Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli

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    This research is a potentially important contribution to the field of protein biosynthesis pathways and their link to aging, especially regarding the thorough analysis of variation in measures expected to correlate with elongation rate in old and new daughter cells derived from old and new mother cells. However, the imaging results, analysis, and methodologies are incomplete, as in its current form several key questions remain unanswered.

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Abstract

Lineages of rod-shaped bacteria such as Escherichia coli exhibit a temporal decline in elongation rate in a manner comparable to cellular or biological aging. The effect results from the production of asymmetrical daughters, one with a lower elongation rate, by the division of a mother cell. The slower daughter compared to the faster daughter, denoted respectively as the old and new daughters, has more aggregates of damaged proteins and fewer expressed gene products. We have examined further the degree of asymmetry by measuring the density of ribosomes between old and new daughters and between their poles. We found that ribosomes were denser in the new daughter and also in the new pole of the daughters. These ribosome patterns match the ones we previously found for expressed gene products. This outcome suggests that the asymmetry is not likely to result from properties unique to the gene expressed in our previous study, but rather from a more fundamental upstream process affecting distribution of ribosomal abundance. Because damage aggregates and ribosomes are both more abundant at the poles of E. coli cells, we suggest that competition for space between the two could explain the reduced ribosomal density in old daughters. Using published values for aggregate sizes and the relationship between ribosomal number and elongation rates, we show that the aggregate volumes could in principle displace quantitatively the amount of ribosomes needed to reduce the elongation rate of the old daughters.

Bacteria exhibit a growth decline in a manner comparable to cellular or biological aging. When a mother bacterium reproduces by binary fission it allocates more damage to one of the two daughters. The extra damage correlates with a slower growth. Thus, a lineage of daughters successively acquiring more damage over generations ages, sometimes even to death under stressful conditions. Aging lineages also have lower levels of expressed gene products. Here we show that the aging process also correlates with lower cellular levels of ribosomes. The identification of a ribosomal effect shows that the aging process is acting at a much more fundamental upstream level. While decreased gene products could have resulted from local regulation of specific genes, a lower ribosomal density affects the entirety of cellular metabolism. Understanding bacterial aging is important because biological aging may have originated in single-celled organisms such as E. coli.

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  1. Author response:

    A general comment was that this study left several key questions unanswered, in particular the causal mechanism for the reported ribosomal distributions. We have been interested in the evolution of asymmetric bacterial growth and aging for many years. However, a motivational difference is that we are more interested in the evolutionary process, and evolution by natural selection works on the phenotype. Thus, we wanted to start with the phenotype closest to fitness, appropriately defined for the conditions, work downwards. We examined first the asymmetry of elongation rates in single cells, then gene products, and now ribosomes. As we have pointed out, our demonstration of ribosomal asymmetry shows that the phenomenon was not peculiar and unique to the gene products we examined. Rather, the asymmetry is acting higher up in the metabolic network and likely affecting all genes. We find such conceptual guidance to be important. In the ideal world, of course we would have liked to have worked out the causal mechanisms in one swoop. In a less than ideal situation, it is a subjective decision as where to stop. We believe that the publication of this manuscript is more than appropriate at this juncture. We work at the interface of evolutionary theory and microbiology. Our results could appeal to both fields. If we attract new researchers, progress could be accelerated. Could the delay caused by publishing only completed stories slow the rate of discovery? These questions are likely as old as science (e.g., https://telliamedrevisited.wordpress.com/2021/01/28/how-not-to-write-a-response-to-reviewers/).

    We present below our response to specific comments by reviewers. We have not added a new discussion of papers suggested by Reviewer #1 because we feel that the speculations would have been too unfocused. We were already criticized for speculation in the Discussion about a link between aggregate size and ribosomal density.

    Respond to Major comments by Reviewer #1.

    (a) Fig. 1 only shows 2 divisions (rather than 3 as per Rev1) to avoid an overly elaborate figure. We have added text to the figure legend that the old and new poles and daughters in the subsequent 3, 4, 5, 6, and 7 generations can be determined by following the same notations and tracking we presented for generations 1 and 2 in Fig. 1. For example, if we know the old and new poles of any of the four daughters after 2 divisions (as in Fig. 1), and allow that daughter to elongate, become a mother, and divide to produce 2 “grand-daughters”, the polarity of the grand-daughters can also be determined.

    (b) Because division times were normalized and analyzed as quartiles, the raw values were never used. Rather than annotating unused values, we have provided the mean division times in the Material and Methods section on normalization to provide representative values.

    (c) We did not quantify in our study the changes over generations for three reasons. First, the sample sizes for the first generations (cohorts of 1, 2, 4, and 8 cells) are statistically small. Second, and most importantly, cells on an agar pad in a microscope slide, despite being inoculated as fresh exponentially growing cells, experience a growth lag, as all cells transferred to a new physiological condition. Thus, to be safe, we do not collect data from cohorts 1, 2, 4, and 8 to ensure that our cells are as much as possible physiologically uniform. Lastly, as we noted in the Material and Methods they also slow down after 7 generations (128 cells). Thus, we have collected ribosome and length measurements primarily from cohorts 16, 32, 64, and 128. Measurable cells from the 128 cohort are actually rare because a colony with that many cells often starts to form double layers, which are not measurable. Most of our measurements came from the 16, 32, and 64 cohorts, in which case a time series would not be meaningful. Some of these details were not included in our manuscript but have been added to the Material and Methods (Microscopy and time-lapse movies). For these reasons we have not added a time series as requested by the reviewer.

    (d) We have added the additional figure as requested, but as a supplement rather than in the main article (Supplemental Materials Fig. S1). This figure showed the normalized density of ribosomes along the normalized length of old and new daughters. The density was continuous rather than quartiles. This figure was included in the original manuscript, but readers recommended that it be removed because the all the analyzed data had been done with quartiles. Readers felt mislead and confused.

  2. eLife assessment

    This research is a potentially important contribution to the field of protein biosynthesis pathways and their link to aging, especially regarding the thorough analysis of variation in measures expected to correlate with elongation rate in old and new daughter cells derived from old and new mother cells. However, the imaging results, analysis, and methodologies are incomplete, as in its current form several key questions remain unanswered.

  3. Reviewer #1 (Public Review):

    The research titled "Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli" by Lin Chao, Chun Kuen Chen, Chao Shi, and Camilla U. Rang addresses the asymmetric distribution of ribosomes in single E. coli cells during aging by time-lapse microscopy, as well as its correlation to protein misfolding. The presented research is an important contribution to the field of protein biosynthesis pathways and their link to aging, especially in regard to the thorough analysis of variation in cell elongation rate in old and new daughter cells derived from old and new mother cells. However, the imaging results, analysis, and methodologies require substantial elaboration, as in its current form several key characteristics remain unanswered. Furthermore, the results should be compared and discussed in regard to several other reports, which analyzed ribosome asymmetric distribution and inheritance in E.coli, see detailed comments below.

    Major comments:
    *It is not clear from the results or the material and methods sections how the authors define and detect old vs. new mother cells up to 128 cells division, which is the limit the manuscript describes in line 574: "To avoid effects of crowding within the micro-colonies, movies were ended when micro-colonies exceeded 128 cells". The results described only refer to 3 cell divisions (Fig.1 for example). As this is the key issue the manuscript addresses this requires elaboration.

    * The authors should present several representative images of the results described, including: "New daughters at birth from old mothers have more ribosomes" - this should include clear quantification, of normalized fluorescence intensity vs. normalized cell length, as well as for "Ribosomal asymmetry between daughters are spatially in place in mothers before division"(line 218) for example. This should include annotation of the exact time points in minutes. The quantification can be done and presented as in their previous work, which provides the basis for this study: (Figure 2b, for example) "Allocation of gene products to daughter cells is determined by the age of the mother in single Escherichia coli cells" Chao Shi, Lin Chao, Audrey Menegaz Proenca, Andrew Qiu, Jasper Chao and Camilla U. Rang, May 2020, https://doi.org/10.1098/rspb.2020.0569.

    * Quantification of variations over generations time during the time lapse is required: the change in cell-length (y-axis, the length of full-grown cell normalized to 1) vs. ribosomes number (y-axis) relative to the generation time analysis should be presented, based on the time-lapse images. The mean from ~10 independent cells should be presented, as in many similar research, for example: "Organization of Ribosomes and Nucleoids in Escherichia coli Cells during Growth and in Quiescence" Qian Chai, Bhupender Singh, Kristin Peisker, Nicole Metzendorf, Xueliang Ge, Santanu Dasgupta, Suparna Sanyal, 2014, JBC (Figure 3b).

    * The distribution of ribosomes should be compared to the nucleoid distribution, as this is a major factor in RNA and translation distribution in bacterial cells (for example Gray, W. T., Govers, S. K., Xiang, Y., Parry, B. R., Campos, M., Kim, S., & Jacobs-Wagner, C. (2019). Nucleoid size scaling and intracellular organization of translation across bacteria. Cell, 177(6), 1632-1648.e20. https://doi.org/10.1016/j.cell.2019.05.017 , as reviewed in RNA localization in prokaryotes: Where, when,how, and why, Mikel Irastortza-Olaziregi, Orna Amster-Choder, 2020). The authors should add and discuss this, or elaborate on the reasons to omit this analysis.

    * The results should be compared and discussed in regard to several other reports, which analyzed ribosome asymmetric distribution and inheritance in E.coli by tagging different ribosomal proteins, as well as different methodologies, including:

    Organization of Ribosomes and Nucleoids in Escherichia coli Cells during Growth and in Quiescence" Qian Chai, Bhupender Singh, Kristin Peisker, Nicole Metzendorf, Xueliang Ge, Santanu Dasgupta, Suparna Sanyal, 2014, JBC

    Gray, W. T., Govers, S. K., Xiang, Y., Parry, B. R., Campos, M., Kim, S., & Jacobs-Wagner, C. (2019). Nucleoid size scaling and intracellular organization of translation across bacteria. Cell, 177(6), 1632-1648.e20. https://doi.org/10.1016/j.cell.2019.05.017

    Spatiotemporal Organization of the E. coli Transcriptome: Translation Independence and Engagement in Regulation Graphical Abstract Highlights d RNAs in E. coli exhibit asymmetric distribution on a transcriptome-wide scale, Shanmugapriya Kannaiah, Jonathan Livny, Orna Amster-Choder, 2019

    Several of the findings reported, including asymmetric ribosome distribution and inheritance levels seem different than the ones reported here. This should be discussed in regard to the different methodologies.

  4. Reviewer #2 (Public Review):

    In the article "Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli" the authors discovered that the aging process correlates with lower cellular levels of ribosomes in Escherichia coli. The article is well-written and easy to follow and understand. The experiments are conducted rigorously with the appropriate controls. However, it is not novel and exhaustive enough. In particular, the causes and effects of this spatial and temporal distribution of ribosomes have not been investigated. What happens when this distribution is perturbed? Does stress influence this distribution? What is the biological significance of this distribution? These are examples of questions that should be addressed in order to broaden the interest of the paper.

  5. Reviewer #3 (Public Review):

    Summary:
    During successive rounds of cell division in E. coli, a lineage of increasingly aging progeny arises whose members exhibit decreased elongation rates, increased accumulation of inclusion bodies, and reduced gene expression. These hallmarks of physiological aging point to an evolutionary antecedent to the better-studied phenomenon of biological aging in eukaryotic systems. In this work, the authors find an upstream phenotype attributable to this aging lineage of E. coli cells: a marked decrease in cellular ribosome levels. The authors conjecture that such an upstream effect may have cascading effects on cellular metabolism and reduced gene expression. This is a new hypothesis that challenges the more broadly held view that toxicity from protein aggregates asymmetrically retained by mother cells is the cause of asymmetric growth rates. The thesis and the broad scope that it entails offer a number of exciting directions to engage with in the future.

    Strengths:
    The authors' single-cell analysis convincingly shows differential partitioning of ribosomes that correlates with growth (elongation) rates between daughter cells. This makes the authors' novel hypothesis that asymmetric ribosome partitioning determines asymmetric cell growth plausible.

    Weaknesses:
    The authors' did not measure levels of misfolded proteins in mother and daughter cells to distinguish between a toxicity model (retained aggregates are toxic to older cells) and a protein synthesis disadvantage model (less ribosomes, slower growth in older cells) to explain slower growth in aged cells. Therefore, while the authors' hypothesis is plausible, it is not the sole potential mechanism that explains their observations.