Early dynamics of chronic myeloid leukemia on nilotinib predicts deep molecular response.

Chronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase. Although ABL1-specific tyrosine kinase inhibitors (TKIs) including nilotinib have dramatically improved the prognosis of patients with CML, the TKI efficacy depends on the individual patient. In this work, we found that the patients with different nilotinib responses can be classified by using the estimated parameters of our simple dynamical model with two common laboratory findings. Furthermore, our proposed method identified patients who failed to achieve a treatment goal with high fidelity according to the data collected only at three initial time points during nilotinib therapy. Since our model relies on the general properties of TKI response, our framework would be applicable to CML patients who receive frontline nilotinib or other TKIs.

Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration.

Collective invasion drives multicellular cancer cells to spread to surrounding normal tissues. To fully comprehend metastasis, the methodology of analysis of individual cell migration in tissue should be well developed. Extracting and classifying cells with similar migratory characteristics in a colony would facilitate an understanding of complex cell migration patterns. Here, we used electrospun fibers as the extracellular matrix for the in vitro modeling of collective cell migration, clustering of mesenchymal and epithelial cells based on trajectories, and analysis of collective migration patterns based on trajectory similarity. We normalized the trajectories to eliminate the effect of cell location on clustering and used uniform manifold approximation and projection to perform dimensionality reduction on the time-series data before clustering. When the clustering results were superimposed on the trajectories before normalization, the results still exhibited positional similarity, thereby demonstrating that this method can identify cells with similar migration patterns. The same cluster contained both mesenchymal and epithelial cells, and this result was related to cell location and cell division. These data highlight the reliability of this method in identifying consistent migration patterns during collective cell migration. This provides new insights into the epithelial-mesenchymal interactions that affect migration patterns.

Intermitochondrial signaling regulates the uniform distribution of stationary mitochondria in axons.

In the central nervous system (CNS), many neurons develop axonal arbors that are crucial for information processing. Previous studies have demonstrated that premature axons contain motile and stationary mitochondria, and their balance is important for axonal arborization. However, the mechanisms by which neurons determine the positions of stationary mitochondria as well as their turnover remain to be elucidated. We observed that the distribution of stationary mitochondrial spots along the unmyelinated and nonsynaptic axons is not random but rather relatively uniform both in primary cultured neurons and in tissues. Intriguingly, whereas the positions of each mitochondrial spot changed over time, the overall distribution remained uniform. In addition, local inactivation of mitochondria by KillerRed mediated chromophore-assisted light inactivation (CALI) inhibited the translocation of mitochondrial spots in adjacent axonal regions, suggesting that functional mitochondria enhance the motility of other mitochondria in the vicinity. Signals of ATP:ADP sensor, PercevalHR indicated that the ATP:ADP ratio was relatively high around mitochondria, and treating axons with phosphocreatine (PCr), which supplies ATP, reduced the immobile mitochondria induced by the local mitochondrial inactivation. In a mathematical model, we found that the ATP gradient generated by mitochondria, and ATP dependent regulation of mitochondrial motility could establish uniform mitochondrial distribution. These observations suggest that axons in the CNS possess the system that distributes mitochondria uniformly, and intermitochondrial signaling contribute to the regulation. In addition, our results suggest the possibility that ATP might be one of the molecules mediating the signaling.

Reliable target ligand detection by noise-induced receptor cluster formation.

Intracellular reactions are intrinsically stochastic. Nonetheless, cells can reliably respond to the changing environment by sensing their target molecules sensitively and specifically, even with the existence of abundant structurally-similar non-target molecules. The mechanism of how the cells can balance and achieve such different characteristics is not yet fully understood. In this work, we demonstrate that these characteristics can be attained by a ligand-induced stochastic cluster formation of receptors via the noise-induced symmetry breaking, in which the intrinsic stochasticity works to enhance sensitivity and specificity. We also show that the noise-induced cluster formation enables cells to detect the target ligand reliably by compensating the abundant non-target ligands in the environment. The proposed mechanism may lead to a deeper understanding of a biological function of the receptor clustering and provide an alternative candidate for the reliable ligand detection to the kinetic proofreading.

Balancing specificity, sensitivity, and speed of ligand discrimination by zero-order ultraspecificity.

Specific interactions between receptors and their target ligands in the presence of nontarget ligands are crucial for biological processes such as T cell ligand discrimination. To discriminate between the target and nontarget ligands, cells have to increase specificity to the target ligands by amplifying the small differences in affinity among ligands. In addition, sensitivity to the ligand concentration and quick discrimination are also important to detect low amounts of target ligands and facilitate fast cellular decision making after ligand recognition. In this work we propose a mechanism for nonlinear specificity amplification (ultraspecificity) based on zero-order saturating reactions, which was originally proposed to explain nonlinear sensitivity amplification (ultrasensitivity) to the ligand concentration. In contrast to the previously proposed proofreading mechanisms that amplify the specificity by a multistep reaction, our model can produce an optimal balance of specificity, sensitivity, and quick discrimination. Furthermore, we show that a model for insensitivity to a large number of nontarget ligands can be naturally derived from a model with the zero-order ultraspecificity. The zero-order ultraspecificity, therefore, may provide an alternative way to understand ligand discrimination from the viewpoint of nonlinear properties in biochemical reactions.

Experimental and theoretical bases for mechanisms of antigen discrimination by T cells.

Interaction only within specific molecules is a requisite for accurate operations of a biochemical reaction in a cell where bulk of background molecules exist. While structural specificity is a well-established mechanism for specific interaction, biophysical and biochemical experiments indicate that the mechanism is not sufficient for accounting for the antigen discrimination by T cells. In addition, the antigen discrimination by T cells also accompanies three intriguing properties other than the specificity: sensitivity, speed, and concentration compensation. In this work, we review experimental and theoretical works on the antigen discrimination by focusing on these four properties and show future directions towards understanding of the fundamental principle for molecular discrimination.