Impact of Microorganisms

TWiM #281: Microbes Making Jet Fuel

Podcast and Annotation Information

1. Paper Abstracts

1.1. Snippet paper; discussion starts at 3:23 minutes

The Most Interesting Things (according to students)

  • The energy output of the synthetic biofuels was put into context of other fuel sources which increased the validity of it being a great energy source.
  • It is important to analyze the input needed to feed and grow these bacteria as potentially using fossil fuels to produce this new biosynthetic fuel would negate the clean energy claim of this new alternative biosynthetic fuel.

“Cyclopropane-functionalized hydrocarbons are excellent fuels due their high energy density. However, the organic synthesis of these molecules is challenging. In this work, we produced polycyclopropanated fatty acids in bacteria. These molecules can be converted into renewable fuels for energy-demanding applications such as shipping, long-haul transport, aviation, and rocketry. We explored the chemical diversity encoded in thousands of bacterial genomes to identify and repurpose naturally occurring cyclopropanated molecules. We identified a set of candidate iterative polyketide synthases (iPKSs) predicted to produce polycyclopropanated fatty acids (POP-FAs), expressed them in Streptomyces coelicolor, and produced POP-FAs. We determined the structure of the molecules and increased their production 22-fold. Finally, we produced polycyclopropanated fatty acid methyl esters (POP-FAMEs). Our POP fuel candidates can have net heating values of more than 50 MJ/L. Our research shows that the POP-FAMEs and other POPs have the energetic properties for energy-demanding applications for which sustainable alternatives are scarce.” (Cruz-Morales et al 2022, no changes)

1.2. Main paper; discussion starts at 23:10 minutes

The Most Interesting Things (according to students)

  • There was a lack of Koch’s postulate which is problematic for physicians trying to treat these infections. Even though they will be able to easily and quickly identify the species present during infection, they won’t be able to pinpoint exactly which one to treat without following the postulate. That conclusion might shift the goal of the paper to a more sequencing based approach, rather than marketing it as a new diagnostic methodology.
  • The authors found a quicker alternative to whole genome sequencing, and they were able to find a lot of new distinct bacterial species.

“Serious infections are characterized by rapid progression, poor prognosis, and difficulty in diagnosis. Recently, a new technique known as nanopore-targeted sequencing (NTS) was developed that facilitates the rapid and accurate detection of pathogenic microorganisms and is extremely suitable for patients with serious infections. The aim of our study was to evaluate the clinical application of NTS in the diagnosis and treatment of patients with serious infections. We developed an NTS technology that could detect microorganisms within a 6-h window based on the amplification of the 16S rRNA gene of bacteria, the internal transcribed spacer region of fungi, and the rpoB gene of Mycobacterium. The NTS detection results were compared with those of blood cultures and anal swabs from 50 patients with blood diseases suffering serious infections. The patient’s condition before and after NTS was compared. The response rate and the infection-related mortality after the adjustment of antibiotics based on NTS were calculated. The positivity rate of pathogens was highest in NTS (90%), followed by blood culture (32.6%) and anal swabs (14.6%). After adjusting antibiotics for bacteria and fungi detected by NTS, the patients’ condition improved significantly. Moreover, the response rate of anti-infective treatment based on NTS was 93.02% (40/43), and infection-related mortality was reduced to 0. NTS is an effective method to identify pathogens in the blood specimens of patients with serious infections and can guide anti-infection treatment and reduce infection-related mortality.” (Zhang et al 2023, no changes)

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

Snippet Main
Vision and Change Topics
  • Metabolic Pathways (V&C_MP)
  • Information Flow and Genetics (V&C_IFG)
  • Impact of Microorganisms (V&C_IM)
  • Impact of Microorganisms (V&C_IM)
  • Structure and Function (V&C_SF)
  • Metabolic Pathways (V&C_MP)
ASM Fundamental Statements
  • Fundamental Statement 13 (ASM_13): Intrinsic factors, such as genotype, metabolism, and cell structures, impact the survival and growth of microbes.
  • Fundamental Statement 26 (ASM_26): Humans leverage microbes and their products to address problems and improve quality of life.
  • Fundamental Statement 8 (ASM_8): Microbes have unique genomes, structures, and/or biochemical characteristics that distinguish them from each other.
  • Fundamental Statement 15 (ASM_15): Most microbial life is currently unculturable and therefore both cultivation dependent and cultivation-independent techniques are used to identify microbial populations and their potential metabolic pathways.
  • Fundamental Statement 29 (ASM_29):The extent of microbial damage can be minimized by host-derived and external factors, including the microbiome, antibiotics, and immunity.

3.  Potential Learning Objectives for the Podcast

The student will be able to: Paper1 Order2
  • Recall actions scientists made to optimize production of fuelimycin.
  • Identify a property of cyclopropane molecules that allows them to be used to generate significant energy.
  • Identify the bacterial genus used in this study and why it was a good choice for producing fuelimycin.
 S L
  • Propose a way to find other high energy biosynthetic gene clusters.
 S H
  • Identify the sequencing method and target gene used to identify bacterial species in this study.
  • Recall which of Koch’s postulates were and were not satisfied in this study.
  • Identify the reason there were less species detected in the sequencing results compared to the culture methods.
 M L
  • Compare the advantages and disadvantages of using nanopore-targeted sequencing, mass spectrometry, and bacterial culture methods to identify species in a clinical setting.
 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

  • Culturing Bacteria (9:28–9:48): These are laboratory methods for culturing microbes.  Here, they grew a culture of Streptomyces albireticuli to analyze the fatty acid profile and detect the presence of secondary metabolites.
  • Transformation (10:10–10:56): This is a method of introducing genetic material into microbes.  Here, the researchers introduced specific genes into E. coli and the E. coli were able to create the proteins of interest.
  • Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) (11:40–12:07): These are analytic techniques to identify and quantify molecules in a mixture.  Here, they were used to predict the structure of the fuelimycin products.

4.2. Main Paper

  • Nanopore Targeted Sequencing (24:19): Nanopore targeted sequencing (NTS) is a method for quickly sequencing genetic material. Here, the authors used it to sequence and identify microbes collected from patients with the aim of faster patient treatment via identification of microbial antibiotic sensitivities.
  • Hematopoietic Stem Cell Transplant (34:31): In this procedure stem cells are transplanted into patients to restore blood cell production and is important to restore patients’ immune systems.

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

5.1. Snippet Paper

  • Polyketide Biosynthesis (4:22–16:18): Polyketide biosynthesis is process in which polyketide synthases are used to produce products of interest.  Here, the authors used microbes to create a synthetic fuel source that has significantly higher potential energy than current market fuels.
  • Genetic Engineering (6:05–7:18): In genetic engineering, researchers introduce or change genetic material of an organism, usually to enable the organism to produce a protein it normally would not.  Here, the authors aimed to enable microbes to make synthetic fuels.
  • Proteomics (11:02–11:26): Proteomics is the study of proteins. In this paper, the proteins studied were four biosynthetic enzymes generated by the POP3.1 strain, subsequently named Fuelimycin A-D.
  • Translation (12:20–12:38): When a mRNA is translated, three bases make up a codon for a particular amino acid.  In this process, specific tRNAs carrying amino acids, the ribosome, and the mRNA are involved in producing the protein by adding one amino acid at a time to the growing polypeptide chain.

5.2. Main Paper

  • Antibiotics (31:21):  Antibiotics are compounds that slow microbial growth or kill microbes by targeting different essential microbial components.  They are used in clinical treatment of bacterial infections. This paper is aimed at shortening the time to treatment by quicker identification of the infectious agent.
  • 16S rRNA (31:40–32:32) : The sequence of the 16S ribosomal RNA gene can be used to  identify bacterial species.
  • Immunocompromised (34:11–40:58) : People who are immunocompromised have a weakened immune system and this increases their risk of infection.
  • Selective/Differential Media (35:03): Species of microbes have different growth requirements and produce different metabolites that allow them to be distinguished from each other when grown on specific media called selective and differential media. For example, the media can be used to determine cell wall type (gram type) and to indicate fermentation.
  • Koch’s Postulates (43:55–45:12):  Koch’s postulates are a set of four criteria that are used to establish that a microbe is the causative agent of a disease.
  • Antibiotic Resistance (51:39): Antibiotic resistance occurs when bacteria evolve or acquire resistance to a particular antibiotic.  Bacteria can evolve or acquire resistance to multiple antibiotics.  Resistant bacteria are a huge problem in clinical settings.

6. Podcast Questions

  1. In the snippet article, why did the molecules containing cyclopropanes produce significant amounts of energy when broken?
    1. The cyclopropanes had decreased ring strain.
    2. The cyclopropanes had increased ring strain.
    3. The cyclopropanes had double bonds.
    4. The cyclopropanes had resonance capabilities.
  2. In the snippet article, which bacterial genus was used as a vector for expression of the biosynthetic gene clusters that make the high energy three member rings and why was it chosen?
    1. Enterococcus metabolites were identified in a small molecule database.
    2. Escherichia is highly amenable to genetic engineering by scientists.
    3. Streptomyces is known to make many small molecule metabolites.
    4. Streptococcus makes more high energy molecules than other species.
  3. Which of the following actions did scientists perform to increase production of fuelimycin?
    1. They activated factors that enable higher translation rates.
    2. They replaced the promoter with a more effective promoter.
    3. They changed the growth temperature of the incubation.
    4. They added an enzyme known to catalyze ring formation.
  4. Identifying other biosynthetic gene clusters similar to the fuelimycin gene cluster might provide a broader range of substrates or different higher energy products.   How might you find other bacteria that also have this gene cluster?
    1. Use the sequence that encodes the gene cluster to search genome databases.
    2. Perform proteomic analysis on soil bacteria cultures isolated from oil-rich regions.
    3. Expose the bacterium to a mutagen and select for microbes that grow on lipid-rich media.
    4. Isolate genomic material from fossilized biofilms and express it in modern bacteria.
  5. What sequencing technology and gene were used to identify bacterial species in this study?
    1. Nanopore sequencing and rpoB
    2. Nanopore sequencing and 16S rDNA
    3. Sanger sequencing and rpoG
    4. Sanger sequencing and 5S rDNA
  6. Which of Koch’s postulates were satisfied in this study?
    1. Bacteria were not present in every disease case and absent in healthy individuals.
    2. Bacteria were not grown in pure culture and identified.
    3. Bacteria were not used to infect a healthy host, causing disease.
    4. Bacteria were not re-isolated from the inoculated host,  grown to pure culture, or  identified as the original species.
    5. None of the above.
  7. Why were there significantly less microbial species detected using culturing methods compared to nanopore-targeted sequencing?
    1. Not enough bacteria was inoculated into the media, so the microbes could not reach a critical mass in the time allotted.
    2. Nanopore-targeted sequencing was carried out at a faster rate leading to more microbial signals than in standard culture.
    3. The patient samples that were cultured had lower rates of infection than those analyzed by nanopore-targeted sequencing.
    4. Laboratory culture conditions do not support the growth of all microbes, which may have different growth requirements.
  8. Match the identification method that is associated with the statement. Pick all that apply. (N = Nanopore sequencing technology; C = traditional bacterial culture methods; M = Mass spectrometry)
    1. _______ The fastest of the three methods
    2. _______ The slowest of the three methods
    3. _______ Compatible with using Koch’s postulates
    4. _______ Able to identify unculturable species

7. Figure Reading Exercises

The following are two figure reading exercises, both are from the main paper (Figure 2 and 3)

7.1. First Figure Reading Exercise

7.1.1. Learning Objectives

Students will be able to: 

  • Identify key features in the bar graphs
  • Identify key features of experimental design including variable types and statistical measures.
  • Predict how the biomarkers levels on day 0 versus day 7 would appear for effective and ineffective treatments.
  • Analyze the data to make conclusions about how the NTS informed antibiotic treatment impacted each measured biomarker.
  • Defend how the changes observed in the biomarkers on day 0 versus day 7 support or do not support the efficacy of NTS informed antibiotic treatment.
Experimental Background (Figure 2)

Historically, identifying the causal bacterial species during severe infections is difficult and slow, due to the need to grow isolates using classic microbiology techniques. Zhang et al (2023) aimed to validate the effectiveness of treatment based on a faster, novel method called nanopore targeted sequencing (NTS).  NTS can determine bacterial species present in a six hour time window using the sequence for the 16S rDNA gene so that clinicians can quickly and correctly identify the microbes causing infections and thereby prescribe effective antibiotics more quickly. To determine the effectiveness of this treatment strategy, biomarkers for infection including body temperature (A), C Reactive Protein level (B), procalcitonin level (C), white blood cell counts (D), and neutrophil counts (E) were measured on days 0 and 7 after NTS-informed antibiotic treatment.  Please note that body temperature, C Reactive Protein level, procalcitonin level are pro-inflammatory markers while white blood cell counts and neutrophil counts are markers of an active immune response.

Bar charts for 5 biomarkers, comparing several factors on the 0th and 7th day.Figure 2. “Comparison between patients on the day of NTS and on the 7th day after the adjustment of antibiotics based on NTS. (A) The temperature of patients was statistically significantly lower after NTS than before (P , 0.0001). (B) The CRP of patients was statistically significantly lower after NTS than before (P , 0.0001). (C) The PCT of patients was statistically significantly lower after NTS than before (P = 0.044). (D) The white blood cell count in patients was statistically significantly higher after NTS than before (P , 0.0001). (E) The neutrophil count was statistically significantly higher after NTS than before (P , 0.0002). Error bars show standard deviations. *, P , 0.05; ***, P , 0.001; ****, P , 0.0001.” (Cruz-Morales et al 2022, no changes)

7.1.2. Questions

  1. The bars in each graph indicate the _____ while the error bars indicate ______.
    1. median; standard error
    2. mean; variance
    3. mean; standard deviation
    4. median; variance
  2. There are one or more asterisks on each graph.  What do these indicate?
    1. The net difference of between each timepoint.
    2. The number of patients in each cohort group.
    3. The days of NTS informed antibiotic treatment.
    4. A significant difference based on the P-value.
  3. For panel A, ______ is the dependent variable and _______ is the independent variable.
    1. patient; temperature
    2. temperature; antibiotic treatment
    3. time; antibiotic treatment
    4. antibiotic treatment; temperature
  4. If a biomarker for infection normally increases with increasing microbial counts, what would you expect to see if NTS informed antibiotic treatment was effective?
    1. Biomarker level should decrease on day 7 compared to day 0.
    2. Biomarker level should increase on day 7 compared to day 0.
    3. There should be no change in the biomarker level between days.
    4. The biomarker level would not be detectable on day 7.
  5. If a biomarker for infection normally increases with increasing microbial counts, what would you have expected to see if NTS informed antibiotic treatment was ineffective?
    1. Biomarker level should decrease on day 7 compared to day 0.
    2. Biomarker level should increase on day 7 compared to day 0.
    3. There should be no change in the biomarker level between days.
    4. The biomarker level would not be detectable on day 7.
  6. What was the effect of seven days of NTS informed antibiotic treatment for each biomarker? (I = increase; D = decrease; NC = no change)
    1. _______ temperature
    2. _______ procalcitonin level
    3. _______ C reactive protein level
    4. _______ white blood cell count
    5. _______ neutrophil count
  7. Indicate whether each biomarker level change supports (S) and does not support (N) the effectiveness of NTS informed antibiotic treatment.
    1. _______ temperature
    2. _______ procalcitonin level
    3. _______ C reactive protein level
    4. _______ white blood cell count
    5. _______ neutrophil count

7.2. Second Figure Reading Exercise

7.2.1. Learning Objectives

Students will be able to:

  • Identify the axes and the dependent and independent variables for each case as appropriate.
  • Evaluate the data and describe how each biomarker changed over time and in response to treatment.
  • Analyze the data and make conclusions about the effectiveness of NTS informed antibiotic treatments and traditional culturing methods.
Experimental Background

In clinical settings, bacterial diagnostic methods are slow and inefficient which is a problem as these infections reach a critical state before proper antibiotics can be prescribed. Zhang et al. (2023) aimed to study the efficacy of nanopore-targeted sequencing (NTS), a novel technique that can rapidly identify bacterial species present using sequencing technology.  Here the authors present data for two patient cases for two inflammation biomarker levels: C reactive protein (CRP) and procalcitonin (PCT). Patient 1 (case 1 in graph A) suffered a severe infection after chemotherapy. When classic culture-based techniques failed to help the physicians accurately prescribe antibiotics,  the patient’s condition continued to worsen and resulted in death on September 18, 2020. NTS was used to posthumously identify the pathogen as Pseudomonas aeruginosa (September 19, 2020; arrow). Patient 2 (case 2 in graph B) contracted an infection after hematopoietic stem cell treatment. NTS was performed on December 9, 2020 (arrow) which identified Micrococcus luteus, Pseudomonas aeruginosa, and Alternaria alternata as bacterial populations in the infected area. Antibiotic treatment was immediately altered based on these data and the patient’s condition improved as of December 17, 2020.

Case 1 and Case 2 as line graphs. In case 1, CRP and PCT both grow quickly. In Case 2, CRP and PCT spike on day 7 but go down over the next 10 days.
Figure 3.  “Typical cases in this study. Changes in the inflammatory indicators of typical patients under the guidance of NTS during hospitalization are shown.” (Zhang et al 2023, no changes)

 

7.2.2. Questions

  1. What was identified as the infectious agent for Case 1?
    1. Alternaria alternata
    2. Staphylococcus aureus
    3. Pseudomonas aeruginosa 
    4. Micrococcus luteus 
  2. Which biomarker level was quantified as square symbols and which y-axis is relevant for this biomarker?
    1. C reactive protein (CRP); right y-axis
    2. procalcitonin (PCT); right y-axis
    3. C reactive protein (CRP); left y-axis
    4. procalcitonin (PCT); left y-axis
  3. What are the dependent and independent variables for case 1 (graph A)?
    1. Time is a dependent variable and CRP is an independent variable.
    2. PCT is a dependent variable and CRP is an independent variable.
    3. Time is a dependent variable and PCT is an independent variable.
    4. There are no variables in these descriptive case data.
  4. What are the dependent and independent variables for case 2 (graph B)?
    1. Time is a dependent variable and CRP is an independent variable.
    2. PCT is a dependent variable and CRP is an independent variable.
    3. CRP is a dependent variable and antibiotic treatment is an independent variable.
    4. There are no variables in these descriptive case data.
  5. Which graph section shows the highest levels of inflammatory biomarkers, indicating the highest level of patient inflammation?
    1. The left side of graph A (patient 1)
    2. The right side of graph A (patient 1)
    3. The left side of graph B (patient 2)
    4. The right side of graph B (patient 2)
  6. Identify the statements below as true (T) or false (F) with regards to how each biomarker changed over time for case 1.
    1. ______ CRP levels were constant and PCT levels increased during the study.
    2. ______ Both CRP and PCT levels increased for the length of the study
    3. ______ CRP increased, but PCT decreased for the length of the study
    4. ______ PCT levels were initially low but increased dramatically after September 16.
    5. ______ CRP levels were initially low but increased dramatically after September 16.
    6. ______ PCT and CRP levels decreased following NTS informed antibiotic treatment.
  7. Identify the statements below as true (T) or false (F) with regards to how each biomarker changed over time for case 2.
    1. ______ Both CRP level and PCT levels increased for the entire length of the study.
    2. ______ CRP levels increased, but PCT levels decreased for the entire length of the study.
    3. ______ PCT and CRP levels steadily decreased following NTS informed antibiotic treatment.
    4. ______ PCT and CRP levels initially decreased following NTS informed antibiotic treatment.
  8. Compare the two case studies. Identify each of the statements as true or false.
    1. ______ Using NTS aided the survival of the patient in case 2, whereas culturing methods were unsuccessful in identifying the pathogen in case 1.
    2. ______ Culturing methods allowed rapid identification of pathogen for the patient in case 2, whereas NTS use was unsuccessful in identifying the pathogen for the patient in case 1.
    3. ______ Using NTS aided the survival of the patient in case 1, whereas culturing methods were unsuccessful in identifying the pathogen in case 2.
    4. ______ Culturing methods allowed rapid identification of pathogen for the patient in case 1, whereas NTS use was unsuccessful in identifying the pathogen for the patient in case 2.

8. Paper Information and Licensing

8.1. Snippet paper

8.2. Main paper

  • Zhang Y, Lu X, Tang LV, Xia L, Hu Y.  2023. Nanopore-Targeted Sequencing Improves the Diagnosis and Treatment of Patients with Serious Infections. mBio. 14(1):e0305522. doi: 10.1128/mbio.03055-22
  • This article is licensed for Creative Commons use using CC BY NC SA 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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