TWiM #167: I Have One Word for You: FLINK!

1. Paper Abstracts

1.1. Snippet paper; discussion starts at 2:36 minutes

“The risk of emerging pandemic influenza A viruses (IAVs) that approach the devastating 1918 strain motivates finding strain-specific host–pathogen mechanisms. During infection, dendritic cells (DC) mature into antigen-presenting cells that activate T cells, linking innate to adaptive immunity. DC infection with seasonal IAVs, but not with the 1918 and 2009 pandemic strains, induces global RNA degradation. Here, we show that DC infection with seasonal IAV causes immunogenic RIPK3-mediated cell death. Pandemic IAV suppresses this immunogenic DC cell death. Only DC infected with seasonal IAV, but not with pandemic IAV, enhance maturation of uninfected DC and T cell proliferation. In vivo, circulating T cell levels are reduced after pandemic, but not seasonal, IAV infection. Using recombinant viruses, we identify the HA genomic segment as the mediator of cell death inhibition. These results show how pandemic influenza viruses subvert the immune response.” (Hartmann et al 2017)

1.2. Main paper; discussion starts at 25:05 minutes

“Despite recent advances to control the spatial composition and dynamic functionalities of bacteria embedded in materials, bacterial localization into complex three-dimensional (3D) geometries remains a major challenge. We demonstrate a 3D printing approach to create bacteria-derived functional materials by combining the natural diverse metabolism of bacteria with the shape design freedom of additive manufacturing. To achieve this, we embedded bacteria in a biocompatible and functionalized 3D printing ink and printed two types of “living materials” capable of degrading pollutants and of producing medically relevant bacterial cellulose. With this versatile bacteria-printing platform, complex materials displaying spatially specific compositions, geometry, and properties not accessed by standard technologies can be assembled from bottom up for new biotechnological and biomedical applications.” (Schaffner et al 2017)

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

3.  Potential Learning Objectives for the Podcast

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

• Comparative Genomics (6:48–20:36): This is a technique that uses genome nucleic acid sequence to examine the shared genetic content, here of viruses, with the aim of identifying evolutionary relationships among the members. These researchers compare seasonal and pandemic flu virus gene segments. Flu virus genomes have 8 different segments. They experimentally develop multiple chimeras that have 7 segments from one strain and 1 segment from the other, pandemic vs seasonal strains. They test and map the series of chimeras to determine which segment suppresses the cell death sensor pathway. 

4.2. Main Paper

• 3D Printing of Biofilms (25:05 –end): Similar to other 3D printing technologies, a machine uses structural materials to build up a designed structure, but here the ink (functional living ink; flink) is formulated to be embedded with bacteria that can form a biofilm and perform a task.
• Bacterial Cellulose (40:45): Cellulose is a complex polysaccharide.  Acetobacter xylinum forms cellulose when exposed to oxygen.

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

5.1. Snippet Paper

5.2. Main Paper

7. Figure Reading Exercises

The following are two figure reading exercises, one from the snippet paper (Figure 6) and one from the main paper (Figure 4).

7.1. First Figure Reading Exercise

Experimental Background (Hartmann et al. Figure 6)

Flu viruses are particularly difficult to form vaccines against because they change so quickly.  In characterizing how a seasonal flu virus was able to work around the immune system, Hartmann et al. (2017) found that the emerging seasonal flu virus strain enhanced programmed cell death of infected dendritic cells and that the 2009 pandemic flu inhibited programmed cell death of infected dendritic cells .  In order to determine which viral segment was responsible for the pandemic-type phenotype of inhibiting dendritic cell death, viral mixtures were prepared to have different RNA segments from either a non-pandemic (NC/99–red)  or pandemic (Cal/09–green) virus.  The eight segments and their origin are visually presented at the top of the figure.  For example, the  fully  pandemic flu virus (Cal/09) is shown with its eight segments as green bars and “mixture virus” Cal (NC NS) has one pandemic segment (the NS segment, red) and 7 non-pandemic segments (green) (Hartmann, et al 2017).  Percent dendritic cell death after viral infection (or mock infection) is displayed as color-coded bars (panels a and b).

7.1.2. Questions

1. Excluding the non-pandemic virus (NC/99), which virus is the most genetically different from the pandemic virus (Cal/09)?
   1. Cal (NC NS)
   2. NC (Ca HA)
   3. NC (Cal NA)
   4. Cal (NC HA, NA)
2. Excluding the pandemic virus (Cal/09), which virus is the most genetically different from the non-pandemic virus (NC/99)?
   1. Cal (NC NS)
   2. NC (Ca HA)
   3. NC (Cal NA)
   4. Cal (NC HA, NA)
3. Excluding the pandemic virus (Cal/09), which statements are true regarding which virus shows the most antigenic drift and which shows the most antigenic shift from the non-pandemic virus (NC/99)? [pick all that apply]
   1. Cal (NC NS) shows the most antigenic drift
   2. Cal (NC NS) shows the most antigenic shift
   3. NC (Ca HA) shows the most antigenic shift
   4. NC (Cal NA) shows the most antigenic drift
   5. Cal (NC HA, NA) shows the most antigenic shift
   6. You can’t tell antigenic drift from this schematic
   7. You can’t tell antigenic shift from this schematic
4. Viruses composed of segment mixtures of the seasonal (NC/99) and 2009 pandemic virus (Cal/09) were used to infect dendritic cells and the cell death measured as percent cell death (panel a and b). Which “mixture” virus(es) behave(s) similarly to the pandemic virus (Cal/09)? Select all that apply.
   1. NC (Cal NA)
   2. Cal (NC NS1)
   3. NC (Cal HA)
   4. Cal (NC HA, NA)
   5. NC (PB1, PB2, NA)
5. Viruses composed of segment mixtures of the seasonal (NC/99) and 2009 pandemic virus (Cal/09) were used to infect dendritic cells and the cell death measured as percent cell death (panel a and b). Which “mixture” virus(es) behave(s) similarly to the seasonal virus (NC/99)? Select all that apply.
   1. NC (Cal NA)
   2. Cal (NC NS1)
   3. NC (Cal HA)
   4. Cal (NC HA, NA)
   5. NC (PB1, PB2, NA)
6. Based on the killing results of the viral mixtures (panels a and b), which viral segment is responsible for the pandemic flu’s trait of inhibiting dendritic cell death? What is the evidence?
   1. PB1; when the Cal/09 BP1 segment is present cell death is higher and when the NC/99 NP segment is present cell death is lower.
   2. PB2; when the Cal/09 BP2 segment is present cell death is higher and when the NC/99 NP segment is present cell death is lower.
   3. HA; when the Cal/09 HA segment is present cell death is lower and when the NC/99 HA segment is present cell death is higher.
   4. NA; when the Cal/09 NA segment is present cell death is lower and when the NC/99 NA segment is present cell death is higher.
   5. NP; when the Cal/09 NP segment is present cell death is higher and when the NC/99 NP segment is present cell death is lower.

7.2. Second Figure Reading Exercise

Experimental Background (Schaffner et al., Figure 4)

Three dimensional (3D) printing technology builds up layers of material to produce specific objects using a digital design.  It has many realized and proposed applications including easy synthesis of designed structures, bioremediation, and biomedicine.  Bioremediation and biomedicine applications would require the delivery of functional, living inks which these researchers have termed flink (Schaffner et al. 2017).  The researchers in this study investigated two bacteria, delivery properties of different hydrogels, and the performance of flink-printed structures.  Here, the researchers performed a “proof of concept” experiment  to test whether the printed flink can perform in a bioremediation context.  They printed a grid of  a phenol-degrading strain of Pseudomonas putida-embedded in flink (panels A and C) or grew the same bacteria in a liquid culture (panel B).

First, they measured several things for the flink-printed grid including the phenol concentration (panel A, right y axis, solid shapes) and the release of bacteria from the grid (panel A, left y axis, open shapes) in the medium over time (x axis) for a first incubation (orange triangles) and second incubation (black circles) of 1% phenol minimal medium (MM).  Both phenol concentration and bacterial release were quantified using spectroscopy.   Bacterial release was quantified using the optical density of the medium at 600 nm (OD600) and phenol % was calculated using a phenol-specific spectroscopic assay with a standard curve (see methods for detail).  To visualize where within the grid structure the bacteria were present after each incubation, the researchers stained the grid with ethidium bromide, which is fluorescent where double-stranded DNA is present (panel C).  As a comparison, they also measured the ability of free bacteria (bacteria in a liquid culture) to degrade phenol and grow (panel B; same axes as panel A).

 

7.2.2. Questions

1. What is optical density and how is it used as a measure of bacterial growth?
   1. Optical density is a spectroscopy technique to measure light reflection.  When bacterial cells are present in a sample, they reflect light in proportion to their concentration.  If you measure it over time, you can see increasing OD as bacteria increase in number.
   2. Optical density is a spectroscopy technique to measure light scattering.  When bacterial cells are present in a sample, they scatter light in proportion to their concentration.  If you measure it over time, you can see increasing OD as bacteria increase in number.
   3. Optical density is a chromatography technique to measure bacterial mass.  When bacterial cells are present in a sample, they acquire mass in proportion to their concentration.  If you measure it over time, you can see increasing OD as bacteria increase in number.
   4. Optical density is a chromatography technique to measure bacterial metabolism.  When bacterial cells are present in a sample, they metabolize compounds in proportion to their concentration.  If you measure it over time, OD increases as bacteria increase in number.
2. Does the line/curve (panel B), indicate bacterial growth or bacterial growth inhibition?  What is your evidence?
   1. The curve noted with closed circles is the optical density at 600 nm, which is a measure of how many bacteria are present in the sample.  The curve decreases in OD600 over time from 0 to 40 hours, so there is growth inhibition.
   2. The curve noted with closed circles is the optical density at 600 nm, which is a measure of how many bacteria are present in the sample.  The curve increases in OD600 over time from 0 to 40 hours, so there is growth inhibition.
   3. The curve noted with open circles is the optical density at 600 nm, which is a measure of how many bacteria are present in the sample.  The curve increases in OD600 over time from 0 to 40 hours, so there is growth.
   4. The curve noted with open circles is the optical density at 600 nm, which is a measure of how many bacteria are inhibited in the sample.  The curve decreases in OD600 over time from 0 to 40 hours, so there is growth.
3. Here the researchers were investigating bioremediation by using bacteria with a specific characteristic.  What is bioremediation and what feature of the bacterium makes it useful in bioremediation?
   1. Bioremediation is using an organism to restructure and improve an environment.  The bacterium increased OD.
   2. Bioremediation is using technology to clean up an environment.  The bacterium could degrade flink.
   3. Bioremediation is using an organism to clean up an environment.  The bacterium could degrade phenol.
   4. Bioremediation is using technology to improve an environment.  The bacterium could degrade flink.
4. The aim of the researchers was to investigate bioremediation for 3D printed structures.  Which panel displays the evidence and was bioremediation successful or not?
   1. Panel A; the reduction in phenol (filled shapes) shows success.
   2. Panel B; the reduction in phenol (filled circles) shows success.
   3. Panel A; the increase in OD (open shapes) shows success.
   4. Panel B; the increase in OD (open circles) shows success.
5. Ethidium bromide is used to stain DNA (panel C). Which statement(s) describe(s) the results for the difference between the staining for the first incubation (panel C, top) and second incubation (panel C, bottom)? Pick all that apply.
   1. The first incubation has less staining, so there are fewer bacteria.
   2. The first incubation has less staining, so there is less phenol.
   3. The first incubation has less staining, so there is a smaller grid.
   4. The first incubation has dim staining so bacteria are not present everywhere in the grid.
   5. The second incubation has more staining, so there are more bacteria.
   6. The second incubation has more staining, so there is more phenol.
   7. The second incubation has bright staining so bacteria are present throughout the biofilm grid.