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Measuring bacterial cell size

A signal routinely measured in other cell systems, now fast enough to follow through a bacterial fermentation, batch or fed-batch

By , CEO·Published

Cell size is already a working signal, just not for bacteria

In mammalian cell culture, watching cell size is routine. Mean cell diameter is tracked to understand how a culture is doing. In Chinese hamster ovary (CHO) fed-batch production, a distinct cell-size-increase phase is documented[1], and shifts in mean cell size track changes in how much product the cells make[2]. Size is treated as information about the state of the cells, not only their number.

Microbial process development has rarely had that lens. Not because bacterial cell size carries less information, but because there has been no fast, direct way to follow it through a cultivation.

BactoBox® counts bacterial cells directly and, from the same reading, measures their size, in about two minutes per sample. A cell-size signal can now sit beside the direct cell count, sample after sample, with samples pulled from several bioreactors on a single BactoBox®. This article makes the case for why that signal is worth watching, what it is known to carry, and where it could earn its place, above all in fed-batch fermentation, where the feed sets the physiology and bulk signals can mislead.

For a bacterium, size means volume, not length

Bacteria come in many shapes, from rods to spheres to chains, and they change shape as conditions change. A length, or the longest dimension, does not compare cleanly between cells, because two cells of the same length can hold very different amounts of material.

The quantity that does carry across shapes is the total volume of the cell. That is also what impedance flow cytometry, the principle behind BactoBox®, senses. As each cell passes the sensor, the size of the electrical signal scales with its volume. BactoBox® reports this as CIZE, the average spherical-equivalent diameter of the counted cells. It is the diameter of a sphere that holds the same volume as the cell. Because the number encodes a volume, a small change in CIZE is a larger change in size than it looks. A cell measured at CIZE of 2 µm holds about 8x the volume of one measured at 1 µm. For how the underlying count is produced, see Understanding BactoBox® cell counts.

Cell size carries the physiological state, and shows it early

Bacterial cell size and growth rate are coupled, but size does not simply follow the rate. When conditions improve, such as a shift to richer medium, average cell size increases promptly while the division rate catches up only after a lag, so size leads the rate rather than trailing it[3][4]. In steady growth, cells then hold a stable size by adding roughly a constant volume each generation[3], so a culture growing as intended holds a characteristic size, and a departure from it is informative in itself. Across a batch, where conditions are not held constant, size drifts with the growth phases[5]. Stress adds its own routes. A shift to nutrient-poor conditions contracts the cytoplasm and shrinks the cell[6], while a block on division, such as the SOS response to DNA damage, lets a cell keep growing and elongate[7][8]. The information is in the trajectory of size over time, measured together with the bacterial cell count, not in any single value and not in a rule that smaller means worse.

The signal shows up early, ahead of the cell count itself. The figure below is one real E. coli batch culture, with the direct cell count and the cell size taken from the same BactoBox® readings. Through the lag phase, roughly the first 1.4 hours, the cell concentration holds near the level it was seeded at, and the population is not yet expanding. Cell size, however, climbs steeply over the same window, from about 0.9 to 2.0 µm, which is roughly an 8x increase in cell volume. The cells are building the machinery to divide before they divide. Once exponential growth begins, the count rises and cell size settles back down as the culture matures toward stationary phase. The size signal moves first. The transition out of lag is visible in size while the count is still flat.

One E. coli batch culture followed on BactoBox. Through the lag phase the direct cell count stays flat near the seeding level while cell size climbs steeply; once exponential growth starts the count rises and cell size falls back.
Figure 1. One E. coli batch culture, followed on BactoBox®. The culture was seeded into fresh LB medium at about 1×10⁶ cells/mL from a starter culture in early stationary phase, then sampled over the next four and a half hours. The violet line (left axis) is the direct cell count in cells/mL. The blue dashed line (right axis) is the cell size, the spherical-equivalent diameter, which is the diameter of a sphere with the same volume as the cell. Through the lag phase (about 1.4 hours) the concentration holds near the seeding level while cell size climbs from about 0.9 to 2.0 µm; because the diameter encodes a volume, that is roughly an 8x increase in cell volume. As exponential growth begins, the count rises and cell size falls back. From SBT internal data, 15 January 2025.

Why this could matter in fed-batch fermentation

Where a culture is fed, the feed sets the physiology, and a bulk signal can hold steady while the cells underneath it change. Optical density is the clearest case. OD600 rises with cell number, but also with cell size, morphology, and particulates, and it cannot separate them (see Understanding OD600). Two cultures can therefore show the same OD while behaving differently.

In a fed-batch fermentation, two schematic runs on an identical OD600 curve. In the on-target run the cell count rises with OD600 and cell size holds steady. In the struggling run far fewer cells form but each is larger, so the two offset and OD600 stays the same. Only a direct cell count and cell size tell the runs apart.
Figure 2. The trap a bulk signal hides. Two runs sit on an identical OD600 curve (grey). In the on-target run (left) the direct cell count rises with OD600 and cell size holds a steady baseline. In the struggling run (right) far fewer cells form, but each is larger, and the two offset so that turbidity, and therefore OD600, stays the same. A direct cell count and a cell size tell the runs apart; OD alone cannot. Schematic, for illustration.

Followed beside the count through a fed-batch culture, a cell-size signal could surface that kind of divergence as it happens, between media, between strains, or as a single culture moves through its phases. It also points to where the signal could matter most, the design of the feed itself. A feed that is too rich, too lean, or mistimed pushes the cells off their balanced state, and because cell size tracks that state directly, it is likely to register the effect faster than the bulk proxies a feed is tuned on today. Measured in near real time, that response could let a team shape a feed-rate profile that holds the cells where they want them, and catch a feed that drifts before it costs the run. In a fed-batch E. coli process, the textbook example is acetate overflow. When the feed outpaces what the cells can use, they spill carbon into acetate and stall[9]. Because cell size tracks the cells' state directly, a size signal could flag that the feed has pushed the culture off balance, from the same reading as the count.

Closing

For a generation, the growth curve has been measured as one quantity over time, either the number of cells or a proxy that stands in for the count. Cell size adds a second axis to the same curve. It does not report how many cells there are, but what state they are in, and it does so from the same reading, at the same cadence. A count tells you the population is expanding; a size signal tells you how the cells are faring while it does.

This kind of scrutiny has long been standard in mammalian cell culture. With a direct cell count and a direct cell-size measurement now available in minutes from one sample, it is becoming part of how bacterial processes are developed too, turning cell size from a property almost no one tracked into a routine second measurement on the growth curve. The sooner a process can see its cells begin to change, the sooner it can respond, and that is the case for putting cell size on the curve from the start.

References

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  2. [2] Schellenberg J, Nagraik T, Wölk M, et al. Stress-induced increase of monoclonal antibody production in CHO cells. Eng Life Sci. 2022;22(6):427–436. https://pmc.ncbi.nlm.nih.gov/articles/PMC9077828/
  3. [3] Jun S, Si F, Pugatch R, Scott M. Fundamental principles in bacterial physiology: cell size control and homeostasis. Rep Prog Phys. 2018;81(5):056601. https://doi.org/10.1088/1361-6633/aaa628
  4. [4] Kjeldgaard NO, Maaløe O, Schaechter M. The transition between different physiological states during balanced growth of Salmonella typhimurium. J Gen Microbiol. 1958;19(3):607–616. https://doi.org/10.1099/00221287-19-3-607
  5. [5] Akerlund T, Nordström K, Bernander R. Analysis of cell size and DNA content in exponentially growing and stationary-phase batch cultures of Escherichia coli. J Bacteriol. 1995;177(23):6791–6797. https://journals.asm.org/doi/10.1128/jb.177.23.6791-6797.1995
  6. [6] Shi H, Westfall CS, Kao J, et al. Starvation induces shrinkage of the bacterial cytoplasm. Proc Natl Acad Sci USA. 2021;118(24):e2104686118. https://doi.org/10.1073/pnas.2104686118
  7. [7] Ultee E, Ramijan K, Dame RT, Briegel A, Claessen D. Stress-induced adaptive morphogenesis in bacteria. Adv Microb Physiol. 2019;74:97–141. https://doi.org/10.1016/bs.ampbs.2019.02.001
  8. [8] Mukherjee A, Cao C, Lutkenhaus J. Inhibition of FtsZ polymerization by SulA, an inhibitor of septation in Escherichia coli. Proc Natl Acad Sci USA. 1998;95(6):2885–2890. https://doi.org/10.1073/pnas.95.6.2885
  9. [9] Eiteman MA, Altman E. Overcoming acetate in Escherichia coli recombinant protein fermentations. Trends Biotechnol. 2006;24(11):530–536. https://doi.org/10.1016/j.tibtech.2006.09.001

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