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[Preprint]. 2023 Jan 12:2023.01.11.523042.
doi: 10.1101/2023.01.11.523042.

Measuring prion propagation in single bacteria elucidates mechanism of loss

Affiliations

Measuring prion propagation in single bacteria elucidates mechanism of loss

Krista Jager et al. bioRxiv. .

Update in

  • Measuring prion propagation in single bacteria elucidates a mechanism of loss.
    Jager K, Orozco-Hidalgo MT, Springstein BL, Joly-Smith E, Papazotos F, McDonough E, Fleming E, McCallum G, Yuan AH, Hilfinger A, Hochschild A, Potvin-Trottier L. Jager K, et al. Proc Natl Acad Sci U S A. 2023 Sep 26;120(39):e2221539120. doi: 10.1073/pnas.2221539120. Epub 2023 Sep 22. Proc Natl Acad Sci U S A. 2023. PMID: 37738299 Free PMC article.

Abstract

Prions are self-propagating protein aggregates formed by specific proteins that can adopt alternative folds. Prions were discovered as the cause of the fatal transmissible spongiform encephalopathies in mammals, but prions can also constitute non-toxic protein-based elements of inheritance in fungi and other species. Prion propagation has recently been shown to occur in bacteria for more than a hundred cell divisions, yet a fraction of cells in these lineages lost the prion through an unknown mechanism. Here, we investigate prion propagation in single bacterial cells as they divide using microfluidics and fluorescence microscopy. We show that the propagation occurs in two distinct modes with distinct stability and inheritance characteristics. We find that the prion is lost through random partitioning of aggregates to one of the two daughter cells at division. Extending our findings to prion domains from two orthologous proteins, we observe similar propagation and loss properties. Our findings also provide support for the suggestion that bacterial prions can form more than one self-propagating state. We implement a stochastic version of the molecular model of prion propagation from yeast and mammals that recapitulates all the observed single-cell properties. This model highlights challenges for prion propagation that are unique to prokaryotes and illustrates the conservation of fundamental characteristics of prion propagation across domains of life.

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Figures

Fig. 1.
Fig. 1.
Experimental setup enables quantification of prion dynamics in single cells. a) Transient expression of the S. cerevisiae New1 protein induces conversion of His6-mEYFP-Ch SSB PrD from its soluble form into the prion form in E. coli. Bacteria with prions have elevated levels of ClpB, such that bacterial colonies with prion-containing cells can be distinguished from colonies with cells containing the protein in the soluble form using a PclpB-lacZ transcriptional reporter (dark blue vs pale colonies, respectively). b) Dark blue colonies contain self-propagating aggregates. (Left) Replating dark blue colonies results in a mix of dark and pale colonies, while replating pale colonies results in only pale colonies. (Right) SDD-AGE shows that different dark blue colonies (A, B and C) contain SDS-stable aggregates, whereas pale colonies contain only soluble Ch SSB PrD (prion formation was induced with New1-CFP; a gel where induction was done with New1-mScarlet-I can be found in Fig. S1d). c) Fluorescence microscopy images of E. coli expressing His6-mEYFP-Ch SSB PrD shows that cells from dark colonies display visible fluorescence aggregation, whereas cells from pale colonies display diffuse YFP fluorescence. d) After prion conversion, cells from a dark blue colony are loaded in a microfluidic device where cells are trapped in dead-end trenches and newborn cells are washed away by the flow of growth medium. Fluorescence time-lapse microscopy montage (kymographs) of individual lineages shows that cells propagate the aggregates for heterogeneous duration (I-III) before irreversibly reverting to diffuse fluorescence. YFP fluorescence is shown false-colored according to the colormap indicated on the graph. The prion loss called by our spot-finding algorithm is indicated by a yellow triangle. Cells that have diffuse fluorescence at the beginning of the experiments maintain it (IV). e) The fraction of cells with prions over time (prion loss curve) for all aggregate phenotypes shows a biphasic decay, suggesting the presence of two distinct subpopulations. f) The prion loss curve for cells with small aggregates fits well to an exponential distribution (red line, R = 0.92). Representative kymograph of cells with small aggregates (top) g) Loss curve for cells with old-pole aggregates. Kymographs for the tracked cell (mother) and its progeny (top). The old-pole aggregate is mostly immobile, and the progeny contain small aggregates. The colormap for the old-pole aggregate is different as these aggregates are brighter. The standard error on the mean (SEM) in e-g was estimated by bootstrapping, and an envelope is shown as 2xSEM.
Fig. 2.
Fig. 2.
Prion loss is driven by partitioning errors at cell division. a) Schematic representation of the hypothesized mechanisms for prion loss in bacterial cells. b) Median concentration of fluorescence (Ch SSB PrD) relative to the loss of the prion is constant (n = 762 cells). The loss event is indicated with a dotted gray line at time 0. c) Histogram of the cell cycle position at the time of loss, where 0 is defined as the moment right after a division and 1 right before. Most cells (~80%) lose the prion immediately after cell division (n = 762 cells). d) Kymographs of loss event show that prion loss happens in only one of the two daughter cells (86% of the losses, n = 356 loss events). YFP fluorescence is shown false colored according to the colormap indicated on the graph. e) Mean absolute partitioning errors at the cell divisions relative to prion loss (n = 349 cells). The absolute partitioning error is constant prior to the loss, and higher than after the loss. f) Mean partitioning errors in the cell divisions relative to the loss show that fluorescence is being transmitted to the daughter at the moment of loss for cells that lost the prion at the moment of cell division (blue lines, n = 349 cells). For the cells that lost the prion at a different moment of the cell cycle, this transfer happens one division prior to the loss (yellow line). For symmetric divisions, the average partitioning error would be ~0, since molecules have an equal chance of being inherited by the mother or daughter cells. g) Average longitudinal position (y) of tracked aggregates shows that they move toward the daughter cell prior to the loss (n = 754 cells). The envelopes represent 2xSEM in b and e-g.
Fig. 3.
Fig. 3.
Orthologous SSB cPrDs form self-propagating aggregates comparable to Ch SSB. a) Prion loss curve for small aggregate cells of Lh SSB PrD (n = 228 cells) and Ml SSB PrD (n = 83 cells) compared to Ch SSB PrD from Fig. 1. b) SDD-AGE of dark and pale colonies confirms the presence of the aggregated prion form of Lh SSB and Ml SSB in cell extracts derived from dark blue colony cultures. Dark blue colonies with high, medium and low prion content as estimated from fluorescence microscopy images were assayed (Fig. S6d, SI 3.1). Pale colony cultures give rise exclusively to the soluble form. c) SSB orthologs form self-propagating aggregates for multiple generations. Replating dark blue colonies gives a mix of dark and pale colonies, while replating pale colonies results in exclusively pale colonies. d) Fraction of prion losses at cell division shows that most loss happens at cell division for the different orthologs (n = 754 cells for Ch, 187 cells for Lh, 47 cells for Ml). The error bars represent 2xSEM as estimated by bootstrapping. e) Average longitudinal position (y) of tracked aggregates shows that they move toward the daughter cell prior to the loss for the different orthologs (n = 187 cells for Lh, 47 cells for Ml). The envelopes represent 2xSEM in a and d-e.
Fig. 4.
Fig. 4.
Distinct bacterial lineages propagating identical prion protein exhibit distinct prion loss kinetics. a) The experimental setup provides precise measurement of the prion loss kinetics. Prion loss curves for one colony of Lh SSB PrD in four different experiments (thin orange lines, average in bold, n = 815 cells total). b) The prion loss curve for a stable lineage of Ch SSB PrD remains constant over multiple rounds of growth (~37 generations each, n = 1,018 cells total). Round 1 refers to the first plating of induced cells cured of New1, and each subsequent round includes an overnight growth in liquid culture and plating on indicator medium. Round 2, 3, and 4 cells were obtained from a colony culture inoculated from a Round 2, 3, and 4 colony, respectively. Another lineage (from Fig. 1, dashed blue line)) is shown as a comparison. The envelopes represent 2xSEM as estimated by bootstrapping. c) Kymograph of a mutant of Ch SSB PrD that can form self-propagating aggregates without the presence of the initiation factor (termed Ch SSBmut PrD). YFP fluorescence is shown false colored according to the colormap indicated on the graph. The prion is eventually lost, but rare spontaneous re-formation (green arrow) happens at low inducer concentration (2 μM IPTG for the duration of experiment). The spontaneous re-formation events were observed following large stochastic fluctuations in fluorescence, likely due to plasmid copy number variation. Such fluctuations were also observed in experiments with other PrDs, but in these cases they did not cause re-formation of the prion. d) Prion loss curve for different colonies of the Ch SSBmut PrD exhibit similar propagation dynamics (thin line, average in bold, n = 155 cells).
Fig. 5.
Fig. 5.
A stochastic nucleated polymerization model recapitulates the experimental results. a) A stochastic model of prion propagation in growing and dividing cells. Soluble fold protein numbers, denoted by X, are produced constitutively with a rate that scales with the cell volume, so that their concentration becomes cell-cycle independent (see SI 3.2.1). The number of prion fold aggregates made of k proteins is denoted by Yk, where k = 1, 2, 3, . . . . When a soluble fold protein collides with an aggregate of size k, it can be converted to prion fold by elongating the aggregate to size k + 1. Assuming mass action kinetics, soluble fold proteins are converted to prion fold with a reaction rate proportional to the protein concentrations. Similarly, chaperon mediated fragmentation follows a reaction that is proportional to the aggregate concentrations, with each binding between any two monomers having the same probability of splitting. Concentrations are given by dividing the protein numbers by the cell volume, which grows exponentially from V0 to 2V0 between divisions with a fixed doubling time. At cell division, protein numbers are split randomly, with each soluble protein and each aggregate having a 50% chance of remaining in the cell. b) Soluble fold production parameter λV0 was estimated to be 1.75 min−1 by comparing the measured partitioning error of cells after loss of prions with their respective simulations (see SI 3.2.3.2). With no minimal seed size n = 0 (see SI 3.2.5 for n = 2), a parameter sweep of elongation and fragmentation parameters shows that prions in cells with larger fragmentation and elongation rates are more stable. An average time of loss of 129.26 min was measured in the experiment shown in Fig. 1f, with the corresponding contour indicated by the dashed orange line. c) Cells with smaller fragmentation rates and larger elongation rates have larger partitioning error prior to loss. An absolute partitioning error prior to loss of 0.125 was measured in the experiment shown in Fig. 2e, with the corresponding contour indicated by the dashed orange line. Using the two contour plots from b and c we find the model parameters that match the measured time of loss and partitioning error, indicated by the orange dot. d) Time of loss curves follow an exponential, in agreement with Fig. 1f. Plotted are the time of loss curves for systems with parameters along the solid orange line in b. Loss is defined as when Yk = 0 for all k. e) The model can predict the aggregate size distribution prior to loss, showing that smaller aggregates are more stable in this parameter regime. f) The total protein concentration is approximately constant leading up to the loss, in agreement with Fig. 2b. g) In this model the prion state is always lost at cell division. h) Absolute partitioning errors are larger before the loss, in agreement with Fig. 2e. i) A large negative partitioning error occurs at the time of loss, in agreement with Fig. 2f.
Fig. 6.
Fig. 6.
Schematic of the two observed modes of prion propagation. Cells with small aggregates have a probability of losing the prion at each cell division through partitioning errors. At cell division, an old-pole aggregate cell generates a small aggregate cell and an old-pole aggregate cell. Although the old-pole aggregate is very stable, the cells containing old-pole aggregates represent a small fraction of a growing culture. The small aggregate cells generated through this division presumably propagate the prion similarly to the other observed small aggregate cells.

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