products and optimize the disinfection process.

Active antibiotic resistome in soils unraveled by single-cell isotope probing and targeted metagenomics

Antimicrobial resistance (AMR) in soils represents a serious risk to human health through the food chain and human-nature contact. However, the active antibiotic-resistant bacteria (ARB) residing in soils that primarily drive AMR dissemination are poorly explored. Here, single-cell Raman-D₂O coupled with targeted metagenomics is developed as a culture-independent approach to phenotypically and genotypically profiling active ARB against clinical antibiotics in a wide range of soils. This method quantifies the prevalence (contamination degree) and activity (spread potential) of soil ARB and reveals a clear elevation with increasing anthropogenic activities such as farming and the creation of pollution, thereby constituting a factor that is critical for the assessment of AMR risks. Further targeted sorting and metagenomic sequencing of the most active soil ARB uncover several uncultured genera and a pathogenic strain. Furthermore, the underlying resistance genes, virulence factor genes, and associated mobile genetic elements (including plasmids, insertion sequences, and prophages) are fully deciphered at the single-cell level. This study advances our understanding of the soil active AMR repertoire by linking the resistant phenome to the genome. It will aid in the risk assessment of environmental AMR and guide the combat under the One Health framework.

Machine Learning-Based Determination of Sampling Depth for Complex Environmental Systems: Case Study with Single-Cell Raman Spectroscopy Data in EBPR Systems

Rapid progress in various advanced analytical methods, such as single-cell technologies, enable unprecedented and deeper understanding of microbial ecology beyond the resolution of conventional approaches. A major application challenge exists in the determination of sufficient sample size without sufficient prior knowledge of the community complexity and, the need to balance between statistical power and limited time or resources. This hinders the desired standardization and wider application of these technologies. Here, we proposed, tested and validated a computational sampling size assessment protocol taking advantage of a metric, named kernel divergence. This metric has two advantages: First, it directly compares data set-wise distributional differences with no requirements on human intervention or prior knowledge-based preclassification. Second, minimal assumptions in distribution and sample space are made in data processing to enhance its application domain. This enables test-verified appropriate handling of data sets with both linear and nonlinear relationships. The model was then validated in a case study with Single-cell Raman Spectroscopy (SCRS) phenotyping data sets from eight different enhanced biological phosphorus removal (EBPR) activated sludge communities located across North America. The model allows the determination of sufficient sampling size for any targeted or customized information capture capacity or resolution level. Promised by its flexibility and minimal restriction of input data types, the proposed method is expected to be a standardized approach for sampling size optimization, enabling more comparable and reproducible experiments and analysis on complex environmental samples. Finally, these advantages enable the extension of the capability to other single-cell technologies or environmental applications with data sets exhibiting continuous features.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Single-cell sorting of microalgae and identification of optimal conditions by using response surface methodology coupled with life-cycle approaches

Response surface methodology (RSM) has been widely used to identify optimal conditions for environmental microorganisms to maximize degrading pollutants and accumulating biomass. However, to date, environmental impact and economic cost have rarely been considered. In this study, a single cell of microalgae Chlorella sorokiniana ZM-5 was sorted, and its enrichment was carried out for the first time. The optimized conditions by RSM for achieving the highest COD, TN, TP removal and 352.61 mg/g lipid production were 24 h light time, 4.3:1C/N, 7.2 pH, and 30 °C temperature, respectively. Life-cycle approaches were then carried out upon this illustrative case, and the results indicated that the implementation of the above optimal conditions could reduce the total environmental impact by 48.0% and the total economic impact by 10.2%. This study showed the feasibility of applying life-cycle approaches to examine the optimal conditions of a biological process in terms of minimizing environmental impact and economic costs.

Assessing the effect of different pH maintenance situations on bacterial SERS spectra

Phenotyping of bacteria with vibrational spectroscopy has caught much attention in bacteria-related research. It is known that many factors could affect this process. Among them, solution pH maintenance is crucial, yet its impact on the bacterial SERS spectra is surprisingly neglected. In this work, we focused on two situations related to pH maintenance: the effect of the same buffer on the SERS spectra of bacteria under different pH values, and the influence of different buffers on the SERS spectra of bacteria under the same pH value. Specifically, Britton-Robison (BR) buffer was used to evaluate the effect of pH value on bacteria SERS spectra thanks to its wide pH range. Four different buffers, namely BR buffer, acetate buffer, phosphate buffer, and carbonate buffer, were used to illustrate the impact of buffer types on SERS spectra of bacteria. The results showed that the intensity and number of characteristic peaks of the SERS spectra of Gram-negative (G -) bacteria changed more significantly than Gram-positive (G +) bacteria with the change of pH value. Furthermore, compared with phosphate buffer and carbonate buffer, BR buffer could bring more characteristic SERS bands with better reproducibility, but slightly inferior to acetate buffer. In conclusion, the influence of the pH and types of the buffer on the SERS spectra of bacteria are worthy of further discussion.

The Impact of the Antibiotic Fosfomycin on Wastewater Communities Measured by Flow Cytometry

Fosfomycin is a re-emergent antibiotic known to be effective against severe bacterial infections even when other antibiotics fail. To avoid overuse and thus the risk of new antibiotic resistance, the European Commission has recommended the intravenous use of fosfomycin only when other antibiotic treatments fail. A release of fosfomycin into the environment via wastewater from not only municipalities but also already from the producing pharmaceutical industry can seriously undermine a sustaining therapeutic value. We showed in long-term continuous-mode bioreactor cultivation and by using microbial community flow cytometry, microbial community ecology tools, and cell sorting that the micro-pollutant altered the bacterial wastewater community (WWC) composition within only a few generations. Under these conditions, fosfomycin was not readily degraded both at lower and higher concentrations. At the same time, operational reactor parameters and typical diversity parameters such as α- and intracommunity β-diversity did not point to system changes. Nevertheless, an intrinsic compositional change occurred, caused by a turnover process in which higher concentrations of fosfomycin selected for organisms known to frequently harbor antibiotic resistance genes. A gfp-labeled Pseudomonas putida strain, used as the model organism and a possible future chassis for fosfomycin degradation pathways, was augmented and outcompeted in all tested situations. The results suggest that WWCs, as complex communities, may tolerate fosfomycin for a time, but selection for cell types that may develop resistance is very likely. The approach presented allows very rapid assessment and visualization of the impact of antibiotics on natural or managed microbial communities in general and on individual members of these communities in particular.

Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing

Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.