Impact of Microorganisms

TWiM #296: Bacterial Channels in Plant Cells

Podcast and Annotation Information
  • Annotation by Adam Helfenbein, Kwaku Bonsu, Isabel Bartlett, Rebecca Seipelt-Thiemann, and Roger Greenwell
  • Podcast audio by TWiM: Listen to TWiM #296 Podcast
  • Podcast transcript by Otter.ai and edited by Hannah Harris and Laurel Thompson: Access Podcast Transcripts
  • Papers Discussed:
    • Aykut B, Pushalkar S, Chen R, Li Q, Abengozar R, Kim JI, Shadaloey SA, Wu D, Preiss P, Verma N, Guo Y, Saxena A, Vardhan M, Diskin B, Wang W, Leinwand J, Kurz E, Kochen Rossi JA, Hundeyin M, Zambrinis C, Li X, Saxena D, Miller G. 2019. The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature. 574(7777):264-267. doi: 10.1038/s41586-019-1608-2
    • Nomura K, Andreazza F, Cheng J, Dong K, Zhou P, He SY. 2023. Bacterial pathogens deliver water- and solute-permeable channels to plant cells. Nature.621(7979):586-591. doi: 10.1038/s41586-023-06531-5

1. Paper Abstracts

1.1. Snippet paper; discussion starts at 3:00 minutes

The Most Interesting Things (according to students)

  • We found it interesting that the claim that microbes are commonly inside of tumors was inconsistently replicable among researchers from different institutions. This raises questions about the validity of these results and, to us, a discussion about whether certain demographics of people are more likely to have characteristic microbes present in their tumor cells.
  • If this discovery was found to be legitimate, it would be interesting because, as proposed in the paper, we could identify certain microbes associated with cancer. These findings would allow us to potentially use antimicrobials, such as antifungals, as an adjunct therapy for cancer. Additionally, identifying microbes that are related to certain cancers would potentially be useful for diagnostic purposes, such as testing for the presence of a microbe that would indicate cancer risk.

Aykut et al. (2019) is not licensed for Creative Commons use, so the abstract cannot be copied here. There is a version of this paper available at PubMed,

1.2. Main paper; discussion starts at 14:22 minutes

The Most Interesting Things (according to students)

  • We found it interesting that AI was used in this topic to predict the structure of these effector proteins. The researchers used AlphaFold2 to predict that the protein resembles a porin. This was later confirmed to be accurate through research using Xenopus oocytes, which demonstrated the formation of these porin-like channels which result in water soaking.
  • Another fascinating part of the main topic is the function of polyamidoamine dendrimers as a potential treatment for water soaking/fireblight. This chemical treatment quite literally plugs these channels, preventing water soaking and cell lysis, protecting plants from infection.

“Many animal- and plant-pathogenic bacteria use a type III secretion system to deliver effector proteins into host cells. Elucidation of how these effector proteins function in host cells is critical for understanding infectious diseases in animals and plants. The widely conserved AvrE-family effectors, including DspE in Erwinia amylovora and AvrE in Pseudomonas syringae, have a central role in the pathogenesis of diverse phytopathogenic bacteria. These conserved effectors are involved in the induction of ‘water soaking’ and host cell death that are conducive to bacterial multiplication in infected tissues. However, the exact biochemical functions of AvrE-family effectors have been recalcitrant to mechanistic understanding for three decades. Here we show that AvrE-family effectors fold into a β-barrel structure that resembles bacterial porins. Expression of AvrE and DspE in Xenopus oocytes results in inward and outward currents, permeability to water and osmolarity-dependent oocyte swelling and bursting. Liposome reconstitution confirmed that the DspE channel alone is sufficient to allow the passage of small molecules such as fluorescein dye. Targeted screening of chemical blockers based on the predicted pore size (15–20 Å) of the DspE channel identified polyamidoamine dendrimers as inhibitors of the DspE/AvrE channels. Notably, polyamidoamines broadly inhibit AvrE and DspE virulence activities in Xenopus oocytes and during E. amylovora and P. syringae infections. Thus, we have unravelled the biochemical function of a centrally important family of bacterial effectors with broad conceptual and practical implications in the study of bacterial pathogenesis.” (Nomura et al. 2019)

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)
  • Information Flow and Genetics (V&C_IFG)
  • Microbial Ecology (V&C_ME)
  • Impact of Microorganisms (V&C_IM)

ASM Fundamental Statements
  • 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 27 (ASM_27): The extent of microbial diversity is largely unknown, and exploration of this diversity is critical to understanding microbes and their role in the biosphere.
  • Fundamental Statement 28 (ASM_28): A minority of microbes are pathogens that can cause diseases and harm host organisms, society, and ecosystems.
  • 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 28 (ASM_28): A minority of microbes are pathogens that can cause diseases and harm host organisms, society, and ecosystems.

3.  Potential Learning Objectives for the Podcast

The student will be able to: Paper1 Order2
  • Identify the method used to detect non-human inhabitants of human tumor tissues.
  • Recall the types of non-human inhabitants found in human tumors.
  • Identify the reasons the various researchers studying this topic are not all in agreement.

S

L
  • Design a research study to investigate the role of microbial communities in tumor growth.

S

H
  • Define watersoaking and identify its consequences.
  • Recall the experimental methods used to study bacterial effector proteins.
  • Identify the function of type III secretion systems in bacteria.

M

L
  • Predict the effect of mutating the gene encoding the porin.

M

H

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

2Learning 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

  • Computational Biology (8:36–9:46): Computational biology used computers to help answer biological questions. Here, computational biology was used to identify potential bacterial sequences scattered among tumors in the tumor database known as Cancer Genome Atlas.
  • Sequencing Techniques (9:46–11:33): Sequencing is used to determine the DNA base sequence and it can be for whole genomes or DNA fragments. Here, the podcasters describe 16S ribosomal DNA (rDNA) sequencing,which commonly used to identify different bacterial species. The ITS region (internal transcribed spacer region) is used to identify fungi in ‘this targeted metagenomic’ sequencing. 16S rDNA sequencing is described as limited as it cannot discern bacteria that are closely related with differential ecological roles.

4.2. Main Paper

  • AlphaFold2 Predictions (28:33–31:07): AlphaFold2 is a computational program used to predict protein structure. Here, the researchers used it to predict the structure of the AvrE family of protein in silico. The researchers found the predicted structure was a beta barrel structure similar to a bacterial porin which led them to test this proposed mechanism/function.
  • Liposome and Fluorescence (31:38–33:11): Liposomes are artificial vesicles used to mimic lipid bilayers. In this experiment, DspE channels were reconstructed in liposomes to test if it allows for the passage of small molecules, in this case fluorescent dyes. This experiment showed size specificity and functionality.
  • Inhibition Assays (33:11–35:07): There are compounds that inhibit certain processes and are often used in cell biology. Here the researchers identified polyamidoamine as a potential inhibitor of these bacterial channel proteins. They were able to determine this through assays using Xenopus oocytes and later with infections caused by Erwinia and Pseudomonas.

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

5.1. Snippet Paper

  • Antimicrobials and TheirTargets (2:45–4:21): They were discussing the potential or outcomes in discovering a unique bacteria/virus in tumors that could be treated with antibiotics depending on the specific bacteria/virus.
  • Human Microbiome (8:36–9:46 ): In the -podcast they were discussing what could have influenced the results of the experiment and one of the reasons was not getting rid of all the human DNA that could have caused change in the experiment.

5.2. Main Paper

  • Plant Microbiome (14:42–22:27): Plant Pathogens(Pseudomonas syringae and Erwinia)
  • Mechanisms of pathogenesis (16:45–19:05): Type III Secretion.
  • Virulence Factors (17:03–19:05): Flagella-like motor. Allows for the bacterium to export proteins through a hollow tube that can infiltrate the cytoplasm of the host cell.
  • Osmosis (22:07–23:26): Watersoaking interrupts osmosis.
  • Novel Antimicrobials (33:11–35:07): Polyamidoamines- design to limit infection in the plants by plugging the leak.

6. Podcast Questions

  1. Which of the following types of non-human DNAs have been found in excess in human tumors?
    1. Bacteria
    2. Fungi
    3. Viruses
    4. All of the above
  2. Which method is commonly used to detect non-human DNA in tumor tissues?
    1. Luciferase assays
    2. DNA sequencing
    3. Blood and saliva tests
    4. Western blot analysis
  3. Why was the notion of unique tumor microbiomes disputed? Pick all that apply.
    1. Some of the studies found no microbial DNA.
    2. Some studies did not use appropriate controls.
    3. Some studies used outdated statistical methods.
    4. Different studies showed different results.
  4. Which of the following would be a reasonable experiment to test microbe contribution to in vivo tumor phenotype?
    1. Co-culture a tumor cell line with different bacteria and quantify the cell line’s growth.
    2. Populate a mouse tumor model with specific bacteria and determine tumor growth.
    3. Use confocal microscopy to identify specific bacteria in sections of human tumors.
    4. Sequence inner and outer sections of human tumors and identify bacterial DNA.
  5. What is the primary consequence of water soaking in plants?
    1. Increased aerobic respiration
    2. Enhanced photosynthesis
    3. Altered pathogen resistance
    4. Loss of nutrients and water
  6. How was artificial intelligence (AI) used by Nomura and colleagues in this study?
    1. To identify chemicals that would preferentially block water soaking activity
    2. To write the manuscript and figure legends, as well as the schematic figure
    3. To generate sequence-based structure models of the AvrE-family of effectors
    4. To generate antibodies against the AvrE-family for use in western blotting
  7. What is the function of type III secretion systems in bacteria?
    1. They help bacteria with motility.
    2. They inject virulence factors into cells.
    3. They provide nutrients to bacteria.
    4. They protect bacteria from antibiotics.
  8. Nomura and colleagues were able to avoid water soaking by using a polyamidoamine to block the porin. What would be the effect of mutating the gene encoding the porin?
    1. The bacteria would be osmotically unstable.
    2. The bacteria would no longer acquire nutrients.
    3. The bacteria would no longer be pathogenic.
    4. The bacteria would be hypertonic or hypotonic.

7. Figure Reading Exercises

The following are two figure reading exercises, one from the snippet paper (Figure 3BCD) and one from the main paper (Figure 4).

7.1. First Figure Reading Exercise

7.1.1. Learning Objectives

Students will be able to:

  • Identify key aspect of experimental design including dependent and independent variables in an experiment as well as the controls and statistical significance notation.
  • Analyze the data to determine the effects of each compound and/or organism on tumor growth.
  • Propose a next experiment for this project.
Experimental Background (Aykut et al., Figure 3BCD)

Pancreatic cancers are typically highly aggressive and patients usually have a poor prognosis because there are few symptoms until the tumors are in very late stages. Some scientists have proposed that fungal species present in the tumor (the mycobiome) play an important role in tumor progression, but this has been controversial. To investigate this hypothesis Aykut et al. (2019) investigated fungal communities in a mouse model of pancreatic ductal adenocarcinoma (PDAC; mouse strain KC). They found that tumors were enriched in Malassezia species, a group of yeast that commonly infect adult skin. To explore a more direct and causative role for fungi in pancreatic tumor progression, KC mice were treated with an antifungal agent (amphotericin B) or vehicle (the solvent used to resuspend the drug). Tumors were sectioned, stained, and quantified for fibrosis, as well as other tumor features (panel a). Next, to examine the effect of the antifungal agent in a wild-type background, wild-type mice were implanted with tumors, treated with amphotericin B or vehicle control, and tumor weight quantified (panel b). To determine the interplay of amphotericin B and a drug normally used to treat tumors (chemotherapy drug gemcitabine), each was used alone or in combination to treat wild-type mice with implanted tumors and tumor weight quantified (panel c). Finally, to determine how fungal repopulation of the tumor affected tumor progression, wild-type mice that had been implanted tumors and treated with amphotericin B were inoculated with one of four different fungi and tumor weight quantified (panel d).

  • Aykut et al. (2019) is not licensed for Creative Commons use, so the figure cannot be copied here. Please see the article at the journal’s web page. There is a version of this paper available at PubMed: https://pmc.ncbi.nlm.nih.gov/articles/PMC6858566/

7.1.2. Questions

  1. The results of the amphotericin B (antifungal drug) and/or gemcitabine (chemotherapic drug) treatment on tumor growth i wild-type mice are shown in panel b. The positive control for the experiment in panel b is ______ and the negative control for the experiment in panel b is ______.
    1. Implanted tumor; no negative control
    2. Gemcitabine; amphotericin B
    3. No positive control; vehicle (solvent)
    4. Amphotericin B; vehicle (solvent)
  2. The results of the amphotericin B (antifungal drug) and/or gemcitabine (chemotherapic drug) treatment on tumor growth i wild-type mice are shown in panel b.  What can you conclude about antifungal treatment and tumor growth based on these data?
    1. Treatment reduced tumor growth.
    2. Treatment completely inhibited tumor growth.
    3. Treatment did not affect tumor growth.
    4. Treatment enhanced tumor growth.
  3. To examine the combined impact (and possible negative impact) of combining antifungal treatment (amphotericin B) and chemotherapy drug treatment (gemcitabine), the researchers treated wild-type mice with tumors with each drug alone, in combination, or a control.  Tumor growth was quantified and is shown in panel c.  Which treatment was most successful in halting tumor progression?
    1. Vehicle
    2. Amphotericin B alone
    3. Gemcitabine alone
    4. Amphotericin B plus gemcitabine
  4. The researchers investigated the possible impact of other fungal species by repopulating the amphotericin B-treated tumors in mice with different fungal species and assessing tumor growth (panel d). The dependent variable for the experiment in panel d is ______ and the independent variable for the experiment in panel d is ______.
    1. S. cerevisiae; M. globosa
    2. Tumor weight; species of fungi
    3. Implanted tumor; no tumor implant
    4. Tumor color; tumor mass
  5. The results of repopulating the amphotericin B-treated tumors with different fungi are shown in panel d.  There are some results that are not statistically different and some that are.  What feature in the bar plot allows you to tell which are which?
    1. The standard error whiskers
    2. The mean bar height
    3. The p value listed above
    4. The value of the y-axis
  6. The results of repopulating the amphotericin B-treated tumors with different fungi are shown in panel d.   Based on these data, which fungus enhanced tumor growth?
    1. Malassezia globosa
    2. Aspergillus
    3. Candida
    4. Saccharomyces cerevisiae
    5. None of the fungi
  7. Which of the following is the best next experiment to further explore this fungal-based tumor progression?
    1. Increase sample size beyond 10 mice and recalculate all measures
    2. Treat with a mixture of Malassezia species and quantify tumors
    3. Perform additional statistical calculations, such as an ANOVA
    4. Examine fungal communities in brain and nervous system tumors

7.2. Second Figure Reading Exercise

7.2.1. Learning Objectives

Students will be able to:

  • Identify key features of experimental design including the dependent and independent variables in an experiment as well as the controls.
  • Evaluate bacterial growth and leaf appearance results to make conclusions about whether they are consistent or inconsistent.
  • Analyze data provided to make conclusions about the effect of PAMAM G1 on bacterial infection, activation of the plant immune response, and fireblight disease.
  • Make conclusions when given alternate results.
Experimental Background (Nomura et al., Figure 4a-d)

Erwinia amylovora is a plant pathogen that causes the disease known as fireblight, which afflicts rosaceous hosts, including members of the pear and apple families, and can destroy harvests. One of the symptoms of fireblight is water soaking in which plants lose integrity and die. A number of plant pathogens including Pantoea stewartii and Pectobacterium carotovorum can also induce water soaking, which is the focus of this study. Earlier in this study, Nomura et al. (2023) identified that each water soaking bacterial pathogen encoded a porin which are collectively known as AvrE-family effectors.  These include AvrE from Pantoea stewartii and DspE from Erwinia amylovora. Additionally, they identified a compound called PAMAM G1 (G1) that was capable of blocking the channels formed by the porin. They next hypothesized that G1 could also be a treatment for water soaking diseases. First, they wanted to determine whether G1 treatment could control bacterial growth on a plant and whether it was porin-dependent. To test this they used Pantoea stewartii strains that were wild-type (DC3000), had a mutation in AvrE (ΔE), had a mutation in a gene that is functionally redundant to AvrE (hopM1; ΔM), or mutations in both (double-mutant ΔME). They inoculated each strain onto Arabidopsis plant leaves that were or were not treated with G1 and quantified bacterial growth (panel a and b). Next, to determine whether the G1 effect was due to activating the Arabidopsis plant immune system, they assayed whether G1 treatment activated expression of an immune response gene PR1 using western blot analysis to detect PR1 protein (panel c). Additionally, as controls, plants were also treated with either benzothiadiazole (BTH) or flg22 (flg22), which are both known to activate PR1 expression (panel c). Finally, to investigate the ability of G1 to inhibit fireblight disease on pears, wild-type Erwinia amylovora (Ea273) or a porin mutant (dspE-) were inoculated onto immature pear fruits that had been treated or not with G1 (panel d).

Bacterial growth, leaf and fruit pathogenesis photographs.
Figure 4. “Effect of PAMAM G1 on bacterial infections. a,b, PAMAM G1 inhibits Pst DC3000 multiplication in an AvrE-dependent manner. A total of 1 × 106 colony-forming units (CFUs) per millilitre of Pst DC3000, the avrE,hopM1 double deletion mutant (ΔEM), the avrE single deletion mutant (ΔE) or the hopM1 single deletion mutant (ΔM) were syringe-inoculated into leaves of Arabidopsis WT Col-0 plants, with or without 50 nM PAMAM G1. Populations of bacteria (mean ± s.e.m.; n = 3 leaf samples) (a) in leaves were determined at day 3 after infiltration. Disease symptom pictures (b) were taken at day 4 after infiltration. c, PAMAM G1 does not induce PR1 protein expression in Arabidopsis. Arabidopsis Col-0 leaves were syringe-infiltrated with 10 µM PAMAM G1. Plants were kept under high humidity (>95%) for 3 days at 23 °C. PR1 protein in leaves was detected by an anti-PR1 polyclonal antibody. As positive controls, 100 µM benzothiadiazole (BTH), a synthetic chemical analogue of salicylic acid, and 1 µM flg22, a synthetic peptide derived from the conserved N-terminal 22 amino acids of bacterial flagellin, induce PR1 expression. The uncropped gel image is shown in Supplementary Fig. 1g. d, PAMAM G1 inhibits fire blight disease by E. amylovora Ea273. Immature pear fruits were spot-inoculated (indicated by arrows) with 10 µl of 1 × 103 CFUs ml−1 of Ea273 or the dspE mutant (dspE−), with or without 10 µM PAMAM G1. Inoculated pears were placed on a wet paper towel in a sterile box and incubated at 28 °C for 10 days. Diseased pears show areas with a dark, necrotic appearance. Experiments were carried out three times with similar results. P values were calculated using two-way ANOVA (a). (Nomura et al. 2023, no changes).

7.2.2. Questions

  1. The bacterial growth on the plants for different bacterial genotypes with G1 (green) and without  G1(blue) treatment are shown in panel a.   There are some results that are not statistically different and some that are.  What feature in the bar plot allows you to tell which are which?
    1. The standard error whiskers
    2. The mean bar height
    3. The p value listed above
    4. The value of the y-axis
  2. The bacterial growth on the plants for different bacterial genotypes with G1 (green) and without  G1(blue) treatment are shown in panel a.  Based on these data, which genes are necessary for bacterial growth in the absence of G1?
    1. Only AvrE is required
    2. Only hopM1 is required
    3. At least AvrE or hopM1
    4. Both genes are required
  3. Do the bacterial growth results in panel a support or conflict with the leaf pathogenesis results in panel b? What is your evidence?
    1. Conflict; when CFU are high, the leaf show health
    2. Support; when CFU are high, the leaf shows disease
    3. Conflict; when left untreated, the disease is inhibited
    4. Support; when disease is high, the genotype is mutant
  4. The bacterial growth on the plants for different bacterial genotypes with G1 (green) and without  G1(blue) treatment are shown in panel a. Based on these data, which gene(s) encode(s) the porin blocked by G1?
    1. avrE
    2. hopM1
    3. Both
    4. Neither
  5. The results for the experiment that determines whether the plant immune system is activated by G1 treatment are shown in panel c.  The positive control(s) for the experiment in panel c is/are ______ and the negative control(s) for the experiment in panel c is/are ______.
    1. Flg22 and water; BTH
    2. G1; flg22 and BTH
    3. BTH and flg22; water
    4. Water; G1 and flg22
  6. The results for the experiment that determines whether the plant immune system is activated by G1 treatment are shown in panel c.  Based on these results does G1 activate the plant immune system? What is your evidence?
    1. Yes, there is PR1 present in G1 treated plant cells.
    2. No, the PR1 protein is expressed under all conditions.
    3. Yes, G1 decreases PR1 levels compared to the control.
    4. No, there is no PR1 present in G1 treated plant cells.
  7. If the PR1 protein had been detected in the leaf treated with G1, what might you conclude?
    1. G1 induces an autoimmune state that is inhibitory to all pathogens
    2. G1 initiates an immune response rather than blocking pathogenesis
    3. G1 enhances both transcription of RNAs and translation of proteins
    4. G1 acts as a chemoattractant for compounds that regulate mitosis
  8. The results for the experiment that determines whether fireblight is affected by G1 treatment are shown in panel d. Based on these results can G1 control fireblight on immature pears? What is your evidence?
    1. Yes, G1 treatment eliminates the disease on wild-type pears.
    2. No, G1 treatment does not reduces disease on either pear.
    3. Yes, but G1 treatment only reduces disease on dspE- pears.
    4. No, G1 treatment enhances disease in wild-type pears.

8. Paper Information and Licensing

8.1. Snippet paper

  • Aykut B, Pushalkar S, Chen R, Li Q, Abengozar R, Kim JI, Shadaloey SA, Wu D, Preiss P, Verma N, Guo Y, Saxena A, Vardhan M, Diskin B, Wang W, Leinwand J, Kurz E, Kochen Rossi JA, Hundeyin M, Zambrinis C, Li X, Saxena D, Miller G. 2019. The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature. 574(7777):264-267. doi: 10.1038/s41586-019-1608-2
  • This article is not licensed for Creative Commons use; see the article’s copyright information. Thus, the abstract and figures cannot be copied here. Please see the article at the journal’s web page.   There is a version of this paper available at PubMed: https://pmc.ncbi.nlm.nih.gov/articles/PMC6858566/

8.2. Main paper

  • Nomura K, Andreazza F, Cheng J, Dong K, Zhou P, He SY. 2023. Bacterial pathogens deliver water- and solute-permeable channels to plant cells. Nature.;621(7979):586-591. doi: 10.1038/s41586-023-06531-5
  • 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. See the article’s copyright information.

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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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