Cells coordinate the activity of biosynthetic and catabolic pathways as well as the uptake and secretion of components in order to maintain appropriate molecular composition. In continuously proliferating cells, these processes are coordinated so that all cellular components are doubled during each cell cycle, whereas differentiating cells may change their composition to match their functions (Cadart et al., 2019; Ho et al., 2018; Lloyd, 2013; Miettinen et al., 2017; Schmoller and Skotheim, 2015). Changes in cells’ molecular composition are typically studied with approaches such as mass spectrometry, which can quantify the molecular details of a cell population after lysis. However, non-invasive methods, which can monitor the cellular composition of live single cells with high resolution, are better suited for the study of dynamic and temporary events such as mitosis.

Cells’ total molecular content, that is, dry mass, can be monitored using methods such as quantitative phase microscopy (QPM). Dry mass measurements are critical for understanding cell size and growth regulation, but they are often limited in resolution and, more importantly, they do not inform us about the composition of the dry mass. One approach that overcomes this is stimulated Raman scattering microscopy, which can measure the total amount of proteins and lipids in a live cell (Figueroa et al., 2021; Oh et al., 2020). While Raman scattering-based methods provide spatial resolution and details about the molecular changes taking place, they can also cause phototoxicity, which significantly limits the temporal resolution when tracking the same cell(s) over time (Zhang et al., 2021). Alternatively, QPM-based dry mass measurements can be coupled to microscopy-based total volume measurements to quantify dry density (dry mass/total volume) (Cooper et al., 2013; Odermatt et al., 2021; Yeo et al., 2021; Zlotek-Zlotkiewicz et al., 2015). These methods include cell’s water content in the total volume quantification. For example, a decrease in the amount of cellular lipids decreases the dry density of a cell, as the cell has less dry mass per total volume.

Here, we introduce a new approach for monitoring single cell’s dry mass (i.e. total mass – water mass), dry volume (i.e. total volume – water volume), and density of the dry mass (i.e. dry mass/dry volume), which we will refer to as dry mass density. Cell’s dry mass, dry volume, and dry mass density can be quantified by comparing the cell’s buoyant mass in normal water (H₂O) and heavy water (deuterium oxide, D₂O)-based solutions (Feijó Delgado et al., 2013). However, high concentration of D₂O prevents cell proliferation and can result in cell death (Kampmeyer et al., 2020; Schroeter et al., 1992; Takeda et al., 1998). Here, we show that we can expose the cell to D₂O only periodically (every 75 s) and for very short durations (10–15 s), thus allowing us to non-invasively monitor the dry mass and dry mass density of the same cell over many generations without compromising cell growth and viability. By definition, the measured dry mass density is independently of the cell’s water content and therefore sensitive toward changes in the relative molecular composition (dry composition), not the overall concentration of dry mass. For example, a decrease in the amount of cellular lipids increases the dry mass density of a cell, as lipids are lower in dry mass density than other cellular components.

We have previously monitored the buoyant mass accumulation of single mammalian cells in mitosis (Miettinen et al., 2019) using the suspended microchannel resonator (SMR), a cantilever-based single-cell buoyant mass sensor (Burg et al., 2007). We found that buoyant mass accumulation rate is high from prophase to metaphase-anaphase transition, that is, early mitosis. In contrast, studies using QPM have suggested that dry mass does not accumulate in early mitosis (Zlotek-Zlotkiewicz et al., 2015), or that cells may even experience a decrease in dry mass in early mitosis (Liu et al., 2020; Liu et al., 2022). If cells actually lose dry mass in mitosis, this would indicate previously unrecognized compositional changes taking place in mitosis. Although the exact dynamics of dry mass accumulation in mitosis remain debatable, our study addresses this seeming contradiction between buoyant and dry mass measurements by providing a high-resolution view of the mitotic dry mass and dry mass density changes.

Measurement method

Measurement principle

In our approach, we consider the buoyant mass of a cell to be dependent on two distinct physical ‘sections’ of the cell, the dry content and the water content. To measure the cell’s dry content independently of the water content, we measure the cell’s buoyant mass in H₂O and D₂O-based solutions. Under these conditions, the influence of the water content on buoyant mass can be excluded, because the intracellular water is exchanged with extracellular water, making the intracellular water content neutrally buoyant with extracellular solution. This allows us to detect the cell’s dry mass (i.e. total mass – water mass), dry volume (i.e. total volume – water volume), and dry mass density (i.e. dry mass/dry volume). Importantly, our approach assumes that all water within the cell is exchangeable between H₂O and D₂O. Accordingly, our dry volume measurement is distinct from the excluded cell volume detected by measuring cell volume following strong hyperosmotic shocks, which does not remove all water from the intracellular space.

In practice, the measured cell first travels through the SMR while filled with H₂O-based solution to obtain a buoyant mass measurement (Figure 1A). On the other side of the SMR, the cell is briefly exposed to D₂O-based solution. Cells constantly exchange their water content, causing intracellular H₂O to be exchanged to D₂O. The cell then travels back through the SMR in D₂O solution to obtain a second buoyant mass measurement (Figure 1B). The densities of the extracellular fluid are not constant due to fluid mixing between measurements, but this is accounted for by directly measuring the extracellular solution density, that is, the baseline frequency of the SMR, together with every buoyant mass measurement. These buoyant mass measurements can then be used to calculate the dry mass, dry volume, and dry mass density of the cell (Figure 1C; Feijó Delgado et al., 2013).

Figure 1 with 2 supplements see all

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Mathematically, the model for our measurement can be written out as:

(1) $m_b=m_{dry}\left(1-\frac{{\rho }_{fluid}}{{\rho }_{drymass}}\right)+V_{water}\left({\rho }_{water}-{\rho }_{fluid}\right)$

where $m_b$ is the buoyant mass of the cell in a given fluid, $m_{dry}$ is the dry mass of the cell, ${\rho }_{fluid}$ is the density of the fluid outside the cell, ${\rho }_{drymass}$ is the dry mass density, $V_{water}$ is the volume of intracellular water content, and ${\rho }_{water}$ is the density of intracellular water content. The first term of Equation 1 describes the contribution of the cell’s dry mass to buoyant mass and the latter term describes the contribution of the cell’s water content to buoyant mass. As H₂O and H₂O-based media are very similar in density (1.00 g/ml), as are D₂O and D₂O-based media (1.10 g/ml), the density of water inside the cell is near identical to the density of fluid outside the cell whether the measurement is carried out in H₂O or D₂O-based solution (see Feijó Delgado et al., 2013, for error estimations). Consequently, the latter term of Equation 1 approaches zero for both the H₂O and the D₂O-based buoyant mass measurements and the two consecutive measurements can be used to solve the first term of the equation, that is, the dry mass and dry mass density of a cell.

Measurement precision and stability

We characterized our measurement precision and stability using several approaches. First, we monitored live non-growing L1210 cells (mouse lymphocytic leukemia cells) by cooling our measurement system down to +4°C to prevent growth and compositional changes. We measured the same cell repeatedly and defined our measurement error as the coefficient of variation during a 1 hr trace. With this approach our measurement errors in dry mass and dry mass density were ~1.3% and ~0.3%, respectively (Figure 1—figure supplement 1A&B). We did not observe measurement drifting even during a longer experiment (Figure 1—figure supplement 1A), suggesting a high level of measurement stability. Second, we monitored fixed cells at +37°C and observed measurement errors that were close to those seen in live cells at +4°C (Figure 1—figure supplement 1C). Third, we monitored the dry mass and density of 10 µm diameter polystyrene beads at +37°C. This suggested similar dry mass measurement errors as the previous experiments with live and fixed cells, but lower errors in dry mass density measurements (Figure 1—figure supplement 1D). We therefore estimate our dry mass measurement error to be ~1.3%, which is comparable to current state-of-the-art QPM measurements (Liu et al., 2020; Reed et al., 2011). For dry mass density measurements, we estimate our measurement error to be ~0.3%. We are not aware of any other single-cell methods capable of quantifying this metric. Furthermore, as we carry out dry mass and dry mass density measurements approximately every 75 s, we can further increase our precision by averaging multiple measurements while still capturing changes on timescales meaningful for studying dynamic and transient events such as mitosis.

Measurement sensitivity to intracellular water exchange

Our measurement principle involves the cells exchanging their intracellular water content between H₂O and D₂O, and this exchange has to be complete for our measurements to reflect the dry mass and dry mass density of cells. Direct experimental evidence suggests that cells normally exchange their water content within ~1 s (Potma et al., 2001; Quirk et al., 2003; Zhao et al., 2008). To support this, we carried out back-of-the-envelope calculations on the intracellular water exchange times, as based on reported aquaporin water permeability (Gravelle et al., 2013; Hashido et al., 2007; Yang and Verkman, 1997), abundance (Denker et al., 1988), and a cell water volume of ~1000 fl (approximate water volume for an L1210 cell). This suggested that cells are capable of exchanging all of their water volume within 0.1–2.5 s, depending on the reported aquaporin water permeability. Notably, the true intracellular water exchange time may differ from this due to intracellular water diffusion, water molecule interactions with other biomolecules, and additional means of water transport in and out of the cell (additional aquaporin isoforms, endo- and exocytosis, etc.).

In our typical measurement, a cell is exposed to D₂O for 10–15 s, which should enable complete water exchange. To validate the completeness of the water exchange, we correlated the measured dry mass and dry mass density to the time that a cell was exposed to the D₂O-based media between each buoyant mass measurement. Whether examining end-point measurements of single L1210 cells in a population (Figure 1—figure supplement 2A), a single-cell trace of a live L1210 cell cooled to +4°C (Figure 1—figure supplement 2B) or a single-cell trace of an L1210 cell at +37°C (Figure 1—figure supplement 2C), the measured dry mass and dry mass density were independent of the time in D₂O-based media. Thus, the rate of intracellular water exchange is not limiting our measurements, as also suggested by previous results in bacteria and yeast (Feijó Delgado et al., 2013).

Here, we have developed a method using the SMR to monitor the dry mass, dry volume, and dry mass density of suspension grown cells over long periods of time with high precision. To the best of our knowledge, this is the first method capable of non-invasively measuring cell’s dry volume or dry mass density. We anticipate several uses for this method. First, our dry mass density measurements provide an orthogonal approach for studying the macromolecular composition of cells. While dry mass density measurements lack molecular specificity, they are non-invasive, quantitative, and have high temporal resolution. Together, these qualities make our measurements valuable for studying the dynamics of molecular composition changes, especially in situations where rapid changes cannot be easily resolved by more typical population level measurements, such as mass spectrometry. Second, our method provides an additional approach for measuring dry mass. QPM has several advantages over our method, including higher throughput and suitability for adherent cells, but our method is comparable in precision and has high temporal resolution. Our method is also not limited by phototoxicity. This enables us to observe dry mass dynamics that may be difficult to capture with other methods. Third, the ability of our method to measure cellular dry volume could enable precise, specific, and non-invasive quantifications of single-cell water content, provided it is coupled with a measurement of total cell volume.

Using our method, we have expanded our previous study of mammalian cell growth dynamics in mitosis. Importantly, the mitotic dry mass dynamics differ from our previously reported buoyant mass dynamics due to a transient change in dry mass density in early mitosis (Equation 1). This finding reconciles our previous mitotic buoyant mass measurements (Miettinen et al., 2019) with the QPM-based dry mass measurements by others (Liu et al., 2020; Zlotek-Zlotkiewicz et al., 2015). The overall dry mass growth remains high in mitosis and cytokinesis, and for L1210 cells over 10% of the total dry mass growth in the cell cycle takes place in mitosis and cytokinesis. This supports our previous main conclusion that average cell growth rates in mitosis and cytokinesis are comparable to those observed in interphase, which is consistent with the high protein synthesis rates reported for unperturbed mitosis (Coldwell et al., 2013; Miettinen et al., 2019; Stonyte et al., 2018; Sun et al., 2019). In interphase, dry mass density is conserved, making buoyant mass an excellent proxy for dry mass.

A key discovery made here is the significant loss of dry mass in early mitosis. Importantly, a loss of dry mass in mitosis has been reported in adherent mammalian cells studied using QPM (Liu et al., 2020; Liu et al., 2022), but the higher temporal resolution of our results enables us to examine this phenotype in more detail. However, our measurement approach decreased the duration of mitosis and cytokinesis, which could potentially influence the dry mass dynamics we observe in mitosis. This decrease in mitotic duration is contradictory to previous studies which show that mitosis is prolonged by D₂O exposure (Lamprecht et al., 1990; Takahashi and Sato, 1983), possibly due to the brief but repeated D₂O exposure in our measurements. Our results reveal a high degree of cell-to-cell variability in the mitotic loss of dry mass and cells can divide without losing mass. Mechanistically, we show that exocytosis of lysosomes is increased in early mitosis and the loss of dry mass is, at least partly, dependent on lysosomal exocytosis. Other mechanisms, especially other forms of exocytosis, may also be involved, as we were not able to completely block the dry mass loss in early mitosis by preventing lysosomal exocytosis. In addition, the loss of dry mass in early mitosis could be partly explained by decreased endocytosis, as the total dry mass of a cell is defined by the balance between uptake and secretion processes, such as endo- and exocytosis, respectively. Our results also show that cells are able to recover dry mass at a high rate at metaphase-anaphase transition. Interestingly, the exocytosis of lysosomes is typically followed by endocytosis, which removes lysosomal membranes from plasma membrane (Idone et al., 2008; Tam et al., 2010). Such a compensatory endocytosis could explain the rapid recovery of dry mass at metaphase-anaphase transition, but further quantitative studies on endo- and exocytosis are needed to confirm this.

The magnitude of dry mass density increase in mitosis was large. We have previously observed similar magnitude changes in dry mass density when perturbing proliferation in mammalian cell (Feijó Delgado et al., 2013). To provide some rough estimates of what kind of compositional changes would be required to achieve the dry mass loss and dry mass density increase, we carried out a back-of-the-envelope calculations. Assuming a typical mammalian cell composition and typical macromolecule dry mass densities (Alberts, 2008; Feijó Delgado et al., 2013), we calculated the degree of lipid loss needed to increase dry mass density by 2.5%. This suggested that cells would have to secrete ~1/3 of their lipid content in early mitosis. This could be achieved via lysosomal exocytosis of lipids. Lipid droplets, the main lipid storages inside cells, are frequently trafficked into and degraded in lysosomes (Singh et al., 2009), and lipid droplets can also be secreted via lysosomal exocytosis (Minami et al., 2022). However, it seems likely that the mitotic dry mass density increase also involves secretion of other low dry mass density components (e.g. lipoproteins, specific metabolites) and/or a minor, transient increase in high dry mass density components (e.g. RNAs, specific proteins) in early mitosis. Indeed, CDK1 activity has been suggested to drive a transient increase in protein and RNA content in early mitosis (Asfaha et al., 2022; Clemm von Hohenberg et al., 2022; Miettinen et al., 2019; Shuda et al., 2015).

Why would cells exocytose lysosomal contents and a significant amount of total cellular biomass in mitosis? We hypothesize three potential reasons for this: (1) Lysosomal exocytosis acts in plasma membrane repair (Reddy et al., 2001), and lysosomal exocytosis could enable a temporarily increase in plasma membrane area for mitotic cell swelling. (2) Lysosomal exocytosis is used for secretion of various proteins and enzymes into the extracellular space (Blott and Griffiths, 2002), and mitotic cells may secrete extracellular matrix modifying enzymes in order to ensure an appropriate physical milieu for cell division. (3) Lysosomal exocytosis has been shown to clear the cell of excessive/toxic cellular proteins and lipids, including α-synuclein (Tsunemi et al., 2019) and tau (Xu et al., 2021). Mitotic lysosomal exocytosis may act as a ‘reset’ that enables the daughter cells to be born with a minimal load of useless/harmful contents. Consequently, non-dividing cells, such as neurons, could be more prone to suffer from excessive/toxic protein and lipid buildup, and the mechanism(s) that promote(s) mitotic lysosomal exocytosis could act as candidate drug target(s) for promoting cellular clearance of toxic/excess components. Lysosomal exocytosis is also perturbed in a variety of lysosomal and lipid storage disorders (reviewed in Samie and Xu, 2014; Settembre and Ballabio, 2014), and lysosomal exocytosis can drive the cellular expulsion of chemotherapeutics out of cancer cells (Vyas et al., 2022; Zhitomirsky and Assaraf, 2017). Understanding the mechanism(s) of mitotic lysosomal exocytosis could have implications for these diseases as well.

Supporting source data files contain all key data (dry mass and dry mass density traces) used in this study.

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Author details

1. Teemu P Miettinen

   1. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
   2. MIT Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

   For correspondence

   teemu@mit.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5975-200X

2. Kevin S Ly

   Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Data curation, Formal analysis, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

3. Alice Lam

   Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4332-4761

4. Scott R Manalis

   1. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
   2. MIT Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, United States
   3. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States
   4. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Funding acquisition, Project administration, Resources, Supervision, Writing – review and editing

   For correspondence

   srm@mit.edu

   Competing interests

   is a co-founder of Travera and Affinity Biosensors, which develop technologies relevant to the research presented in this work

   "This ORCID iD identifies the author of this article:" 0000-0001-5223-9433

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