Serine 26 in the PomB subunit of the flagellar motor is essential for hypermotility of Vibrio cholerae

Investigating Optimal Time Step Intervals of Imaging for Data Quality through a Novel Fully-Automated Cell Tracking Approach

Computer-based fully-automated cell tracking is becoming increasingly important in cell biology, since it provides unrivalled capacity and efficiency for the analysis of large datasets. However, automatic cell tracking’s lack of superior pattern recognition and error-handling capability compared to its human manual tracking counterpart inspired decades-long research. Enormous efforts have been made in developing advanced cell tracking packages and software algorithms. Typical research in this field focuses on dealing with existing data and finding a best solution. Here, we investigate a novel approach where the quality of data acquisition could help improve the accuracy of cell tracking algorithms and vice-versa. Generally speaking, when tracking cell movement, the more frequent the images are taken, the more accurate cells are tracked and, yet, issues such as damage to cells due to light intensity, overheating in equipment, as well as the size of the data prevent a constant data streaming. Hence, a trade-off between the frequency at which data images are collected and the accuracy of the cell tracking algorithms needs to be studied. In this paper, we look at the effects of different choices of the time step interval (i.e., the frequency of data acquisition) within the microscope to our existing cell tracking algorithms. We generate several experimental data sets where the true outcomes are known (i.e., the direction of cell migration) by either using an effective chemoattractant or employing no-chemoattractant. We specify a relatively short time step interval (i.e., 30 s) between pictures that are taken at the data generational stage, so that, later on, we may choose some portion of the images to produce datasets with different time step intervals, such as 1 min, 2 min, and so on. We evaluate the accuracy of our cell tracking algorithms to illustrate the effects of these different time step intervals. We establish that there exist certain relationships between the tracking accuracy and the time step interval associated with experimental microscope data acquisition. We perform fully-automatic adaptive cell tracking on multiple datasets, to identify optimal time step intervals for data acquisition, while at the same time demonstrating the performance of the computer cell tracking algorithms.

Evolution of the Stator Elements of Rotary Prokaryote Motors

The bacterial flagellar motor is driven by an ion flux that is converted to torque by motor-attendant complexes known as stators. The dynamics of stator assembly around the motor in response to external stimuli have been the subject of much recent research, but less is known about the evolutionary origins of stator complexes and how they select for specific ions. Here, we review the latest structural and biochemical data for the stator complexes and compare these with other ion transporters and microbial motors to examine possible evolutionary origins of the stator complex.

Essential ion binding residues for Na+ flow in stator complex of the Vibrio flagellar motor

The bacterial flagellar motor is a unique supramolecular complex which converts ion flow into rotational force. Many biological devices mainly use two types of ions, proton and sodium ion. This is probably because of the fact that life originated in seawater, which is rich in protons and sodium ions. The polar flagellar motor in Vibrio is coupled with sodium ion and the energy converting unit of the motor is composed of two membrane proteins, PomA and PomB. It has been shown that the ion binding residue essential for ion transduction is the conserved aspartic acid residue (PomB-D24) in the PomB transmembrane region. To reveal the mechanism of ion selectivity, we identified essential residues, PomA-T158 and PomA-T186, other than PomB-D24, in the Na⁺-driven flagellar motor. It has been shown that the side chain of threonine contacts Na⁺ in Na⁺-coupled transporters. We monitored the Na⁺-binding specific structural changes using ATR-FTIR spectroscopy. The signals were abolished in PomA-T158A and -T186A, as well as in PomB-D24N. Molecular dynamics simulations further confirmed the strong binding of Na⁺ to D24 and showed that T158A and T186A hindered the Na⁺ binding and transportation. The data indicate that two threonine residues (PomA-T158 and PomA-T186), together with PomB-D24, are important for Na⁺ conduction in the Vibrio flagellar motor. The results contribute to clarify the mechanism of ion recognition and conversion of ion flow into mechanical force.

Position of human blood group O(H) and phenotype-determining enzymes in growth and infectious disease

The human ABO(H) blood group phenotypes arise from the evolutionarily oldest genetic system found in primate populations. While the blood group antigen A is considered the ancestral primordial structure, under the selective pressure of life‐threatening diseases blood group O(H) came to dominate as the most frequently occurring blood group worldwide. Non‐O(H) phenotypes demonstrate impaired formation of adaptive and innate immunoglobulin specificities due to clonal selection and phenotype formation in plasma proteins. Compared with individuals with blood group O(H), blood group A individuals not only have a significantly higher risk of developing certain types of cancer but also exhibit high susceptibility to malaria tropica or infection by Plasmodium falciparum. The phenotype‐determining blood group A glycotransferase(s), which affect the levels of anti‐A/Tn cross‐reactive immunoglobulins in phenotypic glycosidic accommodation, might also mediate adhesion and entry of the parasite to host cells via trans‐species O‐GalNAc glycosylation of abundantly expressed serine residues that arise throughout the parasite's life cycle, while excluding the possibility of antibody formation against the resulting hybrid Tn antigen. In contrast, human blood group O(H), lacking this enzyme, is indicated to confer a survival advantage regarding the overall risk of developing cancer, and individuals with this blood group rarely develop life‐threatening infections involving evolutionarily selective malaria strains.