Polymer-directed inhibition of reversible to irreversible attachment prevents Pseudomonas aeruginosa biofilm formation

Non-toxic, biocompatible materials that inhibit bacterial biofilm formation on implanted medical devices and so prevent infection are urgently required. Weakly amphiphilic acrylate polymers with rigid hydrocarbon pendant groups resist bacterial biofilm formation in vitro and in vivo but the biological mechanism involved is not known. By comparing biofilm formation on polymers with the same acrylate backbone but with different pendant groups, we show that poly(ethylene glycol dicyclopentenyl ether acrylate; pEGdPEA) but not neopentyl glycol propoxylate diacrylate (pNGPDA) inhibited the transition from reversible to irreversible attachment. By using single-cell tracking algorithms and controlled flow microscopy we observed that fewer Pseudomonas aeruginosa PAO1 cells accumulated on pEGdPEA compared with pNGPDA. Bacteria reaching the pEGdPEA surface exhibited shorter residence times and greater asymmetric division with more cells departing from the surface post-cell division, characteristic of reversible attachment. Migrating cells on pEGdPEA deposited fewer exopolysaccharide trails and were unable top adhere strongly. Discrimination between the polymers required type IV pili and flagella. On pEGdPEA, the lack of accumulation of cyclic diguanylate or expression of sadB were consistent with the failure to transit from reversible to irreversible attachment. Constitutive expression of sadB increased surface adhesion sufficient to enable P. aeruginosa to form biofilms in a Mot flagellar stator dependent manner. These findings were extendable to other biofilm resistant acrylates highlighting their unique ability to inhibit reversible to irreversible attachment as a mechanism for preventing biofilm-associated infections.

Tracking cell lineages in 3D by incremental deep learning

Deep learning is emerging as a powerful approach for bioimage analysis. Its use in cell tracking is limited by the scarcity of annotated data for the training of deep-learning models. Moreover, annotation, training, prediction, and proofreading currently lack a unified user interface. We present ELEPHANT, an interactive platform for 3D cell tracking that addresses these challenges by taking an incremental approach to deep learning. ELEPHANT provides an interface that seamlessly integrates cell track annotation, deep learning, prediction, and proofreading. This enables users to implement cycles of incremental learning starting from a few annotated nuclei. Successive prediction-validation cycles enrich the training data, leading to rapid improvements in tracking performance. We test the software’s performance against state-of-the-art methods and track lineages spanning the entire course of leg regeneration in a crustacean over 1 week (504 timepoints). ELEPHANT yields accurate, fully-validated cell lineages with a modest investment in time and effort.

Natural Barcodes for Longitudinal Single Cell Tracking of Leukemic and Immune Cell Dynamics

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.

Accumulation of TERT in Mitochondria Shows Two Opposing Effects on Apoptosis

Telomerase reverse transcriptase (TERT) is a protein that catalyzes the reverse transcription of telomere elongation. TERT is also expected to play a noncanonical role beyond telomere lengthening since it localizes not only in the nucleus but also in mitochondria, where telomeres do not exist. Several studies have reported that mitochondrial TERT regulates apoptosis induced by oxidative stress. However, there remains controversy about whether mitochondrial TERT promotes or inhibits apoptosis, mainly due to the lack of information on changes in the TERT distribution in individual cells over time. Here we simultaneously detected apoptosis and TERT localization after oxidative stress in individual HeLa cells by live-cell tracking. This tracking revealed that the stress-induced accumulation of TERT in mitochondria resulted in apoptosis but that the accumulation positively correlated with the time until cell death. The results suggest a new model in which mitochondrial TERT has two opposing effects at different stages of apoptosis: it predetermines apoptosis at the first stage of cell-fate determination but also delays apoptosis at the second stage. Because these distinct effects respectively support both sides of the controversy regarding the role of mitochondrial TERT in apoptosis, our model integrates two opposing hypotheses. Furthermore, detailed statistical analysis of TERT mutations, which have been predicted to inhibit TERT transport to mitochondria, revealed that these mutations suppress apoptosis independent of the mitochondrial localization of TERT. Together, these results indicate that the non-canonical functions of TERT affect a wide range of apoptotic pathways.

Galvanotaxis of ciliates: Spatiotemporal dynamics of Coleps hirtus under electric fields

Galvanotaxis describes the functional response of organisms to electric fields. In ciliates, the electric field influences the electrophysiology and thus the cilia beat dynamics. This leads to a change of the swimming direction towards the cathode. The dynamical response to electric fields of Coleps hirtus has not been studied since the observations of Verworn in 1890 (1). While galvanotaxis has been studied in other cilitates, C. hirtus exhibit properties not found elsewhere, such as biomineralization-processes of alveolar plates with impact on the intracellular calcium regulation and a bimodal resting membrane potential, which leads unique electrophysiological driven bimodal swimming dynamics. Here, we statistically analyze the galvanotactic dynamics of C. hirtus by automated cell tracking routines. We found that the number of cells that show a galvanotactic response, increases with the increase of the applied electric field strength with a mean at about 2.1 V/cm. The spatiotemporal swimming dynamics change and lead to a statistical increase of linear elongated cell trajectories that point toward the cathode. Further, the increase of the electric fields decreases the mean velocity variance for electric fields larger than about 1.3 V/cm, while showing no significant change in the absolute velocity for any applied electric field. Fully functional galvanotactic responses were observed at a minimum extracellular calcium concentration of 20 μM. The results add important insights to the current understanding of cellular dynamics of ciliates and suggest that the currently accepted model lags the inclusion of the swimming dynamics and the complex calcium regulatory system of the cell. The results of this study do not only extend the fundamental understanding of C. hirtus dynamics, but also open possibilities for technical applications, such as biosensors or microrobots in the future.

N6-methyladenosine (m6A) depletion regulates pluripotency exit by activating signaling pathways in embryonic stem cells

N6-methyladenosine (m6A) deposition on messenger RNA (mRNA) controls embryonic stem cell (ESC) fate by regulating the mRNA stabilities of pluripotency and lineage transcription factors (TFs) [P. J. Batista et al., Cell Stem Cell 15, 707–719 (2014); Y. Wang et al., Nat. Cell Biol. 16, 191–198 (2014); and S. Geula et al., Science 347, 1002–1006 (2015)]. If the mRNAs of these two TF groups become stabilized, it remains unclear how the pluripotency or lineage commitment decision is implemented. We performed noninvasive quantification of Nanog and Oct4 TF protein levels in reporter ESCs to define cell-state dynamics at single-cell resolution. Long-term single-cell tracking shows that immediate m6A depletion by Mettl3 knock-down in serum/leukemia inhibitory factor supports both pluripotency maintenance and its departure. This is mediated by differential and opposing signaling pathways. Increased FGF5 mRNA stability activates pErk, leading to Nanog down-regulation. FGF5-mediated coactivation of pAkt reenforces Nanog expression. In formative stem cells poised toward differentiation, m6A depletion activates both pErk and pAkt, increasing the propensity for mesendodermal lineage induction. Stable m6A depletion by Mettl3 knock-out also promotes pErk activation. Higher pErk counteracts the pluripotency exit delay exhibited by stably m6A-depleted cells upon differentiation. At single-cell resolution, we illustrate that decreasing m6A abundances activates pErk and pAkt-signaling, regulating pluripotency departure.

Label-free Cell Tracking Enables Collective Motion Phenotyping in Epithelial Monolayers

Collective cell migration is an umbrella term for a rich variety of cell behaviors, whose distinct character is essential for biological function, notably for cancer metastasis. One essential feature of collective behavior is the motion of cells relative to their immediate neighbors. We introduce an AI-based pipeline to segment and track cell nuclei from phase contrast images. Nuclei segmentation is based on a U‐Net convolutional neural network trained on images with nucleus staining. Tracking, based on the Crocker-Grier algorithm, quantifies nuclei movement and allows for robust downstream analysis of collective motion. Since the AI algorithm required no new training data, our approach promises to be applicable to and yield new insights for vast libraries of existing collective motion images. In a systematic analysis of a cell line panel with oncogenic mutations, we find that the collective rearrangement metric, D2min, which reflects non-affine motion, shows promise as an indicator of metastatic potential.

An Object-based Climatology of Precipitation Systems in Sydney, Australia

The climate is warming and this is changing some aspects of storms, but we have relatively little knowledge of storm characteristics beyond intensity, which limits our understanding of storms overall. In this study, we apply a cell-tracking algorithm to 20 years of radar data at a mid-latitude coastal-site (Sydney, Australia), to establish a regional precipitation system climatology. The results show that extreme storms in terms of translation-speed, size and rainfall intensity usually occur in the warm season, and are slower and more intense over land between ~10am and ~8pm (AEST), peaking in the afternoon. Precipitation systems are more frequent in the cold season and often initiate over the ocean and move northward, leading to precipitation mostly over the ocean. Using clustering algorithms, we have found five precipitation system types with distinct properties, occurring throughout the year but peaking in different seasons. While overall rainfall statistics don't show any link to climate modes, links do appear for some system types using a multivariate approach. This climatology for a variety of precipitation system characteristics will allow future study of any changes in these characteristics due to climate change.

Cell-Projection Pumping of Fibroblast Contents into Osteosarcoma SAOS-2 Cells Correlates with Increased SAOS-2 Proliferation and Migration, as well as Altered Morphology

We earlier reported that cell-projection pumping transfers fibroblast contents to cancer cells and this alters the cancer cell phenotype. Here, we report on single-cell tracking of time lapse recordings from co-cultured fluorescent fibroblasts and SAOS-2 osteosarcoma cells, tracking 5201 cells across 7 experiments. The fluorescent lipophilic marker DiD was used to label fibroblast organelles and to trace the transfer of fibroblast cytoplasm into SAOS-2 cells. We related SAOS-2 phenotypic change to levels of fluorescence transfer from fibroblasts to SAOS-2 cells, as well as what we term ‘compensated fluorescence’, that numerically projects mother cell fluorescence post-mitosis into daughter cells. The comparison of absolute with compensated fluorescence allowed us to deduct if the phenotypic effects in mother SAOS-2 cells were inherited by their daughters. SAOS-2 receipt of fibroblast fluorescence correlated by Kendall’s tau with cell-profile area and without evidence of persistence in daughter cells (median tau = 0.51, p < 0.016); negatively and weakly with cell circularity and with evidence of persistence (median tau = −0.19, p < 0.05); and very weakly with cell migration velocity and without evidence of persistence (median tau = 0.01, p < 0.016). In addition, mitotic SAOS-2 cells had higher rates of prior fluorescence uptake (median = 64.9 units/day) than non-dividing cells (median = 35.6 units/day, p < 0.016) and there was no evidence of persistence post-mitosis. We conclude that there was an appreciable impact of cell-projection pumping on cancer cell phenotype relevant to cancer histopathological diagnosis, clinical spread and growth, with most effects being ‘reset’ by cancer cell mitosis.