Shining light on the microbial world the application of Raman microspectroscopy

Unlocking the potential of biofilm-forming plant growth-promoting rhizobacteria for growth and yield enhancement in wheat (Triticum aestivum L.)

Plant growth-promoting rhizobacteria (PGPR) boost crop yields and reduce environmental pressures through biofilm formation in natural climates. Recently, biofilm-based root colonization by these microorganisms has emerged as a promising strategy for agricultural enhancement. The current work aims to characterize biofilm-forming rhizobacteria for wheat growth and yield enhancement. For this, native rhizobacteria were isolated from the wheat rhizosphere and ten isolates were characterized for plant growth promoting traits and biofilm production under axenic conditions. Among these ten isolates, five were identified as potential biofilm-producing PGPR based on in vitro assays for plant growth-promoting traits. These were further evaluated under controlled and field conditions for their impact on wheat growth and yield attributes. Surface-enhanced Raman spectroscopy analysis further indicated that the biochemical composition of the biofilm produced by the selected bacterial strains includes proteins, carbohydrates, lipids, amino acids, and nucleic acids (DNA/RNA). Inoculated plants in growth chamber resulted in larger roots, shoots, and increase in fresh biomass than controls. Similarly, significant increases in plant height (13.3, 16.7%), grain yield (29.6, 17.5%), number of tillers (18.7, 34.8%), nitrogen content (58.8, 48.1%), and phosphorus content (63.0, 51.0%) in grains were observed in both pot and field trials, respectively. The two most promising biofilm-producing isolates were identified through 16 s rRNA partial gene sequencing as Brucella sp. (BF10), Lysinibacillus macroides (BF15). Moreover, leaf pigmentation and relative water contents were significantly increased in all treated plants. Taken together, our results revealed that biofilm forming PGPR can boost crop productivity by enhancing growth and physiological responses and thus aid in sustainable agriculture.

Raman cell sorting for single-cell research

Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research. Raman cell sorting technology has garnered attention owing to its non-labeling, non-destructive detection features and the capability to analyze samples containing water. In addition, this technology can provide live cells for subsequent genomics analysis and gene sequencing. This paper emphasizes the importance of single-cell research, describes the single-cell research methods that currently exist, including single-cell manipulation and single-cell identification techniques, and highlights the advantages of Raman spectroscopy in the field of single-cell analysis by comparing it with the fluorescence-activated cell sorting (FACS) technique. It describes various existing Raman cell sorting techniques and introduces their respective advantages and disadvantages. The above techniques were compared and analyzed, considering a variety of factors. The current bottlenecks include weak single-cell spontaneous Raman signals and the requirement for a prolonged total cell exposure time, significantly constraining Raman cell sorting technology's detection speed, efficiency, and throughput. This paper provides an overview of current methods for enhancing weak spontaneous Raman signals and their associated advantages and disadvantages. Finally, the paper outlines the detailed information related to the Raman cell sorting technology mentioned in this paper and discusses the development trends and direction of Raman cell sorting.

Antimicrobial Activity and Mechanisms of Punicalagin against Vibrio parahaemolyticus

This study sought to explore the antimicrobial activity of punicalagin against V. parahaemolyticus and its potential modes of action. V. parahaemolyticus ATCC 17802 and RIMD 2210633Sm were exposed to punicalagin, and the energy production, membrane potential, and envelope permeability, as well as the interaction with cell biomolecules, were measured using a variety of fluorescent probes combined with electrophoresis and Raman spectroscopy. Punicalagin treatment disrupted the envelope integrity and induced a decrease in intracellular ATP and pH. The uptake of 1-N-phenyl-naphtylamine (NPN) demonstrated that punicalagin weakened the outer membrane. Punicalagin damaged the cytoplasmic membrane, as indicated by the membrane depolarization and the leakage of intracellular potassium ions, proteins, and nucleic acids. Electronic microscopy observation visualized the cell damage caused by punicalagin. Further, gel electrophoresis coupled with the Raman spectrum assay revealed that punicalagin affected the protein expression of V. parahaemolyticus, and there was no effect on the integrity of genomic DNA. Therefore, the cell envelope and proteins of V. parahaemolyticus were the assailable targets of punicalagin treatment. These findings suggested that punicalagin may be promising as a natural bacteriostatic agent to control the growth of V. parahaemolyticus.

Correlation analysis between Raman spectral signature and transcriptomic features of carbapenem-resistant Klebsiella pneumoniae

The Raman microspectroscopy technology has been successfully applied to evaluate the molecular composition of living cells for identifying cell types and states, but the rationale behind it was not well investigated. In this study, we acquired single-cell Raman spectra (SCRS) of three Klebsiella pneumoniae (K. pneumoniae) strains with different Carbapenem resistant mechanisms and analyzed them with machine learning algorithm. Two carbapenem resistant Klebsiella pneumoniae (CRKP) strains can be successfully distinguished from susceptible strain and CRKP with KPC or IMP carbapenemases can be classified with an overall accuracy achieving 100 %. Furthermore, we performed a correlation analysis between transcriptome and Raman spectra, and found that Raman shifts such as 752 and 1039 cm-1 highly correlated with drug resistance genes expression and could be regarded as Raman biomarkers for CRKP with different mechanisms. The findings of the study provide a theoretical basis for identifying the relationship between Raman spectra and transcriptome of bacteria, as well as a novel method for rapid identification of CRKP and their carbapenemases types.

Use of in vivo Raman spectroscopy and cryoablation for diagnosis and treatment of bladder cancer

Transurethral resection of bladder tumor (TURBT) is the first-line treatment option for non-muscle invasive bladder cancer (NMIBC), but residual tumor often remains after TURBT, thereby leading to cancer recurrence. Here, we introduce combined use of in vivo Raman spectroscopy and in vivo cryoablation as a new approach to detect and remove residual bladder tumor during TURBT. Bladder cancer (BCa) patients treated with TURBT at our urological department between Dec 2019 and Jan 2021 were collected. First, Raman signals were collected from 74 BCa patients to build reference spectra of normal bladder tissue and of bladder cancers of different pathological types. Then, another 53 BCa patients were randomly categorized into two groups, 26 patients accepted traditional TURBT, 27 patients accepted TURBT followed by Raman scanning and cryoablation if Raman detected existence of residual tumor. The recurrence rates of the two groups until Oct 2022 were compared. Raman was capable of discriminating normal bladder tissue and BCa with a sensitivity and specificity of 90.5% and 80.8 %; and discriminating invasive (T1, T2) and noninvasive (Ta) BCa with a sensitivity and specificity of 83.3 % and 87.3 %. During follow-up, 2 in 27 patients had cancer recurrence in Raman-Cryoablation group, while 8 in 26 patients had cancer recurrence in traditional TURBT group. Combined use of Raman and cryoablation significantly reduced cancer recurrence (p = 0.0394). Raman and cryoablation can serve as an adjuvant therapy to TURBT to improve therapeutic effects and reduce recurrence rate.

Bioaerosols in the atmosphere: A comprehensive review on detection methods, concentration and influencing factors

In the past few decades, especially since the outbreak of the coronavirus disease (COVID-19), the effects of atmospheric bioaerosols on human health, the environment, and climate have received great attention. To evaluate the impacts of bioaerosols quantitatively, it is crucial to determine the types of bioaerosols in the atmosphere and their spatial-temporal distribution. We provide a concise summary of the online and offline observation strategies employed by the global research community to sample and analyze atmospheric bioaerosols. In addition, the quantitative distribution of bioaerosols is described by considering the atmospheric bioaerosols concentrations at various time scales (daily and seasonal changes, for example), under various weather, and different underlying surfaces. Finally, a comprehensive summary of the reasons for the spatiotemporal distribution of bioaerosols is discussed, including differences in emission sources, the impact process of meteorological factors and environmental factors. This review of information on the latest research progress contributes to the emergence of further observation strategies that determine the quantitative dynamics of public health and ecological effects of bioaerosols.

Surface-enhanced Raman spectroscopy for the characterization of bacterial pellets of Staphylococcus aureus infected by bacteriophage

Drug-resistant pathogenic bacteria are a major cause of infectious diseases in the world and they have become a major threat through the reduced efficacy of developed antibiotics. This issue can be addressed by using bacteriophages, which can kill lethal bacteria and prevent them from causing infections. Surface-enhanced Raman spectroscopy (SERS) is a promising technique for studying the degradation of infectious bacteria by the interaction of bacteriophages to break the vicious cycle of drug-resistant bacteria and help to develop chemotherapy-independent remedial strategies. The phage (viruses)-sensitive Staphylococcus aureus (S. aureus) bacteria are exposed to bacteriophages (Siphoviridae family) in the time frame from 0 min (control) to 50 minutes with intervals of 5 minutes and characterized by SERS using silver nanoparticles as SERS substrate. This allows us to explore the effects of the bacteriophages against lethal bacteria (S. aureus) at different time intervals. The differentiating SERS bands are observed at 575 (C-C skeletal mode), 620 (phenylalanine), 649 (tyrosine, guanine (ring breathing)), 657 (guanine (COO deformation)), 728-735 (adenine, glycosidic ring mode), 796 (tyrosine (C-N stretching)), 957 (C-N stretching (amide lipopolysaccharides)), 1096 (PO2 (nucleic acid)), 1113 (phenylalanine), 1249 (CH2 of amide III, N-H bending and C-O stretching (amide III)), 1273 (CH2, N-H, C-N, amide III), 1331 (C-N stretching mode of adenine), 1373 (in nucleic acids (ring breathing modes of the DNA/RNA bases)) and 1454 cm-1 (CH2 deformation of saturated lipids), indicating the degradation of bacteria and replication of bacteriophages. Multivariate data analysis was performed by employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to study the biochemical differences in the S. aureus bacteria infected by the bacteriophage. The SERS spectral data sets were successfully differentiated by PLS-DA with 94.47% sensitivity, 98.61% specificity, 94.44% precision, 98.88% accuracy and 81.06% area under the curve (AUC), which shows that at 50 min interval S. aureus bacteria is degraded by the replicating bacteriophages.

Single-cell phenotypes revealed as a key biomarker in bacterial-fungal interactions: a case study of Staphylococcus and Malassezia

IMPORTANCE

Evaluating bacterial-fungal interactions is important for understanding ecological functions in a natural habitat. Many studies have defined bacterial-fungal interactions according to changes in growth rates when co-cultivated. However, the current literature lacks detailed studies on phenotypic changes in single cells associated with transcriptomic profiles to understand the bacterial-fungal interactions. In our study, we measured the single-cell phenotypes of bacteria co-cultivated with fungi using Raman spectroscopy with its transcriptomic profiles and determined the consequence of these interactions in detail. This rapid and reliable phenotyping approach has the potential to provide new insights regarding bacterial-fungal interactions.

Microbial persisters and host: recent advances and future perspectives

Microbial persisters are defined as the tiny sub-population of microorganisms that develop intrinsic strategies for survival with high tolerance to various antimicrobials. Currently, persister research remains in its infancy, and it is indeed a great challenge to precisely distinguish persister cells from other drug tolerant ones. Notably, the existence of persisters crucially contributes to prolonged antibiotic exposure time and treatment failure, yet there is the formation of antibiotic-resistant mutants. Further understanding on persisters is of profound importance for effective prevention and control of chronic infections/inflammation. The past two decades have witnessed rapid advances on the science, technologies and methodologies for persister investigations, along with deep knowledge about persisters and numerous anti-persister approaches developed. Whereas, various critical issues remain unsolved, such as what are the potential interaction profiles of persisters and host cells, and how to apply what we know about persisters to translational studies and clinical practice. Importantly, it is highly essential to better understand the multifaceted and complex cross-talk of microbial persisters with the host to develop novel tackling strategies for precision healthcare in the near future.

Antimicrobial Resistance Studies Using Raman Spectroscopy on Clinically Relevant Bacterial Strains

There has been a steep rise in the emergence of antibiotic-resistant bacteria in the past few years. A timely diagnosis can help in initiating appropriate antibiotic therapy. However, conventional techniques for diagnosing antibiotic resistance are time-consuming and labor-intensive. Therefore, we investigated the potential of Raman spectroscopy as a rapid surveillance technology for tracking the emergence of antibiotic resistance. In this study, we used Raman spectroscopy to differentiate clinical isolates of antibiotic-resistant and -sensitive bacteria of Escherichia coli, Acinetobacter baumannii, and Enterobacter species. The spectra were collected with or without exposure to various antibiotics (ciprofloxacin, gentamicin, meropenem, and nitrofurantoin), each having a distinct mechanism of action. Ciprofloxacin- and meropenem-treated sensitive strains showed a decrease in the intensity of Raman bands associated with DNA (667, 724, 785, 1378, 1480, and 1575 cm^-1) and proteins (640 and 1662 cm^-1), coupled with an increase in the intensity of lipid bands (891, 960, and 1445 cm^-1). Gentamicin- and nitrofurantoin-treated sensitive strains showed an increase in the intensity of nucleic acid bands (668, 724, 780, 810, 1378, 1480, and 1575 cm^-1) while a decrease in the intensity of protein bands (640, 1003, 1606, and 1662 cm^-1) and the lipid band (1445 cm^-1). The Raman spectral changes observed in the antibiotic-resistant strains were opposite to that of antibiotic-sensitive strains. The Raman spectral data correlated well with the antimicrobial susceptibility test results. The Raman spectral dataset was used for partial least-squares (PLS) analysis to validate the biomarkers obtained from the univariate analysis. Overall, this study showcases the potential of Raman spectroscopy for detecting antibiotic-resistant and -sensitive bacteria.

Nano-biosensor for SARS-CoV-2/COVID-19 detection: methods, mechanism and interface design

The epidemic of coronavirus disease 2019 (COVID-19) was a huge disaster to human society. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to COVID-19, has resulted in a large number of deaths. Even though the reverse transcription-polymerase chain reaction (RT-PCR) is the most efficient method for the detection of SARS-CoV-2, the disadvantages (such as long detection time, professional operators, expensive instruments, and laboratory equipment) limit its application. In this review, the different kinds of nano-biosensors based on surface-enhanced Raman scattering (SERS), surface plasmon resonance (SPR), field-effect transistor (FET), fluorescence methods, and electrochemical methods are summarized, starting with a concise description of their sensing mechanism. The different bioprobes (such as ACE2, S protein-antibody, IgG antibody, IgM antibody, and SARS-CoV-2 DNA probes) with different bio-principles are introduced. The key structural components of the biosensors are briefly introduced to give readers an understanding of the principles behind the testing methods. In particular, SARS-CoV-2-related RNA mutation detection and its challenges are also briefly described. We hope that this review will encourage readers with different research backgrounds to design SARS-CoV-2 nano-biosensors with high selectivity and sensitivity.

Single-Cell Techniques in Environmental Microbiology

Environmental microbiology has been an essential part of environmental research because it provides effective solutions to most pollutants. Hence, there is an interest in investigating microorganism behavior, such as observation, identification, isolation of pollutant degraders, and interactions between microbial species. To comprehensively understand cell heterogeneity, diverse approaches at the single-cell level are demanded. Thus far, the traditional bulk biological tools such as petri dishes are technically challenging for single cells, which could mask the heterogeneity. Single-cell technologies can reveal complex and rare cell populations by detecting heterogeneity among individual cells, which offers advantages of higher resolution, higher throughput, more accurate analysis, etc. Here, we overviewed several single-cell techniques on observation, isolation, and identification from aspects of methods and applications. Microscopic observation, sequencing identification, flow cytometric identification and isolation, Raman spectroscopy-based identification and isolation, and their applications are mainly discussed. Further development on multi-technique integrations at the single-cell level may highly advance the research progress of environmental microbiology, thereby giving more indication in the environmental microbial ecology.

A novel alternative strategy for monitoring and insight into liver fibrosis progression: The combination of surface-enhanced Raman spectroscopy (SERS) and gut microbiota

Nowadays, the studies on the interaction and relationship between the intestinal microorganisms and liver diseases are increasing. However, it is still a huge challenge for the in-depth investigation and dynamic monitoring of such a complex network. Herein, a significant discovery was made. A strong association between gut microbial structural and functional genomics and SERS spectra of hepatocytes were revealed. Based on the study of gut microbes and SERS spectra, complementary information could be provided for the mechanism analysis of related diseases. Liver fibrosis, a chronic liver disease that lack specific cure was thus comprehensive studied. Liver targeting gold nanoparticle dimers were prepared as the SERS tags, and abundant SERS peak signals were acquired. Meanwhile, the gut microbiomes were also comparative studied. The changes of carbohydrates and lipids in liver cells were observed at the early stages of liver fibrosis, and TLR4 (toll-like receptors 4) was activated to elicit immune responses. Then again, oxidative stress, endotoxin and serum inflammatory factors were the major observations at the late stages. The SERS signals and the microbiome analysis were well confirmed and complemented each other, which suggested that the detection strategy could be another valuable method for the "gut-liver axis" study.

Leveraging single-cell Raman spectroscopy and single-cell sorting for the detection and identification of yeast infections

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics.

Dynamic monitoring of bacteriostatic process by SERS analysis based on a simple but effective detection strategy

Investigating antibacterial process at a molecular level is helpful to fully understand the mechanism of bacteriostasis and develop new antimicrobial agents. Herein, a simple but effective sensor strategy of antibacterial nanocomposite combined with surface-enhanced Raman scattering (SERS) substrate was applied for the robust detection of bacteriostatic process. The synergistic SERS effect of nanocomposite and Ag nanoparticles (NPs) substrate was confirmed by finite difference time domain (FDTD) solutions. A curcumin liposome@Au NPs nanocomposite was designed and prepared as a kind of bacteriostatic agent and SERS material as well. By means of electrostatic attraction between the nanocomposite and bacteria (methicillin resistant staphylococcus aureus, MRSA), specific detection of MRSA and monitoring of the molecular structure changes after bacteriostaticeffect were realized by SERS. Important intermediates produced in the bacteriostatic process were also measured at the same time. The relationship between the relative peak intensities and the structure of MRSA were thus established. The results were verified by high performance liquid chromatography-mass spectrometry (HPLC-MS), reactive oxygen species (ROS) kit, and flow cytometry. The detection strategy we proposed could not only be used for real-time detection of bacteriostatic processes with a high efficiency, but also a powerful tool for analyzing the mechanism in biochemical processes.

Surface-enhanced Raman spectroscopy for the characterization of pellets of biofilm forming bacterial strains of Staphylococcus epidermidis

BACKGROUND

Surface-enhanced Raman spectroscopy (SERS) is an effective tool for identifying biofilm forming bacterial strains. Biofilm forming bacteria are considered a major issue in the health sector because they have strong resistance against antibiotics. Staphylococcus epidermidis is commonly present on intravascular devices and prosthetic joints, catheters and wounds.

OBJECTIVES

To identify and characterize biofilm forming and non-biofilm forming bacterial strains, surface- enhanced Raman spectroscopy with principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were used.

METHODS

Surface-enhanced Raman spectroscopy (SERS) with silver nanoparticles were employed for the analysis and characterization of biofilm forming bacterial strains. SERS is used to differentiate between non biofilm forming (five samples), medium biofilm forming (five samples) and strong biofilm forming (five samples) bacterial strains by applying silver nanoparticles (AgNPs) as SERS substrate. Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) were used to discriminate between non, medium and strong biofilm ability of bacterial strains.

RESULTS

Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been used to identify the biochemical differences in the form of SERS features which can be used to differentiate between biofilm forming and non-biofilm forming bacterial strains. PLS-DA provides successful differentiation and classification of these different strains with 94.5% specificity, 96% sensitivity and 89% area under the curve (AUC).

CONCLUSIONS

Surface-enhanced Raman spectroscopy can be utilized to differentiate between non, medium and strong biofilm forming bacterial strains.

Phenotypic convergence of bacterial adaption to sub-lethal antibiotic treatment

Microorganisms can adapt quickly to changes in their environment, leading to various phenotypes. The dynamic for phenotypic plasticity caused by environmental variations has not yet been fully investigated. In this study, we analyzed the time-series of phenotypic changes in Staphylococcus cells during adaptive process to antibiotics stresses using flow cytometry and Raman spectroscopy. The nine antibiotics with four different mode of actions were treated in bacterial cells at a sub-lethal concentration to give adaptable stress. Although the growth rate initially varied depending on the type of antibiotic, most samples reached the maximum growth comparable to the control through the short-term adaptation after 24 h. The phenotypic diversity, which showed remarkable changes depending on antibiotic treatment, converged identical to the control over time. In addition, the phenotype with cellular biomolecules converted into a bacterial cell that enhance tolerance to antibiotic stress with increases in cytochrome and lipid. Our findings demonstrated that the convergence into the phenotypes that enhance antibiotic tolerance in a short period when treated with sub-lethal concentrations, and highlight the feasibility of phenotypic approaches in the advanced antibiotic treatment.

Photonic Microfluidic Technologies for Phytoplankton Research

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world's vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.

Single-cell Raman spectroscopy identifies Escherichia coli persisters and reveals their enhanced metabolic activities

Microbial persisters are the featured tiny sub-population of microorganisms that are highly tolerant to multiple antimicrobials. Currently, studies on persisters remain a considerable challenge owing to technical limitations. Here, we explored the application of single-cell Raman spectroscopy (SCRS) in the investigation of persisters. Escherichia coli (ATCC 25922) cells were treated with a lethal dosage of ampicillin (100 μg/mL, 32 × MIC, 4 h) for the formation of persisters. The biochemical characters of E. coli and its persisters were assessed by SCRS, and their metabolic activities were labeled and measured with D₂O-based single-cell Raman spectroscopy (D₂O-Ramanometry). Notable differences in the intensity of Raman bands related to major cellular components and metabolites were observed between E. coli and its ampicillin-treated persisters. Based on their distinct Raman spectra, E. coli and its persister cells were classified into different projective zones through the principal component analysis and t-distributed stochastic neighbor embedding. According to the D₂O absorption rate, E. coli persisters exhibited higher metabolic activities than those of untreated E. coli. Importantly, after the termination of ampicillin exposure, these persister cells showed a temporal pattern of D₂O intake that was distinct from non-persister cells. To our knowledge, this is the first report on identifying E. coli persisters and assessing their metabolic activities through the integrated SCRS and D₂O-Ramanometry approach. These novel findings enhance our understanding of the phenotypes and functionalities of microbial persister cells. Further investigations could be extended to other pathogens by disclosing microbial pathogenicity mechanisms for developing novel therapeutic strategies and approaches.

DFT-based Raman spectral study of astaxanthin geometrical isomers

Astaxanthin is a carotenoid widely used in food additives, nutritional product and medicines, which shows many physiological functions such as antioxidant, anti-inflammatory, anti-hypertensive and anti-diabetic activities. It has been recognized that astaxanthin has all-trans and nine cis isomers, and these geometrical isomers have very different biological activities. The process of selective enrichment, metabolism and isomerization of astaxanthin in animals remains to be studied. Therefore, identifying isomers and obtaining their structural parameters are important for understanding the active mechanism of different molecular isomers. Although the traditional methods such as high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) spectroscopy can be used to distinguish these isomers, these methods generally require considerable testing time, cost, sample volume, and hardly be applied in vivo. In this work, Raman spectroscopy combined with density functional theory (DFT) calculation was introduced to study different geometrical isomers of astaxanthin. The theoretical and experimental Raman spectra are in agreement, and we have demonstrated that all the known ten geometrical isomers of astaxanthin can be readily distinguished using this spectroscopic approach. The astaxanthin molecular vibrational modes, geometric structures, energies of ten geometric isomers are systematically scrutinized. Moreover, a lot of structural and Raman problems unsolved previously have been solved by the DFT-based spectral analysis. Therefore, this work provides an effective way for identification of different astaxanthin geometrical isomers, and may have important significance for promoting the research of astaxanthin isomers on biological property mechanisms and related applications in food molecular science.

Bacterial Resuscitation from Starvation-Induced Dormancy Results in Phenotypic Diversity Coupled with Translational Activity Depending on Carbon Substrate Availability

Dormancy is a survival strategy of stressed bacteria inhabiting a various environment. Frequent dormant-active transitions owing to environmental changes play an important role in functional redundancy. However, a proper understanding of the phenotypic changes in bacteria during these transitions remains to be clarified. In this study, orthogonal approaches, such as electron microscopy, flow cytometry, and Raman spectroscopy, which can evaluate phenotypic heterogeneity at the single-cell level, were used to observe morphological and molecular phenotypic changes in resuscitated cells, and RNA sequencing (RNASeq) was used to determine the genetic characteristics associated with phenotypes. Within 12 h of the resuscitation process, morphological (cell size and shape) and physiological (growth and viability) characteristics as well as molecular phenotypes (cellular components) were found to be recovered to the extent that they were similar to those in active cells. The recovery rate and detailed phenotypic properties of the resuscitated cells differed significantly depending on the type or concentration of carbon sources. RNASeq analysis revealed that genes related to translation were significantly upregulated under all resuscitation conditions. The simpler the carbon source (e.g., glucose), the higher the expression of genes involved in cellular repair, and the more complex the carbon source (e.g., beef extract), the higher the expression of genes associated with increased energy production associated with cellular aerobic respiration. This study of phenotypic plasticity of resuscitated cells provides fundamental insight into understanding the adaptive fine-tuning of the microbiome in response to environmental changes and the functional redundancy resulting from phenotype heterogeneity.

Impact of silver nanoparticles size on SERS for detection and identification of filamentous fungi

Using the proper size of nanoparticles as an active substrate, Surface-enhanced Raman scattering (SERS) can provide a reliable technique for detecting and identifying fungi, including Alternaria alternata, Aspergillus flavus, Fusarium verticilliodes, and Aspergillus parasiticus that have been associated to biodeterioration and biodegradation of cultural heritage materials. In this research spherical silver nanoparticles (AgNPs) of average size of 10, 30 and 60 nm were synthesized using the wet chemical method with good yield and their size and shape distributions were examined using small-angle X-ray scattering (SAXS). The protocol for fungi sample preparation proved to be critical for producing high-quality and reproducible SERS spectra. We found that the effect of AgNPs on SERS signal enhancement is size dependent under the same experimental conditions; the SERS intensity of fungal strains using 60 nm achieved up to 2.3x10⁵ enhancement, about twice as intense as those produced with 30 nm, and 10 nm produced a minor broad weak peak barely discernible around 1400 cm^-1, similar to the NR spectra profile in the 550-1700 cm^-1 spectral region, and the SERS signals using 60 nm showed high reproducibility, with less than 20% variance. Furthermore, we used principal component analysis (PCA) to statistically classify the SERS spectrum into four separate clusters with 99 percent variability so that the four fungal strains could be clearly detected and identified. The SERS technique, in combination with the PCA developed in this study, provides a simple, rapid, accurate, and cost-effective analytical tool for detecting and identifying filamentous fungal strains.

Raman-Deuterium Isotope Probing and Metagenomics Reveal the Drought Tolerance of the Soil Microbiome and Its Promotion of Plant Growth

Drought has become a major agricultural threat leading crop yield loss. Although a few species of rhizobacteria have the ability to promote plant growth under drought, the drought tolerance of the soil microbiome and its relationship with the promotion of plant growth under drought are scarcely studied. This study aimed to develop a novel approach for assessing drought tolerance in agricultural land by quantitatively measuring microbial phenotypes using stable isotopes and Raman spectroscopy. Raman spectroscopy with deuterium isotope probing was used to identify the Raman signatures of drought effects from drought-tolerant bacteria. Counting drought-tolerant cells by applying these phenotypic properties to agricultural samples revealed that 0% to 52.2% of all measured single cells had drought-tolerant properties, depending on the soil sample. The proportions of drought-tolerant cells in each soil type showed similar tendencies to the numbers of revived pea plants cultivated under drought. The phenotype of the soil microbiome and plant behavior under drought conditions therefore appeared to be highly related. Studying metagenomics suggested that there was a reliable link between the phenotype and genotype of the soil microbiome that could explain mechanisms that promote plant growth in drought. In particular, the proportion of drought-tolerant cells was highly correlated with genes encoding phytohormone production, including tryptophan synthase and isopentenyl-diphosphate delta-isomerase; these enzymes are known to alleviate drought stress. Raman spectroscopy with deuterium isotope probing shows high potential as an alternative technology for quantitatively assessing drought tolerance through phenotypic analysis of the soil microbiome. IMPORTANCE Soil microbiome has played a critical role in the plant survival during drought. However, the drought tolerance of soil microbiome and its ability to promote plant growth under drought is still scarcely studied. In this study, we identified the Raman signature (i.e., phenotype) of drought effects from drought-tolerant bacteria in agricultural soil samples using Raman-deuterium isotope probing (Raman-DIP). Moreover, the number of drought-tolerant cells measured by Raman-DIP was highly related to the survival rate of plant cultivation under drought and the abundance of genes encoding phytohormone production alleviating drought stress in plant. These results suggest Raman-DIP is a promising technology for measuring drought tolerance of soil microbiome. This result give us important insight into further studies of a reliable link between phenotype and genotype of soil microbiome for future plant-bacteria interaction research.

Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy

In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli. Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health.

Raman spectroscopy for the differentiation of Enterobacteriaceae: a comparison of two methods

A comprehensive dataset of bacteria of the family Enterobacteriaceae was collected and measured with Raman spectroscopy. Fiber-probe based Raman spectroscopy enabled classification with 100% accuracy and remained robust with a validation dataset.

Alcoholic Fermentation Monitoring and pH Prediction in Red and White Wine by Combining Spontaneous Raman Spectroscopy and Machine Learning Algorithms

In the following study, total sugar concentrations before and during alcoholic fermentation, as well as ethanol concentrations and pH levels after fermentation, of red and white wine grapes were successfully predicted using Raman spectroscopy. Fluorescing compounds such as anthocyanins and pigmented phenolics found in red wine present one of the primary limitations of enological analysis using Raman spectroscopy. Unlike the spontaneous Raman effect, fluorescence is a highly efficient process and consequently emits a much stronger signal than spontaneous Raman scattering. For this reason, many enological applications of Raman spectroscopy are impractical as the more subtle Raman spectrum of any red wine sample is in large part masked by fluorescing compounds present in the wine. This work employs a simple extraction method to mitigate fluorescence in finished red wines. Ethanol and total sugars (fructose plus glucose) of wines made from red (Cabernet Sauvignon) and white (Chardonnay, Sauvignon Blanc, and Gruner Veltliner) varieties were modeled using support vector regression (SVR), partial least squares regression (PLSR) and Ridge regression (RR). The results, which compared the predicted to measured total sugar concentrations before and during fermentation, were excellent (R2SVR = 0.96, R2PLSR = 0.95, R2RR = 0.95, RMSESVR = 1.59, RMSEPLSR = 1.57, RMSERR = 1.57), as were the ethanol and pH predictions for finished wines after phenolic stripping with polyvinylpolypyrrolidone (R2SVR = 0.98, R2PLSR = 0.99, R2RR = 0.99, RMSESVR = 0.23, RMSEPLSR = 0.21, RMSERR = 0.23). The results suggest that Raman spectroscopy is a viable tool for rapid and trustworthy fermentation monitoring.

Using Stable Isotope Probing and Raman Microspectroscopy To Measure Growth Rates of Heterotrophic Bacteria

The suitability of stable isotope probing (SIP) and Raman microspectroscopy to measure growth rates of heterotrophic bacteria at the single-cell level was evaluated. Label assimilation into Escherichia coli biomass during growth on a complex ¹³C-labeled carbon source was monitored in time course experiments. ¹³C incorporation into various biomolecules was measured by spectral "red shifts" of Raman-scattered emissions. The ¹³C- and ¹²C-isotopologues of the amino acid phenylalanine (Phe) proved to be quantitatively accurate reporter molecules of cellular isotopic fractional abundances (f_cell). Values of f_cell determined by Raman microspectroscopy and independently by isotope ratio mass spectrometry (IRMS) over a range of isotopic enrichments were statistically indistinguishable. Progressive labeling of Phe in E. coli cells among a range of ¹³C/¹²C organic substrate admixtures occurred predictably through time. The relative isotopologue abundances of Phe determined by Raman spectral analysis enabled the accurate calculation of bacterial growth rates as confirmed independently by optical density (OD) measurements. The results demonstrate that combining SIP and Raman microspectroscopy can be a powerful tool for studying bacterial growth at the single-cell level on defined or complex organic ¹³C carbon sources, even in mixed microbial assemblages. IMPORTANCE Population growth dynamics and individual cell growth rates are the ultimate expressions of a microorganism's fitness under its environmental conditions, whether natural or engineered. Natural habitats and many industrial settings harbor complex microbial assemblages. Their heterogeneity in growth responses to existing and changing conditions is often difficult to grasp by standard methodologies. In this proof-of-concept study, we tested whether Raman microspectroscopy can reliably quantify the assimilation of isotopically labeled nutrients into E. coli cells and enable the determination of individual growth rates among heterotrophic bacteria. Raman-derived growth rate estimates were statistically indistinguishable from those derived by standard optical density measurements of the same cultures. Raman microspectroscopy can also be combined with methods for phylogenetic identification. We report the development of Raman-based techniques that enable researchers to directly link genetic identity to functional traits and rate measurements of single cells within mixed microbial assemblages, currently a major technical challenge in microbiological research.

Efficient long-range conduction in cable bacteria through nickel protein wires

Filamentous cable bacteria display long-range electron transport, generating electrical currents over centimeter distances through a highly ordered network of fibers embedded in their cell envelope. The conductivity of these periplasmic wires is exceptionally high for a biological material, but their chemical structure and underlying electron transport mechanism remain unresolved. Here, we combine high-resolution microscopy, spectroscopy, and chemical imaging on individual cable bacterium filaments to demonstrate that the periplasmic wires consist of a conductive protein core surrounded by an insulating protein shell layer. The core proteins contain a sulfur-ligated nickel cofactor, and conductivity decreases when nickel is oxidized or selectively removed. The involvement of nickel as the active metal in biological conduction is remarkable, and suggests a hitherto unknown form of electron transport that enables efficient conduction in centimeter-long protein structures.

Dark-field/hyperspectral microscopy for detecting nanoscale particles in environmental nanotoxicology research

Nanoscale contaminants (including engineered nanoparticles and nanoplastics) pose a significant threat to organisms and environment. Rapid and non-destructive detection and identification of nanosized materials in cells, tissues and organisms is still challenging, although a number of conventional methods exist. These approaches for nanoparticles imaging and characterisation both inside the cytoplasm and on the cell or tissue outer surfaces, such as electron or scanning probe microscopies, are unquestionably potent tools, having excellent resolution and supplemented with chemical analysis capabilities. However, imaging and detection of nanomaterials in situ, in wet unfixed and even live samples, such as living isolated cells, microorganisms, protozoans and miniature invertebrates using electron microscopy is practically impossible, because of the elaborate sample preparation requiring chemical fixation, contrast staining, matrix embedding and exposure into vacuum. Atomic force microscopy, in several cases, can be used for imaging and mechanical analysis of live cells and organisms under ambient conditions, however this technique allows for investigation of surfaces. Therefore, a different approach allowing for imaging and differentiation of nanoscale particles in wet samples is required. Dark-field microscopy as an optical microscopy technique has been popular among researchers, mostly for imaging relatively large specimens. In recent years, the so-called "enhanced dark field" microscopy based on using higher numerical aperture light condensers and variable numerical aperture objectives has emegred, which allows for imaging of nanoscale particles (starting from 5 nm nanospheres) using almost conventional optical microscopy methodology. Hyperspectral imaging can turn a dark-field optical microscope into a powerful chemical characterisation tool. As a result, this technique is becoming popular in environmental nanotoxicology studies. In this Review Article we introduce the reader into the methodology of enhanced dark-field and dark-field-based hyperspectral microscopy, covering the most important advances in this rapidly-expanding area of environmental nanotoxicology.

Monitoring Deuterium Uptake in Single Bacterial Cells via Two-Dimensional Raman Correlation Spectroscopy

Raman-stable isotope labeling using heavy water (Raman-D₂O) is attracting great interest as a fast technique with various applications ranging from the identification of pathogens in medical samples to the determination of microbial activity in the environment. Despite its widespread applications, little is known about the fundamental processes of hydrogen-deuterium (H/D) exchange, which are crucial for understanding molecular interactions in microorganisms. By combining two-dimensional (2D) correlation spectroscopy and Raman deuterium labeling, we have investigated H/D exchange in bacterial cells under time dependence. Most C-H stretching signals decreased in intensity over time, prior to the formation of the C-D stretching vibration signals. The intensity of the C-D signal gradually increased over time, and the shape of the C-D signal was more uniform after longer incubation times. Deuterium uptake showed high variability between the bacterial genera and mainly led to an observable labeling of methylene and methyl groups. Thus, the C-D signal encompassed a combination of symmetric and antisymmetric CD₂ and CD₃ stretching vibrations, depending on the bacterial genera. The present study allowed for the determination of the sequential order of deuterium incorporation into the functional groups of proteins, lipids, and nucleic acids and hence understanding the process of biomolecule synthesis and the growth strategies of different bacterial taxa. We present the combination of Raman-D₂O labeling and 2D correlation spectroscopy as a promising approach to gain a fundamental understanding of molecular interactions in biological systems.

Novel methods to enhance surgical sperm retrieval: a systematic review

Objectives: To explore the use of novel technologies in sperm retrieval in men with azoospermia due to a production defect. Methods: We performed a Preferred Reporting Items for Systemic Reviews and Meta-Analysis (PRISMA)-compliant systemic literature review for manuscripts focussed on novel sperm-retrieval methods. We identified 30 studies suitable for qualitative analysis. Results and Conclusions: We identified multiple new promising technologies, each with its own distinct set of benefits and limitations, to enhance chances of sperm retrieval; these include the use of multiphoton microscopy, Raman spectroscopy, and full-field optical coherence tomography during a microdissection-testicular sperm extraction procedure. ORBEYE and ultrasonography technologies can also serve to better visualise areas of sperm production. Finally, artificial intelligence technology can play a role in the identification of sperm and, perhaps, better-quality sperm for use with assisted reproduction. Abbreviations: AI: artificial intelligence; ANN: artificial neural network; ART: assisted reproductive technology; 3D: three-dimensional; DNN: deep neural networks; FFOCT: full-field optical coherence tomography; H&E: haematoxylin and eosin; ICSI: intracytoplasmic sperm injection; IVF: in vitro fertilisation; MESA: micro-epididymal sperm aspiration; MeSH: Medical Subject Heading; MPM: multiphoton microscopy; (N)OA: (non-)obstructive azoospermia; SCO: Sertoli cell-only syndrome; SRR: sperm retrieval rates; TESA: testicular sperm aspiration; (micro-)TESE: (microdissection-) testicular sperm extraction; (CE)US: (contrast-enhanced) ultrasonography.

Raman spectroscopy reveals alteration of spore compositions under different nutritional conditions in Lysinibacillus boronitolerans YS11

Little is known about final spores components when bacteria undergo sporulation under different nutrient conditions. Different degrees of resistance and germination rates were observed in the three types of spores of Lysinibacillus boronitolerans YS11 (SD, Spores formed in Difco sporulation medium™; SC and SF, Spores formed in an agricultural byproduct medium with 10 mM CaCl2 and with 10 mM FeSO4, respectively). Stronger UV resistance was recorded for SF with 1.8-2.3-fold greater survival than SC and SD under UV treatment. The three spore types showed similar heat resistances at 80°C, but survival rates of SC and SD were much higher (∼1,000 times) than those of SF at 90°C. However, germination capacity of SF was 20% higher than those of SD and SC on Luria-Bertani agar plates for 24 h. SF germinated more rapidly in a liquid medium with high NaCl concentrations than SC and SD, but became slower under alkaline conditions. Raman spectroscopy was used to analyze the heterogeneities in the three types of vegetative cells and their spores under different nutritional conditions. Exponentially grown-each vegetative cells had different overall Raman peak values. Raman peaks of SC, SD, and SF also showed differences in adenine and amide III compositions and nucleic acid contents. Our data along with Raman spectroscopy provided the evidence that spores formed under under different growth conditions possess very different cellular components, which affected their survival and germination rates.

Bacterial phenotype dependency from CO2 measured by Raman spectroscopy

In recent years, Raman spectroscopy has become an established method to study medical, biological or environmental samples. Since Raman spectroscopy is a phenotypic method, many parameters can influence the spectra. One of these parameters is the concentration of CO₂, as this never remains stable in nature, but always adjusts itself in a dynamic equilibrium. So, it is obvious that the concentration of CO₂ cannot be controlled but it might have a big impact on the bacteria and bacterial composition in medical samples. When using a phenotypic method like Raman spectroscopy it is also important to know the influence of CO₂ to the dataset. To investigate the influence of CO₂ towards Raman spectra we cultivated E. coli at different concentration of CO₂ since this bacterium is able to switch metabolism from aerobic to microaerophilic conditions. After applying statistic methods small changes in the spectra became visible and it was even possible to observe the change of metabolism in this species according to the concentration of CO₂.

Detection of SARS-CoV-2 and its S and N proteins using surface enhanced Raman spectroscopy

The COVID-19 pandemic demonstrated the critical need for accurate and rapid testing for virus detection. This need has generated a high number of new testing methods aimed at replacing RT-PCR, which is the golden standard for testing. Most of the testing techniques are based on biochemistry methods and require chemicals that are often expensive and the supply might become scarce in a large crisis. In the present paper we suggest the use of methods based on physics that leverage novel nanomaterials. We demonstrate that using Surface Enhanced Raman Spectroscopy (SERS) of virion particles a very distinct spectroscopic signature of the SARS-CoV-2 virus can be obtained. We demonstrate that the spectra are mainly composed by signals from the spike (S) and nucleocapsid (N) proteins. It is believed that a clinical test using SERS can be developed. The test will be fast, inexpensive, and reliable. It is also clear that SERS can be used for analysis of structural changes on the S and N proteins. This will be an example of application of nanotechnology and properties of nanoparticles for health and social related matters.

The COVID-19 pandemic demonstrated the critical need for accurate and rapid testing for virus detection.

Abiotic stressors impact outer membrane vesicle composition in a beneficial rhizobacterium: Raman spectroscopy characterization

Outer membrane vesicles (OMVs) produced by Gram-negative bacteria have roles in cell-to-cell signaling, biofilm formation, and stress responses. Here, the effects of abiotic stressors on OMV contents and composition from biofilm cells of the plant health-promoting bacterium Pseudomonas chlororaphis O6 (PcO6) are examined. Two stressors relevant to this root-colonizing bacterium were examined: CuO nanoparticles (NPs)-a potential fertilizer and fungicide- and H2O2-released from roots during plant stress responses. Atomic force microscopy revealed 40-300 nm diameter OMVs from control and stressed biofilm cells. Raman spectroscopy with linear discriminant analysis (LDA) was used to identify changes in chemical profiles of PcO6 cells and resultant OMVs according to the cellular stressor with 84.7% and 83.3% accuracies, respectively. All OMVs had higher relative concentrations of proteins, lipids, and nucleic acids than PcO6 cells. The nucleic acid concentration in OMVs exhibited a cellular stressor-dependent increase: CuO NP-induced OMVs > H2O2-induced OMVs > control OMVs. Biochemical assays confirmed the presence of lipopolysaccharides, nucleic acids, and protein in OMVs; however, these assays did not discriminate OMV composition according to the cellular stressor. These results demonstrate the sensitivity of Raman spectroscopy using LDA to characterize and distinguish cellular stress effects on OMVs composition and contents.

Advances in Optical Detection of Human-Associated Pathogenic Bacteria

Bacterial infection is a global burden that results in numerous hospital visits and deaths annually. The rise of multi-drug resistant bacteria has dramatically increased this burden. Therefore, there is a clinical need to detect and identify bacteria rapidly and accurately in their native state or a culture-free environment. Current diagnostic techniques lack speed and effectiveness in detecting bacteria that are culture-negative, as well as options for in vivo detection. The optical detection of bacteria offers the potential to overcome these obstacles by providing various platforms that can detect bacteria rapidly, with minimum sample preparation, and, in some cases, culture-free directly from patient fluids or even in vivo. These modalities include infrared, Raman, and fluorescence spectroscopy, along with optical coherence tomography, interference, polarization, and laser speckle. However, these techniques are not without their own set of limitations. This review summarizes the strengths and weaknesses of utilizing each of these optical tools for rapid bacteria detection and identification.

Raman Spectroscopy-Based Measurements of Single-Cell Phenotypic Diversity in Microbial Populations

Microbial cells that live in the same community can exist in different physiological and morphological states that change as a function of spatiotemporal variations in environmental conditions. This phenomenon is commonly known as phenotypic heterogeneity and/or diversity. Measuring this plethora of cellular expressions is needed to better understand and manage microbial processes. However, most tools to study phenotypic diversity only average the behavior of the sampled community. In this work, we present a way to quantify the phenotypic diversity of microbial samples by inferring the (bio)molecular profile of its constituent cells using Raman spectroscopy. We demonstrate how this tool can be used to quantify the phenotypic diversity that arises after the exposure of microbes to stress. Raman spectroscopy holds potential for the detection of stressed cells in bioproduction.

Microbial cells experience physiological changes due to environmental change, such as pH and temperature, the release of bactericidal agents, or nutrient limitation. This has been shown to affect community assembly and physiological processes (e.g., stress tolerance, virulence, or cellular metabolic activity). Metabolic stress is typically quantified by measuring community phenotypic properties such as biomass growth, reactive oxygen species, or cell permeability. However, bulk community measurements do not take into account single-cell phenotypic diversity, which is important for a better understanding and the subsequent management of microbial populations. Raman spectroscopy is a nondestructive alternative that provides detailed information on the biochemical makeup of each individual cell. Here, we introduce a method for describing single-cell phenotypic diversity using the Hill diversity framework of Raman spectra. Using the biomolecular profile of individual cells, we obtained a metric to compare cellular states and used it to study stress-induced changes. First, in two Escherichia coli populations either treated with ethanol or nontreated and then in two Saccharomyces cerevisiae subpopulations with either high or low expression of a stress reporter. In both cases, we were able to quantify single-cell phenotypic diversity and to discriminate metabolically stressed cells using a clustering algorithm. We also described how the lipid, protein, and nucleic acid compositions changed after the exposure to the stressor using information from the Raman spectra. Our results show that Raman spectroscopy delivers the necessary resolution to quantify phenotypic diversity within individual cells and that this information can be used to study stress-driven metabolic diversity in microbial populations.

IMPORTANCE Microbial cells that live in the same community can exist in different physiological and morphological states that change as a function of spatiotemporal variations in environmental conditions. This phenomenon is commonly known as phenotypic heterogeneity and/or diversity. Measuring this plethora of cellular expressions is needed to better understand and manage microbial processes. However, most tools to study phenotypic diversity only average the behavior of the sampled community. In this work, we present a way to quantify the phenotypic diversity of microbial samples by inferring the (bio)molecular profile of its constituent cells using Raman spectroscopy. We demonstrate how this tool can be used to quantify the phenotypic diversity that arises after the exposure of microbes to stress. Raman spectroscopy holds potential for the detection of stressed cells in bioproduction.

Improvement of Surface-Enhanced Raman Scattering Method for Single Bacterial Cell Analysis

Surface-enhanced Raman scattering (SERS) is a useful tool for label-free analysis of bacteria at the single cell level. However, low reproducibility limits the use of SERS. In this study, for the sake of sensitive and reproducible Raman spectra, we optimized the methods for preparing silver nanoparticles (AgNPs) and depositing AgNPs onto a cell surface. We found that fast dropwise addition of AgNO₃ into the reductant produced smaller and more stable AgNPs, with an average diameter of 45 ± 4 nm. Compared with that observed after simply mixing the bacterial cells with AgNPs, the SERS signal was significantly improved after centrifugation. To optimize the SERS enhancement method, the centrifugal force, method for preparing AgNPs, concentration of AgNPs, ionic strength of the solution used to suspend the cells, and density of the cells were chosen as impact factors and optimized through orthogonal experiments. Finally, the improved method could generate sensitive and reproducible SERS spectra from single Escherichia coli cells, and the SERS signals primarily arose from the cell envelope. We further verified that this optimal method was feasible for the detection of low to 25% incorporation of ¹³C isotopes by the cells and the discrimination of different bacterial species. Our work provides an improved method for generating sensitive and reproducible SERS spectra.

Microbial single-cell omics: the crux of the matter

Abstract

Single-cell genomics and transcriptomics can provide reliable context for assembled genome fragments and gene expression activity on the level of individual prokaryotic genomes. These methods are rapidly emerging as an essential complement to cultivation-based, metagenomics, metatranscriptomics, and microbial community-focused research approaches by allowing direct access to information from individual microorganisms, even from deep-branching phylogenetic groups that currently lack cultured representatives. Their integration and binning with environmental ‘omics data already provides unprecedented insights into microbial diversity and metabolic potential, enabling us to provide information on individual organisms and the structure and dynamics of natural microbial populations in complex environments. This review highlights the pitfalls and recent advances in the field of single-cell omics and its importance in microbiological and biotechnological studies.

Key points

• Single-cell omics expands the tree of life through the discovery of novel organisms, genes, and metabolic pathways.

• Disadvantages of metagenome-assembled genomes are overcome by single-cell omics.

• Functional analysis of single cells explores the heterogeneity of gene expression.

• Technical challenges still limit this field, thus prompting new method developments.

Infrared spectroscopy of live cells from a flowing solution using electrically-biased plasmonic metasurfaces

Spectral cytopathology (SCP) is a promising label-free technique for diagnosing diseases and monitoring therapeutic outcomes using FTIR spectroscopy. In most cases, cells must be immobilized on a substrate prior to spectroscopic interrogation. This creates significant limitations for high throughput phenotypic whole-cell analysis, especially for the non-adherent cells. Here we demonstrate how metasurface-enhanced infrared reflection spectroscopy (MEIRS) can be applied to a continuous flow of live cell solution by applying AC voltage to metallic metasurfaces. By integrating metasurfaces with microfluidic delivery channels and attracting the cells to the metasurface via dielectrophoretic (DEP) force, we collect the infrared spectra of cells in real time within a minute, and correlate the spectra with simultaneously acquired images of the attracted cells. The resulting DEP-MEIRS technique paves the way for rapid SCP of complex cell-containing body fluids with low cell concentrations, and for the development of a wide range of label-free liquid biopsies.

Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features

This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.

Rapid and accurate identification of marine microbes with single-cell Raman spectroscopy

Rapid and accurate identification of individual microorganisms, such as pathogenic or unculturable microbes, is significant in microbiology. In this work, rapid identification of marine microorganisms by single-cell Raman spectroscopy (scRS) using one-dimensional convolutional neural networks (1DCNN) was explored. Here, single-cell Raman spectra of ten species of marine actinomycetes, two species of non-marine actinomycetes and E. coli (as a reference) were individually collected. Several common classification algorithms in chemometrics, including linear discriminant analysis with principal component analysis and a support vector machine, were applied to evaluate the 1DCNN performance based on the raw and pre-processed Raman spectra. 1DCNN showed superior performance on the raw data in terms of its accuracy and recall rate compared with other classification algorithms. Our investigation demonstrated that the scRS-integrating advanced 1DCNN classification algorithm provided a rapid and accurate approach for identifying individual microorganisms without time-consuming cell culture and sophisticated or specific techniques, which could be a useful methodology for discriminating the microbes that cannot be cultured under normal conditions, especially for 'biological risk'-related emergencies.

Discriminating Bacterial Phenotypes at the Population and Single-Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting

Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, such as flow cytometry and Raman spectroscopy, which describe optical properties of the individual cell. In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth stages of three replicate Escherichia coli populations were characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high-throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single-cell level (i.e., more biochemical information is recorded). Therefore, it can identify distinct phenotypic populations when coupled with analyses tailored toward single-cell data. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. We propose a computational workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external data set. We recommend using flow cytometry to quantify phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in-depth analysis of heterogeneity at the single-cell level. © 2019 International Society for Advancement of Cytometry.

Bactericidal Activity of Copper-Zinc Hybrid Nanoparticles on Copper-Tolerant Xanthomonas perforans

Bacterial spot of tomato, caused by Xanthomonas perforans, X. euvesicatoria, X. vesicatoria and X. gardneri, is a major disease, contributing to significant yield losses worldwide. Over dependence of conventional copper bactericides over the last decades has led to the prevalence of copper-tolerant strains of Xanthomonas spp., making copper bactericides ineffective. Thus, there is a critical need to develop new strategies for better management of copper-tolerant Xanthomonas spp. In this study, we investigated the antimicrobial activity of a hybrid nanoparticle, copper-zinc (Cu/Zn), on copper-tolerant and sensitive strains. The hybrid nanoparticle significantly reduced bacterial growth in vitro compared to the non-treated and micron-size commercial copper controls. Tomato transplants treated with the hybrid nanoparticle had significantly reduced disease severity compared to the controls, and no phytotoxicity was observed on plants. We also studied the hybrid nanoparticle effect on the bacterial pigment xanthomonadin using Near-Infra Red Raman spectroscopy as an indicator of bacterial degradation. The hybrid nanoparticle significantly affected the ability of X. perforans in its production of xanthomonadin when compared with samples treated with micron-size copper or untreated. This study sheds new light on the potential utilization of this novel multi-site Cu/Zn hybrid nanoparticle for bacterial spot management.