Raman
Raman
China; 2Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong,
People’s Republic of China; 3Department of Clinical Laboratory, Shenzhen Hospital of Southern Medical University, Guangzhou, Guangdong, People’s
Republic of China
Correspondence: Ling Yang, Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou,
Guangdong, 510120, People’s Republic of China, Tel/Fax +86-20-83062158, Email jykresearch@126.com; Dingqiang Chen, Microbiome Medicine
Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, People’s Republic of
For personal use only.
Background: Antibiotic resistance represents a serious global health challenge, particularly with the emergence of strains resistant to
last-resort antibiotics such as tigecycline, polymyxin B, and vancomycin. Urgent measures are required to alleviate this situation. To
facilitate the judicious use of antibiotics, rapid and precise antimicrobial susceptibility testing (AST) is essential. Heavy water
(deuterium oxide, D2O)-labeled Raman spectroscopy has emerged as a promising time-saving tool for microbiological testing.
Methods: Deuterium incorporation and experimental conditions were examined to develop and apply a Raman-based AST method to
evaluate the efficacy of last-resort antibiotics, including tigecycline, polymyxin B, and vancomycin, against Escherichia coli,
Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterococcus faecium. Essential agreement and categorical agreement were
used to assess the metabolism inactivation concentration based on Raman spectroscopy (R-MIC)–a new metric developed in this study
—and minimum inhibitory concentration (MIC) determined via the traditional microdilution broth method. Spearman’s rank correla
tion coefficient was employed to measure the association between R-MIC and MIC values.
Results: The Raman-based AST method achieved a 100% categorical agreement (92/92) with the traditional microdilution broth
method within five hours, while the traditional method required approximately 24 h. The R-MIC values shared 68.5% (63/92)
consistency with the MIC values. In addition, the R-MIC and MIC values were highly correlated (Spearman’s r=0.96), resulting in an
essential agreement of 100%.
Conclusion: Our optimized experimental method and conditions indicate that Raman-based AST holds great promise as a solution to
overcome the time-consuming challenges of traditional AST methods.
Keywords: Raman spectroscopy, tigecycline resistant, polymyxin B resistant, vancomycin resistant, antimicrobial susceptibility
testing
Introduction
The global spread of antimicrobial resistance genes and the resultant emergence of drug-resistant bacterial strains has
become a major concern in recent decades.1 In 2017, the World Health Organization (WHO) compiled a list of priority
pathogens,2 designating Pseudomonas aeruginosa (P. aeruginosa), Enterobacteriaceae, and Enterococcus faecium as
critical or high priority tiers. Current treatment options for these antimicrobial-resistant pathogens are limited to last-
resort antibiotics, including polymyxin B,3 tigecycline,4 and vancomycin.5 Fast and accurate antimicrobial susceptibility
testing (AST) results are needed to prescribe appropriate antibiotics that can deal with the infection problem and ease the
drug-resistant struggle; misuse of antibiotics may worsen the current situation. Moreover, early identification of “superb
ugs” that are non-susceptible to last-resort antibiotics is crucial for prevention and control. However, the culture-
dependent AST method currently in use is time consuming and labor intensive. In addition, although the VITEK-2
COMPACT system—an automated AST instrument—can facilitate the process, it is not suitable for all clinically used
antimicrobials, such as tigecycline6 and polymyxin B.7
Several rapid identification methods based on genotype have been developed, which offer the advantages of being
culture-independent and capable of revealing drug-resistant mechanisms. However, these methods do exhibit certain
limitations. For instance, despite the occurrence of genotype-phenotype discrepancies,8 genotypic approaches overlook
the complex interaction between bacteria and antibiotics.9 Moreover, our limited understanding of numerous drug
resistance genes and mutations10 presents a major obstacle to their clinical application. In recent years, vibrational
spectroscopy-based methods, particularly Raman spectroscopy, have emerged as a promising approach in microbiology,
with the potential to provide detailed biochemical information11 (eg, nucleic acid, protein, lipid) of individual cells
in situ, which is unique for different species.12 Raman spectroscopy involves the measurement of scattering spectra,
wherein incident light interacts with particles and generates scattered light with different wavelengths, resulting in the
formation of the Raman spectrum. Raman spectroscopy offers several advantages, including that it is non-destructive,13
time saving, and can investigate individual cells.14
Single-cell Raman spectra consist of a specific number of Raman peaks, with different peaks representing distinct
wavelength positions and corresponding intensities. The vibration of particular molecular bonds or groups is associated
with specific spectral peaks. Thus, the Raman spectrum serves as a unique “fingerprint” of a specific sample, providing
a clear insight into the biological macromolecules such as lipids, proteins, and nucleic acids within cells at the single-cell
level. The fingerprint region of Raman spectra has been utilized in combination with machine learning to identify
microorganisms cultured from various samples, including urine,11 blood,15 and environmental samples.16 The Raman
silent region (1800–2800 cm−1) shows no detectable band, while the C-H band region displays an exclusive band that
reflects the presence of C-Hx. The addition of isotope labeling has rendered Raman-based technology more versatile and
less complex, and deuterium is a popular choice of isotope owing to its availability, stability, and cost-effectiveness. The
process of heavy water (deuterium oxide, D2O) labeling17 is straightforward, as active microbial cells can incorporate
deuterium from D2O, leading to the synthesis of deuterium-labeled macromolecules and the appearance of a significantly
broad band in the silent region of Raman spectra, reflecting the substitution of C-Hx by C-Dx.18
In the past few years, extensive research on the combination of deuterium labeling and Raman spectroscopy has led to
increasing reports on D2O-labeled Raman-based methods for AST. The tracking of the incorporation of D2O19 showed
that it was possible to study metabolism in active microorganisms using D2O as a probe. After only 20 minutes of
incubation in D2O-containing media, a visible carbon-deuterium (C-D) characteristic band appeared on the Raman
spectrum (2040–2300 cm−1). In terms of AST, when exposed to antibiotics, susceptible strains experience inhibited
metabolism and cannot incorporate deuterium. The D2O-Raman method has been used to measure the metabolic activity
of five different types of oral bacteria in response to sodium fluoride (NaF), chlorhexidine (CHX), and ampicillin.20
Additionally, a new concept called MIC-MA (Minimum Inhibitory Concentration based on Metabolic Activity) has been
proposed to distinguish Raman-based AST from the traditional MIC. The MIC-MA varies significantly from the MIC.
A more formal protocol for the determination of single-cell metabolism inactivation concentration (SC-MIC) within 2.5
h was reported in 2020.21 The SC-MIC, obtained from this Raman-based AST protocol, shared 94.6% categorical
agreement with the MIC obtained from the traditional AST method. Despite the insufficiency of antibiotics selected for
each strain in the study, the findings represented a significant breakthrough in Raman-based AST research. Subsequent
studies have continued to build on this progress. A fast Raman-assisted antibiotic susceptibility test (FRAST)22 could
directly obtain MICs (for various common antibiotics) from urine or blood samples within 3 hours and 21 hours,
respectively, with an overall agreement of 88%. However, although D2O-Raman has demonstrated its practicality, it is
rarely used in systematic AST for polymyxin B, tigecycline, and vancomycin.
This study focused on last-resort antibiotics and aimed to establish a protocol for Raman-based AST. A new metric—
the minimum metabolism inactivation concentration based on the Raman spectra (R-MIC)—was developed to quantify
strain susceptibility. R-MIC is defined as the minimum concentration of antibiotic required to inactivate metabolism of
a strain. Several clinically isolated strains with varying susceptibilities to polymyxin B, tigecycline, and vancomycin
were collected to verify the reliability of this method for discriminating susceptible and non-susceptible strains.
Compared with traditional AST, our Raman-based AST using R-MIC could identify strains that were non-susceptible to
tigecycline and vancomycin and strains non-resistant to polymyxin B, after only 4 h of incubation, with 100% categorical
agreement. The R-MIC results were in 100% essential agreement with conventional MIC results.
S I R
All Raman measurements were conducted using the Clinical Antimicrobial Susceptibility Test Ramanometry (CAST-
R) instrument (Qingdao Single-cell Biotech, CN) with a grating of 600 g/mm and an acquisition time of 3 seconds.; the
laser power was set to 60 mW.
Excel, SPSS software (version 25.0), and Graphpad Prism (version 8) were used for statistical analysis and data
visualization.
Results
Strain Collection and AST
A total of 80 strains isolated from clinical samples were collected, along with 3 laboratory-induced drug-resistant strains—a
tigecycline-resistant strain of K. pneumoniae (Kp-InR48), a polymyxin B-resistant strain of K. pneumoniae (Kp-InR37), and
a polymyxin B-resistant strain of P. aeruginosa (Pa-InR389). Five sets of pathogen-antibiotic samples (Table 1) that have
marked clinical significance were examined. Strains were obtained from urine, feces, sputum, blood, or other samples. Clinical
information of the collected strains and their corresponding MIC results are detailed in Table S1.
The study included 19 strains that were non-susceptible to tigecycline, 4 strains that were resistant to polymyxin B,
and 6 strains that were non-susceptible to vancomycin.
Figure 1 The Raman spectrum at C-D band and the corresponding images of Escherichia coli after D2O incubation for 3 hours under 0.5mg/L tigecycline. (A) Image of strain
R4 under 0.5mg/L tigecycline. (B) Image of strain ATCC 25922 under 0.5mg/L tigecycline pressure. (C) The Raman spectrum at C-D band. The blue triangle represents the
C-D band of strain R4.
Figure 2 Deuterium labeling in the Raman-based AST method. (A) Growth curve of E. coli ATCC 25922 with and without deuterium. (B) CD-ratio of E. coli ATCC 25922
incubated in medium containing 0% (blue boxes) and medium containing 30% D2O(red boxes) for 4 h. (C) CD-ratio of ATCC 29212 incubated in cation-adjusted MHB medium
(CAMHB) for 7 h. (D) CD-ratio of ATCC 29212 incubated in CAMHB and brain heart infusion (BHI) broth, respectively.
within the first 4 hours. Thus, 30% D2O was selected as the optimal concentration for subsequent bacterial experiments in
this study. The specific D2O incubation time, combined with antibiotic pretreatment time, requires further testing on both
susceptible and resistant strains.
The growth pattern of Enterococcus was studied separately as there was no detectable deuterium signal when
Enterococcus faecalis ATCC 29212 was incubated in CAMHB, with a mean CD-ratio under 0.02, which was similar
to the 0% D2O group of Escherichia coli ATCC 25922 (Figure 2C). BHI broth is a nutritional medium for microorganism
enrichment. We found that Enterococcus faecalis incubated in BHI broth could absorb D2O and exhibit a detectable
C-D peak. The CD-ratio of Enterococcus faecalis ATCC 29212 cultured in BHI broth showed a significant increase
compared with that of the CAMHB culture (Figure 2D).
Figure 3 Raman testing on four different preincubation-incubation time combinations with Escherichia coli. (A) CD-ratio comparison of tigecycline-susceptible strain (ATCC
25922) and tigecycline-resistant strain (R4) incubated with 0.5 mg/L tigecycline using different preincubation-incubation combinations. Incubation methods A, B, and D were
preincubation for 1 h, followed by D2O incubation for 1, 2, and 3 h, respectively. Incubation method C consisted of preincubation for 2 h followed by D2O incubation for 2 h. (B–
E) ROC curves of schemes A–D, respectively.
K. pneumoniae-Polymyxin B group had the lowest consistency with 30.7%. The agreement between MIC and R-MIC is
summarized in Tables 3–8 show the agreement of R-MIC and MIC for each of the five sets of pathogen-antibiotic
combinations. All of the results fell within the grey shading, yielding high EA. The categorical results were calculated in
Table 9 and 10 based on the referenced breakpoints.
Discussion
The emergence of strains that are resistant to last-resort antibiotics is a major global concern in healthcare.25–28 These
resistant strains often carry genes that can be transferred between different species, leading to large-scale outbreaks and
Figure 4 Establishment of a Raman-based antimicrobial susceptibility testing (AST) method. (A) Workflow of the Raman-based AST. (B) CD-ratio of 20 strains of Escherichia
coli. Blue boxes indicate strains identified as susceptible, and the red boxes indicate otherwise.
increased prevalence of antibiotic resistance.29 It is critical to identify this type of resistant strain from the outset when
treating a clinical infection. In this study, we investigated the characteristics of deuterium incorporation and developed
a rapid and accurate approach to identify the antibiotic susceptibility of bacterial strains. Our Raman-based AST method
yielded results in just 5 hours (incubation for 4 hours and 1 hour of sediment washing and spectrum collection).
Importantly, the method showed 100% CA with traditional AST, but was significantly faster, reducing the time needed by
79.2%. Furthermore, there is potential to apply this Raman-based AST directly to clinical specimens, such as urine or
blood.19 In comparison, traditional AST is limited in its ability to identify persistent30 or heteroresistant31 cells.
Despite the widespread attention and applications of Raman-based detection methods, particularly in combination with
deuterium labeling, antibiotics of last resort have not been thoroughly investigated, mainly owing to limitations in access to
resistant strains. However, the isolation of strains that are resistant to these antibiotics, and even pandrug-resistant bacteria, is
Notes: The higher the CD-ratio, the darker the box. The last column shows the consistency of MIC and R-MIC; circles indicate that the R-MIC was consistent with the MIC
and the arrows indicate that the R-MIC was higher than the MIC. Bold black frames indicate the R-MIC values.
increasing globally.32 The selection of tigecycline, polymyxin B, and vancomycin in this study was based on several factors.
First, these antibiotics have different mechanisms of action. Second, resistance to these antibiotics is increasing in drug
resistance surveillance. Finally, it is critical to promptly detect pathogens that are non-susceptible to these drugs in clinical
practice. This study included 29 strains resistant to tigecycline, polymyxin B, or vancomycin, supplementing the current
vacancy of the establishment of the Raman-based AST method, especially for tigecycline. The study encompassed not only
clinically isolated strains, but also tigecycline-resistant K. pneumoniae, polymyxin B-resistant K. pneumoniae, and polymyxin
B-resistant P. aeruginosa strains that were induced in the laboratory.
Two different culture media were employed in this study, namely CAMHB and BHI broth, with CAMHB being
recommended by CLSI for AST. However, owing to the slow growth and metabolism-dependent characteristics of
Enterococcus strains, deuterium incorporation was inadequate in this medium. Consequently, BHI broth was employed for
Enterococcus strains and although these strains absorbed less D2O than other strains included in this study, a detectable
C-D vibrational band was still evident in the Raman spectra. There are no published studies comparing the impact of different
culture media, such as CAMHB and BHI broth, on Raman spectra, but previous research has shown that the growth medium
and growth phase can affect Raman spectra when analyzed by machine learning.33 The D2O-labeling technology enables us to
focus on the C-D and C-H bands, and the calculation of CD-ratio using RStudio provides a simple means to quantify the
incorporation of deuterium. Moreover, given that the growth patterns of microorganisms may differ between CAMHB and
BHI broth, we separated the groups according to the culture medium used and established different cutoff values. Our findings
indicate that BHI broth could be considered for other slow-growing microorganisms in future Raman research, although the
relative metabolic results may not be directly comparable when culture media vary.
Our Raman-based method yielded R-MICs that exhibited only 68.5% (63/92) consistency compared with traditional
MICs. However, the traditional method relies on growth, whereas the Raman-based AST method is metabolism-
dependent; therefore, it is reasonable to expect some variability between the two methods. In our study, the R-MICs
Figure 5 R-MIC determination from Raman-based AST method. (A) CD-ratio of Escherichia coli Ec764 treated with different concentrations of tigecycline. (B) CD-ratio of
K. pneumoniae Kp302 treated with different concentrations of tigecycline. (C) CD-ratio of P. aeruginosa Pa555 treated with different concentrations of polymyxin B. (D) CD-
ratio of Enterococcus faecium Ef11 treated with different concentrations of vancomycin. Dotted lines represent the cutoff values (upper limit of 99% reference interval).
achieved 100% CA without any ME or VME, indicating that there were no false-susceptible or false-resistant results and
every result was categorized accurately.34
The consistency of R-MIC results for different pathogen-antibacterial combinations varied when compared with the
MIC results obtained by the microdilution broth method. The combinations of P. aeruginosa-polymyxin B,
K. pneumoniae-tigecycline, and Enterococcus faecium-vancomycin exhibited higher consistency between R-MIC and
MIC results, whereas the consistency was lower in the Escherichia coli-tigecycline and K. pneumoniae-polymyxin
B combinations. In the Escherichia coli-tigecycline group, there was no significant trend in the difference between
R-MIC and MIC, but in the K. pneumoniae-polymyxin B combination, the R-MIC was one gradient concentration lower
than the MIC. Two discordant results were observed in the P. aeruginosa-polymyxin B combination, where the R-MIC
was also one gradient concentration smaller than the MIC. This difference may be attributed to the mechanism of action
0.625
0.125 2 9 1
0.25 3 5 1
0.5 1 1
1 1
2 1
4 1 3
8 2 3 1
16 1 2
Notes: The gray shadings indicate the R-MIC and MIC have 100% essential agreement.
0.25 2
0.5 1 2
1 1
2 2
8 2
(≥)16 1 1
Notes: The gray shadings indicate the R-MIC and MIC have 100% essential agreement.
of polymyxin B, which binds to lipopolysaccharide (LPS), disrupting the integrity of the bacterial outer membrane,
increasing permeability, and causing cell rupture. Such a mechanism may significantly impact microorganism metabo
lism in a short period, causing a significant decrease in R-MIC compared to MIC. Moreover, most of the collected strains
had MICs of 1 mg/L, which could also contribute to the discordance observed in the polymyxin B group.
Although the Raman-based AST method proposed in this paper shows potential, there are several limitations to our study.
First, the number of included antibiotics was limited, and it is not known whether this method can be applied to other commonly
used antibiotics in clinical practice. Second, the selected research strains were limited to Escherichia coli, K. pneumoniae,
P. aeruginosa, and Enterococcus faecium, and several other common clinical pathogens, such as Acinetobacter baumannii,
Enterococcus faecalis, and Staphylococcus aureus, were not included in this research. Third, the distribution of MIC values of the
collected strains was not dispersed. For example, in the Enterococcus faecium-vancomycin group, the MIC values of strains of
Enterococcus faecium were distributed in four concentrations (0.5, 1, 2, and ≥ 64 mg/L), and strains with other MIC values were
missing. Future in-depth studies should include more strains and collect data to address these limitations.
1 2 4 8 (≥)16
1 8
2 2
8 1
(≥)16 2
Notes: The gray shadings indicate the R-MIC and MIC have 100% essential agreement.
1 2 4 8
1 10 2
2 1
8 1
Notes: The gray shadings indicate the R-MIC and MIC have 100% essential agreement.
0.5 1 2 4 8 16 32 (≥)64
0.5 1
1 4
2 3 1
16
32
(≥)64 6
Notes: The gray shadings indicate the R-MIC and MIC have 100% essential agreement.
Susceptible 40 0 40
Non-susceptible 0 25 25
Sum 40 25 65
Resistant 4 0 4
Non-resistant 0 23 23
Sum 4 23 27
Conclusion
The Raman-based AST method described in this study shows great potential in meeting the current need for rapid AST in
clinical settings. Among the pathogen-antibiotic sets studied, this method demonstrated a high ability to examine the
antimicrobial susceptibility within 5 hours. Moreover, the EA between MIC and R-MIC was 100%. However, further
clinical investigations are required to validate and popularize this new method.
Ethics Statement
The procedure was approved by the Ethics Committee of Zhujiang Hospital of Southern Medical University (No. 2021-
KY-046-01). The study focused on previously isolated bacteria and did not involve direct contact with patients or
personal information. Therefore, the informed consent was waived.
Author Contributions
All authors made a significant contribution to the work reported, whether that was in the conception, study design,
execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically
reviewing the article; gave final approval of the version to be published; agreed on the journal to which the article has
been submitted; and agree to be accountable for all aspects of the work.
Funding
This work was supported by grants from the National Natural Science Foundation of China (No. 81974318), China
Primary Health Care Foundation (No. MTP2022D027), Guangzhou Municipal Science and Technology Bureau
(No. 202102010233), Guangdong Zhong Nanshan Medical Foundation (No. 20220015), and the Research Foundation
of Shenzhen Hospital of Southern Medical University (No. PY2020YM02 and ZDXKKYTS007).
Disclosure
The authors report no conflicts of interest in this work.
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