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Reverse and multiple stable isotope probing to study bacterial metabolism and interactions at the single cell level Yun Wang, Yizhi Song, Yifan Tao, Howbeer Muhamadali, Royston Goodacre, Ning-Yi Zhou, Gail M. Preston, Jian Xu, and Wei E. Huang Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b01602 • Publication Date (Web): 02 Sep 2016 Downloaded from http://pubs.acs.org on September 3, 2016

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Analytical Chemistry

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Reverse and multiple stable isotope probing to study bacterial metabolism and interactions at the single cell level

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Yun Wang1, Yizhi Song2, Yifan Tao3, Howbeer Muhamadali4, Royston Goodacre4, Ning-Yi Zhou5, Gail M. Preston6, Jian Xu1*, Wei E. Huang2*

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1. CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics and Single Cell Center, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, P. R. China. 2. Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, United Kingdom. 3. Department of Operative Dentistry and Endodontics, Guanghua School and Hospital of Stomatology, Sun Yat-sen University, Guangzhou, 510055, China. 4. School of Chemistry, Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, United Kingdom. 5. State Key Laboratory of Microbial Metabolism and School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China 6. Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, United Kingdom. *Corresponding author: Wei E. Huang and Jian Xu [email protected] (Wei E, Huang) Telephone: +44 (0)1865 283786, Fax: +44 (0)1865 374992

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ABSTRACT

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The interactions between microorganisms driven by substrate metabolism and energy flow are important

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to shape diversity, abundance, and structure of a microbial community. Single cell technologies are

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useful tools for dissecting the functions of individual members and their interactions in microbial

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communities. Here, we developed a novel Raman stable isotope probing (Raman-SIP), which uses

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Raman micro-spectroscopy coupled with reverse and D2O co-labelling to study metabolic interactions in

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a two-species community consisting of Acinetobacter baylyi ADP1 and Escherichia coli. This Raman-

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SIP approach is able to detect carbon assimilation and general metabolic activity simultaneously. Taking

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advantage of Raman shift of single cell Raman spectra (SCRS) mediated by incorporation of stable-

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isotopic substrates, Raman-SIP with reverse labelling has been applied to detect initially

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bands of ADP1 SCRS reverting back to

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D2O labelling has been employed to probe metabolic activity of single cells without the need of cell

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replication. Our results show that E. coli alone in minimal medium with citrate as the sole carbon source

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had no metabolic activity, but became metabolically active in the presence of ADP1. Mass

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spectrometry-based metabolite footprint analysis suggests that putrescine and phenylalanine excreted by

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ADP1 cells may support the metabolic activity of E. coli. This study demonstrates that Raman-SIP with

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reverse labelling would be a useful tool to probe metabolism of any carbon substrate, overcoming

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limitations when stable isotopic substrates are not readily available. It is also found that Raman-SIP with

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D2O labelling is a sensitive and reliable approach to distinguish metabolically active cells but not

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quiescent cells. This novel approach extends the application of Raman-SIP and demonstrates its

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potential application as a valuable strategic approach for probing cellular metabolism, metabolic activity

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and interactions in microbial communities at the single cell level.

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C positions in the presence of

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C-labelled

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C citrate. Raman-SIP with

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Introduction

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Microorganisms play fundamental roles during natural biogeochemical cycles of the biosphere and

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human biological processes, and thus studying their functions and activity in situ is of great importance1.

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In natural environment, microorganisms usually exist in complex communities, so substrate metabolism

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and energy flow in these communities are inevitably intertwined by competition and cooperation among

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community members2. Although biological, physical, and chemical interactions have significant impact

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on structure, diversity and stability of a microbial community, the metabolic interactions of cells in

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these communities are important drivers to microbial interactions3.

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Metagenomics provide an overall picture of microbial diversity, abundance, structure and the potential

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functional genes present in a natural community4,5. The next questions are what the active functions of

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individual members in a community are and how they interact2. The majority (over 99%) of

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microorganisms in the natural environment are not yet cultivated under laboratory conditions6 and cell

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phenotypes and behaviour are usually different in pure culture compared to their biological context in

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microbial communities. Moreover, functional validation cannot be achieved without an effective

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strategy for identification of cellular phenotypes7. These challenges emphasise the importance of single

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cell study of microbial metabolism and their interactions within communities 8,9.

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The application of single cell technologies may provide further insights into microbial communities,

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allowing linkage of specific metabolic activities to the relevant community members. To date, single

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cell technologies have been applied to diverse ecological niches including marine10, freshwater11, soil12

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and human subgingival crevice13 etc. Among these single cell techniques, Raman micro-spectroscopy is

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a label-free and non-destructive tool, compared to fluorescence-based approaches and mass

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spectrometry (MS), enabling the biochemical investigation of microbes in their natural habitat14. A

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single cell Raman spectrum (SCRS) is defined as the ‘bio-chemical fingerprint’ of a cell, which reflects

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comprehensive intrinsic biochemical information. Combination of Raman micro-spectroscopy with

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stable isotope labelling (Raman-SIP) has been demonstrated to be a promising approach for

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understanding the complex metabolic behaviour of various microbial communities, as some Raman

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bands of SCRS shift to lower wavenumbers when

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cells15-18. Raman-SIP has been applied to probe substrate-specific metabolic pathways17-19 and carbon

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flow in a food chain20. One problem is that many isotope substrates are either unavailable (for example

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there is no 13C fully labelled citrate) or very expensive. Initial labelling of cells using readily available

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Another problem is that 13C- Raman-SIP alone may not be adequate to study metabolism, as metabolic

C substrates (e.g.

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13

C and

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N from substrates are incorporated into

C-glucose) and then detecting reverse shift of SCRS may overcome the problem.

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activity can be independent on carbon substrate incorporation. This leads to the insensitivity of

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C-

Raman-SIP to detect cellular metabolic activity for substrate turnover when there is insufficient carbon incorporation. However, the application of heavy water (D2O) to probe microbial community may be sensitive enough to unravel general metabolic activity without cell reproduction21. In this study, we applied Raman-SIP with

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C-reverse and D2O co-labelling to monitor substrate

metabolism, cell activity and their interactions of a two-species community consisting of Acinetobacter baylyi ADP1 and Escherichia coli DH5α-GFP. Whilst Raman-SIP with

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C-reverse labelling revealed

the carbon flow, D2O labelling was used to unravel the energy flow and general metabolic activity. In this reverse labelling process,

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C-substrates (citrate in this study) were introduced into a co-culture in

which all cells were initially 13C- labelled. 13C-cells that can metabolise the 12C-substate were reverted to

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C- cells in a time-dependent manner, which were quantified by Raman reverse-shift in SCRS. E.

coli alone in minimal medium with citrate as the sole carbon source had no metabolic activity, but became metabolically active in the presence of ADP1. Metabolite footprint analysis using gas chromatography-mass spectrometry (GC-MS) confirms the Raman-SIP results.

Experimental methods Strains and growth conditions All chemicals in this study were obtained from Sigma-Aldrich UK. Escherichia coli DH5α-GFP used in this study contained a modified p18GFP plasmid

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which

constitutively expresses a gfp gene. Acinetobacter baylyi ADP1 and DH5α-GFP were cultured in minimal medium (MM)23 supplemented with appropriate carbon sources at 37 oC, with 150 rpm shaking. When required, 100 µg/mL ampicillin was added into the medium to cultivate DH5α-GFP and ADP1 separately or together. Wild type ADP1 can grow in a medium with 100 µg/mL ampicillin because it contains a gene encoding AmpC β-lactamase in the chromosome24. MM with 5 g/L glucose (MMG) of 12

C-D-glucose/99% uniformly labelled

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C-D-glucose or 10 mM citrate (MMC) were used to cultivate

cells. MMC with a final concentration of 40% ‘heavy water’ (D2O, 99.9 atom% D, Sigma-Aldrich, Germany) was used for the deuterium labelling experiment. To examine cell growth, ADP1 and DH5α-GFP were initially incubated in LB with ampicillin (100 µg/mL) overnight. Cells were then harvested by centrifugation at 3000 ×g and washed twice with minimal medium and resuspended in the same volume of MM. Then 250 µL of the cell suspension were inoculated into 5 mL of MM or MMC. Aliquots (200 µL) of the inoculated media were transferred into 4 Environment ACS Paragon Plus

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a 96-well plate and the growth profiles were recorded by measuring the optical density at 600 nm every 15 mins using a microplate reader (Synergy HT, BioTek). Five biological replicates were carried out for each condition. A schematic of co-culture experiment using reverse and D2O labelling is shown in Fig. S1. Generally, 12

C- ,

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C- cells of ADP1, DH5α-GFP or mixture of ADP1 – DH5α-GFP grown in

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C- or

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C-MMG

overnight were washed, diluted with 1:10 by MM and introduced into 20 mL of MMC with 100 µg/mL of ampicillin with or without 40% D2O in the form of either pure culture or co-culture. Cell counting was performed using a hemocytometer under fluorescent Raman microscope25. In the co-culture, DH5αGFP cells contain constitutively expressed green fluorescent protein (GFP), thus can be readily distinguished from ADP1 under a Raman-fluorescent microscope17. The initial cell densities of ADP1 and DH5α-GFP were ca. 0.7×108 and 1.1×108 CFU/mL separately. Co-culture cells were incubated on a shaker at 37 oC, 120 rpm and sampled at 0, 1, 2, 4 and 7 h for Raman measurement. The supernatants were collected and stored at -80 oC for metabolic footprint analysis, described in details below. Three biological replicates were carried out for each condition. Raman micro-spectroscopy analysis All of the cell samples were washed with dionised water three times to remove the culture medium. Cell density was adjusted accordingly to ensure sufficient dispersion of individual cells on the slide. After washing and re-suspending, a 1.5 µL cell suspension was transferred onto a calcium fluoride (CaF2) slide and air-dried prior to Raman analysis. Raman spectra were obtained using a modified confocal Raman-fluorescent microscope based on LabRam HR (Horiba Ltd, UK) as previously described25. A 100× magnifying dry objective (NA = 0.90, Olympus, UK) was used for sample observation and Raman signal acquisition. A 532 nm Nd:YAG laser (Ventus, Laser Quantum Ltd, UK) was used as the light source for Raman measurement, and the power on the sample was 3-5 mW. The acquisition time for each spectrum was 10 s. The scattered photons were collected by a Newton EMCCD (DU970N-BV, Andor, UK). A 300 grooves/mm diffraction grating was used for most of the measurements unless otherwise stated, resulting in a spectral resolution of ~ 2 cm-1 with 1581 data points spanning the range 394-3341 cm-1. Data analysis of Raman spectra The Raman spectra were processed by background subtraction (using spectra of the cell free regions on the same slide), baseline correction and normalization using the Labspec5 software (HORIBA Jobin Yvon Ltd, UK) before further analysis. For quantification of the degree of D substitution in C-H bonds (%C-D), the bands assigned to C-D (2,040-2,300 cm-1) and C-H (2,800-3,100 cm-1) were calculated 5 Environment ACS Paragon Plus

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using integration of the specified region21. Since the presence of D2O made the ~1006 cm-1 band (C-C aromatic ring stretching of phenylalanine26) split into two sharp bands (~1006 and 994 cm-1), integrations of the region 1001-1009 cm-1 and 987-995 cm-1 were combined together to indicate -1

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C

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replacement, while integration of the region 963-971 cm was used to represent C incorporation. Metabolic footprint analysis Samples were taken from each of the growth conditions as 500 µL aliquots and centrifuged at 4 °C, 5000 ×g for 10 min using a microcentrifuge (5415R, Eppendorf). The supernatants were transferred into new microcentrifuge tubes, flash frozen in liquid nitrogen for 1 min, and stored at -80 oC until further analysis. Cell pellets were discarded. Upon analysis, 50 µL aliquots from each of the samples were combined in a new 15 mL Falcon tube to be used as quality control (QC) samples27. Internal standard solution (0.2 mg mL-1 succinic-d4 acid, 0.2 mg mL-1 glycine-d5, 0.2 mg mL-1 benzoic-d5 acid, and 0.2 mg mL-1 lysine-d4) was added as 100 µL aliquot to all the samples (including QCs), followed by an overnight drying step using a speed vacuum concentrator (Concentrator 5301, Eppendorf, Cambridge, UK). The dried pellets were derivatized following a two-step procedure, which include: oximation (using methoxyamine-hydrochloride in pyridine) followed by a silylation step (using N-Methyl-N(trimethylsilyl) trifluoroacetamide)28. All derivatized samples were analysed using a Gerstel MPS-2 autosampler (Gerstel, Baltimore, MD), on an Agilent 6890N GC oven (Wokingham, UK) coupled to a Leco Pegasus III mass spectrometer (St Joseph, USA) following previously published methods29-30. Leco ChromaTOF software was employed to de-convolute the data, and subsequent identification of the peaks was carried out using an in-house library (Table S1), and following metabolomics standard initiative (MSI) guidelines31.

Results Reverse labelling for pure cultures of A. baylyi ADP1 and E. coli DH5α-GFP SCRS of

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C-labelled ADP1 and DH5α-GFP bacteria showed

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C characteristic Raman bands at 785

cm-1 (ring breathing modes in the DNA/RNA bases), 1006 cm-1 (ring breathing mode of benzene ring compounds; most notably from phenylalanine), 1666 cm-1 (protein band vibrations) and 2938 cm-1 (C-H vibration) (Fig. S2A, S2B and Table 1). Correspondingly, SCRS of 13C-labelled ADP1 and DH5α-GFP had 13C-shifted Raman bands at 772, 970, 1623 and 2930 cm-1, indicating complete 13C-substitution in cells (Fig. 1A, 1B and Table 1). Figure S3 shows SCRS of A. baylyi ADP1 and E. coli DH5α-GFP without labeling and with only 2H or 13C labeling as well as both labeling. Cells of 13C-fully labelled A. baylyi ADP1 and E. coli DH5α-GFP were separately prepared by growth in MM with 13C-D-glucose as 6 Environment ACS Paragon Plus

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the sole carbon source. Cells were grown 16 h overnight to ensure full incorporation of 13C into the cells. Then these 13C-labelled ADP1 and DH5α-GFP bacteria were transferred into fresh MMC to examine (so called) reverse labelling. After 7 h of incubation, those initial 13C-characteristic Raman bands of SCRS in ADP1 were reverted back to 12C-positions at 785, 1006, 1666 and 2938 cm-1 (Fig. 1A and Table 1), indicating that

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C in ADP1 cells has been replaced by

source. When 40% D2O is added, apart from the above

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C from citrate, which was the sole carbon

C-reverse bands, ADP1 cells also displayed

additional bands at 994 and 2187 cm-1 which are the results of the incorporation of D into benzene ring and C-D formation (Fig. 1A and Table 1). Since A. baylyi ADP1 is able to grow by using citrate as a sole carbon source whilst E. coli DH5α-GFP cannot use citrate under aerobic condition32-33 (Fig. S4), the SCRS of DH5α-GFP did not show any changes after 7 h of incubation in MMC (Fig. 1B), which confirms the inability of DH5α-GFP to assimilate citrate. The results of reverse labelling and D2Ocombined labelling are consistent (Fig. 1), suggesting that this strategy could link Raman spectra to carbon assimilation and general metabolic activity at the single cell level. SCRS dynamics of reverse labelling in the co-culture of A. baylyi ADP1 and E. coli DH5α-GFP SCRS of ADP1 and DH5α-GFP in their mixed co-culture with or without 40% D2O were sampled and measured separately. In the co-culture, cells of E. coli DH5α-GFP were distinguishable from A. baylyi ADP1 cells as they showed fluorescence (Fig. S5). Time-course SCRS of

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C-labelled A. baylyi ADP1 and

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C- E. coli DH5α-GFP, which were co-

incubated in MMC as a control, did not show any observable change of their SCRS throughout the whole time course (Fig. 2A and 3A). By contrast, cells in the co-culture starting from

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C-labelled

ADP1 and 13C-labelled DH5α-GFP bacteria in MMC performed differently. In 7 h of incubation, 13C in the ADP1 cells was gradually replaced by 12C, causing reverse shifts from 13C Raman bands at 770, 970, 1623, and 2930 cm-1 back to 12C Raman bands at 785, 1006, 1666, and 2938 cm-1 (Fig. 2B and Table 1). The SCRS reverse shift of 13C-labelled DH5α-GFP was inconclusive (Fig. 3B), suggesting the weak 12C substitution in

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C- DH5α-GFP cells if there are any. These findings are consistent with the cell

counting results of ADP1 and DH5α-GFP in the co-culture, which indicate that while ADP1 cells were multiplying, DH5α-GFP cells had no observable growth during the 7 h of co-cultivation (Fig. S6). Interestingly, the SCRS under the co-culture condition with D2O (40%) suggest that both ADP1 and DH5α-GFP were metabolically active in co-culture. SCRS showed that the C-D band around 2187 cm-1 was present after just 1 h for ADP1 (Fig. 2C) and after 4 h for DH5α-GFP (Fig. 3C). The C-D band around 2187 cm-1 has been used previously as an indicator of general metabolic activity in cells

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. In

addition, lipid bands at 1126 and 1168 also shifted to 1104 cm-1 due to deuterium incorporation (Fig. 2C, 3C and Table 1). Although E. coli DH5α-GFP in MMC can neither grow nor show any metabolic 7 Environment ACS Paragon Plus

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activity (Fig. S3 and Fig. 1B), DH5α-GFP in the presence of ADP1 in co-culture displays clear metabolic activity (Fig. 3C). The delay of its general metabolic activity after 4 h suggests that DH5αGFP may consume the metabolic byproducts of ADP1 which are excreted in the co-culture medium. Double probing (reverse 13C-labelling and D2O probing) was also applied to the co-culture starting from 13

C- ADP1 and

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C- DH5α-GFP with 40% D2O in MMC. These results show that in the initial

characteristic bands in SCRS of ADP1 shifted back to

13

C

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C positions, and the C-D band at 2187 cm-1

appeared after 1 h of incubation (Fig. 2D). It was also observed that DH5α-GFP became active after 2 h in the presence of ADP1 (Fig. 3D). The results of D2O and double labelling suggest that ADP1 metabolites were used by DH5α-GFP to keep cells active but the metabolites were insufficient to support cell reproduction. This is also consistent to the cell counting results (Fig. S6). Dynamics of SCRS characteristic bands in co-culture To measure the reverse shifts and C-D labelling quantitatively and to assess phenotypic heterogeneity of single cells, dynamic ratios of SCRS characteristic bands from ADP1 and DH5α-GFP in the co-culture are plotted in Fig. 4. Each point represents the average SCRS of 30 individual cells with three biological replicates. The relative intensity ratio of 970 to 1006 cm-1 was used to evaluate the

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C- reverse shift,

and the relative intensity ratio of band CD peaked at 2187 cm-1 to CH+CD (2938 cm-1 + 2187 cm -1) to assess general metabolic activity of cells. Integration of a region around the above mentioned wavenumbers was used for calculation (more details are provided in the methods section). It shows that 13

C- labelled vibrations at 970 cm-1 in ADP1 completely shifted back to

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C at 1006 cm-1 after 4 h of

incubation (Fig. 4A), and that DH5α-GFP only partially reversely shifted back (Fig. 4B). The increase of the CD/(CH+CD) ratio in ADP1 can be observed within 1 h and kept increasing in 7 h of incubation, indicating strong metabolic activity (Fig. 4C). The ratio of CD/(CH+CD) in DH5α-GFP also had a clear increase after 4 h, suggesting that DH5α-GFP remained inactive at the beginning, and then became metabolically active with ADP1 when usable energy sources were present in the co-culture (Fig. 4D). Metabolic footprint analysis confirmed that DH5α-GFP used metabolites from ADP1 in the coculture Although DH5α-GFP alone cannot use citrate as the carbon source and it remained inactive in the MMC medium, the D2O labelling results indicate that this E. coli strain had become metabolically active in the presence of ADP1 (Fig. 3C and 3D and 4D). Among the 16 metabolites detected by GC-MS analysis of the footprint samples, putrescine and phenylalanine were abundant in the ADP1 pure culture, while these two metabolites were significantly reduced under the co-culture conditions. It is also worth noting that putrescine was absent in the DH5α-GFP pure culture after incubating in MMC for 7 h (Fig. 5). Prieto-Santos and colleagues34 reported the ability of E. coli cells to utilize putrescine as the sole 8 Environment ACS Paragon Plus

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nitrogen, carbon, and energy source to support growth. These authors suggested that E. coli may catabolize putrescine to γ-amino-butyrate, using putrescine-α-ketoglutarate transaminase and γaminobutyraldehyde dehydrogenase enzymes. Therefore since E. coli is able to catabolize putrescine and phenylalanine 35-36, it is likely that putrescine and phenylalanine produced from ADP1 in the MMC co-culture supported metabolic activity of DH5α-GFP (Fig. 5).

Discussion Reverse labelling overcomes the limits of availability of 13C-substrates It has been previously reported that Raman-SIP is able to link bacterial cells to their ecological functions15,

18, 21, 37

. However, this Raman-SIP technology is usually limited by the availability of

specific stable isotopically labelled substrates. It is also difficult to apply Raman-SIP to study metabolic activity of cells with complex carbon background in environmental samples. This reverse labelling approach is useful to study the metabolic activity of those substrates when isotopically labelled forms are unavailable or excessively expensive. The application of reverse labelling technology relies on the presence of initially labelled cells, which can be achieved by using readily available such as

13

13

C- compounds

C-D-glucose, or via cross-feeding, which appears much more common in the natural

environment, where communities of bacteria come together to share resources. Here, we have attempted to prove the above concept using a co-culture of ADP1 and DH5α-GFP to metabolise citrate, as the 13Clabelled form of citric acid is not available. Heavy water (D2O) incorporation is a universally sensitive approach to indicate general metabolic activity in single cells It is well known that E. coli is unable to use citrate as an energy source under aerobic conditions due to lacking of essential functional genes32-33. The cultivation results of our study confirm that E. coli DH5αGFP is indeed unable to metabolise citrate aerobically, while A. baylyi ADP1 was able to use citrate for growth (Fig. S4). When citrate was employed as the sole carbon source and D2O was added in the culture medium, the C-D peak (2040-2300 cm-1) appeared in SCRS of ADP1 (Fig. 1A), indicating high metabolic activity of ADP1 cells. On the contrary, no C-D peak arose for DH5α-GFP at all, even after 7 h of incubation, confirming its inability to assimilate citrate (Fig. 1B). However, when ADP1 and DH5α-GFP were co-cultivated in MMC, the C-D peak not only appeared in the SCRS of ADP1 (Fig. 2C and 2D), but was also detected in SCRS of DH5α-GFP as soon as 2 h (Fig. 3C and 3D), although no growth of DH5α-GFP was observed during the 7 h of incubation (Fig. S6). The presence of the C-D band reveals incorporation of deuterium from D2O via NADPH/NADH activity, which associates with 9 Environment ACS Paragon Plus

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general metabolic activity of cells. The C-D peak (2040-2300 cm-1) is located at the ‘silent zone’ (18002800 cm-1) which are flat and no Raman bands to usual SCRS. Hence, the C-D band appeared at the ‘silent zone’ can be easily distinguished. The above results suggest that Raman-SIP with D2O labelling could be sensitive and reliable, as it only labelled the live cells that were metabolically active, while inactive cells were unable to incorporate deuterium. Although the high percentage of heavy water could be toxic to plants, animals and humans, heavy water less than 50% has no significant impact on the growth rate of many microbial strains21 including E.coli and A. baylyi in this case (Fig. S7). Thus toxicity is not a limiting factor for application of heavy water in Raman-SIP. Multiple stable isotope probing is able to study single cell metabolism and interactions in a microbial community A number of characteristic bands in SCRS of

13

C-labelled cells such as the benzene ring vibrational

band were suggested as suitable biomarkers to quantitatively indicate the 13C content in single cells 20. After 7 h of incubation of the ADP1 and DH5α-GFP co-culture, SCRS of

13

C-ADP1 show that

characteristic 13C-band at 970 cm-1 reversely shifted back to its corresponding 12C- position at 1006 cm-1 (Fig. 3A), indicating reverse replacement of

13

C by

12

C in cells. However, SCRS of

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C-DH5α-GFP

show insignificant change (Fig. 3B). This is consistent with the cell counting results in the co-culture, which shows that ADP1 significantly grew but the cell number of DH5α-GFP remained unchanged after 7 h (Fig. S6). Interestingly, the CD band in SCRS of DH5α-GFP was detectable after 2 h (Fig. 3D). Raman-SIP with

13

C reverse and D2O double labelling provide two separate insights of carbon

anabolism and general metabolic activity simultaneously at the single cell level. This novel approach is able to differentiate the species responsible for carbon anabolism from those for metabolic activity only. D2O labelling is also sensitive enough to quantitatively distinct strong, weak active and inactive cells. Potentially, reverse labelling of 15N-substrate could also be combined with D2O probing to indicate the nitrogen anabolism as well. Whlist some reports have claimed that A. baylyi would kill active E. coli via bacterial type VI secretion system (T6SS), suggesting a hostile predation between A. baylyi and E. coli

38-39

, others have reported

that E. coli can connect to A. baylyi via membrane derived nanotubes and exchange nutrients40. These reports suggest that entangled metabolic interactions could occur between A. baylyi and E. coli. Our findings demonstrated that E. coli alone in MMC had no metabolic activity, but became active in the presence of A. baylyi (Fig. 1B, 3C and 3D), indicating that E. coli can be activated by taking metabolites excreted from A. baylyi ADP1. Our complementary analyses using MS-based metabolite footprint analysis suggest that putrescine and phenylalanine could be the candidate metabolites that support

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Analytical Chemistry

metabolic activity of E. coli. It suggests that a metabolic interaction- commensalism could happen between A. baylyi and E. coli mediated by carbon and energy flowing via a food-chain. The reverse and multiple stable isotope probing can be used as a culture-independent and semiquantitative approach indicating cell metabolism and interactions at the single cell level. This could be applied to study whether cell general metabolic activity is linked to usage of the 13C-labeled substrate. It might be difficult to apply it to a complex environmental sample when multiple carbon sources are available. In these situations, application of reverse and multiple labelling will become complicated as the cells would incorporate

12

C from other carbon sources and deuterium from D2O. However, such

difficulty can be overcome by setting a time-course and comprehensive controls. For example, cells that are able to metabolise a specific carbon source could be sorted out by identification of cells with intermediate state of labelling (e.g. 50% 12C and 50% 13C) and comparing cells with controls.

Conclusions We have demonstrated a novel Raman-SIP approach coupled with 13C-reverse and D2O co-labelling to study carbon substrate metabolism and microbial interactions in a two-species community. Raman-SIP with reverse labelling would be a useful tool to probe metabolism of any carbon substrates, overcoming limitations when stable isotopic substrates are unavailable. This opens a new door for SIP experiments that cannot be done previously. Raman-SIP with D2O labelling is growth-independent and universal applicable approach, sensitive enough to probe metabolically active cells without the need of cell replication. This will be particularly valuable to study cell metabolism when the nutrients are not rich enough to support cell multiplication or to probe substrate turnover associated with cellular enzyme activity. This Raman-SIP approach represents an important approach for probing cellular substrate metabolism, metabolic activity and interactions simultaneously at the single cell level within microbial communities.

Supporting Information Available: This material is available free of charge via the Internet at http://pubs.acs.org.

Acknowledgements WEH acknowledges support from EPSRC (EP/M002403/1) and NERC (NE/M002934/1) in the UK. YW and JX thank support from NSFC (31400436), CAS (XDB15040100) and Shandong Key Project (2015ZDJS04002) in China. HA and RG thank the European Commission’s Seventh Framework Program for funding (STREPSYNTH; Project No. 613877), and RG is also very grateful to BBSRC for financial support and, in particular, for Raman microscopy (BB/L014823/1). 11 Environment ACS Paragon Plus

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1 2 3 336 4 5 337 6 7 338 8 339 9 340 10341 11342 12 343 13 14344 15345 16346 17347 18348 19 20349 21350 22351 23352 24353 25 354 26 27355 28356 29357 30358 31 359 32 360 33 34361 35362 36363 37364 38 365 39 366 40 41367 42368 43369 44 370 45 46371 47372 48373 49374 50375 51 376 52 53377 54378 55379 56380 57 381 58 382 59 60

REFERENCES 1. Falkowski, P. G.; Fenchel, T..Delong, E. F. Science 2008, 320, 1034-1039. 2. Little, A. E. F.; Robinson, C. J.; Peterson, S. B.; Raffa, K. E..Handelsman, J. Annu Rev Microbiol 2008, 62, 375-401. 3. Grosskopf, T..Soyer, O. S. Curr Opin Microbiol 2014, 18, 72-77. 4. Handelsman, J. Microbiol Mol Biol Rev 2004, 68, 669-685. 5. Tringe, S. G.; von Mering, C.; Kobayashi, A.; Salamov, A. A.; Chen, K.; Chang, H. W.; Podar, M.; Short, J. M.; Mathur, E. J.; Detter, J. C.; Bork, P.; Hugenholtz, P..Rubin, E. M. Science 2005, 308, 554-557. 6. Amann, R. I.; Ludwig, W..Schleifer, K. H. Microbiol Rev 1995, 59, 143-169. 7. Wang, Y.; Chen, Y.; Zhou, Q.; Huang, S.; Ning, K.; Xu, J.; Kalin, R. M.; Rolfe, S..Huang, W. E. Plos One 2012, 7. 8. Marx, V. Nat Methods 2012, 9, 1151-1155. 9. Kalisky, T.; Blainey, P..Quake, S. R. Annu Rev Genet 2011, 45, 431-445. 10. Swan, B. K.; Martinez-Garcia, M.; Preston, C. M.; Sczyrba, A.; Woyke, T.; Lamy, D.; Reinthaler, T.; Poulton, N. J.; Masland, E. D. P.; Gomez, M. L.; Sieracki, M. E.; DeLong, E. F.; Herndl, G. J..Stepanauskas, R. Science 2011, 333, 1296-1300. 11. Garcia, S. L.; McMahon, K. D.; Martinez-Garcia, M.; Srivastava, A.; Sczyrba, A.; Stepanauskas, R.; Grossart, H.-P.; Woyke, T..Warnecke, F. ISME J 2013, 7, 137-147. 12. Kvist, T.; Ahring, B.; Lasken, R..Westermann, P. Appl Microbiol Biotechnol 2007, 74, 926-935. 13. Marcy, Y.; Ouverney, C.; Bik, E. M.; Loesekann, T.; Ivanova, N.; Martin, H. G.; Szeto, E.; Platt, D.; Hugenholtz, P.; Relman, D. A..Quake, S. R. Proc Natl Acad Sci 2007, 104, 11889-11894. 14. Li, M.; Xu, J.; Romero-Gonzalez, M.; Banwart, S. A..Huang, W. E. Curr Opin Biotechnol 2012, 23, 56-63. 15. Huang, W. E.; Ferguson, A.; Singer, A. C.; Lawson, K.; Thompson, I. P.; Kalin, R. M.; Larkin, M. J.; Bailey, M. J..Whiteley, A. S. Appl Environ Microb 2009, 75, 234-241. 16. Huang, W. E.; Griffiths, R. I.; Thompson, I. P.; Bailey, M. J..Whiteley, A. S. Anal Chem 2004, 76, 4452-4458. 17. Huang, W. E.; Stoecker, K.; Griffiths, R.; Newbold, L.; Daims, H.; Whiteley, A. S..Wagner, M. Environ Microbiol 2007, 9, 1878-1889. 18. Li, M.; Canniffe, D. P.; Jackson, P. J.; Davison, P. A.; FitzGerald, S.; Dickman, M. J.; Burgess, J. G.; Hunter, C. N..Huang, W. E. ISME J 2012, 6, 875-885. 19. Kubryk, P.; Koelschbach, J. S.; Marozava, S.; Lueders, T.; Meckenstock, R. U.; Niessner, R..Ivleva, N. P. Anal Chem 2015, 87, 6622-6630. 20. Li, M.; Huang, W. E.; Gibson, C. M.; Fowler, P. W..Jousset, A. Anal Chem 2013, 85, 16421649. 21. Berry, D.; Mader, E.; Lee, T. K.; Woebken, D.; Wang, Y.; Zhu, D.; Palatinszky, M.; Schintimeister, A.; Schmid, M. C.; Hanson, B. T.; Shterzer, N.; Mizrahi, I.; Rauch, I.; Decker, T.; Bocklitz, T.; Popp, J.; Gibson, C. M.; Fowler, P. W.; Huang, W. E..Wagner, M. Proc Natl Acad Sci 2015, 112, E194-E203. 22. Uchiyama, T.; Abe, T.; Ikemura, T..Watanabe, K. Nat Biotech 2005, 23, 88-93. 23. Huang, W. E.; Wang, H.; Zheng, H. J.; Huang, L. F.; Singer, A. C.; Thompson, I..Whiteley, A. S. Environ Microbiol 2005, 7, 1339-1348. 24. Beceiro, A.; Perez-Llarena, F. J.; Perez, A.; del Mar Tomas, M.; Fernandez, A.; Mallo, S.; Villanueva, R..Bou, G. J Antimicrob Chemother 2007, 59, 996-1000. 25. Wang, Y.; Ji, Y.; Wharfe, E. S.; Meadows, R. S.; March, P.; Goodacre, R.; Xu, J..Huang, W. E. Anal Chem 2013, 85, 10697-10701. 12 Environment ACS Paragon Plus

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Analytical Chemistry

26. O Faolain, E.; Hunter, M. B.; Byrne, J. M.; Kelehan, P.; McNamara, M.; Byrne, H. J..Lyng, F. M. Vib Spectrosc 2005, 38, 121-127. 27. Fiehn, O.; Wohlgemuth, G.; Scholz, M.; Kind, T.; Lee, D. Y.; Lu, Y.; Moon, S..Nikolau, B. Plant J 2008, 53, 691-704. 28. Wedge, D. C.; Allwood, J. W.; Dunn, W.; Vaughan, A. A.; Simpson, K.; Brown, M.; Priest, L.; Blackhall, F. H.; Whetton, A. D.; Dive, C..Goodacre, R. Anal Chem 2011, 83, 6689-6697. 29. Begley, P.; Francis-McIntyre, S.; Dunn, W. B.; Broadhurst, D. I.; Halsall, A.; Tseng, A.; Knowles, J.; Goodacre, R.; Kell, D. B..Consortium, H. Anal Chem 2009, 81, 7038-7046. 30. Dunn, W. B.; Broadhurst, D.; Begley, P.; Zelena, E.; Francis-McIntyre, S.; Anderson, N.; Brown, M.; Knowles, J. D.; Halsall, A.; Haselden, J. N.; Nicholls, A. W.; Wilson, I. D.; Kell, D. B.; Goodacre, R..Human Serum Metabolome, H. C. Nat Protoc 2011, 6, 1060-1083. 31. Sumner, L. W.; Amberg, A.; Barrett, D.; Beale, M. H.; Beger, R.; Daykin, C. A.; Fan, T. W. M.; Fiehn, O.; Goodacre, R.; Griffin, J. L.; Hankemeier, T.; Hardy, N.; Harnly, J.; Higashi, R.; Kopka, J.; Lane, A. N.; Lindon, J. C.; Marriott, P.; Nicholls, A. W.; Reily, M. D.; Thaden, J. J..Viant, M. R. Metabolomics 2007, 3, 211-221. 32. Blount, Z. D.; Barrick, J. E.; Davidson, C. J..Lenski, R. E. Nature 2012, 489, 513-518. 33. Lutgens, M..Gottschalk, G. J Gen Microbiol 1980, 119, 63-70. 34. Prieto-Santos, M. I.; Martin-Checa, J.; Balana-Fouce, R..Garrido-Pertierra, A. Biochimica Et Biophysica Acta 1986, 880, 242-244. 35. Kurihara, S.; Tsuboi, Y.; Oda, S.; Kim, H. G.; Kumagai, H..Suzuki, H. J Bacteriol 2009, 191, 2776-2782. 36. Teufel, R.; Mascaraque, V.; Ismail, W.; Voss, M.; Perera, J.; Eisenreich, W.; Haehnel, W..Fuchs, G. Proc Natl Acad Sci 2010, 107, 14390-14395. 37. Zhang, D.; Berry, J. P.; Zhu, D.; Wang, Y.; Chen, Y.; Jiang, B.; Huang, S.; Langford, H.; Li, G.; Davison, P. A.; Xu, J.; Aries, E..Huang, W. E. ISME J 2015, 9, 603-614. 38. Basler, M.; Ho, B. T..Mekalanos, J. J. Cell 2013, 152, 884-894. 39. Shneider, M. M.; Buth, S. A.; Ho, B. T.; Basler, M.; Mekalanos, J. J..Leiman, P. G. Nature 2013, 500, 350-353. 40. Pande, S.; Shitut, S.; Freund, L.; Westermann, M.; Bertels, F.; Colesie, C.; Bischofs, I. B..Kost, C. Nat Commun 2015, 6.

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415

1 500

2 500

3 000

1 000

2930 2930

1623 1623

1623 1623

1623 1623

2930

1623 1623

970 970

772 772 772 772

970 970 970 970

772 772

500

970 970

772 772

2 000

2930

MMC+D2O, 7h MMC+D2O, 0h 13C-DH5α-GFP, MMC+H O, 7h 2 13C-DH5α-GFP, MMC+H O, 0h 2 13C-DH5α-GFP,

2930

1666 1666

2930

1623 1623

2938

2187 2187

1666 1666

13C-DH5α-GFP,

B

1623 1623

1168 1168 1168 1168

1006 1006

1 000

1168 1168

994 1006 1006 1104 1104 1168 1168 970 970

772 772 785 785 772 772

500

970 970

785 785

13C-ADP1,

Intensity (a.u.)

MMC+D2O, 7h MMC+D2O, 0h 13C-ADP1, MMC+H O, 7h 2 13C-ADP1, MMC+H O, 0h 2

2938

13C-ADP1,

A

Intensity (a.u.)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18416 19 417 20 21418 22419 23420 24421 25422 26 423 27 28424 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1 500

2 000

2 500

3 000

Wavenumber (cm-1)

Wavenumber (cm-1)

Figure 1(A) Reverse labelling of A. baylyi ADP1 pure culture. SCRS of 13C-labelled ADP1 cells grown in MMC with/without 40% D2O. After 7 h of incubation, some bands of 13C-SCRS shifted from 772, 970, 1623 and 2930 cm-1 back to 12C-SCRS positions at 785, 1005, 1666 and 2938 cm-1 due to 12C substitution of 13C in cells, and the C-D band appeared around 2187 cm-1 in the presence of 40% D2O; 1(B) Reverse labelling of E. coli DH5α-GFP pure culture. SCRS of 13C-labelled DH5α-GFP cells grown in MMC with/without 40% D2O. After 7 hours of incubation, there was no observable change of 772, 970, 1623 or 2930 cm-1, and no C-D band appeared around 2187 cm-1 in the presence of D2O.

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2938 2938

1666 1666

2930

1623 1623 1623 1623 1623 1623

1h

500

1 500

2 000

Wavenumber

(cm-1)

2 500

3 000

1 000

1 500

2 000

2 500

3 000

2938 2938 2930 2938

2187 2187 2187 2187

1666 1666

2930

2187 2187 2187 2187

1006 1006 1104 1104 1006 1006 1104 1104

1666 1666

785 785 785 785

1104 1104 1168 1168

1623 1623 1623 1623 1666 1666

2h 1h

0h 500

7h 4h

1623 1623

1h

1104 1104 1168 1168

2h

1104 1104 1168 1168

4h

785 785

7h

Intensity (a.u.)

2938 2938 2938

2187 2187 2187 2187

1666 1666 1666 1666

2938

2187 2187

2187 2187

1666 1666 1666 1666 1666 1666

1006 1006 1104 1104 1006 1006 1104 1104 1006 1006

1126 1124 1168 1168

1006 1006 1126 1124 1168 1168 1006 1006 1126 1124 1168 1168

785 785 785 785

785 785 785 785

785 785

1 000

D

2938

C

Intensity (a.u.)

0h

3 000

970 970 1006 1006

2 500

970 970

Wavenumber

(cm-1)

770 772

2 000

970 970

1 500

772 772

1 000

4h 2h

0h 500

7h

2938

1666 1666

1006 1006 1006 1006

785 785 772 772 770 772

1h

970 970 1006 1006

785 785

1666 1666

770 772

2h

970 970 1006 1006

4h

Intensity (a.u.)

2938 2938 2938

7h

970 970 1006 1006

2938

B

2938

1666 1666

1666 1666 1666 1666

1666 1666

1006 1006 1006 1006 1006 1006 1006 1006 1006 1006

785 785

785 785

785 785

785 785

Intensity (a.u.)

785 785

A

2938

425

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16426 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31427 32 33428 34429 35 430 36 431 37 38432 39433 40434 41435 42 436 43 44437 45438 46439 47440 48 441 49 442 50 51443 52 53 54 55 56 57 58 59 60

0h 500

1 000

1 500

2 000

2 500

3 000

Wavenumber (cm-1)

Wavenumber (cm-1)

Figure 2(A) Time-course of A. baylyi ADP1 SCRS from the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC in H2O as a control. During 7 hours of incubation, there was no observable change of 12C-SCRS positions. 2(B) Time-course of 13C-labelled A. baylyi ADP1 SCRS from the coculture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC in H2O. During 7 hours of incubation, some bands of 13C-SCRS gradually shifted from 772, 970, 1623 and 2930 cm-1 back to 12C-SCRS positions at 785, 1005, 1666 and 2938 cm-1. 2(C) Time-course of A. baylyi ADP1 SCRS from the coculture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC with 40% D2O. During 7 h of incubation, There was no observable change of 785, 1006, 1666 or 2938 cm-1. Due to deuterium incorporation, the C-D band appeared at 2187 cm-1 in 1 h and gradually increased its intensity, and lipids bands at 1168 and 1124 cm-1 shifted to 1104 cm-1. 2(D) Time-course of 13C-labelled A. baylyi ADP1 SCRS from the co-culture of A. baylyi ADP1 – E. coli DH5a grown in MMC with 40% D2O. During 7 h of incubation, some bands of 13C-SCRS gradually shifted from 772, 970, 1623 and 2930 cm1 back to 12C-SCRS positions at 785, 1005, 1666 and 2938 cm-1. The C-D band appeared around 2187 cm-1 in 1 h and gradually increased its intensity, and lipid band at 1168 cm-1 shifted to 1104 cm-1.

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3 000

2930 2930

1623 1623

2930

1623 1623

2930

1623 1623 1623 1623

2 000

(cm-1)

2 500

1 000

1 500

2 000

Wavenumber

(cm-1)

2 500

3 000

2930 2930 2930 2930

1623 1623

2187 2187

1623 1623

2187 2187

2930

2187 2187

1623 1623 1623 1623

1104 1104 1168 1168 1104 1104 1168 1168 1104 1104 1168 1168 1126 1126 1168 1168

7h 4h 2h 1h 0h

0h 500

2h

3 000

1623 1623

772 772

1666 1666

1h

1126 1126 1168 1168

772 772 772 772 772 772

2h

772 772

4h

Intensity (a.u.)

7h

970 970

2938 2938 2938

1666 1666

2938

1666 1666

2187 2187

1666 1666

1 500

D

2938

2187 2187

1666 1666

1006 1006 1104 1104 1126 1006 1006

1126 1126 1168 1168

1006 1006 1126 1126 1168 1168 1006 1006 1126 1126 1168 1168 1006 1006

1126 1126 1168 1168

785 785 785 785

785 785 785 785 785 785

1 000

Wavenumber

C

Intensity (a.u.)

500

970 970

Wavenumber

2 500

(cm-1)

970 970

2 000

970 970

1 500

970 970

1 000

4h

0h

0h 500

7h

1h

1623 1623

772 772

970 970 1006 1006 970 1006

772 772 772 772

1666 1666

1h

970 970

772 772 772 772

2h

Intensity (a.u.)

2938 2938 2938

4h

970 970

1666 1666 1666 1666

1666 1666 1666 1666

7h

970 970

2938

B

2938

1006 1006 1006 1006 1006 1006 1006 1006 1006 1006

785 785

785 785

785 785

785 785

Intensity (a.u.)

785 785

A

2930

444

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16445 17 18 19 20 21 22 23 24 25 26 27 28 29 30 446 31 32447 33448 34449 35 450 36 37451 38452 39453 40454 41 455 42 43456 44457 45 458 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

500

1 000

1 500

2 000

Wavenumber

(cm-1)

2 500

3 000

Figure 3(A) Time-course of E. coli DH5a-GFP SCRS from the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC in H2O as a control. During 7 h incubation, there was no observable change of 12C-SCRS positions. 3(B) Time-course of 13C-labelled E. coli DH5a-GFP SCRS from the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC in H2O. During 7 h of incubation, the 13Cphenylalaine band slightly moved from 970 back to 12C-phenylalaine band position at 1006 cm-1, but 772, 1623 and 2930 cm-1 did not shift. 3(C) Time-course of E. coli DH5a-GFP SCRS from the coculture of A. baylyi ADP1 – E. coli DH5a-GFP grown in MMC with 40% D2O. During 7 h of incubation, the C-D band appeared at 2180 cm-1 in 4 h and gradually increased its intensity. 3(D) Time course of 13C-labelled E. coli DH5a-GFP SCRS from the co-culture of A. baylyi ADP1 – E. coli DH5a grown in MMC with 40% D2O. During 7 h of incubation, the 13C-SCRS positions did not shift obviously, and the C-D band appeared at 2187 cm-1 in 2 h.

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459

1.2

A

13C_D2O_ADP1

1

Ratio of 970cm-1/1006cm-1 (13C/12C)

Ratio of 970cm-1/1006 cm-1 (13C/12C)

1.2

12C_D2O_ADP1 13C_H2O_ADP1

0.8

12C_H2O_ADP1

B

1

0.8

0.6

13C_D2O_DH5α-GFP

0.6

0.4

12C_D2O_DH5α-GFP 13C_H2O_DH5α-GFP

0.4

0.2

12C_H2O_DH5α-GFP

0.2

0

0 0

0.3

1

2

3 4 Time (h)

5

6

7

0 0.3

C

1

2

3 4 Time (h)

5

6

7

5

6

7

D

0.2 13C_D2O_ADP1 13C_H2O_ADP1

0.1

12C_D2O_ADP1

CD/(CH+CD)

13C_D2O_DH5α-GFP

CD/(CH+CD)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17460 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33461 34 462 35 463 36 37464 38465 39466 40467 41 42468 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

13C_H2O_DH5α-GFP

0.2

12C_D2O_DH5α-GFP 12C_H2O_DH5α-GFP

0.1

12C_H2O_ADP1

0

0 0

1

2

3 4 Time (h)

5

6

7

0

1

2

3 4 Time (h)

Figure 4(A) Dynamics of 13C replacement by 12C incorporation of ADP1 cells in the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP. 4(B) Dynamics of 13C replacement by 12C incorporation of DH5αGFP cells in the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP. 4(C) Dynamics of deuterium incorporation of ADP1 cells in the co-culture of A. baylyi ADP1 – E. coli DH5a-GFP. 4(D) Dynamics of deuterium incorporation of DH5α-GFP cells in the co-culture of A. baylyi ADP1 – E. coli DH5aGFP.

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ADP1 pure culture DH5a-GFP pure culture Co-culture of ADP1 and DH5a-GFP Blank medium

0.06 0.05

Peak Intensity

1 2 470 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 471 19 20472 21473 22474 23 24475 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

0.04 0.03 0.02 0.01 0 Putrescine

Phenylalanine

Figure 5. GC-MS analysis results of the metabolites in different cultures. Putrescine and phenylalanine generated by A. baylyi ADP1 are responsible for the metabolic activity of E. coli DH5a-GFP in the medium with citrate as a sole carbon source.

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476

1 2 3 477 4 5 478 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 479 27 28 480 29 30481 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Table 1. Representative Raman band shifts and their putative assignments due to substitutions. Wavenumber to C-cells (cm-1)

12

Wavenumber to C- cells (cm-1)

13

785

770

1006

970

Wavenumber to Assignment 2 H cells (cm-1)

Reference

cytosine, uracil (ring, str)

17

994

ring breathing mode of benzene ring compounds

17,21

1126

1104

lipids

17,21

1168

1104

lipids

17,21

C=C stretching band

17

C-H vibration

17

1666

1623

2938

2930

2040-2300*

* Peak at 2187 cm-1.

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C and 2H

Analytical Chemistry

1 000

2187

1666

2187

1666

2187 2187

1623 1623

1006

1104

1623 1666

1104

785

1006 970 1006

1104 1168

970

785

500

1104 1168

770 772

MM+13C-glucose

970

13 C-reverse and C- ADP1 D O co-labeling 2

13

1104 1168

A. baylyi ADP1

785

for TOC only

1 500

2 000

2 500

3 000

Time course of 13C- ADP1

1 000

2187

1623

2187

1623

2187

1623 1623 1623

772

1104 1168

970

1104 1168

772

970

772

1104 1168

970

1126 1168

772

500

970

C- DH5a-GFP

MM+13C-glucose

970

MM+12C-citrate+D2O 13

1126 1168

E. coli DH5α-GFP

772

482

1 483 2 3 484 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1 500

2 000

2 500

3 000

Time course of 13C- DH5α-GFP

20 Environment ACS Paragon Plus

Page 20 of 21

Page 21 of 21

1 000

2187

1666

2187

1666

2187 2187

1623 1623

785

1104

1623 1666

1104

785

1006 970 1006

1104 1168

785

500

970

772

MM+13C-glucose

1104 1168

13 C-reverse and C- ADP1 D O co-labeling 2

770

13

970

A. baylyi ADP1

1 500

2 000

2 500

3 000

Time course of 13C- ADP1

1 000

2187

1623

2187

1623

2187

1623 1623 1623

772

1104 1168

970

1104 1168

772

970

1104 1168

772 772

500

970

C- DH5a-GFP

MM+13C-glucose

1126 1168

13

970

MM+12C-citrate+D2O

E. coli DH5α-GFP

970

4

1104 1168

3

1006

for TOC only

1126 1168

1 2

772

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

1 500

2 000

2 500

3 000

Time course of 13C- DH5α-GFP

1

ACS Paragon Plus Environment