Yuichi Wakamoto

On-chip single-cell microcultivation assay for monitoring environmental effects on isolated cells.

We have developed a on-chip single-cell microcultivation assay as a means of observing the adaptation process of single bacterial cells during nutrient concentration changes. This assay enables the direct observation of single cells captured in microchambers made on thin glass slides and having semipermeable membrane lids, in which cells were kept isolated with optical tweezers. After changing a medium of 0.2% (w/v) glucose concentration to make it nutrient-free 0.9% NaCl medium, the growth of all cells inserted into the medium stopped within 20 min, irrespective of their cell cycles. When a nutrient-rich medium was restored, the cells started to grow again, even after the medium had remained nutrient-free for 42 h. The results indicate that the cells growth and division are directly related to their nutrient condition. The growth curve also indicates that the cells keep their memory of what their growth and division had been before they stopped growing.

Single-cell dynamics of the chromosome replication and cell division cycles in mycobacteria.

During the bacterial cell cycle, chromosome replication and cell division must be coordinated with overall cell growth in order to maintain the correct ploidy and cell size. The spatial and temporal coordination of these processes in mycobacteria is not understood. Here we use microfluidics and time-lapse fluorescence microscopy to measure the dynamics of cell growth, division and chromosome replication in single cells of Mycobacterium smegmatis. We find that single-cell growth is size-dependent (large cells grow faster than small cells), which implicates a size-control mechanism in cell-size homoeostasis. Asymmetric division of mother cells gives rise to unequally sized sibling cells that grow at different velocities but show no differential sensitivity to antibiotics. Individual cells are restricted to one round of chromosome replication per cell division cycle, although replication usually initiates in the mother cell before cytokinesis and terminates in the daughter cells after cytokinesis. These studies reveal important differences between cell cycle organization in mycobacteria compared with better-studied model organisms.

Noise-driven growth rate gain in clonal cellular populations

Significance Differences between individuals exist even in the absence of genetic differences, e.g., in identical twins. Over the last decade, experiments have shown that even genetically identical microbes exhibit large cell-to-cell differences. In particular, the timing of cell division events is highly variable between single bacterial cells. The effect of this variability on long-term growth and survival of bacteria, however, remains elusive. Here, we present a striking finding showing that a bacterial population grows faster on average than its constituent cells. To explain this counterintuitive result, we present a mathematical model that precisely predicts our measurements. Furthermore, we show an empirical growth law that constrains the maximal growth rate of Escherichia coli. Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a “speed limit” for proliferation.

OPTIMAL LINEAGE PRINCIPLE FOR AGE-STRUCTURED POPULATIONS

We present a formulation of branching and aging processes that allows age distributions along lineages to be studied within populations, and provides a new interpretation of classical results in the theory of aging. We establish a variational principle for the stable age distribution along lineages. Using this optimal lineage principle, we show that the response of a population’s growth rate to age‐specific changes in mortality and fecundity—a key quantity that was first calculated by Hamilton—is given directly by the age distribution along lineages. We apply our method also to the Bellman–Harris process, in which both mother and progeny are rejuvenated at each reproduction event, and show that this process can be mapped to the classic aging process such that age statistics in the population and along lineages are identical. Our approach provides both a theoretical framework for understanding the statistics of aging in a population, and a new method of analytical calculations for populations with age structure. We discuss generalizations for populations with multiple phenotypes, and more complex aging processes. We also provide a first experimental test of our theory applied to bacterial populations growing in a microfluidics device.

Bacterial Autoimmunity Due to a Restriction-Modification System

Restriction-modification (RM) systems represent a minimal and ubiquitous biological system of self/non-self discrimination in prokaryotes [1], which protects hosts from exogenous DNA [2]. The mechanism is based on the balance between methyltransferase (M) and cognate restriction endonuclease (R). M tags endogenous DNA as self by methylating short specific DNA sequences called restriction sites, whereas R recognizes unmethylated restriction sites as non-self and introduces a double-stranded DNA break [3]. Restriction sites are significantly underrepresented in prokaryotic genomes [4-7], suggesting that the discrimination mechanism is imperfect and occasionally leads to autoimmunity due to self-DNA cleavage (self-restriction) [8]. Furthermore, RM systems can promote DNA recombination [9] and contribute to genetic variation in microbial populations, thus facilitating adaptive evolution [10]. However, cleavage of self-DNA by RM systems as elements shaping prokaryotic genomes has not been directly detected, and its cause, frequency, and outcome are unknown. We quantify self-restriction caused by two RM systems of Escherichia coli and find that, in agreement with levels of restriction site avoidance, EcoRI, but not EcoRV, cleaves self-DNA at a measurable rate. Self-restriction is a stochastic process, which temporarily induces the SOS response, and is followed by DNA repair, maintaining cell viability. We find that RM systems with higher restriction efficiency against bacteriophage infections exhibit a higher rate of self-restriction, and that this rate can be further increased by stochastic imbalance between R and M. Our results identify molecular noise in RM systems as a factor shaping prokaryotic genomes.

Measurement of incident angle dependence of swimming bacterium reflection using on-chip single-cell cultivation assay

We have developed an on-chip single-cell microcultivation assay as a means of continuously observing certain single swimming cells in order to trace their movement. The single cells were captured in microchambers fabricated on thin glass slides and having semipermeable membrane lids, in which cells can swim within the space for a long term without escaping. This assay enables the direct measurement of the reflection of certain cells against the microchamber walls depending on their incidence angles. Using this assay, the reflection was examined. We found that the ratio of reflection of cells to those of non-reverse was almost the same, though most of cells reflected when their incident angle was perpendicular to the wall.

Inferring fitness landscapes and selection on phenotypic states from single-cell genealogical data

Recent advances in single-cell time-lapse microscopy have revealed non-genetic heterogeneity and temporal fluctuations of cellular phenotypes. While different phenotypic traits such as abundance of growth-related proteins in single cells may have differential effects on the reproductive success of cells, rigorous experimental quantification of this process has remained elusive due to the complexity of single cell physiology within the context of a proliferating population. We introduce and apply a practical empirical method to quantify the fitness landscapes of arbitrary phenotypic traits, using genealogical data in the form of population lineage trees which can include phenotypic data of various kinds. Our inference methodology for fitness landscapes determines how reproductivity is correlated to cellular phenotypes, and provides a natural generalization of bulk growth rate measures for single-cell histories. Using this technique, we quantify the strength of selection acting on different cellular phenotypic traits within populations, which allows us to determine whether a change in population growth is caused by individual cells’ response, selection within a population, or by a mixture of these two processes. By applying these methods to single-cell time-lapse data of growing bacterial populations that express a resistance-conferring protein under antibiotic stress, we show how the distributions, fitness landscapes, and selection strength of single-cell phenotypes are affected by the drug. Our work provides a unified and practical framework for quantitative measurements of fitness landscapes and selection strength for any statistical quantities definable on lineages, and thus elucidates the adaptive significance of phenotypic states in time series data. The method is applicable in diverse fields, from single cell biology to stem cell differentiation and viral evolution.

Simultaneous Measurement of Growth and Movement of Cells Exploiting On-Chip Single-Cell Cultivation Assay

We have developed an on-chip single-cell microcultivation assay as a means of simultaneously observing the growth and movement of single bacterial cells during long-term cultivation. This assay enables the direct observation of single cells captured in microchambers fabricated on thin glass slides and having semipermeable membrane lids, in which the cells can swim within the space without escape for the long periods. Using this system, the relationship between the cell cycle and the tendency of movement was observed and it was found that the mean free path length did not change during the cell cycle, and that the growth and the swimming were not synchronized. The result indicates that the ability of movement of the cells was independent of the cell cycle.

Aging, mortality, and the fast growth trade-off of Schizosaccharomyces pombe

Replicative aging has been demonstrated in asymmetrically dividing unicellular organisms, seemingly caused by unequal damage partitioning. Although asymmetric segregation and inheritance of potential aging factors also occur in symmetrically dividing species, it nevertheless remains controversial whether this results in aging. Based on large-scale single-cell lineage data obtained by time-lapse microscopy with a microfluidic device, in this report, we demonstrate the absence of replicative aging in old-pole cell lineages of Schizosaccharomyces pombe cultured under constant favorable conditions. By monitoring more than 1,500 cell lineages in 7 different culture conditions, we showed that both cell division and death rates are remarkably constant for at least 50–80 generations. Our measurements revealed that the death rate per cellular generation increases with the division rate, pointing to a physiological trade-off with fast growth under balanced growth conditions. We also observed the formation and inheritance of Hsp104-associated protein aggregates, which are a potential aging factor in old-pole cell lineages, and found that these aggregates exhibited a tendency to preferentially remain at the old poles for several generations. However, the aggregates were eventually segregated from old-pole cells upon cell division and probabilistically allocated to new-pole cells. We found that cell deaths were typically preceded by sudden acceleration of protein aggregation; thus, a relatively large amount of protein aggregates existed at the very ends of the dead cell lineages. Our lineage tracking analyses, however, revealed that the quantity and inheritance of protein aggregates increased neither cellular generation time nor cell death initiation rates. Furthermore, our results demonstrated that unusually large amounts of protein aggregates induced by oxidative stress exposure did not result in aging; old-pole cells resumed normal growth upon stress removal, despite the fact that most of them inherited significant quantities of aggregates. These results collectively indicate that protein aggregates are not a major determinant of triggering cell death in S. pombe and thus cannot be an appropriate molecular marker or index for replicative aging under both favorable and stressful environmental conditions.

Transcriptomes and Raman spectra are linked linearly through a shared low-dimensional subspace

Raman spectroscopy is an imaging technique that can reflect whole-cell molecular compositions in vivo, and has been applied recently in cell biology to characterize different cell types and states. However, due to the complex molecular compositions and spectral overlaps, the interpretation of cellular Raman spectra have remained unclear. In this report, we compared cellular Raman spectra to transcriptomes of Schizosaccharomyces pombe and Escherichia coli, and provide firm evidence that they can be computationally connected and interpreted. Specifically, we find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA-seq can be effectively reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to reconstruct global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Strikingly, highly expressed ncRNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe, which implies their major role in coordinating molecular compositions. This compatibility between whole-cell Raman spectra and transcriptomes marks an important and promising step towards establishing spectroscopic live-cell omics studies.