In situ identification of environmental microorganisms with Raman spectroscopy

Raman-AFM-fluorescence-guided impact of linoleic and eicosapentaenoic acids on subcellular structure and chemical composition of normal and cancer human colon cells

The regular overconsumption of high-energy food (rich in lipids and sugars) results in elevated nutrient absorption in intestine and consequently excessive accumulation of lipids in many organs e.g.: liver, adipose tissue, muscles. In the long term this can lead to obesity and obesity-associated diseases e.g. type 2 diabetes, non-alcoholic fatty liver disease, cardiovascular disease, inflammatory bowel disease (IBD). In the presented paper based on RI data we have proved that Raman maps can be used successfully for subcellular structures visualization and analysis of fatty acids impact on morphology and chemical composition of human colon single cells - normal and cancer. Based on Raman data we have investigated the changes related to endoplasmic reticulum, mitochondria, lipid droplets and nucleus. Analysis of ratios calculated based on Raman bands typical for proteins (1256, 1656 cm-1), lipids (1304, 1444 cm-1) and nucleic acids (750 cm-1) has confirmed for endoplasmic reticulum the increased activity of this organelle in lipoproteins synthesis upon FAs supplementation; for LDs the changes of desaturation of accumulated lipids with the highest unsaturation level for CaCo-2 cells upon EPA supplementation; for mitochondria the stronger effect of FAs supplementation was observed for CaCo-2 cells confirming the increased activity of this organelle responsible for energy production necessary for tumor development; the weakest impact of FAs supplementation was observed for nucleus for both types of cells and both types of acids. Fluorescence imaging was used for the investigations of changes in LDs/ER morphology. Our measurements have shown the increased area of LDs/ER for CaCo-2 cancer cells, and the strongest effect was noticed for CaCo-2 cells upon EPA supplementation. The increased participation of lipid structures for all types of cells upon FAs supplementation has been confirmed also by AFM studies. The lowest YM values have been observed for CaCo-2 cells including samples treated with FAs.

Application of single-cell Raman-deuterium isotope probing to reveal the resistance of marine ammonia-oxidizing archaea SCM1 against common antibiotics

Antimicrobial resistance (AMR) in oceans poses a significant threat to human health through the seafood supply chain. Ammonia-oxidizing archaea (AOA) are important marine microorganisms and play a key role in the biogeochemical nitrogen cycle around the world. However, the AMR of marine AOA to aquicultural antibiotics is poorly explored. Here, Raman-deuterium isotope probing (Raman-DIP), a single-cell tool, was developed to reveal the AMR of a typical marine species of AOA, Nitrosopumilus maritimus (designated SCM1), against six antibiotics, including erythromycin, tetracycline, novobiocin, neomycin, bacitracin, and vancomycin. The D2O concentration (30% v/v) and culture period (9 days) were optimized for the precise detection of metabolic activity in SCM1 cells through Raman-DIP. The relative metabolic activity of SCM1 upon exposure to antibiotics was semi-quantitatively calculated based on single-cell Raman spectra. SCM1 exhibited high resistance to erythromycin, tetracycline, novobiocin, neomycin, and vancomycin, with minimum inhibitory concentration (MIC) values between 100 and 400 mg/L, while SCM1 is very sensitive to bacitracin (MIC: 0.8 mg/L). Notably, SCM1 cells were completely inactive under the metabolic activity minimum inhibitory concentration conditions (MA-MIC: 1.6-800 mg/L) for the six antibiotics. Further genomic analysis revealed the antibiotic resistance genes (ARGs) of SCM1, including 14 types categorized into 33 subtypes. This work increases our knowledge of the AMR of marine AOA by linking the resistant phenome to the genome, contributing to the risk assessment of AMR in the underexplored ocean environment. As antibiotic resistance in marine microorganisms is significantly affected by the concentration of antibiotics in coastal environments, we encourage more studies concentrating on both the phenotypic and genotypic antibiotic resistance of marine archaea. This may facilitate a comprehensive evaluation of the capacity of marine microorganisms to spread AMR and the implementation of suitable control measures to protect environmental safety and human health.

Research progress of microfluidics-based food safety detection

High demands for food safety detection and analysis have been advocated with people's increasing living standards. Even though numerous analytical testing techniques have been proposed, their widespread adoption is still constrained by the high limit of detection, narrow detection ranges, and high implementation costs. Due to their advantages, such as reduced sample and reagent consumption, high sensitivity, automation, low cost, and portability, using microfluidic devices for food safety monitoring has generated significant interest. This review provides a comprehensive overview of the latest microfluidic detection platforms (published in recent 4 years) and their applications in food safety, aiming to provide references for developing efficient research strategies for food contaminant detection and facilitating the transition of these platforms from laboratory research to practical field use.

Research progress in isolation and identification of rumen probiotics

With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.

Examining Sound, Light, and Vibrations as Tools to Manage Microbes and Support Holobionts, Ecosystems, and Technologies

The vast array of interconnected microorganisms across Earth's ecosystems and within holobionts has been called the "Internet of Microbes." Bacteria and archaea are masters of energy and information collection, storage, transformation, and dissemination using both "wired" and wireless (at a distance) functions. Specific tools affecting microbial energy and information functions offer effective strategies for managing microbial populations within, between, and beyond holobionts. This narrative review focuses on microbial management using a subset of physical modifiers of microbes: sound and light (as well as related vibrations). These are examined as follows: (1) as tools for managing microbial populations, (2) as tools to support new technologies, (3) as tools for healing humans and other holobionts, and (4) as potential safety dangers for microbial populations and their holobionts. Given microbial sensitivity to sound, light, and vibrations, it is critical that we assign a higher priority to the effects of these physical factors on microbial populations and microbe-laden holobionts. We conclude that specific sound, light, and/or vibrational conditions are significant therapeutic tools that can help support useful microbial populations and help to address the ongoing challenges of holobiont disease. We also caution that inappropriate sound, light, and/or vibration exposure can represent significant hazards that require greater recognition.

Assessment of Drug Activities against Giardia Using Hyperspectral Raman Microscopy

This study demonstrates the capability of Raman microscopy for detecting structural differences in Giardia cells exposed to different drugs and incubation times. While metronidazole (MTZ) visibly affects the cells by inducing extracellular vesicle releases of toxic iron intermediates and modified triple-bond moieties, oseltamivir (OSM) alters the phenylalanine and lipid structures. Modifications in the heme protein environment and the transformation of iron from ferric to ferrous observed for both drug treatments are more notable for MTZ. Different contents and amounts of vesicle excretion are detected for 24 h or 48 h with MTZ incubation. At a shorter drug exposure, releases of altered proteins, glycogen, and phospholipids dominate. Agglomerates of transformed iron complexes from heme proteins and multiple-bond moieties prevail at 48 h of treatment. No such vesicle releases are present in the case of OSM usage. Drug incorporations into the cells and their impact on the plasma membrane and the dynamics of lipid raft confirmed by confocal fluorescence microscopy reveal a more destructive extent by OSM, corroborating the Raman results. Raman microscopy provides a broader understanding of the multifaceted factors and mechanisms responsible for giardiasis treatment or drug resistance by enabling a label-free, simultaneous monitoring of structural changes at the cellular and molecular levels.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Rapid detection of six Oceanobacillus species in Daqu starter using single-cell Raman spectroscopy combined with machine learning

Many traditional fermented foods and beverages industries around the world request the addition of multi-species starter cultures. However, the microbial community in starter cultures is subject to fluctuations due to their exposure to an open environment during fermentation. A rapid detection approach to identify the microbial composition of starter culture is essential to ensure the quality of the final products. Here, we applied single-cell Raman spectroscopy (SCRS) combined with machine learning to monitor Oceanobacillus species in Daqu starter, which plays crucial roles in the process of Chinese baijiu. First, a total of six Oceanobacillus species (O. caeni, O. kimchii, O. iheyensis, O. sojae, O. oncorhynchi subsp. Oncorhynchi and O. profundus) were detected in 44 Daqu samples by amplicon sequencing and isolated by pure culture. Then, we created a reference database of these Oceanobacillus strains which correlated their taxonomic data and single-cell Raman spectra (SCRS). Based on the SCRS dataset, five machine-learning algorithms were used to classify Oceanobacillus strains, among which support vector machine (SVM) showed the highest rate of accuracy. For validation of SVM-based model, we employed a synthetic microbial community composed of varying proportions of Oceanobacillus species and demonstrated a remarkable accuracy, with a mean error was less than 1% between the predicted result and the expected value. The relative abundance of six different Oceanobacillus species during Daqu fermentation was predicted within 60 min using this method, and the reliability of the method was proved by correlating the Raman spectrum with the amplicon sequencing profiles by partial least squares regression. Our study provides a rapid, non-destructive and label-free approach for rapid identification of Oceanobacillus species in Daqu starter culture, contributing to real-time monitoring of fermentation process and ensuring high-quality products.

Pilot SERS Monitoring Study of Two Natural Hypersaline Lake Waters from a Balneary Resort during Winter-Months Period

Water samples from two naturally hypersaline lakes, renowned for their balneotherapeutic properties, were investigated through a pilot SERS monitoring program. Nanotechnology-based techniques were employed to periodically measure the ultra-sensitive SERS molecular characteristics of the raw water-bearing microbial community and the inorganic content. Employing the Pearson correlation coefficient revealed a robust linear relationship between electrical conductivity and pH and Raman and SERS spectral data of water samples, highlighting the interplay complexity of Raman/SERS signals and physicochemical parameters within each lake. The SERS data obtained from raw waters with AgNPs exhibited a dominant, reproducible SERS feature resembling adsorbed β-carotene at submicromole concentration, which could be related to the cyanobacteria-AgNPs interface and supported by TEM analyses. Notably, spurious SERS sampling cases showed molecular traces attributed to additional metabolites, suggesting multiplexed SERS signatures. The conducted PCA demonstrated observable differences in the β-carotene SERS band intensities between the two lakes, signifying potential variations in picoplankton abundance and composition or environmental influences. Moreover, the study examined variations in the SERS intensity ratio I245/I1512, related to the balance between inorganic (Cl--induced AgNPs aggregation) and organic (cyanobacteria population) balance, in correlation with the electrical conductivity. These findings signify the potential of SERS data for monitoring variations in microorganism concentration, clearly dependent on ion concentration and nutrient dynamics in raw, hypersaline water bodies.

The neglected ammonia leaching calcium in anaerobic granular sludge

Previous researches have primarily emphasized the deleterious impacts of NH4+ on anaerobic granular sludge due to its biotoxicity. Despite this, the role of NH4+ as a monovalent cation in leaching multivalent Ca2+, thereby hindering granule formation and undermining its stability, remains underappreciated. This study investigated the potential of NH4+ to leach Ca2+ from anaerobic granular sludges. The results indicated that a shock loading of NH4+ at a concentration of 900 mg/L caused a Ca2+ leaching of 57.1 mg/L at pH 7.0. In an acidified environment (pH 5.0), the shock loading resulted in a Ca2+ release of 127.3 mg/L, a magnitude 5.24 times greater than the control group. The leaching process modestly affected granular sludge activity and size but markedly compromised granular strength due to calcium loss. Subsequent to the NH4+ shock, the granular strength manifested a significant reduction, as evidenced by a 15-fold increase in protein release from the granules compared to the intact ones. Additionally, NH4+ shock altered the calcium partitioning within the granular sludge, resulting in a decrease in residual calcium and a concomitant increase in bound calcium, further affecting granular strength. This study underscores the overlooked significant phenomenon of NH4+ shock-leaching Ca2+ in anaerobic granular sludge, which warrants significant attention given to its rapid and deleterious effects on granular strength and the shift in calcium state.

Recent advances in enrichment, isolation, and bio-electrochemical activity evaluation of exoelectrogenic microorganisms

Exoelectrogenic microorganisms (EEMs) catalyzed the conversion of chemical energy to electrical energy via extracellular electron transfer (EET) mechanisms, which underlay diverse bio-electrochemical systems (BES) applications in clean energy development, environment and health monitoring, wearable/implantable devices powering, and sustainable chemicals production, thereby attracting increasing attentions from academic and industrial communities in the recent decades. However, knowledge of EEMs is still in its infancy as only ~100 EEMs of bacteria, archaea, and eukaryotes have been identified, motivating the screening and capture of new EEMs. This review presents a systematic summarization on EEM screening technologies in terms of enrichment, isolation, and bio-electrochemical activity evaluation. We first generalize the distribution characteristics of known EEMs, which provide a basis for EEM screening. Then, we summarize EET mechanisms and the principles underlying various technological approaches to the enrichment, isolation, and bio-electrochemical activity of EEMs, in which a comprehensive analysis of the applicability, accuracy, and efficiency of each technology is reviewed. Finally, we provide a future perspective on EEM screening and bio-electrochemical activity evaluation by focusing on (i) novel EET mechanisms for developing the next-generation EEM screening technologies, and (ii) integration of meta-omics approaches and bioinformatics analyses to explore nonculturable EEMs. This review promotes the development of advanced technologies to capture new EEMs.

Comparative Analysis Using Raman Spectroscopy of the Cellular Constituents of Lacticaseibacillus paracasei Zhang in a Normal and Viable but Nonculturable State

This study aimed to investigate the molecular composition of a viable but nonculturable (VBNC) state of a probiotic strain, Lacticaseibacillus paracasei Zhang (L. paracasei Zhang), using single-cell Raman spectroscopy (SCRS). Fluorescent microcopy with live/dead cell staining (propidium iodide and SYTO 9), plate counting, and scanning electron microscopy were used in combination to observe bacteria in an induced VBNC state. We induced the VBNC state by incubating the cells in de Man, Rogosa, and Sharpe broth (MRS) at 4 °C. Cells were sampled for subsequent analyses before VBNC induction, during it, and up to 220 days afterwards. We found that, after cold incubation for 220 days, the viable plate count was zero, but active cells could still be observed (as green fluorescent cells) under a fluorescence microscope, indicating that Lacticaseibacillus paracasei Zhang entered the VBNC state under these conditions. Scanning electron microscopy revealed the altered ultra-morphology of the VBNC cells, characterized by a shortened cell length and a wrinkled cell surface. Principal component analysis of the Raman spectra profiles revealed obvious differences in the intracellular biochemical constituents between normal and VBNC cells. Comparative analysis of the Raman spectra identified 12 main differential peaks between normal and VBNC cells, corresponding to carbohydrates, lipids, nucleic acids, and proteins. Our results suggested that there were obvious cellular structural intracellular macromolecular differences between normal and VBNC cells. During the induction of the VBNC state, the relative contents of carbohydrates (such as fructose), saturated fatty acids (such as palmitic acid), nucleic acid constituents, and some amino acids changed obviously, which could constitute a bacterial adaptive mechanism against adverse environmental conditions. Our study provides a theoretical basis for revealing the formation mechanism of a VBNC state in lactic acid bacteria.

Monitoring of microbial proteome dynamics using Raman stable isotope probing

Abnormal protein kinetics could be a cause of several diseases associated with essential life processes. An accurate understanding of protein dynamics and turnover is essential for developing diagnostic or therapeutic tools to monitor these changes. Raman spectroscopy in combination with stable isotope probes (SIP) such as carbon-13, and deuterium has been a breakthrough in the qualitative and quantitative study of various metabolites. In this work, we are reporting the utility of Raman-SIP for monitoring dynamic changes in the proteome at the community level. We have used ¹³ C-labeled glucose as the only carbon source in the medium and verified its incorporation in the microbial biomass in a time-dependent manner. A visible redshift in the Raman spectral vibrations of major biomolecules such as nucleic acids, phenylalanine, tyrosine, amide I, and amide III were observed. Temporal changes in the intensity of these bands demonstrating the feasibility of protein turnover monitoring were also verified. Kanamycin, a protein synthesis inhibitor was used to assess the feasibility of identifying effects on protein turnover in the cells. Successful application of this work can provide an alternate/adjunct tool for monitoring proteome-level changes in an objective and nondestructive manner.

Current Perspectives on Viable but Non-Culturable Foodborne Pathogenic Bacteria: A Review

Foodborne diseases caused by foodborne pathogens pose risks to food safety. Effective detection and efficient inactivation of pathogenic bacteria has always been a research hotspot in the field of food safety. Complicating these goals, bacteria can be induced to adopt a viable but non-culturable (VBNC) state under adverse external environmental stresses. When in the VBNC state, pathogens cannot form visible colonies during traditional culture but remain metabolically active and toxic. The resulting false negative results in growth-related assays can jeopardize food safety. This review summarizes the latest research on VBNC foodborne pathogens, including induction conditions, detection methods, mechanism of VBNC formation, and possible control strategies. It is hoped that this review can provide ideas and methods for future research on VBNC foodborne pathogenic bacteria.

Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning

Rapid, accurate, and label-free detection of pathogenic bacteria and antibiotic resistance at single-cell resolution is a technological challenge for clinical diagnosis. Overcoming the cumbersome culture process of pathogenic bacteria and time-consuming antibiotic susceptibility assays will significantly benefit early diagnosis and optimize the use of antibiotics in clinics. Raman spectroscopy can collect molecular fingerprints of pathogenic bacteria in a label-free and culture-independent manner, which is suitable for pathogen diagnosis at single-cell resolution. Here, we report a method based on Raman spectroscopy combined with machine learning to rapidly and accurately identify pathogenic bacteria and detect antibiotic resistance at single-cell resolution. Our results show that the average accuracy of identification of 12 species of common pathogenic bacteria by the machine learning method is 90.73 ± 9.72%. Antibiotic-sensitive and antibiotic-resistant strains of Acinetobacter baumannii isolated from hospital patients were distinguished with 99.92 ± 0.06% accuracy using the machine learning model. Meanwhile, we found that sensitive strains had a higher nucleic acid/protein ratio and antibiotic-resistant strains possessed abundant amide II structures in proteins. This study suggests that Raman spectroscopy is a promising method for rapidly identifying pathogens and detecting their antibiotic susceptibility.