Measuring compositional and growth properties of single cells

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 119-128).The physical properties of a cell are manifestations of its most basic molecular and metabolic processes. In particular, size has been a sought metric, which can be difficult to ascertain with great resolution or for smaller organisms. The advancement of single-cell measurement techniques and the understanding of cell-to-cell variability have renewed the interest in size characterization. In addition, knowledge of how individual cells grow and coordinate their growth with the cell cycle is of fundamental interest to understanding cell development, but various approaches for describing cellular growth patterns have often reached irreconcilable conclusions. In this thesis, a highly sensitive microfabricated single-cell mass sensor - the suspended microchannel resonator - is used to demonstrate cellular growth measurements by mass accumulation for several microorganism, ranging from bacterial cells to eukaryotes and mammalian cells. From those measurements insights about cellular growth are derived, demonstrating that larger cells grow faster than smaller ones, consistent with exponential-like growth patterns and incompatible with linear growth models. Subsequently, the implementation of mechanical traps as means to optimize existing sensors is presented and the techniques are applied to the measurement of total mass, density and volume at the single-cell level. Finally, a method is introduced to quantify cellular dry mass, dry density and water content. It is based on weighing the same cell first in a water-based fluid and subsequently in a deuterium oxide-based fluid, which rapidly exchanges the intracellular water content. Correlations between dry density and cellular proliferation and composition are described. Dry density is described as a quantitative index that correlates with proliferation and cellular chemical composition.by Francisco Feijó Delgado.Ph.D

In Vivo Volume and Hemoglobin Dynamics of Human Red Blood Cells

Human red blood cells (RBCs) lose ∼30% of their volume and ∼20% of their hemoglobin (Hb) content during their ∼100-day lifespan in the bloodstream. These observations are well-documented, but the mechanisms for these volume and hemoglobin loss events are not clear. RBCs shed hemoglobin-containing vesicles during their life in the circulation, and this process is thought to dominate the changes in the RBC physical characteristics occurring during maturation. We combine theory with single-cell measurements to investigate the impact of vesiculation on the reduction in volume, Hb mass, and membrane. We show that vesicle shedding alone is sufficient to explain membrane losses but not volume or Hb losses. We use dry mass measurements of human RBCs to validate the models and to propose that additional unknown mechanisms control volume and Hb reduction and are responsible for ∼90% of the observed reduction. RBC population characteristics are used in the clinic to monitor and diagnose a wide range of conditions including malnutrition, inflammation, and cancer. Quantitative characterization of cellular maturation processes may help in the early detection of clinical conditions where maturation patterns are altered

Intracellular Water Exchange for Measuring the Dry Mass, Water Mass and Changes in Chemical Composition of Living Cells

We present a method for direct non-optical quantification of dry mass, dry density and water mass of single living cells in suspension. Dry mass and dry density are obtained simultaneously by measuring a cell’s buoyant mass sequentially in an H[subscript 2]O-based fluid and a D[subscript 2]O-based fluid. Rapid exchange of intracellular H[subscript 2]O for D[subscript 2]O renders the cell’s water content neutrally buoyant in both measurements, and thus the paired measurements yield the mass and density of the cell’s dry material alone. Utilizing this same property of rapid water exchange, we also demonstrate the quantification of intracellular water mass. In a population of E. coli, we paired these measurements to estimate the percent dry weight by mass and volume. We then focused on cellular dry density – the average density of all cellular biomolecules, weighted by their relative abundances. Given that densities vary across biomolecule types (RNA, DNA, protein), we investigated whether we could detect changes in biomolecular composition in bacteria, fungi, and mammalian cells. In E. coli, and S. cerevisiae, dry density increases from stationary to exponential phase, consistent with previously known increases in the RNA/protein ratio from up-regulated ribosome production. For mammalian cells, changes in growth conditions cause substantial shifts in dry density, suggesting concurrent changes in the protein, nucleic acid and lipid content of the cell.National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)National Institutes of Health (U.S.) (Center for Cell Division Process Grant P50GM6876)National Institutes of Health (U.S.) (Contract R01CA170592)United States. Army Research Office (Institute for Collaborate Biotechnologies Contract W911NF-09-D-0001

Aspiration technique-based device is more reliable in cervical stiffness assessment than digital palpation

BACKGROUND The purpose of this study was to compare the reliability and reproducibility of the traditional qualitative method of assessing uterine cervical stiffness with those of a quantitative method using a novel device based on the aspiration technique. METHODS Five silicone models of the uterine cervix were created and used to simulate different cervical stiffnesses throughout gestation. The stiffness of the five cervix models was assessed both by digital palpation (firm, medium and soft) and with the Pregnolia System. Five self-trained participants conducted the device-based assessment, whereas 63 obstetricians and midwives, trained in digital palpation, conducted the cervical palpation. RESULTS The results of the two methods were analyzed in terms of inter-and intra-observer variability. For digital palpation, there was no common agreement on the assessment of the stiffness, except for the softest cervix. When assessing the same cervix model for a second time, 76% of the obstetricians and midwives disagreed with their previous assessment. In contrast, the maximum standard deviation for the device-based stiffness assessment for intra- and inter-observer variability was 3% and 3.4%, respectively. CONCLUSIONS This study has shown that a device based on the aspiration technique provides obstetricians and midwives with a method for objectively and repeatably assess uterine cervical stiffness, which can eliminate the need to rely solely on a subjective interpretation, as is the case with digital palpation

Estimated fraction of volume and Hb lost (mean ± std) by vesiculation as a fraction of total volume or Hb lost during maturation.

1<p>For these values ( = 4, <i>r_i</i> = 100) we get ∼100% for the fraction of surface area lost via vesiculation.</p>2<p>Vesicle [Hb] is that of the shedding cell, which is later referred to as model 1.</p><p>We assume a vesicle radius of 100 nm (the 90th percentile).</p><p>Estimated fraction of volume and Hb lost (mean ± std) by vesiculation as a fraction of total volume or Hb lost during maturation.</p

The changes in volume, Hb mass, and concentration in healthy adult humans (<i>n</i> = 21).

1<p>Formally, , where <i>X</i>, (<i>X</i>₀) is respectively, (initial) volume, Hb mass, or concentration (, for [Hb]).</p><p>The change is the difference between means of reticulocytes (red dots in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003839#pcbi-1003839-g001" target="_blank">Figure 1</a>) and the total population (blue dots in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003839#pcbi-1003839-g001" target="_blank">Figure 1</a>).</p><p>The changes in volume, Hb mass, and concentration in healthy adult humans (<i>n</i> = 21).</p

The raw data used to calculate the values in Table 1.

<p>The raw data used to calculate the values in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003839#pcbi-1003839-t001" target="_blank">Table 1</a>.</p

SMR measurements of dry mass and dry density, samples (S1-S5) with the corresponding modeling based on Advia data (first row, model 1, second row model 2, each column is the same SMR sample).

<p>For model 1, is calculated from the Hb mass model (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003839#pcbi.1003839.e081" target="_blank">Eq. (8)</a>), while for model 2 it is fixed to 11. Young cells (red dots) are evolved using either model 1 or 2 to obtain the older cells (blue dots), and compared to the measured SMR data (purple dots). The green line is an example trajectory of a single RBC. Notice that the simulation results (blue dots) are a small random sample from the entire simulated data, matching in size to the SMR sample size.</p