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

mSphere ◽  
2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Cristina García-Timermans ◽  
Ruben Props ◽  
Boris Zacchetti ◽  
Myrsini Sakarika ◽  
Frank Delvigne ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Raman Spectra ◽  
Phenotypic Diversity ◽  
Cell Permeability ◽  
Microbial Populations ◽  
Molecular Profile ◽  
Microbial Cells ◽  
Content Type ◽  
Stressed Cells

ABSTRACT 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.

scholarly journals Raman spectroscopy-based measurements of single-cell phenotypic diversity in microbial communities

2020 ◽  
Author(s):  
Cristina García-Timermans ◽  
Ruben Props ◽  
Boris Zacchetti ◽  
Myrsini Sakarika ◽  
Frank Delvigne ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Microbial Communities ◽  
Single Cell ◽  
Raman Spectra ◽  
Phenotypic Diversity ◽  
Single Cells ◽  
Cell Permeability ◽  
Molecular Profile ◽  
Cell Physiology ◽  
Physiological Changes

AbstractMicrobial 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 other processes such as stress tolerance, virulence or cell physiology. Metabolic stress is one such physiological changes and is typically quantified by measuring community phenotypic properties such as biomass growth, reactive oxygen species or cell permeability. However, community measurements do not take into account single-cell phenotypic diversity, important for a better understanding and management of microbial populations. Raman spectroscopy is a non-destructive alternative that provides detailed information on the biochemical make-up 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 non-treated. 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 composition 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 communities.ImportanceMicrobes that live in the same community respond differently to stress. This phenomemon is known as phenotypic diversity. Describing this plethora of expressions can help to better understand and manage microbial processes. However, most tools to study phenotypic diversity only average the behaviour of the community. In this work, we present a way to quantify the phenotypic diversity of single cells using Raman spectroscopy - a tool that can describe the molecular profile of microbes. We demonstrate how this tool can be used to quantify the phenotypic diversity that arises after the exposure of microbes to stress. We also show its potential as an ‘alarm’ system to detect when communities are changing into a ‘stressed’ type.

scholarly journals Raman Spectroscopy as a Potential Tool for Detection of Brucella spp. in Milk

2012 ◽  
Vol 78 (16) ◽  
pp. 5575-5583 ◽  
Author(s):  
Susann Meisel ◽  
Stephan Stöckel ◽  
Mandy Elschner ◽  
Falk Melzer ◽  
Petra Rösch ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Raman Spectra ◽  
Detection System ◽  
Support Vector ◽  
Promising Alternative ◽  
Content Type ◽  
Micro Raman Spectroscopy ◽  
Genotypic Characteristics ◽  
Potential Tool

ABSTRACTDetection ofBrucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possibleBrucellaisolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identifyBrucellafrom agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of differentBrucella,Escherichia,Ochrobactrum,Pseudomonas, andYersiniaspp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% forBrucellafrom medium and 94% forBrucellafrom milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detectingBrucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.

scholarly journals Evidence for Phenotypic Plasticity among Multihost Campylobacter jejuni and C. coli Lineages, Obtained Using Ribosomal Multilocus Sequence Typing and Raman Spectroscopy

2012 ◽  
Vol 79 (3) ◽  
pp. 965-973 ◽  
Author(s):  
Daniel S. Read ◽  
Dan J. Woodcock ◽  
Norval J. C. Strachan ◽  
Kenneth J. Forbes ◽  
Frances M. Colles ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectra ◽  
Campylobacter Jejuni ◽  
Multilocus Sequence Typing ◽  
Clonal Complex ◽  
Phenotypic Characterization ◽  
Spectrometric Analysis ◽  
Content Type ◽  
Automatic Relevance Determination ◽  
Clonal Origin

ABSTRACTClosely related bacterial isolates can display divergent phenotypes. This can limit the usefulness of phylogenetic studies for understanding bacterial ecology and evolution. Here, we compare phenotyping based on Raman spectrometric analysis of cellular composition to phylogenetic classification by ribosomal multilocus sequence typing (rMLST) in 108 isolates of the zoonotic pathogensCampylobacter jejuniandC. coli. Automatic relevance determination (ARD) was used to identify informative peaks in the Raman spectra that could be used to distinguish strains in taxonomic and host source groups (species, clade, clonal complex, and isolate source/host). Phenotypic characterization based on Raman spectra showed a degree of agreement with genotypic classification using rMLST, with segregation accuracy between species (83.95%), clade (inC. coli, 98.41%), and, to some extent, clonal complex (86.89%C. jejuniST-21 and ST-45 complexes) being achieved. This confirmed the utility of Raman spectroscopy for lineage classification and the correlation between genotypic and phenotypic classification. In parallel analysis, relatively distantly related isolates (different clonal complexes) were assigned the correct host origin irrespective of the clonal origin (74.07 to 96.97% accuracy) based upon different Raman peaks. This suggests that the phenotypic characteristics, from which the phenotypic signal is derived, are not fixed by clonal descent but are influenced by the host environment and change as strains move between hosts.

scholarly journals Proteorhodopsin Overproduction Enhances the Long-Term Viability of Escherichia coli

2019 ◽  
Vol 86 (1) ◽  
Author(s):  
Yizhi Song ◽  
Michaël L. Cartron ◽  
Philip J. Jackson ◽  
Paul A. Davison ◽  
Mark J. Dickman ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Raman Spectroscopy ◽  
Cell Membrane ◽  
Single Cell ◽  
Marine Bacteria ◽  
Membrane Area ◽  
Content Type ◽  
E Coli ◽  
Wide Range

ABSTRACT Genes encoding the photoreactive protein proteorhodopsin (PR) have been found in a wide range of marine bacterial species, reflecting the significant contribution that PR makes to energy flux and carbon cycling in ocean ecosystems. PR can also confer advantages to enhance the ability of marine bacteria to survive periods of starvation. Here, we investigate the effect of heterologously produced PR on the viability of Escherichia coli. Quantitative mass spectrometry shows that E. coli, exogenously supplied with the retinal cofactor, assembles as many as 187,000 holo-PR molecules per cell, accounting for approximately 47% of the membrane area; even cells with no retinal synthesize ∼148,000 apo-PR molecules per cell. We show that populations of E. coli cells containing PR exhibit significantly extended viability over many weeks, and we use single-cell Raman spectroscopy (SCRS) to detect holo-PR in 9-month-old cells. SCRS shows that such cells, even incubated in the dark and therefore with inactive PR, maintain cellular levels of DNA and RNA and avoid deterioration of the cytoplasmic membrane, a likely basis for extended viability. The substantial proportion of the E. coli membrane required to accommodate high levels of PR likely fosters extensive intermolecular contacts, suggested to physically stabilize the cell membrane and impart a long-term benefit manifested as extended viability in the dark. We propose that marine bacteria could benefit similarly from a high PR content, with a stabilized cell membrane extending survival when those bacteria experience periods of severe nutrient or light limitation in the oceans. IMPORTANCE Proteorhodopsin (PR) is part of a diverse, abundant, and widespread superfamily of photoreactive proteins, the microbial rhodopsins. PR, a light-driven proton pump, enhances the ability of the marine bacterium Vibrio strain AND4 to survive and recover from periods of starvation, and heterologously produced PR extends the viability of nutrient-limited Shewanella oneidensis. We show that heterologously produced PR enhances the viability of E. coli cultures over long periods of several weeks and use single-cell Raman spectroscopy (SCRS) to detect PR in 9-month-old cells. We identify a densely packed and consequently stabilized cell membrane as the likely basis for extended viability. Similar considerations are suggested to apply to marine bacteria, for which high PR levels represent a significant investment in scarce metabolic resources. PR-stabilized cell membranes in marine bacteria are proposed to keep a population viable during extended periods of light or nutrient limitation, until conditions improve.

scholarly journals Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities

2019 ◽  
Vol 85 (8) ◽  
Author(s):  
Jasmine Heyse ◽  
Benjamin Buysschaert ◽  
Ruben Props ◽  
Peter Rubbens ◽  
Andre G. Skirtach ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Raman Spectroscopy ◽  
Single Cell ◽  
Phenotypic Diversity ◽  
Microbial Interactions ◽  
Phenotypic Heterogeneity ◽  
Bacterial Populations ◽  
The Individual ◽  
Axenic Conditions ◽  
The Impact

ABSTRACT Isogenic bacterial populations are known to exhibit phenotypic heterogeneity at the single-cell level. Because of difficulties in assessing the phenotypic heterogeneity of a single taxon in a mixed community, the importance of this deeper level of organization remains relatively unknown for natural communities. In this study, we have used membrane-based microcosms that allow the probing of the phenotypic heterogeneity of a single taxon while interacting with a synthetic or natural community. Individual taxa were studied under axenic conditions, as members of a coculture with physical separation, and as a mixed culture. Phenotypic heterogeneity was assessed through both flow cytometry and Raman spectroscopy. Using this setup, we investigated the effect of microbial interactions on the individual phenotypic heterogeneities of two interacting drinking water isolates. Through flow cytometry we have demonstrated that interactions between these bacteria lead to a reduction of their individual phenotypic diversities and that this adjustment is conditional on the bacterial taxon. Single-cell Raman spectroscopy confirmed a taxon-dependent phenotypic shift due to the interaction. In conclusion, our data suggest that bacterial interactions may be a general driver of phenotypic heterogeneity in mixed microbial populations. IMPORTANCE Laboratory studies have shown the impact of phenotypic heterogeneity on the survival and functionality of isogenic populations. Because phenotypic heterogeneity plays an important role in pathogenicity and virulence, antibiotic resistance, biotechnological applications, and ecosystem properties, it is crucial to understand its influencing factors. An unanswered question is whether bacteria in mixed communities influence the phenotypic heterogeneity of their community partners. We found that coculturing bacteria leads to a reduction in their individual phenotypic heterogeneities, which led us to the hypothesis that the individual phenotypic diversity of a taxon is dependent on the community composition.

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

The Analyst ◽  
2020 ◽  
Vol 145 (9) ◽  
pp. 3297-3305 ◽  
Author(s):  
Yaoyao Liu ◽  
Jingjing Xu ◽  
Yi Tao ◽  
Teng Fang ◽  
Wenbin Du ◽  
...  
Keyword(s):  
Neural Networks ◽  
Raman Spectroscopy ◽  
Single Cell ◽  
Raman Spectra ◽  
Convolutional Neural Networks ◽  
Marine Microbes ◽  
Accurate Identification ◽  
One Dimensional

Rapid and accurate identification of individual microorganisms using single-cell Raman spectra combining with one-dimensional convolutional neural networks.

scholarly journals Direct Observation of the Dynamics of Single-Cell Metabolic Activity during Microbial Diauxic Growth

mBio ◽  
2020 ◽  
Vol 11 (2) ◽  
Author(s):  
H. L. O. McClelland ◽  
C. Jones ◽  
L. M. Chubiz ◽  
D. A. Fike ◽  
A. S. Bradley
Keyword(s):  
Single Cell ◽  
Metabolic Activity ◽  
Single Cells ◽  
Indirect Evidence ◽  
Biomedical Science ◽  
Microbial Populations ◽  
Diurnal Changes ◽  
Diauxic Growth ◽  
Content Type ◽  
Regulatory Cascade

ABSTRACT Population-level analyses are rapidly becoming inadequate to answer many of biomedical science and microbial ecology’s most pressing questions. The role of microbial populations within ecosystems and the evolutionary selective pressure on individuals depend fundamentally on the metabolic activity of single cells. Yet, many existing single-cell technologies provide only indirect evidence of metabolic specialization because they rely on correlations between transcription and phenotype established at the level of the population to infer activity. In this study, we take a top-down approach using isotope labels and secondary ion mass spectrometry to track the uptake of carbon and nitrogen atoms from different sources into biomass and directly observe dynamic changes in anabolic specialization at the level of single cells. We investigate the classic microbiological phenomenon of diauxic growth at the single-cell level in the model methylotroph Methylobacterium extorquens. In nature, this organism inhabits the phyllosphere, where it experiences diurnal changes in the available carbon substrates, necessitating an overhaul of central carbon metabolism. We show that the population exhibits a unimodal response to the changing availability of viable substrates, a conclusion that supports the canonical model but has thus far been supported by only indirect evidence. We anticipate that the ability to monitor the dynamics of anabolism in individual cells directly will have important applications across the fields of ecology, medicine, and biogeochemistry, especially where regulation downstream of transcription has the potential to manifest as heterogeneity that would be undetectable with other existing single-cell approaches. IMPORTANCE Understanding how genetic information is realized as the behavior of individual cells is a long-term goal of biology but represents a significant technological challenge. In clonal microbial populations, variation in gene regulation is often interpreted as metabolic heterogeneity. This follows the central dogma of biology, in which information flows from DNA to RNA to protein and ultimately manifests as activity. At present, DNA and RNA can be characterized in single cells, but the abundance and activity of proteins cannot. Inferences about metabolic activity usually therefore rely on the assumption that transcription reflects activity. By tracking the atoms from which they build their biomass, we make direct observations of growth rate and substrate specialization in individual cells throughout a period of growth in a changing environment. This approach allows the flow of information from DNA to be constrained from the distal end of the regulatory cascade and will become an essential tool in the rapidly advancing field of single-cell metabolism.

scholarly journals Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman Spectroscopy

2021 ◽  
Vol 22 (19) ◽  
pp. 10481
Author(s):  
Aikaterini Pistiki ◽  
Anuradha Ramoji ◽  
Oleg Ryabchykov ◽  
Daniel Thomas-Rüddel ◽  
Adrian T. Press ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Raman Spectra ◽  
Fungal Pathogens ◽  
Infection Model ◽  
Label Free ◽  
Analytical Technique ◽  
Monocytes And Lymphocytes

Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lymphocytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lymphocytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the monocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be explained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells.

Submicron Simultaneous IR and Raman Spectroscopy (IR+Raman): Breakthrough Developments in Optical Photothermal IR (O-PTIR) Combined for Enhanced Failure Analysis

2019 ◽  
Author(s):  
Jay Anderson ◽  
Mustafa Kansiz ◽  
Michael Lo ◽  
Curtis Marcott
Keyword(s):  
Raman Spectroscopy ◽  
Failure Analysis ◽  
Data Quality ◽  
Raman Spectra ◽  
Spatial Resolution ◽  
Far Field ◽  
Field Mode ◽  
Microscopic Scale ◽  
Analytical Tools ◽  
Ir And Raman

Abstract Failure analysis of organics at the microscopic scale is an increasingly important requirement, with traditional analytical tools such as FTIR and Raman microscopy, having significant limitations in either spatial resolution or data quality. We introduce here a new method of obtaining Infrared microspectroscopic information, at the submicron level in reflection (far-field) mode, called Optical-Photothermal Infrared (O-PTIR) spectroscopy, that can also generate simultaneous Raman spectra, from the same spot, at the same time and with the same spatial resolution. This novel combination of these two correlative techniques can be considered to be complimentary and confirmatory, in which the IR confirms the Raman result and vice-versa, to yield more accurate and therefore more confident organic unknowns analysis.

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