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Bacillus subtilis Biosensor Engineered To Assess Meat Spoilage
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iGEM Teaching Program, Team 2012, Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
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ACS Synthetic Biology

Cite this: ACS Synth. Biol. 2014, 3, 12, 999–1002
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https://doi.org/10.1021/sb5000252
Published December 19, 2014

Copyright © 2014 American Chemical Society. This publication is available under these Terms of Use.

Abstract

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Here, we developed a cell-based biosensor that can assess meat freshness using the Gram-positive model bacterium Bacillus subtilis as a chassis. Using transcriptome analysis, we identified promoters that are specifically activated by volatiles released from spoiled meat. The most strongly activated promoter was PsboA, which drives expression of the genes required for the bacteriocin subtilosin. Next, we created a novel BioBrick compatible integration plasmid for B. subtilis and cloned PsboA as a BioBrick in front of the gene encoding the chromoprotein amilGFP inside this vector. We show that the newly identified promoter could efficiently drive fluorescent protein production in B. subtilis in response to spoiled meat and thus can be used as a biosensor to detect meat spoilage.

This publication is licensed for personal use by The American Chemical Society.

Copyright © 2014 American Chemical Society

SPECIAL ISSUE

This article is part of the iGEM 2013 special issue.

Every year, one-third of global food production is unused and thrown away. The prime reason is that perfectly edible food is disposed of prematurely due to the “best before date” indicator system. Thus, fast and reliable systems are required to assess food spoilage to prevent health hazards and economic losses, as well as for ethical reasons. With food spoilage mainly being caused by degradative enzymes and toxins from food-associated bacteria and fungi, the classic “scientific” way to test whether food is spoiled is by counting colony forming units (CFU) in plating assays. While these tests give an estimate of the microbial load, they are very time-consuming, and furthermore cannot detect nonculturable microbes. It has long been appreciated that biological, cell-based biosensors could provide more sensitive and user-friendly devices compared to electronic ones, drawing on their evolutionary optimized systems to detect various analytes and the continuous self-renewal of the sensors within the living system. (1) Although cell-based biosensors have been successfully designed for a number of applications such as heavy metal or explosives detection and antibiotic quantification, (2) only few examples exist that can assess food spoilage such as a mammalian cell-system that reports on fruit quality. (3) So far, none have been commercially implemented in the food sector. (4)
Bacillus subtilis is a very promising organism for the development of novel biosensors since it has a GRAS status (generally regarded as safe), it is genetically tractable and is commonly used in industry. Several successful examples of B. subtilis as a biosensor exist. For instant, using firefly luciferase promoter fusions, it was shown that B. subtilis cells can be very effective biosensors toward several classes of antibiotics. (5) As a biosensor, B. subtilis offers the added benefit that it can produce dormant spores which allow for the long-term preservation, storage, and transport of the biosensor. (6) Together, this inspired us to explore the possibility whether we could engineer a new B. subtilis based biosensor that would be specifically responsive to spoiled meat.
Here, we describe the design, construction, and evaluation of a biosensor based on Bacillus subtilis cells that sense and respond to spoiled meat. Using DNA-microarray analysis we have identified several promoters that are upregulated when B. subtilis cells were exposed to volatiles coming from spoiled meat, but not from fresh meat. One of the most highly upregulated promoters, PsboA, was selected and further characterized as a biosensor. To the best of our knowledge, this is the first example of using bacteria as a biosensor for food spoilage and the used strategy might be generally applicable to engineer other biosensors.

Results and Discussion

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Toward engineering B. subtilis for detecting and indicating spoiled meat (70%/30% pork/cow minced meat), we first developed an experimental approach with which we investigated B. subtilis’ natural response to spoiled meat: the headspace gas of a container with either fresh (<103 CFU/gram) or spoiled (>106 CFU/gram) meat was flushed through an exponentially growing B. subtilis culture (Supporting Information Movie S1). To identify whether B. subtilis contains an endogenous response to volatiles present in the spoiled meat headspace, we performed a transcriptome analysis. After 2 h of incubation, B. subtilis cells were harvested and total RNA was isolated and compared to that of B. subtilis cells flushed with the headspace of fresh meat using DNA-microarrays (GEO accession number: GSE50538). 297 genes were more than 2-fold up- or down-regulated. Using Genome2d, (7) we identified 19 operons of which all genes where more than 2-fold upregulated. We ranked the operons by fold change and ruled out the operons related to general stress response. One of the strongest up-regulated promoters (12.5-fold, p < 0.0001) remaining was PsboA which, interestingly, drives expression of the genes required for the bacteriocin subtilosin. (8) Subtilosin is a peptide with antimicrobial activity against a wide range of bacteria and subtilosin expression is under complex gene-regulatory control. (8)
BioBrick prefix and suffix were added to PsboA by PCR resulting in the part BBa_K818100. Next, we generated a BioBrick compatible B. subtilis integration vector BBa_K818000 by addition of the BioBrick prefix and suffix and the transcriptional terminator (part BBa_B0015) to plasmid pSac-Cm (Genbank accession number: AY464562). (9) BBa_K818000 integrates via double crossover at the nonessential sacA locus. As a visual readout of the promoter activity, we employed the chromoprotein amilGFP, which is fluorescent and, when expressed in bacteria, pigments cells yellow visible to humans with the naked eye. (10) Using BioBrick assembly, we combined amilGFP (part BBa_K592010), the ribosome binding site (part BBa_K592010) and PsboA, resulting in part BBa_K818600 (PsboA-amilGFP, Figure 1A), which was stably integrated in the B. subtilis chromosome using plasmid BBa_K818000 resulting in the meat-spoilage biosensor (Figure 1B).

Figure 1

Figure 1. (A) Schematic representation of the meat-biosensor BioBrick BBa_K816000. (B) Schematic representation of the sacA B. subtilis integration vector BBa_K818000. The sacA homology regions are indicated. The cat gene provides chloramphenicol resistance in B. subtilis and the bla gene confers ampicillin resistance in E. coli. (C) B. subtilis cells harboring the biosensor-construct were grown to midexponential growth phase in LB-medium, split in two cultures and the headspace of either fresh meat (kept on ice) or of spoiled meat (kept at room temperature) was flushed continuously through the shaking cultures. Fluorescence (arbitrary units) of 10 000 cells was determined by flow cytometry at timely intervals and a typical outcome of data from cells incubated for 5 h is shown.

To test the functionality of the biosensor, cells were incubated as described above (Supporting Information Movie S1) and fluorescence from amilGFP was examined using flow cytometry. As shown in Figure 1C, after 5 h of incubation, biosensor cells showed strong fluorescence in the presence of spoiled meat but not in the presence of fresh meat.
This is a proof of principle project that shows that B. subtilis can be used as a biosensor to assess meat spoilage. Our strategy to identify the genetic program of B. subtilis in response to volatiles coming from spoiled meat is potentially universal and could be used to identify other specific transcriptional responses of B. subtilis (e.g., to spoiled fish or heavy metals) or of other organisms.

Methods

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DNA Techniques, Media and Growth Conditions

Procedures for DNA purification, restriction, ligation, agarose gel electrophoresis, transformation, and growth of E. coli and B. subtilis were carried out as described before. (11) The biosensor construct (BBa_K818600) was sequence verified and is shown in the Supporting Information.

DNA Microarrays

B. subtilis cultures were grown shaking in 40 mL of LB medium 40 mL in 100 mL Schott-Duran bottles (Schott, U.S.A.) at 37 °C. At midexponential growth (OD600 nm ∼0.1) either the headspace of a container with fresh (<103 CFU/g) meat (70/30 pork/cow minced meat) or spoiled meat was flushed through the culture using a peristaltic pump system (see Supporting Information Movie S1). After 2 h of incubation when cells were approximately OD 0.8, cells were collected by centrifugation at 7500 rcf for 5 min and frozen for RNA isolation with liquid nitrogen. RNA isolation, cDNA preparation, labeling, hybridization, scanning, and data analysis was performed as described on GEO (accession number GSE50538). Two biological replicates and 2 technical replicates were performed.

Total Aerobic Microbial Count Assays (TAMC)

Meat was considered spoiled according to EU regulation ISO 16140:2003(E) (containing >106 CFU/g in a TAMC assay). TAMC’s were performed by resuspending 1 g of meat in 100 mL of Trypton Soy Broth and serial dilutions were plated in triplicate in Trypton Soy Agar and incubated at 37 °C. After 3 days of incubation, CFU’s were counted.

Construction of Plasmids and Strains

To generate a BioBrick compatible integration vector for B. subtilis, we first introduced a RFC(10) standard compatible multiple cloning site (EcoRI, XbaI, SpeI, PstI) together with a double transcriptional terminator into plasmid pSac-Cm, (9) resulting in vector BBa_K818000. The double terminator and prefix and suffix were amplified by PCR using primers AP_BB-B0015_fwd (5′-GCATAGAATTCACAGGTCTAGAGTGCAATAACTAGTATCATCTGCAGCCAGGCATCAAATAAAACGAAAGG-3′) and AP_BB-B0015_rev (5′-ATCGAAAGCTTAATATAAACGCAGAAAGGCCCACC-3′) and BioBrick B0015 as a template. The amplified fragment was subsequently cleaved with EcoRI and HindIII and ligated into the corresponding sites of pSac-Cm, resulting in plasmid BBa_K818000. This vector replicates in E. coli (selection with ampicillin) but not in B. subtilis where it will integrate at the sacA locus via double homologous recombination (upon selection with chloramphenicol) provided by the two sacA flanking regions present on BBa_K818000 (see Figure 1B). The BioBrick compatible MCS is present between the sacA integration regions.
To construct BioBrick BBa_K818100 (PsboA) which encodes the B. subtilis sboA promoter with the BioBrick prefix and suffix according to the RFC(10) standard, a PCR with the primers AO_20120816_P_sboA_fw (5′- CTATCGGAATTCTCTA GACTGCTTCTATCTTACCATCATTGC-3′) and AO_20120821_P_sboA_rev (5′- CATGCCTGCAGACTAGTGACAGCTTTTTTCATAATTG-3′) was performed, using chromosomal DNA of B. subtilis 168 as a template. To amplify amilGFP, a PCR using primers AP_amilGFP_fwd (5′-GCGGTGAATTCTCTAGAAAAGAGGAGAAAATGT CTTATTCAAAGCATGGCATCG-3′) and AP_amilGFP_rev (5′-GCTGCACTAGTC TGCAGTTATTATTTAACCTTCAAAGGG-3′) was performed using BioBrick BBa_K592010 as a template. amilGFP and plasmid BBa_K818000 were digested with XbaI and PstI. The two fragments where ligated and used to transform E. coli. The resulting plasmid K818000-amilGFP was isolated and digested with EcoRI and XbaI and PsboA was digested with EcoRI and SpeI. The two fragments were ligated and used to transform E. coli, resulting in plasmid BBa_K818600 (PsboA-amilGFP).
The B. subtilis spoiled meat biosensor strain (sacA::PsboA-amilGFP, cat) was obtained by a double crossover recombination event between the sacA regions located on plasmid BBa_K818600 (Figure 1B) and the chromosomal sacA gene of strain 168. Transformants were selected on LB agar plates containing chloramphenicol after overnight incubation at 37 °C. Correct integration into the sacA gene was tested and confirmed by PCR using primers prIDJ215 (5′-GTGTCAGCGTTCATTGCAGC-3′) and prIDJ216 (5′- GAATAGCACAGATGGCTCAG-3′). All constructed parts are listed in Table 1.
Table 1. Parts and BioBricks Used in This Study
part/plasmidBioBrick numberdescriptionsource
PsboABBa_K818100promoter induced by rotten meat volatilesthis study
PsboA-amilGFPBBa_K818600production of yellow pigment amilGFP induced by rotten meat volatilesthis study
K818000BBa_K818000plasmid replicates in E. coli and integrates into the Bacillus subtilis genome via double crossover; contains BioBrick MCS and double terminator B0015this study
amilGFPBBa_K592010fluorescent and bright colored proteiniGEM Uppsala 2011
K818000-amilGFP intermediate plasmid for creation of PsboA-amilGFP in K818000this study
B0015BBa_B0015double terminatorparts registry
RBSBBa_B0034ribosome binding site used widely in the iGEM competitionparts registry

Flow Cytometry

Cells were diluted 100 fold in 0.2 μM filtered minimal medium and scatter and emission were directly measured on a BD FACSCanto Flow Cytometer (BD Bioscience, NL) equipped with a 488 nm solid state, 20 mW laser. Fluorescence intensity of 105 cells was measured with at medium flow and forward scatter, side scatter and fluorescence (FL-1) was recorded. Data was analyzed using matlab (Mathworks, U.S.A.) and plotted using Sigmaplot (Systat Software Inc., U.S.A.).

Supporting Information

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Movie S1, a plasmid map and the sequence of the biosensor construct. Movie S1 shows the experimental setup: the headspace of trays containing either fresh meat (on ice) or spoiled meat (>106 CFU/g meat) (room temperature) are pumped through shaking cultures of the B. subtilis biosensor. This material is available free of charge via the Internet at http://pubs.acs.org.

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Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
    • Matthias Heinemann†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands Email: [email protected]
  • Authors
    • Alicja Daszczuk†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Yonathan Dessalegne†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Ismaêl Drenth†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Elbrich Hendriks†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Emeraldo Jo†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Tom van Lente†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Arjan Oldebesten†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Jonathon Parrish†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Wlada Poljakova†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Annisa A. Purwanto†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Renske van Raaphorst†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Mirjam Boonstra†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Auke van Heel†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Martijn Herber†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Sjoerd van der Meulen†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Jeroen Siebring†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Robin A. Sorg†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands
    • Oscar P. Kuipers†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands Email: [email protected]
    • Jan-Willem Veening†iGEM Teaching Program, Team 2012, ‡Molecular Genetics Group, and §Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen, 9747 AG Groningen, The Netherlands Email: [email protected]
  • Author Contributions

    A.D., Y.D., I.D., E.H., E.J., T.v.L., A.O., J.P., W.P., A.A.P., and R.v.R. contributed equally. A.D., Y.D., I.D., E.H., E.J., T.v.L., A.O., J.P., W.P., A.A.P., and R.v.R. conceived and carried out the experiments. M.B., A.v.H., M.H., S.v.d.M., J.S., and R.A.S. supervised and helped with the experiments. M.H., O.P.K., and J.-W.V. supervised and coordinated the project and wrote the manuscript. All authors read and approved the final manuscript.

  • Notes
    The authors declare no competing financial interest.

Acknowledgment

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We thank the sponsors of the Groningen 2012 iGEM team (http://2012.igem.org/Team:Groningen/our_sponsors). We thank Roel Bovenberg, Gert-Jan Euverink, and Marnix Medema for valuable discussions.

References

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This article references 11 other publications.

  1. 1
    Michener, J. K., Thodey, K., Liang, J. C., and Smolke, C. D. (2012) Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways Metab. Eng. 14, 212 222
  2. 2
    van der Meer, J. R. and Belkin, S. (2010) Where microbiology meets microengineering: Design and applications of reporter bacteria Nat. Rev. Microbiol. 8, 511 522
  3. 3
    Weber, W., Luzi, S., Karlsson, M., and Fussenegger, M. (2009) A novel hybrid dual-channel catalytic-biological sensor system for assessment of fruit quality J. Biotechnol. 139, 314 317
  4. 4
    Kerry, J. P., O’Grady, M. N., and Hogan, S. A. (2006) Past, current, and potential utilisation of active and intelligent packaging systems for meat and muscle-based products: A review Meat Science 74, 113 130
  5. 5
    Urban, A., Eckermann, S., Fast, B., Metzger, S., Gehling, M., Ziegelbauer, K., Rübsamen-Waigmann, H., and Freiberg, C. (2007) Novel whole-cell antibiotic biosensors for compound discovery Appl. Environ. Microbiol. 73, 6436 6443
  6. 6
    Knecht, L. D., Pasini, P., and Daunert, S. (2011) Bacterial spores as platforms for bioanalytical and biomedical applications Anal. Bioanal. Chem. 400, 977 989
  7. 7
    Baerends, R. J., Smits, W. K., de Jong, A., Hamoen, L. W., Kok, J., and Kuipers, O. P. (2004) Genome2D: A visualization tool for the rapid analysis of bacterial transcriptome data Genome Biol. 5, R37
  8. 8
    Zheng, G., Yan, L. Z., Vederas, J. C., and Zuber, P. (1999) Genes of the sbo-alb locus of Bacillus subtilis are required for production of the antilisterial bacteriocin subtilosin J. Bacteriol. 181, 7346 7355
  9. 9
    Middleton, R. and Hofmeister, A. (2004) New shuttle vectors for ectopic insertion of genes into Bacillus subtilis Plasmid 51, 238 245
  10. 10
    Alieva, N. O., Konzen, K. A., Field, S. F., Meleshkevitch, E. A., Hunt, M. E., Beltran-Ramirez, V., Miller, D. J., Wiedenmann, J., Salih, A., and Matz, M. V. (2008) Diversity and evolution of coral fluorescent proteins PLoS One 3, e2680
  11. 11
    Harwood, C. R. and Cutting, S. M. (1990) Molecular Biological Methods for Bacillus, John Wiley and Sons Ltd., Chichester.

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ACS Synthetic Biology

Cite this: ACS Synth. Biol. 2014, 3, 12, 999–1002
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https://doi.org/10.1021/sb5000252
Published December 19, 2014

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  • Abstract

    Figure 1

    Figure 1. (A) Schematic representation of the meat-biosensor BioBrick BBa_K816000. (B) Schematic representation of the sacA B. subtilis integration vector BBa_K818000. The sacA homology regions are indicated. The cat gene provides chloramphenicol resistance in B. subtilis and the bla gene confers ampicillin resistance in E. coli. (C) B. subtilis cells harboring the biosensor-construct were grown to midexponential growth phase in LB-medium, split in two cultures and the headspace of either fresh meat (kept on ice) or of spoiled meat (kept at room temperature) was flushed continuously through the shaking cultures. Fluorescence (arbitrary units) of 10 000 cells was determined by flow cytometry at timely intervals and a typical outcome of data from cells incubated for 5 h is shown.

  • References


    This article references 11 other publications.

    1. 1
      Michener, J. K., Thodey, K., Liang, J. C., and Smolke, C. D. (2012) Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways Metab. Eng. 14, 212 222
    2. 2
      van der Meer, J. R. and Belkin, S. (2010) Where microbiology meets microengineering: Design and applications of reporter bacteria Nat. Rev. Microbiol. 8, 511 522
    3. 3
      Weber, W., Luzi, S., Karlsson, M., and Fussenegger, M. (2009) A novel hybrid dual-channel catalytic-biological sensor system for assessment of fruit quality J. Biotechnol. 139, 314 317
    4. 4
      Kerry, J. P., O’Grady, M. N., and Hogan, S. A. (2006) Past, current, and potential utilisation of active and intelligent packaging systems for meat and muscle-based products: A review Meat Science 74, 113 130
    5. 5
      Urban, A., Eckermann, S., Fast, B., Metzger, S., Gehling, M., Ziegelbauer, K., Rübsamen-Waigmann, H., and Freiberg, C. (2007) Novel whole-cell antibiotic biosensors for compound discovery Appl. Environ. Microbiol. 73, 6436 6443
    6. 6
      Knecht, L. D., Pasini, P., and Daunert, S. (2011) Bacterial spores as platforms for bioanalytical and biomedical applications Anal. Bioanal. Chem. 400, 977 989
    7. 7
      Baerends, R. J., Smits, W. K., de Jong, A., Hamoen, L. W., Kok, J., and Kuipers, O. P. (2004) Genome2D: A visualization tool for the rapid analysis of bacterial transcriptome data Genome Biol. 5, R37
    8. 8
      Zheng, G., Yan, L. Z., Vederas, J. C., and Zuber, P. (1999) Genes of the sbo-alb locus of Bacillus subtilis are required for production of the antilisterial bacteriocin subtilosin J. Bacteriol. 181, 7346 7355
    9. 9
      Middleton, R. and Hofmeister, A. (2004) New shuttle vectors for ectopic insertion of genes into Bacillus subtilis Plasmid 51, 238 245
    10. 10
      Alieva, N. O., Konzen, K. A., Field, S. F., Meleshkevitch, E. A., Hunt, M. E., Beltran-Ramirez, V., Miller, D. J., Wiedenmann, J., Salih, A., and Matz, M. V. (2008) Diversity and evolution of coral fluorescent proteins PLoS One 3, e2680
    11. 11
      Harwood, C. R. and Cutting, S. M. (1990) Molecular Biological Methods for Bacillus, John Wiley and Sons Ltd., Chichester.
  • Supporting Information

    Supporting Information


    Movie S1, a plasmid map and the sequence of the biosensor construct. Movie S1 shows the experimental setup: the headspace of trays containing either fresh meat (on ice) or spoiled meat (>106 CFU/g meat) (room temperature) are pumped through shaking cultures of the B. subtilis biosensor. This material is available free of charge via the Internet at http://pubs.acs.org.


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