Impact of Microorganisms

TWiM #252: Electrifying Microbial Fuel Cells

Podcast and Annotation Information
  • Annotation by Maura Gyan Thukral, Jorden Espsito, Meaghan Morrison, Jaya Dasgupta, and Rebecca Seipelt-Thiemann
  • Podcast audio by TWiM: Listen to TWiM #252 Podcast
  • Podcast transcript by Otter.ai and edited by Aidan Sasaoka and Rebecca Seipelt-Thiemann: Access Podcast Transcripts
  • Papers Discussed:
    • Cohen-Khait R, Ameya Harmalkar, Pham P, Webby MN, Housden NG, Elliston E, Hopper JTS, Mohammed S, Robinson CV, Gray JJ, et al. 2021. Colicin-Mediated Transport of DNA through the Iron Transporter FepA. MBio. 12(5). doi: 10.1128/mbio.01787-21
    • Cao B, Zhao Z, Peng L, Shiu H-Y, Ding M, Song F, Guan X, Lee CK, Huang J, Zhu D, et al. 2021. Silver nanoparticles boost charge-extraction efficiency in Shewanella microbial fuel cells. Science. 373(6561):1336–1340. doi: 10.1126/science.abf3427.

1. Paper Abstracts

1.1. Snippet paper; discussion starts at 4:18 minutes

The Most Interesting Things (according to students)

  • The use of colicin as a “vector” for short pieces of DNA. This has major implications for the future of genetics and research as it offers a new, seemingly more effective, way of inserting DNA into a bacterial cell.
  • The Protein Data Bank (PDB) and the 3D modeling of proteins. Not only is it heartwarming that there is a free resource constantly updated by scientists around the globe, but it also looks like it would save so much time and effort on research prep.

“Colicins are protein antibiotics deployed by Escherichia coli to eliminate competing strains. Colicins frequently exploit outer membrane (OM) nutrient transporters to penetrate the selectively permeable bacterial cell envelope. Here, by applying live-cell fluorescence imaging, we were able to monitor the entry of the pore-forming toxin colicin B (ColB) into E. coli and localize it within the periplasm. We further demonstrate that single-stranded DNA coupled to ColB can also be transported to the periplasm, emphasizing that the import routes of colicins can be exploited to carry large cargo molecules into bacteria. Moreover, we characterize the molecular mechanism of ColB association with its OM receptor FepA by applying a combination of photoactivated cross-linking, mass spectrometry, and structural modeling. We demonstrate that complex formation is coincident with large-scale conformational changes in the colicin. Thereafter, active transport of ColB through FepA involves the colicin taking the place of the N-terminal half of the plug domain that normally occludes this iron transporter.” (Cohen-Khait et al. 2021)

1.2. Main paper; discussion starts at 19:16 minutes

The Most Interesting Things (according to students)

  •  The “fuel cells” can create electricity by “feeding” the microbes waste. I knew that most organic waste could be broken down by something into fuel for itself, but I had no idea a sizable amount of energy could be generated from it.
  • The silver ions are actually embedded into the membrane connecting the bacteria to the graphene oxide structure. It seems like a very efficient way to ferry off the excess electrons from the electron transport chain (ETC).

This article is not licensed for Creative Commons use. Thus, the abstract cannot be copied here. Please view the article on the journal’s website.

2. Vision and Change Core Concepts and 2024 ASM Fundamental Statements

Snippet Main
Vision and Change Topics
  • Information Flow and Genetics (V&C_IFG)
  • Structure and Function (V&C_SF)
  • Impact of Microorganisms (V&C_IM)
  • Metabolic Pathways (V&C_MP)
  • Microbial Ecology (V&C_ME)
  • Impact of Microorganisms (V&C_IM)
ASM Fundamental Statements
  • Fundamental Statement 3 (ASM_3): The evolution of microbes is impacted by their interactions with the environment and a variety of ecological forces, including other microbes, humans, and habitats.
  • Fundamental Statement 5 (ASM_5): The structure and function of microbes are revealed by the use of microscopy, culture, and metabolic analyses, molecular methods, and bioinformatic tools.
  • Fundamental Statement 6 (ASM_6): The distinct structures and processes in microbes can be targets for interspecies competition, antimicrobial treatments, and host immunity.
  • Fundamental Statement 14 (ASM_14): Extrinsic factors, such as abiotic and biotic interactions in the environment, can impact survival and growth of microbes.
  • Fundamental Statement 20 (ASM_20): Microbes are ubiquitous, found in diverse and dynamic ecosystems, where they use available resources and often form complex communities.
  • Fundamental Statement 26 (ASM_26):Humans leverage microbes and their products to address problems and improve quality of life.

3.  Potential Learning Objectives for the Podcast

The student will be able to: Paper1 Order2
  • Identify the functions of key players Colicin B and FepA.
  • Identify key features of the Colicin B-FepA translocation mechanism.
  • Recall an application for this research.
 S L
  • Predict how import would be affected by fepA mutation if the translocation was different.
 S H
  • Recall where the bacterial biofilm forms in the biofuel cell.
  • Recall why Shewanella produces electrons.
  • Identify the most successful biofuel set up.
 M L
  • Hypothesize specific features that would need to be considered when using other bacterial species in microbial fuel cells.
 M H

1 Papers: Snippet (S) or Main (M)

2 Learning Objectives: Lower Order or Higher Order (H)

4. Techniques Described (with Time Stamps)

Here is a link to a bio-dictionary that has many, but not all definitions if you need a definition: Explore Biology Bio-Dictionary

4.1. Snippet Paper

  • Fluorescent Tagging (4:50–5:50): This is a method for tracking movement/increasing the visibility of various proteins/biological structures (antibodies, DNA, bacterial toxins). A fluorescent molecule/protein is attached to the molecule/structure of interest, allowing it to be visualized and tracked. Here, it was used to track the toxin as it entered the bacteria.
  • Mass Spectrometry (6:42–6:49 ): This is a technology to measure mass to charge ratio of ions to identify and quantify components of mixture. It does this by ionizing the substance being tested (usually by removing an electron to create a cation). The resulting ions are organized by mass and charge. The mass/charge values are then charted/graphed.  Here, it was used to find the stoichiometry of toxin to receptor.
  • Rosetta Software (7:45–8:37): This is a community-developed molecular modeling software. It was used to examine potential binding arrangements/structures for the toxin/receptor and the results were then used to design further experiments.
  • Chemical Cross-Linking (8:59–9:46): This is a method to secure interactions so the moieties involved can be identified.  It was used to identify which amino acids of the toxin are interacting with which amino acids of the receptor.

4.2. Main Paper

  • Live/Dead Staining (38:54–39.22): This is a method to determine dead and live cells. It was performed using a confocal laser scanning microscope and SYTO 9 dye. A living cell will take up the dye, causing it to emit a green fluorescence under the scanning microscope. The more green is visible, the more living cells are present.
  • Scanning Transmission Electron Microcopy (45:23–46.07): This is a high resolution microscopy technique.  Here, bacteria were sectioned using an ultratome into 60-200 nanometer thick layers for electron microscopy analysis and X-ray diffraction to identify the structure and nature of the components of the fuel cell/bacterium interaction.

5. Connections to General Microbiology Processes/Concepts (with Time Stamps)

5.1. Snippet Paper

  • Chemical Cross-Linking (8:59–9:46): Small molecules can bind to targeted amino acids and when activated by a UV light, the will cross-link to other nearby amino acids. This is used to identify whether and which parts of a molecule/protein are interacting with another molecule/protein.
  • Transformation (10:00–20:00): Transformation in bacteria is the ability to take up external DNA. General use of toxins such as colicin as a DNA uptake agent could open up new genetically modifying techniques using such a process.

5.2. Main Paper

  • Biofilm (23:00–35:00): Biofilms are a microbial population based on different communities and types of microbes which come together to form a matrix. Biofilms can be highly antibiotic resistant and very communicative between the separate colonies. Shewanella uses nanowires in order to transfer electrons across the biofilm.
  • Metabolism (33:11–34:19): Lactate dehydrogenase is used to break down carbon in its reduced form into either pyruvate, which eventually becomes lactic acid, or into glucose for glycolysis, the first step of cellular respiration

6. Podcast Questions

  1. Colicin B is a/an _________.
    1. antibiotic
    2. enzyme
    3. toxin
    4. receptor
  2. What mechanism of transport does Colicin B use to enter the bacterial cell?
    1. Diffusion
    2. Active Transport
    3. Facilitated diffusion
    4. Endocytosis
  3. ColicinB uses the FepA receptor to enter the bacterial cell. What is the  normal function of this bacterial receptor?
    1. Transports DNA
    2. Transports glucose
    3. Transports iron
    4. Transports antibiotics
  4. Which option best describes a potential application using colicin B-FepA?
    1. Use as a delivery tool.
    2. Modify bacterial genome.
    3. Test antibiotic sensitivity.
    4. Make a new biofilm.
  5. Deleting the gene encoding the FepA protein stopped colicin B translocation.  If colicin B could use two different receptors, how would deleting fepA  have affected colicin B transport?
    1. It could have increased it above the normal level.
    2. It could have changed it in an unpredictable way.
    3. It could have blocked translocation completely.
    4. It could have reduced it, but not eliminated it.
  6. Biofilm formation is an important part of a successful microbial fuel cell in this study.  Where does the biofilm need to form to be productive?
    1. In the electrolyte
    2. On the cathode
    3. At the terminal
    4. On the anode
  7. Electron flow is an important feature in biofuel science.  Which of the following best describes why the Shewanella cell normally produces electrons?
    1. They are used to re-charge itself.
    2. They are used to destroy superoxide.
    3. They are a metabolic waste product.
    4. They are used to make conductive pili.
  8. Of the biofuel anodes tested, which was most successful?
    1. Carbon paper lacking a metallic lattice
    2. Reduced graphene oxide coupled to silver
    3. Oxidized graphene oxide coupled to iron
    4. Oxidized graphene oxide coupled to copper
  9. The following are a list of bacterial characteristics.  Based on this study, which would you need to consider to find other bacteria that are likely to be successful in microbial fuel cell setup such as described in this study?
    1. Gram stain results
    2. Resistance to silver
    3. Resistance to copper
    4. Ability to form biofilms
    5. Presence of pili
    6. Ability to ferment

7. Figure Reading Exercises

The following are two figure reading exercises, one from the snippet paper (Figure 1) and one from the main paper (Figure 3).

7.1. First Figure Reading Exercise

7.1.1. Learning Objectives

Students will be able to: 

  • Identify key features of a bar graph.
  • Predict the fluorescent values expected for different cell localizations, with and without protease treatments.
  • Identify key features of the experimental design including controls and variable types.
  • Evaluate the data to make conclusions about how cell treatments impact colB translocation and colB-mediated cargo uptake.
  • Analyze the data to make conclusions about how genetic modifications to the bacteria and cargo impact colB translocation and colB-mediated cargo uptake.
Experimental Background (Cohen-Kait et al., Figure 1)

Competition for resources is high in the natural world and some species have evolved specific mechanisms to eliminate competitors.  One such system used by Escherichia coli (E. coli) is the pore-forming bacterial toxin, colicin B (ColB).  The receptor for this toxin is known to be FepA.  In this study, Cohen-Kait et al. (2021) investigate the toxin’s mechanism of action.  First, to determine whether the toxin acts at the surface or enters the target cell, they tagged engineered ColB with a fluorescent marker (BRT), performed fluorescent microscopy, and quantified periplasmic fluorescence for wild-type target cells using their wild-type ColB tagged with BRT (panel A, cell: WT, Label: BRT). To determine whether a particular domain within ColB called TonB was involved in transport, they deleted this domain to create a TonB colicin B mutant toxin  (panel A, cell: WT, Label: ΔTonB Box).  They next investigated the effect of deleting the target bacterial receptor gene fepA from the target bacteria (panel A, Cell: FepA KO).  There are several controls in this set of experiments because the bacterial cell locations are very close (see microscopy images below each panel). They needed to determine how much of the microscopy fluorescence that they observed was due to: 1) fluorescent toxin being translocated to the cytoplasm, 2) binding of the fluorescent toxin to the outer membrane, or 3) fluorescent toxin being present in the periplasm. To do this they treated the target bacteria with trypsin, a protease that would destroy protein bound to the outer membrane only (panel A, Treatment: Tryp). Second, they treated the target bacteria with lyticase to destroy the outer membrane and release the periplasm, which gives the bacteria a spherical shape (panel A, Treatment: Sphe).

Having established conditions for successful transport, they were interested in whether they could apply this system to transport other molecules.  They chose to investigate DNA transport, so they performed similar experiments using the engineered ColB that was complexed with one of two different fluorescent single-stranded DNAs: 15 adenines (panel B, Label: 15A) or 10 cytosines and 5 adenines (panel B; Label: 10C 5A), or with one fluorescent partially double-stranded DNA: 10 cytosines with 5 adenines bound to 10 guanines (panel B, Label: 10C 5A + 10G).  Example microscopy images are shown below each panel.

Bar plots alongside microscopy images of E coli cells.
Figure 1. “ssDNA follows the ColB-RT translocation path into E. coli cells. (A) Translocation of ColB-RT-Alexa 488 (BRT) or ColB-RT ΔTonB box–Alexa 488 (ΔTonB box) constructs into E. coli MG1655 cells (WT) or E. coli BW25113 ΔFepA (FepA knockout [KO]) cells grown in minimal medium to mid-log growth phase (OD600, ∼0.35). OM translocation was defined as fluorescent signal resistant to trypsin treatment (Tryp). Cytoplasmic localization was defined as fluorescent signal remaining after spheroplasting the cells, which results in the removal of the OM and the periplasmic peptidoglycan layer (Sphe). The averaged fluorescence intensities were calculated from at least 120 cells (30 cells × 4 biological repeats), and standard error bars of each treatment are shown. Representative cellular images are below each treatment. Scale bar, 1 μm. (B) Translocation of ColB-RT-DNA-fused constructs were ColB-RT-A15 Alexa 488 (15A), ColB-RT A5C10 Alexa 488 (10C 5A), and ColB-RT A5C10 Alexa 488 + G10 (A5C10 + G10).” (Cohen-Kait et al. 2021)

7.1.2. Questions

  1. What does the bar height indicate for these data?
    1. The median fluorescence of four biological replicates
    2. The mean fluorescence of four biological replicates
    3. The median fluorescence of 120 biological replicates
    4. The mean fluorescence of 120 biological replicates
  2. What could a high fluorescence level for cells not treated with any proteases (e.g., no Tryp, no Sphe) indicate for this experiment (panel A or panel B)? [pick all that apply]
    1. ColB was translocated to the periplasm
    2. ColB was translocated to the cytoplasm
    3. ColB binds the outer membrane
    4. ColB inhibits peptidoglycan synthesis
  3. What could a high fluorescence level for cells treated with trypticase (Tryp) indicate for this experiment (panel A or panel B)? [pick all that apply]
    1. ColB was translocated to the periplasm
    2. ColB was translocated to the cytoplasm
    3. ColB binds the outer membrane
    4. ColB inhibits peptidoglycan synthesis
  4. In this experiment (panel A), ______ is the negative control and _______ is the positive control.
    1. WT BRT -; FepA KO BRT –
    2. WT–- ; WT BRT Sphe
    3. WT–- ; WT BRT –
    4. WT BRT Tryp; WT BRT –
  5. The researchers knew that FepA was one receptor for the toxin, but it is possible that the toxin could enter the cell using other receptors, too.  They tested this by removing just FepA (panel A; FepA KO BRT–).  Can the toxin be transported by other receptors? What is your evidence?
    1. Yes, ColB transport is unaffected in the FepA KO vs. wild-type.
    2. No, ColB transport is near the levels of the positive control.
    3. Yes, ColB transport is reduced but still present in the FepA KO.
    4. No,  ColB transport is near the levels of the negative control.
  6. Is the toxin’s TonB box required for each of the following functions? What is your evidence? (Y = yes; N = no;)
Function Evidence
a._______FepA receptor binding 1. The TonB box mutant has reduced transport to the periplasm (WT ΔTonB Box Tryp vs. WT BRT Tryp)
b._______transport to the periplasm 2. The TonB box mutant binds the outer membrane and is found in the periplasm (WT ΔTonB Box vs. WT  BRT–)
3. The TonB box mutant has the same transport to the periplasm as wild-type  (WT BRT–vs WT ΔTonB Box -)
4. The TonB box mutant binds the outer membrane and binding is abolished by Tryp treatment (WT ΔTonB Box Tryp vs. WT ΔTonB Box -)
  1. The researchers tested whether ColB could be used to delivery three different types of DNA into the cells (panel B): single stranded DNA of just adenine bases (15A), single-stranded DNA of ten cytosine and five adenine bases (10C 5A), and double-stranded DNA of ten cytosine and five adenine hydrogen bonded to ten guanine bases (10C 5A+10G).  Which DNAs could be transported by ColB?  Which DNA was transported into the cell most successfully?
    1. Only 15A; 15A
    2. Only 10C 5A; 10C 5A
    3. Only single-stranded DNAs; 15A
    4. Only double-stranded DNA; 10C 5A+10G
    5. All of them; 15A
    6. None of them were transported into the cell
  2. The researchers knew that FepA was one receptor for the toxin, but it is possible that the toxin with DNA cargo might be able to enter the cell using other receptors.  They tested this by removing just FepA (panel B; FepA KO 15A and FepA KO 10C 5A). Can the toxin:DNA complex be transported by other receptors? What is your evidence?
    1. Yes, ColB transport is unaffected in the FepA KO vs. wild-type.
    2. No, ColB transport is near the levels of the positive control.
    3. Yes, ColB transport is reduced but still present in the FepA KO.
    4. No,  ColB transport is near the levels of the negative control.

7.2. Second Figure Reading Exercise

7.2.1. Learning Objectives

Students will be able to:

  • Identify key features in bar plots.
  • Identify key features of the experimental design including controls, variable types, and expected results.
  • Evaluate the data to make conclusions about how altering the anode/electrode affects key Shewanella biofuel cell metrics.
  • Analyze the biofuel cell metrics to make conclusions about the best fuel cell set up.
Experimental Background (Cao et al., Figure 3)

Many global initiatives are being put in place to reduce carbon emissions from fossil fuels and promote clean, renewable energy practices.  Microbe-derived energy would be both clean and renewable, but the technologies do not yet produce sufficient energy output to be practical.  In this study, Cao et al. (2021) focus on “proof of principle” experiments using microbial fuel cells where microbes convert chemical energy into electrical energy as a product of their metabolism. The organism these researchers utilize is the bacterium Shewanella, which is widely used in bioremediation. In this study, success would be indicated by bacteria forming dense biofilm structures on the anode (panel A), high efficiency delivery of electrons to the anode (panel B), and high turnover frequency (panel C), which is calculated using cell number and electron transfer to enable a fairer comparison among samples when cell numbers are different.  They tested three different anodes/electrodes: carbon paper, carbon paper with reduced graphene oxide (rGO), and carbon paper with reduced graphene oxide impregnated with silver nanoparticles (rGO/Ag).

Please note that the authors do not indicate in their legend or in the paper what the bar height indicates, the number of replicates used to generate the data, or what the error bars indicate, but traditionally, bar height is the mean and error bars are standard deviation, and they would have needed at least three replicates to generate a standard deviation.

7.2.2. Questions

  1. Which color bar represents the data for the anode/electrode with silver nanoparticles?
    1. Gray
    2. Blue
    3. Red
  2. What would a high bacteria number indicate for this experiment (panel A)?
    1. Many species are present in the biofilms.
    2. Bacteria formed/grew dense biofilms.
    3. Bacteria grew in reducing conditions.
    4. Bacteria moved electrons efficiently.
  3. In this experiment (panel A), ______ is the negative control and _______ is the positive control.
    1. Carbon paper; there is no positive control
    2. Carbon paper; Carbon paper with reduced graphene
    3. Carbon paper with reduced graphene; no positive control
    4. There is no negative control; carbon paper
  4. What is the approximate number of bacteria growing on the rGO anode and what level of success does this indicate (panel A)?
    1. 6.50 x10⁹; great success
    2. 4.00 x10⁹; some success
    3. 2.25 x10⁹; some success
    4. 1.50 x10⁹; no success
  5. What is the approximate current density for the rGO/Ag anode and what level of success does this indicate (panel B)?
    1. 0.4 mA/cm2; little success
    2. 0.75 mA/cm2; some success
    3. 1.5 mA/cm2; some success
    4. 3.75 mA/cm2; great success
  6. Turnover efficiency is calculated and presented in panel C.  This is a fairer comparison of microbial fuel cell performance when bacterial cell numbers populating the anode/electrode differ.  Based on these data, what is the conclusion you can make about turnover efficiency and therefore, the best fuel cell?
    1. Use of silver decreased turnover frequency; so the plain reduced graphene is best.
    2. Use of silver increased turnover frequency; this makes the best overall fuel cell.
    3. Use of silver decreased turnover frequency; this makes a moderate fuel cell.
    4. Use of silver increased turnover frequency; so the plain reduced graphene is best.

8. Paper Information and Licensing

8.1. Snippet paper

  • Cohen-Khait R, Ameya Harmalkar, Pham P, Webby MN, Housden NG, Elliston E, Hopper JTS, Mohammed S, Robinson CV, Gray JJ, et al. 2021. Colicin-Mediated Transport of DNA through the Iron Transporter FepA. MBio. 12(5). doi: 10.1128/mbio.01787-21.
  • This article is licensed for Creative Commons use using CC BY 4.0, which allows re-use and adaptation with proper attribution and notation of any changes.

8.2. Main paper

  • Cao B, Zhao Z, Peng L, Shiu H-Y, Ding M, Song F, Guan X, Lee CK, Huang J, Zhu D, et al. 2021. Silver nanoparticles boost charge-extraction efficiency in Shewanella microbial fuel cells. Science. 373(6561):1336–1340. doi: 10.1126/science.abf3427.
  • This article is not licensed for Creative Commons use. See the article’s copyright information. Thus, the abstract and figures cannot be copied here.

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Podcast Annotation and Resources in Microbiology Copyright © 2025 by Rebecca Seipelt-Thiemann; Nancy Boury; Gwendowlyn S. Knapp; Amaya Garcia Costas; and Patrick Armstrong is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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