Faster-growing bacteria released more purine metabolites than slower-growing onesMost purine moieties in E. coli are predominantly found in several key molecules, particularly RNA species (Supplementary Table S1). In bacteria, the intracellular levels of ATP and RNA species generally exhibit a positive correlation with their growth rates10,21. This suggests that bacteria might release more purine metabolites if ATP and RNA species are indeed the primary molecular sources of dominant SERS peaks.To investigate this hypothesis, we cultured E. coli in either a nutrient-rich medium (MHB) or a minimal medium (M9 with glucose). The observed doubling times during the exponential phase were approximately 25–30 min in MHB and 50–60 min in M9, respectively (Fig. 1a). Upon harvesting an equal volume of both cultures at OD600 ~ 0.5, followed by washing and soaking in double-distilled water (ddH2O), we found that cells cultured in MHB released significantly more purine metabolites in SERS-based analyses compared to those cultured in M9 with glucose (Fig. 1b). Additionally, RNA extraction revealed that MHB-cultured cells had about 1.4 times higher RNA content than those cultured in M9 with glucose (Fig. 1c).Figure 1Influence of growth rate on SERS signals and RNA content in E. coli. (a) Growth curves of E. coli cultivated in either MHB or M9 with glucose. Samples collected at OD600 ~ 0.5 (marked by arrows) underwent washing for SERS measurements (b) and RNA extraction (c). (b) The bacteria were washed, immersed in ddH2O, and incubated at 37℃ for 30 min. SERS spectra were obtained from supernatants post-centrifugation to remove bacteria. (c) Rapid RNA extraction from 400 μL of each culture was performed using the RNA snap â„¢ method; the extracted RNA was resuspended in 120 μL and quantified using a NanoDrop spectrophotometer. The data represent the mean ± SD of three experiments.These findings corroborate the hypothesis that faster-growing bacteria with higher RNA concentrations can release greater quantities of purine metabolites following water washing compared to their slower-growing counterparts with lesser RNA. However, given the significant variation in purine content across ATP and different RNA species, the specific contributions of these species to SERS signals warrant further investigation.SERS detection of purine derivatives in the m-M9 mediumGiven the distinct turnover rates of ATP and RNA species, analyzing the time-dependent changes in SERS signatures post-washing could elucidate the origins of purine metabolites. To circumvent the potential side effects of multiple washing cycles before SERS measurement, we utilized a chemically defined medium devoid of purine derivatives, m-M9. This medium, a modification of the M9 minimal medium, was optimized by replacing two main chlorine-containing components to reduce its suppression of SERS detection sensitivity, particularly for hypoxanthine (Supplementary Fig. S2). The suppression is likely due to chloride ions competing with analytes for adsorption on the silver substrate.We validated the capability of detecting purine derivatives in m-M9 by measuring SERS spectra of 10−5 M solutions of adenine, hypoxanthine, guanine, or xanthine, prepared either in ddH2O or m-M9. In ddH2O (Fig. 2a), adenine displayed characteristic dominant peaks at 732 and 1333 cm−1, while hypoxanthine exhibited peaks at 739 and 1317 cm−1. Guanine and xanthine both showed dominant peaks at 658 cm−1. The assignments of these major purine derivative bands have been well documented in the literature1,28,29,30,31,32. Signals at around 925 and 970 cm−1, possibly originating from AgSO2, Ag2SO3, and Ag2SO4 formed on the Ag/AAO SERS substrate during fabrication (Supplementary Fig. S3), were excluded from the analysis33,34,35.Figure 2SERS detection of purine derivatives in m-M9 medium. The SERS spectra of purine derivatives (10–5 M) in ddH2O (a) and m-M9 (b). Key peaks corresponding to various purine derivatives are enumerated.In the m-M9 medium, components produced broad spectra in the ranges of 520–630 and 890–1140 cm−1, obscuring the signals of purine derivatives (Fig. 2b). Adenine and hypoxanthine in m-M9 showed additional dominant peaks at 735 and 743 cm−1, respectively, shifting by 3–4 cm−1 compared to their aqueous solutions. Another hypoxanthine’s peak also shifted from 1317 to 1323 cm−1, and adenine’s 1333 cm−1 peak in aqueous solution became a broad spectrum in m-M9. The dominant peaks of guanine and xanthine shifted slightly from 658 to 660 cm−1 (Fig. 2b).Thus, these results confirm that SERS can detect several major peaks of E. coli purine metabolites in situ in the m-M9 medium. The observed peak shifts between preparations in ddH2O and m-M9 could be attributed to interactions with m-M9 medium components. It is also important to note that other factors, such as analyte concentration and environmental pH, are known to influence peak positions36,37.Time-dependent release of purine derivatives and RNA integrity after washingTo assess the rapidity of E. coli’s response to water washing, we pelleted cells cultured in m-M9 with glucose, resuspended them in ddH2O, and obtained bacterium-free supernatants using 0.2 μm syringe filters to minimize operational time. Although omitting multiple washing steps in sample preparation raised concerns about residual medium influence, especially at initial time points, this method allowed sample harvesting within 10 s post-ddH2O addition.Figure 3a reveals that major peaks, characteristic of hypoxanthine at 742 and 1322 cm−1, along with minor peaks associated with other purine derivatives, were present immediately at the first sampling point (i.e., 10 s). These signals were notably above background levels in five out of six independent experiments, as measured against controls of ddH2O or m-M9 (Fig. 3b). Intriguingly, several tests showed a transient decrease in the intensity of the 742 cm−1 peak between 2 and 5 min, followed by a resurgence to higher signal intensities (Fig. 3b). Additionally, a shoulder peak at approximately 733 cm−1 appeared at 60 min, potentially indicative of increased release of hypoxanthine and/or adenine (Fig. 3a).Figure 3Temporal dynamics of purine derivative release in starved E. coli. (a) SERS spectra derived from E. coli cultured in m-M9 with glucose, subsequently centrifuged and resuspended in ddH2O. Samples from the cell suspensions were taken at the specified time intervals, filtered using 0.2 μm syringe filters to eliminate bacteria, and the filtrates were analyzed to obtain spectra. (b) The peak intensities at 742 cm–1 from six experiments are illustrated. To normalize for variations in sensitivity among SERS substrates, intensities in each experiment were adjusted by setting the intensity at the 60-min mark to 1. The gray shaded areas approximately below 40 a.u. denote the background intensities at 742 cm–1, ascertained using ddH2O or m-M9. The spectra corresponding to the experiment marked by an arrow are displayed in (a).Considering these observations and the known rapid turnover rate of E. coli’s ATP under starvation conditions10,11, the immediate signals post-water washing could be attributed to swift ATP degradation. E. coli has been reported to uptake extracellular purine derivatives within the first few minutes of starvation38, which could transiently diminish extracellular SERS signatures. However, it is hypothesized that the immediately released metabolites from ATP degradation might be eliminated in the 2–3 washing cycles typically employed in SERS analysis of bacteria. Consequently, the primary molecular sources are likely attributed to the subsequent degradation of RNA, which gradually amplified the SERS signal intensities following bacterial soaking in ddH2O.To investigate RNA species degradation post-soaking in ddH2O, we rapidly extracted total RNA using the RNA snap â„¢ method and analyzed it through electrophoresis. As depicted in Fig. 4a, major rRNA bands (23S and 16S rRNAs in E. coli) remained largely intact for several hours post-washing, exceeding the typical 10–20 min washing duration in SERS-based bacterial analysis.Figure 4RNA degradation in starved E. coli. (a) E. coli was washed, soaked in ddH2O at 37℃, and RNA was extracted at the specified time points using the RNA snap â„¢ method for electrophoresis analysis. Notable bands, likely representing 23S, 16S, 5S rRNA, and tRNAs, are identified. (b) Alterations in the relative abundances of two mRNAs (gapA and rpsS) and one tRNA (ileV) following washing and soaking in ddH2O are presented. At designated times, total RNA was purified, converted to cDNA via reverse transcription. The relative cDNA abundance of each target compared to the 16S rRNA was quantified using semi-quantitative PCR. The data depict changes in relative abundances, with the baseline (t = 0 min) set to 100%. The data represent the mean ± SD of three experiments.Furthermore, the degradation of mRNA and tRNA was examined via semi-quantitative PCR, using 16S rRNA as a reference (Fig. 4b). Within 20 min post-washing, representative mRNAs (gapA and rpsS) degraded to approximately 25–35%, while a representative tRNA (ileV) degraded to about 15%. Notably, the half-lives of various mRNA and tRNA species vary, with most ranging from a few to tens of minutes12. The selected mRNAs, gapA and rpsS, represent some of E. coli’s most abundant mRNAs during the log phase and have half-lives near the average, around 5.5 min12.These results suggest that ATP degradation occurs rapidly post-water washing, followed by mRNA and tRNA degradation. Such degradation is likely to transpire during the bacterial preparation for SERS analysis, typically lasting from a few to tens of minutes, depending on the protocol. The purine content in ATP, mRNA, and tRNA is estimated at around 106–107 molecules per cell (Supplementary Table S1), corresponding with the level of released purine derivatives observed in our previous study3. Conversely, rRNA species, which harbor the highest intracellular purine content, generally remain intact post-water washing. If rRNA were to degrade and be released, bacteria could potentially yield considerably more intense SERS signals.RNA degradation by acid depurination enhanced SERS signal intensitiesPurine metabolites released after water washing are thought to arise from enzymatic reactions. However, nucleic acids can also release nucleobases through non-enzymatic reactions, such as acid depurination, which involves breaking glycosidic bonds under specific conditions like heating in acidic environments39,40.To induce acid depurination, we added HCl to the E. coli culture to achieve final concentrations ranging from 0.1 to 0.3 M and incubated at 95℃. The sample was then cooled to room temperature and neutralized to approximately pH 7 using NaOH to prevent the strong acid from degrading the SERS substrate’s performance and causing peak position shifts. Considering E. coli’s mesophilic nature and non-acidophilic characteristics, these conditions are likely detrimental to most cellular proteins, indicating that purine derivatives released under these conditions are probably not products of active purine metabolism.SERS analysis of the bacterium-free supernatants revealed that heating in 0.3 M HCl for 30–60 min produced the highest signal intensities (Fig. 5a), surpassing those observed following water washing. Dominant peaks at 734 and 1329 cm−1 suggested the release of adenine as a result of acid depurination. Rapid RNA extraction and electrophoresis further confirmed the near-complete absence of intact rRNA bands post-acid depurination (Fig. 5b).Figure 5Effects of extreme heating in strong acid on purine derivative signals and RNA degradation in E. coli. (a) E. coli cultured in m-M9 with glucose was treated with 0.1–0.3 M HCl at 95℃ for either 30 or 60 min, cooled, and neutralized. Samples were adjusted to the same final volumes, centrifuged to remove bacteria, and analyzed by SERS. (b) RNA was extracted pre- or post-treatments using the RNA snap â„¢ method for electrophoresis analysis. Major bands, likely representing 23S, 16S, 5S rRNA, and tRNAs, are indicated. The HCl-treated samples were analyzed on the same gel shown in Fig. 4a; the control image used was identical.To better understand the relationship between SERS signal intensity and the concentration of analytes, we quantified the relative amount of released purine derivatives by measuring signals from HCl-treated samples after various dilutions with water. Figures 6a and b show that the intensity of the HCl-treated sample, after approximately a 40-fold dilution, was comparable to that of bacteria soaked in ddH2O. This suggests that acid treatment led to the release of about 40 times more purine derivatives compared to water washing. The enhancement in signal intensity was not due to the presence of HCl in the sample. This is because the acidity was neutralized by NaOH prior to the SERS measurements, and the presence of chloride ions could potentially reduce, rather than amplify, the signal intensities of purine derivatives in our system.Figure 6Substantial increase in purine derivative release following intense heating of bacteria in strong acid. (a) E. coli cultured in m-M9 with glucose underwent either washing and soaking in ddH2O or treatment with 0.3 M HCl at 95℃, followed by cooling and neutralization. The samples were normalized to the same final volumes, centrifuged to exclude bacteria, and analyzed using SERS. (b) Peak intensities at 734 or 743 cm–1, including those from the HCl-treated sample after various dilutions before measurements. (c) Staphylococcus sp., P. aeruginosa, or M. tuberculosis were subjected to similar treatments as in (a) for SERS analysis.Acid depurination was also applied to other bacterial species, including Staphylococcus sp., Pseudomonas aeruginosa, and Mycobacterium tuberculosis. These latter two species typically exhibit low signal intensities following water washing. As demonstrated in Fig. 6c, acid depurination consistently produced higher SERS signals compared to water washing across all tested species. Therefore, we infer that only a minor fraction of intracellular purine-containing molecules undergo degradation and release after water washing. In contrast, a sample preparation approach that includes rRNA degradation could significantly amplify SERS signal intensities.Release of purine derivatives after mild heatingThis finding spurred the hypothesis that other treatments that trigger RNA degradation and leave the purine degradation machinery intact might also induce the release of purine metabolites. The employment of a chemically defined medium facilitated the monitoring of purine metabolite release from E. coli in response to various stressors, such as temperature changes.When the temperature for E. coli cultured in m-M9 with glucose was raised from 37℃ to 50℃, slightly above its optimal growth range, a marked increase in SERS signal intensities at 658, 734, and 1329 cm−1 was observed in the culture supernatant within 10 min (Fig. 7a). Such mild heating in salt solutions can facilitate rRNA degradation (Fig. 7b). The distinct dominant peak at 743 cm−1 observed post-water washing, as opposed to the major 733–734 cm−1 peak induced by mild heating (Fig. 7a), suggests that different metabolic pathways or mechanisms are activated under varying conditions. However, peak intensities diminished when cells were subjected to 60 °C, although rRNA degradation was still extensive (Fig. 7a and b). This suggests that at higher temperatures, enzymes in the purine metabolic pathway might become thermolabile and stop producing small-molecule end products.Figure 7Enhanced rRNA degradation and purine metabolite release from bacteria due to mild heating in salt solutions. (a) E. coli, cultured in m-M9 with glucose, was either directly heated at 50 or 60℃ for 10 min or washed and incubated in ddH2O at 37℃ for 10 min. SERS spectra were obtained from the solutions post-centrifugation to eliminate bacteria. (b) RNA was extracted from samples before and after heating using the RNA snap â„¢ method for electrophoresis analysis. Significant bands, likely representing 23S, 16S, 5S rRNA, and tRNAs, are indicated.While many RNases remain active even after cellular damage, enzymes involved in subsequent purine degradation pathways might be differentially sensitive to environmental factors such as salt conditions, temperature, and pH. This could lead to a shift in metabolic pathway selection, potentially affecting the efficient production or release of small molecule end products. Therefore, rRNA degradation in damaged cells may not directly correlate with the observed SERS signatures. It is also crucial to recognize that these responses can significantly vary across different bacterial species due to genetic diversity. This highlights the complexity and variability in bacterial responses to environmental stressors and the consequent impact on purine metabolism and SERS signal profiles.
