TWiM #187: Rounding up the Bees

1. Paper Abstracts

1.1. Snippet papers; discussion starts at 8:22 minutes

The abstract for Snippet 1 cannot be copied due to licensing restrictions. Please see licensing information and links to the article at the journal’s web page and/or PubMed in Section 8.1. 

“Some phages encode anti-CRISPR (acr) genes, which antagonize bacterial CRISPR-Cas immune systems by binding components of its machinery, but it is less clear how deployment of these acr genes impacts phage replication and epidemiology. Here, we demonstrate that bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages often need to cooperate in order to overcome CRISPR resistance, with a first phage blocking the host CRISPR-Cas immune system to allow a second Acr-phage to successfully replicate. This cooperation leads to epidemiological tipping points in which the initial density of Acr-phage tips the balance from phage extinction to a phage epidemic. Furthermore, both higher levels of CRISPR-Cas immunity and weaker Acr activities shift the tipping points toward higher initial phage densities. Collectively, these data help elucidate how interactions between phage-encoded immune suppressors and the CRISPR systems they target shape bacteria-phage population dynamics.” (Landesberg et al. 2018)

1.2. Main paper; discussion starts at 22:20 minutes

“Glyphosate, the primary herbicide used globally for weed control, targets the 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) enzyme in the shikimate pathway found in plants and some microorganisms. Thus, glyphosate may affect bacterial symbionts of animals living near agricultural sites, including pollinators such as bees. The honey bee gut microbiota is dominated by eight bacterial species that promote weight gain and reduce pathogen susceptibility. The gene encoding EPSPS is present in almost all sequenced genomes of bee gut bacteria, indicating that they are potentially susceptible to glyphosate. We demonstrated that the relative and absolute abundances of dominant gut microbiota species are decreased in bees exposed to glyphosate at concentrations documented in the environment. Glyphosate exposure of young workers increased mortality of bees subsequently exposed to the opportunistic pathogen Serratia marcescens. Members of the bee gut microbiota varied in susceptibility to glyphosate, largely corresponding to whether they possessed an EPSPS of class I (sensitive to glyphosate) or class II (insensitive to glyphosate). This basis for differences in sensitivity was confirmed using in vitro experiments in which the EPSPS gene from bee gut bacteria was cloned into Escherichia coli. All strains of the core bee gut species, Snodgrassella alvi, encode a sensitive class I EPSPS, and reduction in S. alvi levels was a consistent experimental result. However, some S. alvi strains appear to possess an alternative mechanism of glyphosate resistance. Thus, exposure of bees to glyphosate can perturb their beneficial gut microbiota, potentially affecting bee health and their effectiveness as pollinators.” (Motta et al. 2018)

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

• Plaque Assay (11:43–12:23): This is the standard method used to determine virus presence and also concentration in terms of infectious dose. This method is used to aid the calculation of the multiplicity of infection (MOI).
• CRISPR-Cas9 (15:00–15:13): This is a specific, efficient, and versatile gene-editing technology we can harness to modify, delete or correct precise regions of DNA. CRISPR is the DNA sequence that works in harmony with the Cas9 enzyme, which uses the CRISPR sequence as a guide for cleaving the complementary CRISPR sequence.

4.2. Main Paper

• Control vs. Treatment Groups (27:18–28:30; 37:20–42:00; 43:00–43:19; 43:33–43:51): These are experimental treatment group names.  Here, the researchers harvested bees and separated them into 3 cohorts/groups and treated each cohort with a different level of herbicide. Several groups of bees are treated with the herbicide while at least one group remains untreated in order to act as a comparison (the control).
• Kaplan-Meier Survival Chart (44:59–45:17): This the name for the chart depicting the survival of a population over time.  It is used to assay mortality rate.
• Monocolonization (46:00; 54:50–55:04): The colonization of a an environment by single species to prevent confounding effects such as interference by other species.
• Cloning (52:27–52:50): This is a molecular technique to study a gene in a more controlled way, often to introduce the gene into another organism.  Here, it was used to determine why some strains of organisms from the bee microbiota are unable to grow in the presence of the herbicide.  They cloned these genes into Escherichia coli and studied them further in that system.

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 snippet paper 2 (Figure 2) and one from the main paper (Figure 2G).

7.1. First Figure Reading Exercise

Experimental Background (Landesberger et al., Figure 2)

Bacteria have evolved defense mechanisms against bacteriophages, prevalent bacterial viruses that are known to influence bacterial evolution and ecology.  The bacterial adaptive immunity defense system is known as clustered regularly interspaced short palindromic repeats or CRISPR. Briefly, bacteria incorporate small bacteriophage genome sequences and express small phage-derived RNA within a complex to degrade a matching incoming bacteriophage genome thereby stopping phage infection.  Bacteriophages have also evolved protections against CRISPR, anti-CRISPR (acr) genes.  To better understand the resistance properties of anti-CRISPR, Landesberger et al. (2018) first quantified the ability of phages with acr genes to infect different bacterial host strains with CRISPR-based immunity and found infection outcomes were dependent on both the phage and host strains.  To further characterize this interaction and determine the effect of 1) Multiplicity of Infection (MOI or phage:bacteria ratio, 2) phage acr alleles, and 3) host CRISPR status, they carried out infections of three phages (wild-type  = DMS3vir; phage with acr allele F1 = DMS3vir-AcrIF1; phage with acr allele F4 = DMS3vir-AcrIF1) and four bacterial host strains (wild-type = WT; a strain engineered to remove or “knock out” its CRISPR = CRISPR KO; a strain with 2 spacers targeting DMS3 phage = BIM2; a strain with 5 spacers targeting DMS3 phage) over a range of MOI.  For each graph, MOI is noted on the x-axis and phage titer, which is an indicator of phage infection success, is on the y-axis. Initial phage titers are noted by gray open circles and phage titers at 24 hours post-infection are noted by solid color circles.

7.1.2. Questions

1. What is the relationship of potential pathogen and host in multiplicity of infection (MOI)? [Pick all that apply]
   1. It is the ratio of the number of pathogen individuals to the number of host individuals.
   2. It is the number of individuals that are necessary for quorum sensing to start infection.
   3. It is the number of pathogen ligands required to fill host receptors to cause infection.
   4. It is the ratio of pathogen:host pairs that initiates the host defense gene expression.
2. Identify each statement as describing anti-CRISPR (A), CRISPR (C), or both (B).
   1. Uses phage genetic material
   2. Is present in the bacterial genome
   3. Is present in the phage genome
   4. Uses RNA
   5. Responsible for phage immunity
   6. Antagonizes phage immunity
   7. Defense against phage infection
   8. Defense against adaptive immunity
3. Two anti-CRISPR alleles (AcrIF1 and AcrIF4) were tested for the ability and extent to which they affect CRISPR adaptive immunity using different MOI.  A wild-type Pseudomonas strain (WT; panels D-F) and a Pseudomonas strain lacking CRISPR (CRISPR KO, panels A-C) were exposed to wild-type phage (DMS3mvir, panels A & D), phage with AcrIF1 (DMS3mvirAcrIF1, panels B & E), or phage with AcrIF4 (DMS3mvirAcrIF4, panels C & F).  In which panel(s) is/are phage infection successful for any virus type, bacterial type, or MOI and what is your evidence?
   1. Knockout panels show successful infection; phage titer is high for all MOI.
   2. Wild-type panels show successful infection; phage titer increased with MOI.
   3. All panels show successful infection; phage titer is high for at least 1 MOI.
   4. No panels show successful infection; phage titer does increase above initial.
4. In addition to the KO and WT Pseudomonas strains, two other Pseudomonas strains were tested. These differ in the number of CRISPR components (spacers) present in the bacterial genome that target the DMS3vir phage. BIM2 has two spacers to target the phage and BIM5 has five spacers to target the phage. Which phage-Pseudomonas strain combinations within panels G-L are least and most successful and what do these results indicate?
   1. Least: DMS3virAcrIF4-BIM2; Most: DMS3mvirAcrIF1-BIM2; the anti-CRISPR allele is most important for a successful infection
   2. Least: DMS3vir-BIM2; Most: DMS3mvirAcrIF4-BIM2; the combination of spacer number and anti-CRISPR allele are both important
   3. Least: DMS3vir-BIM5; Most: DMS3mvirAcrIF4-BIM2; the number of CRISPR spacers is most important for successful infection
   4. Least: DMS3virAcrIF1-BIM5; Most: DMS3mvirAcrIF4-BIM5; the genotype of the anti-CRISPR spacers is most important
5. If you were to mutate all five CRISPR spacers in the Pseudomonas BIM5 strain and use the DMS3vir-AcrIF4 phage to infect with different MOI, what amount of infection success would you expect?
   1. High infection regardless of the MOI
   2. Moderate infection at high MOI only
   3. Low success regardless of the MOI
   4. No success at low, but moderate at high MOI

7.2. Second Figure Reading Exercise

7.2.1. Learning Objectives

Students will be able to:

• Identify statistical measures and their meaning for a plot.
• Identify the bee treatments for each survival curve.
• Identify the point at which there is 50% mortality for each bee population.
• Analyze a Kaplan-Meier survival plot to determine the effect of different treatments on survival.
• Predict the shape of a Kaplan-Meier survival plot when given different hypothetical situations.

Experimental Background (Motta et al., Figure 2G)

Herbicides and pesticides have many environmental effects in addition to their intended effects of controlling specific species.  Here, Motta et al. (2018) investigate the effect of glyphosate, the herbicide known as RoundUp, on honey bee gut microbiome and honey bee mortality. In the initial experiments, they found that  glyphosate exposure caused significant shifts (known as dysbiosis) in honey bee gut microbiome particularly in four normally abundant species: Snodgrassella alvi, Bifidobacterium, Lactobacillus spp. Firm-4 and Firm-5.  To investigate how this shift in gut microbiome could affect bee susceptibility to pathogens, the researchers exposed newly emerged worker (NEW) bees which have little gut microbiome to a variety of conditions when they would normally be acquiring their normal microbiome bacteria.  Bees were exposed to gut homogenate to populate their microbiome (GH) or left microbe-free (MF), as well as exposed to glyphosate (Gly) or not (no text).  After 5 days, they challenged each set of bees (MF+Gly, MF, GH+Gly, GH) with the opportunistic pathogen, Serratia marcescens kz19 (Ser) or not (no text) and characterized survival.  Survival is displayed as a Kaplan-Meier survival plot with percent survival on the y axis and days of survival on the x axis (panel G).  NOTE: This figure has the Creative Commons No Derivative designation, so the figure is not cropped to just panel G.

“Changes in gut microbiota composition following glyphosate exposure of young honey bees and susceptibility to Serratia infection. (A) Stacked column graph showing the relative and absolute abundances of gut bacterial species in control and glyphosate-treated bees. Each column represents one bee. (B–E) Boxplots of total bacterial 16S rDNA copies and of absolute and relative abundances of two gut bacterial species for control (n = 14) and glyphosate-treated (n = 11) bees. **P < 0.01, and ***P < 0.001, Wilcoxon rank sum test followed by Bonferroni correction. (F) Principal coordinate analysis of gut community composition using weighted UniFrac (permanova test with 9,999 permuations; P = 0.0078, pseudo-F statistic = 6.66). (G) The percent survival of age-controlled bees after Serratia kz19 exposure, shown as a Kaplan–Meier survival curve. ***P < 0.001, coxph model implemented in the “survival” package in R. GH, gut homogenate-exposed bees; Gly, glyphosate treatment; MF, microbiota-free bees; Ser, Serratia challenge” (Motta et al. 2018)

7.2.2. Questions

1. Which line(s) in the plot represent(s) survival of bees treated only with gut homogenate and the opportunistic pathogen? [Pick all that apply]
   1. GH+Ser (dark pink)
   2. GH+ Gly+Ser (red)
   3. MF+Ser (pale green)
   4. MF+Gly+Ser (green)
2. At what day is there 50% survival of microbe-free bees treated with glyphosate and the opportunistic pathogen? What is your evidence?
   1. Day 1; this is the day when GH + Gly+ Ser drops below 50%.
   2. Day 1; this is the day when MF + Gly + Ser drops below 50%.
   3. Day 2; this is the day when GH + Gly + Ser drops below 50%.
   4. Day 2; this is the day when MF + Gly + Ser drops below 50%.
3. The Kaplan-Meier survival plot (panel G) shows two sets of asterisks. What do these indicate, both in general and specifically for these data?
   1. Non-normal distributions in the data; the data required additional conversion to show significance.
   2. Unequal numbers in the groups; t-tests could not be performed so another statistical test was used.
   3. Statistical significance at P < 0.001; data fall into three statistically significant different groups.
   4. Differences in mean values; data averages were used to identify outliers and remove them.
4. Based on these data, what conclusion(s) can you make about how glyphosate affects bee health? [Pick all that apply]
   1. Glyphosate makes bees sensitive to pathogens by causing dysbiosis.
   2. Glyphosate exposure has sub-lethal effects on most bees.
   3. Glyphosate is lethal to bees because it inhibits their digestive enzymes.
   4. Glyphosate treatment does not affect the ability of bees to survive Serratia.
5. Let’s examine a hypothetical species called Gorgon selectus. Your research group suspects that a hypothetical fungus called Mycolytica janus is responsible for recent declines in the G. selectus population. To test this, your group exposes G. selectus to different environmental isolates M. janus in its spore state or vegetative state and quantifies survival.  If your group plots survival as a Kaplan-Meier survival plot and spores, but not vegetative M. janus are deadly to G. selectus, what would the plot look like?
   1. Untreated and spore-treated lines would remain high over the days, but vegetative-treated lines would decrease.
   2. Vegetative-treated and spore-treated lines would remain high over the days, but untreated lines would decrease.
   3. Untreated and vegetative-treated lines would decrease over the days, but spore-treated lines would increase.
   4. Untreated and vegetative-treated lines would remain high over the days, but spore-treated lines would decrease.

8. Paper Information and Licensing

8.1.1 Snippet paper 1

• Snippet 1: Borges AL, Zhang JY, Rollins MF, Osuna BA, Wiedenheft B, Bondy-Denomy J. 2018. Bacteriophage Cooperation Suppresses CRISPR-Cas3 and Cas9 Immunity. Cell, 174(4):917-925.e10. doi: 10.1016/j.cell.2018.06.013.
• This article is not licensed for Creative Commons use. Thus, the abstract and figures cannot be copied here. Please see the article on the journal’s web page.

8.1.2 Snippet paper 2

• Landsberger M, Gandon S, Meaden S, Rollie C, Chevallereau A, Chabas H, Buckling A, Westra ER, van Houte S. 2018. Anti-CRISPR phages cooperate to overcome CRISPR-Cas immunity. Cell, 174(4), 908-916. doi: 10.1016/j.cell.2018.05.058.
• 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

8.2. Main paper

• Motta EVS, Raymann K, Moran NA. 2018. Glyphosate perturbs the gut microbiota of honey bees. Proc Natl Acad Sci USA. 115(41):10305-10310. doi: 10.1073/pnas.1803880115
• This article is licensed for Creative Commons use using CC BY-NC-ND 4.0, which allows use with proper attribution but no commercial use or derivatives. See the article’s copyright information.