Metabolic Pathways

TWiM #278: Bacteria Sing the Blues

Podcast and Annotation Information
  • Annotation by Joseph M. Gibson, Craig M. Mulhern, Jr., Rebecca Seipelt-Thiemann, and Karen P. York
  • Podcast audio by TWiM: Listen to TWiM #278 Podcast
  • Podcast transcript by Otter.ai and edited by Rebecca Seipelt-Thiemann and Laurel Thompson: Access Podcast Transcripts
  • Papers Discussed:
    • Radjabzadeh D, Bosch JA, Uitterlinden AG, Zwinderman AH, Ikram MA, van Meurs JB, Luik AI, Nieuwdorp M, Lok A, van Duijn CM, Kraaij R, Amin N. 2022. Gut microbiome-wide association study of depressive symptoms. Nat Commun 13(1):7128 https://doi.org/10.1038/s41467-022-34502-3 
    • Bosch JA, Nieuwdorp M, Zwinderman AH, Deschasaux M, Radjabzadeh D, Kraaij R, Davids M, de Rooij SR, Lok, A. 2022. The gut microbiota and depressive symptoms across ethnic groups. Nat Commun 13(1):7129. https://doi.org/10.1038/s41467-022-34504-1  
    • Nolan A C, Zeden MS, Kviatkovski I, Campbell C, Urwin L, Corrigan RM, Gründling A, O’Gara JP. 2023. Purine nucleosides interfere with c-di-AMP levels and act as adjuvants to re-sensitize MRSA to β-lactam antibiotics. mBio 14(1):e0247822. https://doi.org/10.1128/mbio.02478-22

1. Paper Abstracts

1.1. Snippet papers; discussion starts at 1:16 minutes and 17:55 minutes

The Most Interesting Things (according to students)

This study provided evidence for an association between 13 taxa of human gut bacteria and depressive symptoms. Moreover, the specific bacteria identified included taxa that are known to affect the synthesis of neurotransmitters associated with depressive symptoms and treatment plans. A second study they mentioned extended the first study by increasing the number and ethnic diversity of participants living in the same urban area. This study showed the association of human gut bacteria with depressive symptoms did not differ between ethnic groups.  

“Depression is one of the most poorly understood diseases due to its elusive pathogenesis. There is an urgency to identify molecular and biological mechanisms underlying depression and the gut microbiome is a novel area of interest. Here we investigate the relation of fecal microbiome diversity and composition with depressive symptoms in 1,054 participants from the Rotterdam Study cohort and validate these findings in the Amsterdam HELIUS cohort in 1,539 subjects. We identify association of thirteen microbial taxa, including genera Eggerthella, Subdoligranulum, Coprococcus, Sellimonas, Lachnoclostridium, Hungatella, Ruminococcaceae (UCG002, UCG003 and UCG005), LachnospiraceaeUCG001, Eubacterium ventriosum and Ruminococcusgauvreauii group, and family Ruminococcaceae with depressive symptoms. These bacteria are known to be involved in the synthesis of glutamate, butyrate, serotonin and gamma amino butyric acid (GABA), which are key neurotransmitters for depression. Our study suggests that the gut microbiome composition may play a key role in depression.” (Radjabzadeh et al. 2022, with no changes)

“The gut microbiome is thought to play a role in depressive disorders, which makes it an attractive target for interventions. Both the microbiome and depressive symptom levels vary substantially across ethnic groups. Thus, any intervention for depression targeting the microbiome requires understanding of microbiome-depression associations across ethnicities. Analysing data from the HELIUS cohort, we characterize the gut microbiota and its associations with depressive symptoms in 6 ethnic groups (Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish, Moroccan; N = 3211), living in the same urban area. Diversity of the gut microbiota, both within (α-diversity) and between individuals (β-diversity), predicts depressive symptom levels, taking into account demographic, behavioural, and medical differences. These associations do not differ between ethnic groups. Further, β-diversity explains 29%–18% of the ethnic differences in depressive symptoms. Bacterial genera associated with depressive symptoms belong to multiple families, prominently including the families Christensenellaceae, Lachnospiraceae, and Ruminococcaceae. In summary, the results show that the gut microbiota are linked to depressive symptom levels and that this association generalizes across ethnic groups. Moreover, the results suggest that ethnic differences in the gut microbiota may partly explain parallel disparities in depression.” (Bosch et al. 2022, with no changes)

1.2. Main paper; discussion starts at 31:30 minutes

The Most Interesting Things (according to students)

The addition of the purine, guanosine, was shown to significantly increase the effectiveness of β-lactam antibiotics to control growth of methicillin-resistant Staphylococcus aureus (MRSA). The extra guanosine interferes with purine derived signaling molecules (such as cyclic-di-AMP) affecting the resistance mechanism. Guanine can be potentially used therapeutically with beta-lactam antibiotics to increase the efficacy in treating highly resistant clinical strains of MRSA.  

“The purine-derived signaling molecules c-di-AMP and (p)ppGpp control mecA/PBP2a-mediated β-lactam resistance in methicillin-resistant Staphylococcus aureus (MRSA) raise the possibility that purine availability can control antibiotic susceptibility. Consistent with this, exogenous guanosine and xanthosine, which are fluxed through the GTP branch of purine biosynthesis, were shown to significantly reduce MRSA β-lactam resistance. In contrast, adenosine (fluxed to ATP) significantly increased oxacillin resistance, whereas inosine (which can be fluxed to ATP and GTP via hypoxanthine) only marginally increased oxacillin susceptibility. Furthermore, mutations that interfere with de novo purine synthesis (pur operon), transport (NupG, PbuG, PbuX) and the salvage pathway (DeoD2, Hpt) increased β-lactam resistance in MRSA strain JE2. Increased resistance of a nupG mutant was not significantly reversed by guanosine, indicating that NupG is required for guanosine transport, which is required to reduce β-lactam resistance. Suppressor mutants resistant to oxacillin/guanosine combinations contained several purine salvage pathway mutations, including nupG and hpt. Guanosine significantly increased cell size and reduced levels of c-di-AMP, while inactivation of GdpP, the c-di-AMP phosphodiesterase negated the impact of guanosine on β-lactam susceptibility. PBP2a expression was unaffected in nupG or deoD2 mutants, suggesting that guanosine-induced β-lactam susceptibility may result from dysfunctional c-di-AMP-dependent osmoregulation. These data reveal the therapeutic potential of purine nucleosides, as β-lactam adjuvants that interfere with the normal activation of c-di-AMP are required for high-level β-lactam resistance in MRSA.” (Nolan et al. 2022, with no changes)

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

Snippet Main
Vision and Change Topics
  • Microbial Ecology (V&C_ME)
  • Metabolic Pathways (V&C_MP)
  • Structure and Function (V&C_SF)
ASM Fundamental Statements
  • Fundamental Statement 22 (ASM_22): Most microbes interact with hosts in beneficial or neutral ways, with a minority having a detrimental impact on their host.
  • Fundamental Statement 7 (ASM_7): Microbes have evolved structures adapted for specific functions that are often associated with a fitness advantage in a particular environment.
  • Fundamental Statement 13 (ASM_13): Intrinsic factors, such as genotype, metabolism, and cell structures, impact the survival and growth of microbes.

 

3.  Potential Learning Objectives for the Podcast

The student will be able to: Paper1 Order2
  • Identify the experimental question the researchers are addressed in the snippet papers.
  • Identify the difference between a controlled microbiome study and an association microbiome study.
  • Map similar features in genome wide association studies and microbiome studies.
  • Recall the research conclusion for the gut microbiome-depression studies.
 S L
  • Predict the results of an experiment based on the results of these studies.
 S H
  • Recall features that contribute to the spread and pathogenicity of methicillin-resistant Staphylococcus aureus (MRSA)
  • Recall specific antibiotics that belong to the beta-lactam class of antibiotics.
  • Identify features related to the disk diffusion assay method.
 M L
  • Evaluate the results of a disk diffusion assay and draw conclusions about each compound’s effectiveness.
 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

  • Association Study (3:25–7:06): This is a correlation type of study where a particular trait is assayed between groups and is not an experiment with dependent and independent variable.  Association studies include both genome wide association studies (GWAS) and many microbiome studies.  Here, microbiome studies, also called metagenomic studies, were performed using amplicon sequence variant (ASV) to compare the microbiome bacterial species present in people with and without depressive symptoms. 
  • Odds Ratio (5:18–6:41): The odds ratio is a probability.  It quantifies the association between an organismal trait and an exposure vs. a non-exposure.  For example, lung cancer and smoking vs. non-smoking.  Here the comparison was for depressive symptoms and a specific microbiome composition vs another specific microbiome composition.
  • Mendelian Randomization (11:47–17:00): This analysis is for determining whether a specific exposure (here microbiome composition) has a causal relationship with an outcome, such as disease (here depressive symptoms).

4.2. Main Paper

  • Minimal Inhibitory Concentration (MIC) (38:36–39:16): This is the lowest concentration of a substance to show an effect.  Here, the MIC for oxacillin decreased when the guanosine was added.
  • Disk Diffusion Assay (42:11–43:13): This assay is used to determine antibiotic effectiveness by impregnating a paper disk with a compound and placing it on a lawn of bacteria.  If the bacteria are sensitive to the compound, then you’ll see a zone of clearance where the bacteria cannot grow.  The used this assay to determine whether the effect they found with oxacillin was also true for other antibiotics.

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

5.1. Snippet Paper

  • Association Study (3:25–7:06): This is a correlation type of study where a particular trait is assayed between groups and is not an experiment with dependent and independent variable.  Association studies include both genome wide association studies (GWAS) and many microbiome studies.  Here, microbiome studies, also called metagenomic studies, were performed using amplicon sequence variant (ASV) to compare the microbiome bacterial species present in people with and without depressive symptoms. 

5.2. Main Paper

  • Pathogenicity of Staphylococcus aureus (32:18–32:56):  This topic involves how a bacterium causes disease in the host, here for Staphylococcus aureus.
  • Methicillin-resistant Staphylococcus aureus (MRSA) (32:56–36:29): These bacteria are resistant to many antibiotics.

6. Podcast Questions

  1. What is the main experimental question the researchers are asking in the two studies discussed in the snippet?
    1. Which human genes are associated with depressive symptoms in humans?
    2. Which gut microorganisms are associated with depressive symptoms in humans?
    3. Which gut bacteriophages (viruses) are associated with depressive symptoms in humans?
    4. Which microbial metabolites are associated with depressive symptoms in humans?
  2. Which type of study could establish a direct cause and effect between microbes and their effect on their host physiology ?
    1. A study that assays the microbes with data from > 300 participants from many ethnic populations.
    2. A study that adds microbe metabolites in nutritional supplements with evaluation of  host symptoms.
    3. A study that assays the bacteriophages from > 3000 participants that are age and sex-matched.
    4. A study that adds certain microbes into germ free mice with evaluation for host symptoms.
  3. Both genome wide association studies and many microbiome studies are simliar in that they are both correlation studies.  Which feature in microbiome studies is equivalent to having different versions of a gene (allele)?
    1. different bacterial species composition
    2. different genes in the same bacteria
    3. different bacteriophage being present
    4. different plasmids in the same species
  4. What is the main finding of the Radjabzadeh et al. (2022) study as it relates to a direction connection between microbiome and depressive disorders?
    1. The microbiome bacteriophages that were identified are known to improve digestion of food and affect nutrition broadly in the host.
    2. The microbiome bacteria that were identified can produce neuroactive metabolites that impact depressive symptoms in the host.
    3. The microbiome bacteria that were identified compete with pathogens for the niche; when filled with pathogens, depression results.
    4. The microbiome bacteriophages that were identified lyse specific microbes and the bacterial lysates contain neuroactive peptides.
  5. The podcasters note near the end of the snippet discussion that most probiotics available for retail purchase have a bacterium called Bifidobacterium longum. They further note that the researchers identified this bacterium as being correlated to depressive symptoms, but that many B. longum strains exist, so it may be strain-specific. There are measures for testing depressive symptoms in mice (Belovicova et al. 2017), such as the tail suspension test (TST). You acquire mice with a “typical” microbiome and supplement the chow of 10 mice per group with different strains of B. longum or no additional microbes and use the TST to quantify mouse depression.  Match the results you would expect for each hypothesis.
Hypothesis Results
a. ________ B. longum induces depressive symptoms in mice. 1. All mice show equally low depressive symptoms regardless of B. longum strain, and the level is equivalent to the “no microbes” group of mice.
b. ________ B. longum induction of depressive symptoms in mice is strain-specific. 2. All mice show equally high depressive symptoms regardless of B. longum strain, but the “no microbes” group does not show depressive symptoms.
c. ________ B. longum does not induce depressive symptoms in mice. 3. Different groups show different levels of depressive symptoms based on B. longum strain, and some are equivalent to the “no microbes” group of mice.

Belovicova K, Bogi E, Csatlosova K, Dubovicky M. Animal tests for anxiety-like and depression-like behavior in rats. Interdiscip Toxicol. 2017 Sep;10(1):40-43. doi: 10.1515/intox-2017-0006

  1. Penicillin and methicillin are members of a broad group of safe and effective antibiotics used for the treatment of bacterial infections. What is this broad group of antibiotics called?
    1. tetracyclins
    2. chloramphenicols
    3. glycopeptides
    4. beta-lactams
  2. Methicillin-resistant Staphylococcus aureus (MRSA) infections are challenging for many reasons. Which of the following statements are true about MRSA? [pick all that apply]
    1. It is very commonly circulated amongst individuals in human populations.
    2. It survives on surfaces in the environment for more 24 hours and up to a week.
    3. It can cause a variety of diseases including pneumonia and skin infections.
    4. It is resistant to some of the most widely used and safe antibiotics.
  3. Antibiotic effectiveness can be quantified using the disk diffusion assay.  In this assay method, where is the source/location of the antibiotic?
    1. The solid agar medium is made using the antibiotic.
    2. The liquid medium used to make the bacterial lawn.
    3. The paper disk itself is impregnated with  the antibiotic.
    4. The antibiotic is applied to the agar plate before the bacteria.

Kirby-Bauer Susceptibility test results9. The results of a disk diffusion test are shown in the image where four different antibiotics (1-4) were tested for a particular bacterium.  Based on these results, the bacterium is least to which antibiotic? What is your evidence?

    1. 1; the zone of inhibition is smallest
    2. 2; the zone of inhibition is cloudiest
    3. 3; the zone of inhibition is clearest
    4. 4; the zone of inhibition is largest

Image source: Flores H, Luethy P, Doub JB. 2024. Discordant Susceptibilities of Enterobacterales to Different Tetracycline Classes. Cureus. 16(12):e74917. doi: 10.7759/cureus.74917. PMID: 39742159; PMCID: PMC11687707. (Figure 1A, CC 4.0 license; see the article’s copyright information, changes: labeled disks with letters for clarity)

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 2).

7.1. First Figure Reading Exercise

7.1.1. Learning Objectives

Students will be able to: 

  • Identify key features of taxonomic representations of microbiome association studies.
  • Identify the relationship of abundance and association in microbiome studies.
  • Analyze the data to make conclusions about the taxonomy of bacteria that are positively and negatively associated with depressive symptoms.
  • Propose a therapeutic intervention based on these studies.
Experimental Background (Radjabzadeh et al., Figure 1)

The gut microbiome is implicated in overall health, particularly in nutrient uptake and the immune system.  Dysbiosis is the state in which the ratio, species, or number of gut microbiota is compromised and has been implicated in a large number of diseases including many autoimmune diseases.  Radjabzadeh et al. (2022) were interested in the relationship of the gut microbiome and human depressive symptoms.  To investigate differences in the gut microbiome of people with and without depressive symptoms, they collected fecal samples from 2,672 total participants who were profiled for depressive symptoms.  The researchers identified the gut bacterial community composition and diversity using 16S ribosomal DNA (rDNA) sequencing. Statistical analyses were used to identify bacterial genera (or families) associated with depressive symptoms.  The bacteria identified within the study are presented within a taxonomic context, as a phylogenetic tree, with those that correlated with some aspect of depressive symptoms (presence or absence) having special notation as indicated in the figure legend.  The phyla are represented as colored sectors: green = Firmicutes; purple = Verrucomicrobiota; gold = Actinomycetota; red = Pseudomonadota; blue = Bacteroidota.

 

Pie chart of taxonomies.
Figure 1. “The taxonomic tree showing the 13 genera associated with depressive symptoms. Red dots depict negatively associated genera with depressive symptoms and blue ones depict positively associated genera with depressive symptoms. The outermost layer depicts the phylum level followed by class, order, family and genus levels.” (Radjabzadeh et al. 2022, no changes).

 

7.1.2. Questions

  1.  Which phylum has the most genera associated with depressive symptoms and which color is the sector?
    1. Actinomycetota; gold
    2. Bacteroidota; blue
    3. Firmicutes; green
    4. Pseudomonadota; red
    5. Verrucomicrobiota; purple
  2. The bacteria associated with depressive symptoms are designated as either a positive or a negative association.  A positive association means that people with depressive symptoms are ______ to have these bacteria while a negatively association means that people with depressive symptoms are _____ to have these bacteria.
    1. more likely; less likely
    2. less likely; more likely
    3. always found; never found
    4. never found; always found
  3. Which color dot represents genera that have a negative association with depressive symptoms?
    1. blue
    2. green
    3. gold
    4. red
  4. In which phylum are most of the bacteria that were identified as associated with depressive symptoms?
    1. Actinomycetota
    2. Bacteroidota
    3. Firmicutes
    4. Pseudomonadota
    5. Verrucomicrobiota
  5. Which family of bacteria has the most genera that are negatively associated with depressive symptoms?
    1. Eubacteriaceae
    2. Lachnospiraceae
    3. Ruminococcaceae
    4. Bifidobacteriaceae
  6. Which family of bacteria has the most genera that are positively associated with depressive symptoms?
    1. Eubacteriaceae
    2. Lachnospiraceae
    3. Ruminococcaceae
    4. Bifidobacteriaceae
  7. Which Actinomycetota genus was associated with depressive symptoms, and was it a positive or negative association?
    1. Eggerthella; positive
    2. Sellimonas; positive
    3. Hungatella; positive
    4. Coprococcus; negative
  8. If further research demonstrates a clear causal relationship between the bacteria identified in this study and depressive symptoms, which of the following describe(s) convenient strategy(ies) for depression therapy intervention? [pick all that apply]
    1. Administering a probiotic of “negative association” bacteria in the diet of patients with depressive symptoms.
    2. Administering a probiotic of “positive association” bacteria in the diet of patients with depressive symptoms.
    3. Removing or blocking the activity of “negative association” bacteria in patients with depressive symptoms.
    4. Removing or blocking the activity of “positive association” bacteria in patients with depressive symptoms.

7.2. Second Figure Reading Exercise

7.2.1. Learning Objectives

Students will be able to:

  • Identify key features of disk diffusion assay experimental design and results, as well as data represented in bar graphs.
  • Interpret the data to make conclusions about antibiotic effectiveness.
  • Evaluate the data to draw conclusions about whether guanosine does or does not enhance antibiotic effectiveness.
Experimental Background (Nolan et al., Figure 2)

Antibiotics are grouped into a variety of classes and each class typically interacts with different host cell machinery and has distinct features. Methicillin-resistant Staphylococcus aureus (MRSA), is a bacterium that infects many body locations and is resistant to many common antibiotics. In this study, Nolan et al (2022) wanted to investigate whether guanosine addition could enhance the effects of different antibiotic classes against methicillin-resistant Staphylococcus aureus. To test this, they used a disk diffusion assay, also called a Kirby-Bauer susceptibility test, with four different β-lactam antibiotics (panel A) in the presence (MHA Gua) or absence (MHA) of the nucleoside guanosine. Disk diffusion results were then quantified for these antibiotics (beta-lactam antibiotics, panel B) and other classes of antibiotics whose disk diffusion assays were not shown (panel C).

Two slides and the zone diameter of accompanying treatments sown in photos and as bar charts.
Figure 2. “Exogenous guanosine only increases susceptibility of MRSA to β-lactam and not other classes of antibiotic. (A) Susceptibility of wild-type JE2 to the β-lactam antibiotics cefotaxime (top left), cefoxitin (top right), cefaclor (bottom left) and penicillin G (bottom right) determined by disk diffusion assay on Mueller-Hinton 2% NaCl agar (MHA) (left), or MHA supplemented with 0.2 g/l guanosine (MHA Gua) (right). This experiment was repeated three times and a representative image is shown. (B) Susceptibility of wild-type JE2 to the β-lactam antibiotics cefotaxime, cefoxitin, cefaclor and penicillin G determined by disk diffusion assay on MHA or MHA with 0.2 g/l guanosine (Gua). (C) Susceptibility of wild-type JE2 to tetracycline, vancomycin, chloramphenicol or gentamicin determined by disk diffusion assay on MHA, or MHA with 0.2 g/l Gua. Data (zone diameters, mm) are the average of 3 independent experiments and error bars represent standard deviation. Statistical significance was determined by one-way ANOVA. ****, P , 0.0001, ns, not significant” (Nolan et al. 2022, no changes).

 

7.2.2. Questions

  1. What is the difference between the disk diffusion assays shown by the two plates in panel A?
    1. The left plate and the right plate used different antibiotics.
    2. The right plate includes a nucleoside and the left plate does not.
    3. The left plate and the right plate used different bacterial species.
    4. The right plate is a different standard medium than the left plate.
  2. Based only on the disk diffusion results (panel A), what is the most effective antibiotic or antibiotic combination?
    1. Cefotaxime without guanosine
    2. Defoxitin without guanosine
    3. Cefaclor with guanosine
    4. Penicillin G with guanosine
  3. Disk diffusion results were quantified and averages to generate the data in panels B and C.  The data are displayed by bar graphs. Match the bar graph feature with its description. (1 = mean; 2 = median; 3 = outlier; 4 = results are statistically significant; 5 = individual measures; 6= full data range excluding outliers; 7 = results are not statistically significant; 8 = standard deviation)
    1. _______ Asterisks
    2. _______ Whiskers
    3. _______ Bar height
    4. _______ Circles 
    5. _______ ns
  4. Based on the quantified, averaged disk diffusion results shown in panel B, what is the average diameter of the zone of clearing for MRSA using cefotaxime in MHA agar in the absence of additional guanosine?
    1. 8 mm
    2. 9 mm
    3. 14 mm
    4. 8 cm
    5. 12 cm
  5. Based on the quantified, averaged disk diffusion results shown in panel B, what is the average diameter of the zone of clearing for MRSA with Penicillin G in MHA agar with added guanosine?
    1. 9 mm
    2. 12 mm
    3. 14 mm
    4. 18 mm
    5. 35 mm
  6. Based on the quantified, averaged disk diffusion results for beta-lactam antibiotics (panel B), which antibiotics are more effective against MRSA in the presence of additional guanosine?  What is your evidence? [pick all that apply]
    1. Cefotaxime; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    2. Defoxitin; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    3. Cefaclor; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    4. Penicillin G; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    5. none of the above
  7. Based on the quantified, averaged disk diffusion results for “other” antibiotics (panel C), which antibiotics are more effective against MRSA in the presence of additional guanosine?  What is your evidence? [pick all that apply]
    1. Tetracycline; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    2. Vancomycin; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    3. Chloramphenicol; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    4. Gentamycin; the average is higher for + Gua than antibiotic alone and the difference is statistically significant.
    5. none of the above
  8. What is the most significant result from this experiment regarding treatment of MRSA infections?
    1. Adding guanosine increases resistance of MRSA to β-lactam antibiotics.
    2. Adding guanosine makes MRSA more susceptible to β-lactam antibiotics.
    3. Adding guanosine makes MRSA more susceptible to all classes of antibiotics.
    4. Adding guanosine makes no difference to the susceptibility of antibiotics.
  9. True or False; These data support the idea of adding guanosine to help in treating MRSA with any antibiotic.
    1. True
    2. False

8. Paper Information and Licensing

8.1. Snippet paper

8.2. Main paper

  • Nolan A C, Zeden MS, Kviatkovski I, Campbell C, Urwin L, Corrigan RM, Gründling A, O’Gara JP. 2023. Purine nucleosides interfere with c-di-AMP levels and act as adjuvants to re-sensitize MRSA to β-lactam antibiotics. mBio 14(1):e0247822. https://doi.org/10.1128/mbio.02478-22
  • 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 https://journals.asm.org/doi/10.1128/mbio.02478-22 

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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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