Label-free molecular imaging of bacterial communities of the opportunistic pathogen Pseudomonas aeruginosa

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

Spatiotemporal distribution of chemical signatures exhibited by Myxococcus xanthus in response to metabolic conditions

Myxococcus xanthus is a common soil bacterium with a complex life cycle, which is known for production of secondary metabolites. However, little is known about the effects of nutrient availability on M. xanthus metabolite production. In this study, we utilize confocal Raman microscopy (CRM) to examine the spatiotemporal distribution of chemical signatures secreted by M. xanthus and their response to varied nutrient availability. Ten distinct spectral features are observed by CRM from M. xanthus grown on nutrient-rich medium. However, when M. xanthus is constrained to grow under nutrient-limited conditions, by starving it of casitone, it develops fruiting bodies, and the accompanying Raman microspectra are dramatically altered. The reduced metabolic state engendered by the absence of casitone in the medium is associated with reduced, or completely eliminated, features at 1140 cm^-1, 1560 cm^-1, and 1648 cm^-1. In their place, a feature at 1537 cm^-1 is observed, this feature being tentatively assigned to a transitional phase important for cellular adaptation to varying environmental conditions. In addition, correlating principal component analysis heat maps with optical images illustrates how fruiting bodies in the center co-exist with motile cells at the colony edge. While the metabolites responsible for these Raman features are not completely identified, three M. xanthus peaks at 1004, 1151, and 1510 cm^-1 are consistent with the production of lycopene. Thus, a combination of CRM imaging and PCA enables the spatial mapping of spectral signatures of secreted factors from M. xanthus and their correlation with metabolic conditions.

Differentiation of Closely Related Oak-Associated Gram-Negative Bacteria by Label-Free Surface Enhanced Raman Spectroscopy (SERS)

Due to the harmful effects of chemical fertilizers and pesticides, the need for an eco-friendly solution to improve soil fertility has become a necessity, thus microbial biofertilizer research is on the rise. Plant endophytic bacteria inhabiting internal tissues represent a novel niche for research into new biofertilizer strains. However, the number of species and strains that need to be differentiated and identified to facilitate faster screening in future plant-bacteria interaction studies, is enormous. Surface enhanced Raman spectroscopy (SERS) may provide a platform for bacterial discrimination and identification, which, compared with the traditional methods, is relatively rapid, uncomplicated and ensures high specificity. In this study, we attempted to differentiate 18 bacterial isolates from two oaks via morphological, physiological, biochemical tests and SERS spectra analysis. Previous 16S rRNA gene fragment sequencing showed that three isolates belong to Paenibacillus, 3-to Pantoea and 12-to Pseudomonas genera. Additional tests were not able to further sort these bacteria into strain-specific groups. However, the obtained label-free SERS bacterial spectra along with the high-accuracy principal component (PCA) and discriminant function analyses (DFA) demonstrated the possibility to differentiate these bacteria into variant strains. Furthermore, we collected information about the biochemical characteristics of selected isolates. The results of this study suggest a promising application of SERS in combination with PCA/DFA as a rapid, non-expensive and sensitive method for the detection and identification of plant-associated bacteria.

Depth distributions of signaling molecules in Pseudomonas aeruginosa biofilms mapped by confocal Raman microscopy

Pseudomonas aeruginosa is an opportunistic human pathogen implicated in both acute and chronic diseases, which resists antibiotic treatment, in part by forming physical and chemical barriers such as biofilms. Here, we explore the use of confocal Raman imaging to characterize the three-dimensional (3D) spatial distribution of alkyl quinolones (AQs) in P. aeruginosa biofilms by reconstructing depth profiles from hyperspectral Raman data. AQs are important to quorum sensing (QS), virulence, and other actions of P. aeruginosa. Three-dimensional distributions of three different AQs (PQS, HQNO, and HHQ) were observed to have a significant depth, suggesting 3D anisotropic shapes-sheet-like rectangular solids for HQNO and extended cylinders for PQS. Similar to observations from 2D imaging studies, spectral features characteristic of AQs (HQNO or PQS) and the amide I vibration from peptide-containing species were found to correlate with the PQS cylinders typically located at the tips of the HQNO rectangular solids. In the QS-deficient mutant lasIrhlI, a small globular component was observed, whose highly localized nature and similarity in size to a P. aeruginosa cell suggest that the feature arises from HHQ localized in the vicinity of the cell from which it was secreted. The difference in the shapes and sizes of the aggregates of the three AQs in wild-type and mutant P. aeruginosa is likely related to the difference in the cellular response to growth conditions, environmental stress, metabolic levels, or other structural and biochemical variations inside biofilms. This study provides a new route to characterizing the 3D structure of biofilms and shows the potential of confocal Raman imaging to elucidate the nature of heterogeneous biofilms in all three spatial dimensions. These capabilities should be applicable as a tool in studies of infectious diseases.

Biological and clinical significance of quorum sensing alkylquinolones: current analytical and bioanalytical methods for their quantification

Quorum sensing (QS) is a sophisticated bacterial communication system which plays a key role in the virulence and biofilm formation of many pathogens. The Pseudomonas aeruginosa QS network consists of four sets of connected systems (las, rlh, pqs and iqs) hierarchically organized. The pqs system involves characteristic autoinducers (AI), most of them sharing an alkylquinolone (AQ) structure, and is able to carry out several relevant biological functions besides its main signalling activity. Their role in bacterial physiology and pathogenicity has been widely studied. Indeed, the presence of these metabolites in several body fluids and infected tissues has pointed to their potential value as biomarkers of infection. In this review, we summarize the most recent findings about the biological implications and the clinical significance of the main P. aeruginosa AQs. These findings have encouraged the development of analytical and bioanalytical techniques addressed to assess the role of these metabolites in bacterial growth and survival, during pathogenesis or as biomarkers of infections. The availability of highly sensitive reliable analytical methods suitable for clinical analysis would allow getting knowledge about pathogenesis and disease prognosis or progression, supporting clinicians on the decision-making process for the management of these infections and guiding them on the application of more effective and appropriate treatments. The benefits from the implementation of the point-of-care (PoC)-type testing in infectious disease diagnostics, which are seen to improve patient outcomes by promoting earlier therapeutic interventions, are also discussed.

Biopolymer Patterning-Directed Secretion in Mucoid and Nonmucoid Strains of Pseudomonas aeruginosa Revealed by Multimodal Chemical Imaging

Quinolone, pyocyanin, and rhamnolipid production were studied in Pseudomonas aeruginosa by spatially patterning mucin, a glycoprotein important to infection of lung epithelia. Mass spectrometric imaging and confocal Raman microscopy are combined to probe P. aeruginosa biofilms from mucoid and nonmucoid strains grown on lithographically defined patterns. Quinolone signatures from biofilms on patterned vs unpatterned and mucin vs mercaptoundecanoic acid (MUA) surfaces were compared. Microbial attachment is accompanied by secretion of 2-alkyl-4-quinolones as well as rhamnolipids from the mucoid and nonmucoid strains. Pyocyanin was also detected both in the biofilm and in the supernatant in the mucoid strain only. Significant differences in the spatiotemporal distributions of secreted factors are observed between strains and among different surface patterning conditions. The mucoid strain is sensitive to composition and patterning while the nonmucoid strain is not, and in promoting community development in the mucoid strain, nonpatterned surfaces are better than patterned, and mucin is better than MUA. Also, the mucoid strain secretes the virulence factor pyocyanin in a way that correlates with distress. A change in the relative abundance for two rhamnolipids is observed in the mucoid strain during exposure to mucin, whereas minimal variation is observed in the nonmucoid strain. Differences between mucoid and nonmucoid strains are consistent with their strain-specific phenology, in which the mucoid strain develops highly protected and withdrawn biofilms that achieve Pseudomonas quinolone signal production under limited conditions.

Spatiotemporal Distribution of Pseudomonas aeruginosa Alkyl Quinolones under Metabolic and Competitive Stress

Alkyl quinolones (AQs), including Pseudomonas quinolone signal (PQS), made by the opportunistic pathogen Pseudomonas aeruginosa have been associated with both population density and stress. The regulation of AQ production is known to be complex, and the stimuli that modulate AQ responses are not fully clear. Here, we have used hyperspectral Raman chemical imaging to examine the temporal and spatial profiles of AQs exhibited by P. aeruginosa under several potentially stressful conditions. We found that metabolic stress, effected by carbon limitation, or competition stress, effected by proximity to other species, resulted in accelerated PQS production. This competition effect did not require cell-to-cell interaction, as evidenced by the fact that the addition of supernatants from either Escherichia coli or Staphylococcus aureus led to early appearance of PQS. Lastly, the fact that these modulations were observed for PQS but not for all AQs suggests a high level of complexity in AQ regulation that remains to be discerned.

Pseudomonas aeruginosa is an opportunistic human pathogen important to diseases such as cystic fibrosis. P. aeruginosa has multiple quorum-sensing (QS) systems, one of which utilizes the signaling molecule 2-heptyl-3-hydroxy-4-quinolone (Pseudomonas quinolone signal [PQS]). Here, we use hyperspectral Raman imaging to elucidate the spatiotemporal PQS distributions that determine how P. aeruginosa regulates surface colonization and its response to both metabolic stress and competition from other bacterial strains. These chemical imaging experiments illustrate the strong link between environmental challenges, such as metabolic stress caused by nutritional limitations or the presence of another bacterial species, and PQS signaling. Metabolic stress elicits a complex response in which limited nutrients induce the bacteria to produce PQS earlier, but the bacteria may also pause PQS production entirely if the nutrient concentration is too low. Separately, coculturing P. aeruginosa in the proximity of another bacterial species, or its culture supernatant, results in earlier production of PQS. However, these differences in PQS appearance are not observed for all alkyl quinolones (AQs) measured; the spatiotemporal response of 2-heptyl-4-hydroxyquinoline N-oxide (HQNO) is highly uniform for most conditions. These insights on the spatiotemporal distributions of quinolones provide additional perspective on the behavior of P. aeruginosa in response to different environmental cues.

IMPORTANCE Alkyl quinolones (AQs), including Pseudomonas quinolone signal (PQS), made by the opportunistic pathogen Pseudomonas aeruginosa have been associated with both population density and stress. The regulation of AQ production is known to be complex, and the stimuli that modulate AQ responses are not fully clear. Here, we have used hyperspectral Raman chemical imaging to examine the temporal and spatial profiles of AQs exhibited by P. aeruginosa under several potentially stressful conditions. We found that metabolic stress, effected by carbon limitation, or competition stress, effected by proximity to other species, resulted in accelerated PQS production. This competition effect did not require cell-to-cell interaction, as evidenced by the fact that the addition of supernatants from either Escherichia coli or Staphylococcus aureus led to early appearance of PQS. Lastly, the fact that these modulations were observed for PQS but not for all AQs suggests a high level of complexity in AQ regulation that remains to be discerned.

Electrochemical Surface-Enhanced Raman Spectroscopy of Pyocyanin Secreted by Pseudomonas aeruginosa Communities

Pyocyanin (PYO) is one of many toxins secreted by the opportunistic human pathogenic bacterium Pseudomonas aeruginosa. Direct detection of PYO in biofilms is crucial because PYO can provide important information about infection-related virulence mechanisms in P. aeruginosa. Because PYO is both redox-active and Raman-active, we seek to simultaneously acquire both spectroscopic and redox state information about PYO. The combination of surface-enhanced Raman spectroscopy (SERS) and voltammetry is used here to provide insights into the molecular redox behavior of PYO while controlling the SERS and electrochemical (EC) response of PYO with external stimuli, such as pH and applied potential. Furthermore, PYO secretion from biofilms of different P. aeruginosa strains is compared. Both SERS spectra and EC behavior are observed to change with pH, and several pH-dependent bands are identified in the SERS spectra, which can potentially be used to probe the local environment. Comparison of the voltammetric behavior of wild-type and a PYO-deficient mutant unequivocally identifies PYO as a major component of the secretome. Spectroelectrochemical studies of the PYO standard reveal decreasing SERS intensities of PYO bands under reducing conditions. Extending these experiments to pellicle biofilms shows similar behavior with applied potential, and SERS imaging indicates that secreted PYO is localized in regions approximately the size of P. aeruginosa cells. The in situ spectroelectrochemical biofilm characterization approach developed here suggests that EC-SERS monitoring of secreted molecules can be used diagnostically and correlated with the progress of infection.

Detection of Pyocyanin Using a New Biodegradable SERS Biosensor Fabricated Using Gold Coated Zein Nanostructures Further Decorated with Gold Nanoparticles

In this paper, a biodegradable gold coated zein film surface enhanced Raman spectroscopy (SERS) platform, with gold nanoparticles (AuNPs) deposited on the surface to further enhance the Raman signal, was used to detect pyocyanin (PYO), the toxin secreted by Pseudomonas aeruginosa. An inverted pyramid structure imprinted on a zein film and gold coated during the transfer process was further improved with the deposition and fixing of gold nanoparticles, which resulted in enhancement of the SERS signal by approximately a decade. This new platform served as a lab-on-a-chip sensor to enable the sensitive and rapid detection of PYO in drinking water. The size, distribution, and morphology of the zein film nanostructures including the presence and distribution of gold nanoparticles were characterized by scanning electron microscopy (SEM). The new zein-based platform has the advantage of being largely biodegradable compared with commercial silicon- or glass-based platforms. The limit of detection for PYO using the newly developed zein-based SERS sensor platform was calculated as 25 μM, considerably lower than the concentration of PYO in the blood of people with cystic fibrosis which has been reported to be 70 μM.

Spatiotemporal Dynamics of Molecular Messaging in Bacterial Co-Cultures Studied by Multimodal Chemical Imaging

Microbial community behavior is coupled to a set of genetically-regulated chemical signals that correlate with cell density - the quorum sensing (QS) system - and there is growing appreciation that the QS-regulated behavior of bacteria is chemically, spatially, and temporally complex. In addition, while it has been known for some time that different species use different QS networks, we are beginning to appreciate that different strains of the same bacterial species also differ in their QS networks. Here we combine mass spectrometric imaging (MSI) and confocal Raman microscopy (CRM) approaches to investigate co-cultures involving different strains (FRD1 and PAO1C) of the same species (Pseudomonas aeruginosa) as well as those involving different species (P. aeruginosa and E. coli). Combining MSI and CRM makes it possible to supersede the limits imposed by individual imaging approaches and enables the spatial mapping of individual bacterial species and their microbial products within a mixed bacterial community growing in situ on surfaces. MSI is used to delineate the secretion of a specific rhamnolipid surfactant as well as alkyl quinolone (AQ) messengers between FRD1 and PAO1C strains of P. aeruginosa, showing that the spatial distribution and production rate of AQ messengers in PAO1C far outstrips that of FRD1. In the case of multiple species, CRM is used to show that the prolific secretion of AQs by the PAO1C strain of P. aeruginosa is used to mediate its interaction with co-cultured E. coli.

Quantitative SIMS Imaging of Agar-Based Microbial Communities

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.