AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells.

Cell polarity is a macroscopic phenomenon established by a collection of spatially concentrated molecules and structures that culminate in the emergence of specialized domains at the subcellular level. It is associated with developing asymmetric morphological structures that underlie key biological functions such as cell division, growth, and migration. In addition, the disruption of cell polarity has been linked to tissue-related disorders such as cancer and gastric dysplasia. Current methods to evaluate the spatiotemporal dynamics of fluorescent reporters in individual polarized cells often involve manual steps to trace a midline along the cells' major axis, which is time consuming and prone to strong biases. Furthermore, although ratiometric analysis can correct the uneven distribution of reporter molecules using two fluorescence channels, background subtraction techniques are frequently arbitrary and lack statistical support. This manuscript introduces a novel computational pipeline to automate and quantify the spatiotemporal behavior of single cells using a model of cell polarity: pollen tube/root hair growth and cytosolic ion dynamics. A three-step algorithm was developed to process ratiometric images and extract a quantitative representation of intracellular dynamics and growth. The first step segments the cell from the background, producing a binary mask through a thresholding technique in the pixel intensity space. The second step traces a path through the midline of the cell through a skeletonization operation. Finally, the third step provides the processed data as a ratiometric timelapse and yields a ratiometric kymograph (i.e., a 1D spatial profile through time). Data from ratiometric images acquired with genetically encoded fluorescent reporters from growing pollen tubes were used to benchmark the method. This pipeline allows for faster, less biased, and more accurate representation of the spatiotemporal dynamics along the midline of polarized cells, thus advancing the quantitative toolkit available to investigate cell polarity. The AMEBaS Python source code is available at: https://github.com/badain/amebas.git.

Electrifying rhythms in plant cells.

Physiological oscillations (or rhythms) pervade all spatiotemporal scales of biological organization, either because they perform critical functions or simply because they can arise spontaneously and may be difficult to prevent. Regardless of the case, they reflect regulatory relationships between control points of a given system and offer insights as read-outs of the concerted regulation of a myriad of biological processes. Here we review recent advances in understanding ultradian oscillations (period < 24h) in plant cells, with a special focus on single-cell oscillations. Ion channels are at the center stage due to their involvement in electrical/excitabile phenomena associated with oscillations and cell-cell communication. We highlight the importance of quantitative approaches to measure oscillations in appropriate physiological conditions, which are essential strategies to deal with the complexity of biological rhythms. Future development of optogenetics techniques in plants will further boost research on the role of membrane potential in oscillations and waves across multiple cell types.

West Nile virus transmission potential in Portugal.

It is unclear whether West Nile virus (WNV) circulates endemically in Portugal. Despite the country's adequate climate for transmission, Portugal has only reported four human WNV infections so far. We performed a review of WNV-related data (1966-2020), explored mosquito (2016-2019) and land type distributions (1992-2019), and used climate data (1981-2019) to estimate WNV transmission suitability in Portugal. Serological and molecular evidence of WNV circulation from animals and vectors was largely restricted to the south. Land type and climate-driven transmission suitability distributions, but not the distribution of WNV-capable vectors, were compatible with the North-South divide present in serological and molecular evidence of WNV circulation. Our study offers a comprehensive, data-informed perspective and review on the past epidemiology, surveillance and climate-driven transmission suitability of WNV in Portugal, highlighting the south as a subregion of importance. Given the recent WNV outbreaks across Europe, our results support a timely change towards local, active surveillance.

Spatiotemporal Quantification of Cytosolic pH in Arabidopsis Pollen Tubes.

Ion-specific probes and fluorescent indicators have been key in establishing the role of ion signaling, namely calcium, protons, and anions, in plant development, providing a robust approach for monitoring spatiotemporal changes in intracellular ion dynamics. The integration of protons/pH in signaling mechanisms is especially important as reports of their biological functions continue to expand; however, attaining quantitative estimates with high spatiotemporal resolution in single cells poses a major research challenge. Here, we detail the use of the genetically encoded pH-sensitive pHluorin reporter expressed in Arabidopsis thaliana pollen tubes to assess cytosolic measurements with calibration to provide actual pH values. This technique enabled us to identify critical phenotypes and establish the importance of tip-focused pH gradient for pollen tube growth, although it can be adapted to other experimental systems.

An optimized genetically encoded dual reporter for simultaneous ratio imaging of Ca2+ and H+ reveals new insights into ion signaling in plants.

Whereas the role of calcium ions (Ca2+ ) in plant signaling is well studied, the physiological significance of pH-changes remains largely undefined. Here we developed CapHensor, an optimized dual-reporter for simultaneous Ca2+ and pH ratio-imaging and studied signaling events in pollen tubes (PTs), guard cells (GCs), and mesophyll cells (MCs). Monitoring spatio-temporal relationships between membrane voltage, Ca2+ - and pH-dynamics revealed interconnections previously not described. In tobacco PTs, we demonstrated Ca2+ -dynamics lag behind pH-dynamics during oscillatory growth, and pH correlates more with growth than Ca2+ . In GCs, we demonstrated abscisic acid (ABA) to initiate stomatal closure via rapid cytosolic alkalization followed by Ca2+ elevation. Preventing the alkalization blocked GC ABA-responses and even opened stomata in the presence of ABA, disclosing an important pH-dependent GC signaling node. In MCs, a flg22-induced membrane depolarization preceded Ca2+ -increases and cytosolic acidification by c. 2 min, suggesting a Ca2+ /pH-independent early pathogen signaling step. Imaging Ca2+ and pH resolved similar cytosol and nuclear signals and demonstrated flg22, but not ABA and hydrogen peroxide to initiate rapid membrane voltage-, Ca2+ - and pH-responses. We propose close interrelation in Ca2+ - and pH-signaling that is cell type- and stimulus-specific and the pH having crucial roles in regulating PT growth and stomata movement.

Potential impact of individual exposure histories to endemic human coronaviruses on age-dependent severity of COVID-19.

BACKGROUND: Cross-reactivity to SARS-CoV-2 from exposure to endemic human coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and COVID-19 severity. Here we explore the potential role of cross-reactivity induced by eHCoVs on age-specific COVID-19 severity in a mathematical model of eHCoV and SARS-CoV-2 transmission. METHODS: We use an individual-based model, calibrated to prior knowledge of eHCoV dynamics, to fully track individual histories of exposure to eHCoVs. We also model the emergent dynamics of SARS-CoV-2 and the risk of hospitalisation upon infection. RESULTS: We hypothesise that primary exposure with any eHCoV confers temporary cross-protection against severe SARS-CoV-2 infection, while life-long re-exposure to the same eHCoV diminishes cross-protection, and increases the potential for disease severity. We show numerically that our proposed mechanism can explain age patterns of COVID-19 hospitalisation in EU/EEA countries and the UK. We further show that some of the observed variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates under this model. CONCLUSIONS: This study provides a "proof of possibility" for certain biological and epidemiological mechanisms that could potentially drive COVID-19-related variation across age groups. Our findings call for further research on the role of cross-reactivity to eHCoVs and highlight data interpretation challenges arising from health care capacity and SARS-CoV-2 testing.

Analyzing Intracellular Gradients in Pollen Tubes.

Conspicuous intracellular gradients manifest and/or drive intracellular polarity in pollen tubes. However, quantifying these gradients raises multiple technical challenges. Here we present a sensible computational protocol to analyze gradients in growing pollen tubes and to filter nonrepresentative time points. As an example, we use imaging data from pollen tubes expressing a genetically encoded ratiometric Ca2+ probe, Yellow CaMeleon 3.6, from which a kymograph is extracted. The tip of the pollen tube is detected with CHUKNORRIS, our previously published methodology, allowing the reconstruction of the intracellular gradient through time. Statistically confounding time points, such as growth arrest where gradients are highly oscillatory, are filtered out and a mean spatial profile is estimated with a local polynomial regression method. Finally, we estimate the gradient slope by the linear portion of the decay in mean fluorescence, offering a quantitative method to detect phenotypes of gradient steepness, location, intensity, and variability. The data manipulation protocol proposed can be achieved in a simple and efficient manner using the statistical programming language R, opening paths to perform high-throughput spatiotemporal phenotyping of intracellular gradients in apically growing cells.

GLUTAMATE RECEPTOR-LIKE channels are essential for chemotaxis and reproduction in mosses.

Glutamate receptors are well characterized channels that mediate cell-to-cell communication during neurotransmission in animals, but their functional role in organisms without a nervous system remains unclear. In plants, genes of the GLUTAMATE RECEPTOR-LIKE (GLR) family have been implicated in defence against pathogens, reproduction, control of stomata aperture and light signal transduction. However, the large number of GLR genes present in angiosperm genomes (20 to 70) has prevented the observation of strong phenotypes in loss-of-function mutants. Here we show that in the basal land plant Physcomitrella patens, mutation of the GLR genes GLR1 and GLR2 causes failure of sperm cells to target the female reproductive organs. In addition, we show that GLR genes encode non-selective Ca2+-permeable channels that can regulate cytoplasmic Ca2+ and are needed to induce the expression of a BELL1-like transcription factor essential for zygote development. Our work reveals functions for GLR channels in sperm chemotaxis and transcriptional regulation. Sperm chemotaxis is essential for fertilization in both animals and early land plants such as bryophytes and pteridophytes. Therefore, our results suggest that ionotropic glutamate receptors may have been conserved throughout plant evolution to mediate cell-to-cell communication during sexual reproduction.

Oscillatory signatures underlie growth regimes in Arabidopsis pollen tubes: computational methods to estimate tip location, periodicity, and synchronization in growing cells.

Oscillations in pollen tubes have been reported for many cellular processes, including growth, extracellular ion fluxes, and cytosolic ion concentrations. However, there is a shortage of quantitative methods to measure and characterize the different dynamic regimes observed. Herein, a suite of open-source computational methods and original algorithms were integrated into an automated analysis pipeline that we employed to characterize specific oscillatory signatures in pollen tubes of Arabidopsis thaliana (Col-0). Importantly, it enabled us to detect and quantify a Ca2+ spiking behaviour upon growth arrest and synchronized oscillations involving growth, extracellular H+ fluxes, and cytosolic Ca2+, providing the basis for novel hypotheses. Our computational approach includes a new tip detection method with subpixel resolution using linear regression, showing improved ability to detect oscillations when compared to currently available methods. We named this data analysis pipeline 'Computational Heuristics for Understanding Kymographs and aNalysis of Oscillations Relying on Regression and Improved Statistics', or CHUKNORRIS. It can integrate diverse data types (imaging, electrophysiology), extract quantitative and time-explicit estimates of oscillatory characteristics from isolated time series (period and amplitude) or pairs (phase relationships and delays), and evaluate their synchronization state. Here, its performance is tested with ratiometric and single channel kymographs, ion flux data, and growth rate analysis.