Fluid flow reconstruction around a free-swimming sperm in 3D.

We investigate the dynamics and hydrodynamics of a human spermatozoa swimming freely in 3D. We simultaneously track the sperm flagellum and the sperm head orientation in the laboratory frame of reference via high-speed high-resolution 4D (3D+t) microscopy, and extract the flagellar waveform relative to the body frame of reference, as seen from a frame of reference that translates and rotates with the sperm in 3D. Numerical fluid flow reconstructions of sperm motility are performed utilizing the experimental 3D waveforms, with excellent accordance between predicted and observed 3D sperm kinematics. The reconstruction accuracy is validated by directly comparing the three linear and three angular sperm velocities with experimental measurements. Our microhydrodynamic analysis reveals a novel fluid flow pattern, characterized by a pair of vortices that circulate in opposition to each other along the sperm cell. Finally, we show that the observed sperm counter-vortices are not unique to the experimental beat, and can be reproduced by idealised waveform models, thus suggesting a fundamental flow structure for free-swimming sperm propelled by a 3D beating flagellum.

Building momentum through networks: Bioimaging across the Americas.

In September 2023, the two largest bioimaging networks in the Americas, Latin America Bioimaging (LABI) and BioImaging North America (BINA), came together during a 1-week meeting in Mexico. This meeting provided opportunities for participants to interact closely with decision-makers from imaging core facilities across the Americas. The meeting was held in a hybrid format and attended in-person by imaging scientists from across the Americas, including Canada, the United States, Mexico, Colombia, Peru, Argentina, Chile, Brazil and Uruguay. The aims of the meeting were to discuss progress achieved over the past year, to foster networking and collaborative efforts among members of both communities, to bring together key members of the international imaging community to promote the exchange of experience and expertise, to engage with industry partners, and to establish future directions within each individual network, as well as common goals. This meeting report summarises the discussions exchanged, the achievements shared, and the goals set during the LABIxBINA2023: Bioimaging across the Americas meeting.

Feature-based 3D+t descriptors of hyperactivated human sperm beat patterns.

The flagellar movement of the mammalian sperm plays a crucial role in fertilization. In the female reproductive tract, human spermatozoa undergo a process called capacitation which promotes changes in their motility. Only capacitated spermatozoa may be hyperactivated and only those that transition to hyperactivated motility are capable of fertilizing the egg. Hyperactivated motility is characterized by asymmetric flagellar bends of greater amplitude and lower frequency. Historically, clinical fertilization studies have used two-dimensional analysis to classify sperm motility, despite the inherently three-dimensional (3D) nature of sperm motion. Recent research has described several 3D beating features of sperm flagella. However, the 3D motility pattern of hyperactivated spermatozoa has not yet been characterized. One of the main challenges in classifying these patterns in 3D is the lack of a ground-truth reference, as it can be difficult to visually assess differences in flagellar beat patterns. Additionally, it is worth noting that only a relatively small proportion, approximately 10-20% of sperm incubated under capacitating conditions exhibit hyperactivated motility. In this work, we used a multifocal image acquisition system that can acquire, segment, and track sperm flagella in 3D+t. We developed a feature-based vector that describes the spatio-temporal flagellar sperm motility patterns by an envelope of ellipses. The classification results obtained using our 3D feature-based descriptors can serve as potential label for future work involving deep neural networks. By using the classification results as labels, it will be possible to train a deep neural network to automatically classify spermatozoa based on their 3D flagellar beating patterns. We demonstrated the effectiveness of the descriptors by applying them to a dataset of human sperm cells and showing that they can accurately differentiate between non-hyperactivated and hyperactivated 3D motility patterns of the sperm cells. This work contributes to the understanding of 3D flagellar hyperactive motility patterns and provides a framework for research in the fields of human and animal fertility.

Human sperm rotate with a conserved direction during free swimming in four dimensions.

Head rotation in human spermatozoa is essential for different swimming modes and fertilisation, as it links the molecular workings of the flagellar beat with sperm motion in three-dimensional (3D) space over time. Determining the direction of head rotation has been hindered by the symmetry and translucent nature of the sperm head, and by the fast 3D motion driven by the helical flagellar beat. Analysis has been mostly restricted to two-dimensional (2D) single focal plane image analysis, which enables tracking of head centre position but not tracking of head rotation. Despite the conserved helical beating of the human sperm flagellum, human sperm head rotation has been reported to be uni- or bi-directional, and even to intermittently change direction in a given cell. Here, we directly measure the head rotation of freely swimming human sperm using multi-plane 4D (3D+t) microscopy and show that: (1) 2D microscopy is unable to distinguish head rotation direction in human spermatozoa; (2) head rotation direction in non-capacitating and capacitating solutions, for both aqueous and viscous media, is counterclockwise (CCW), as seen from head to tail, in all rotating spermatozoa, regardless of the experimental conditions; and (3) head rotation is suppressed in 36% of spermatozoa swimming in non-capacitating viscous medium, although CCW rotation is recovered after incubation in capacitating conditions within the same viscous medium, possibly unveiling an unexplored aspect of the essential need of capacitation for fertilisation. Our observations show that the CCW head rotation in human sperm is conserved. It constitutes a robust and persistent helical driving mechanism that influences sperm navigation in 3D space over time, and thus is of critical importance in cell motility, propulsion of flagellated microorganisms, sperm motility assessments, human reproduction research, and self-organisation of flagellar beating patterns and swimming in 3D space.

A Machine Learning Workflow of Multiplexed Immunofluorescence Images to Interrogate Activator and Tolerogenic Profiles of Conventional Type 1 Dendritic Cells Infiltrating Melanomas of Disease-Free and Metastatic Patients.

Melanoma is the deadliest form of skin cancer. Due to its high mutation rates, melanoma is a convenient model to study antitumor immune responses. Dendritic cells (DCs) play a key role in activating cytotoxic CD8+ T lymphocytes and directing them to kill tumor cells. Although there is evidence that DCs infiltrate melanomas, information about the profile of these cells, their activity states, and potential antitumor function remains unclear, particularly for conventional DCs type 1 (cDC1). Approaches to profiling tumor-infiltrating DCs are hindered by their diversity and the high number of signals that can affect their state of activation. Multiplexed immunofluorescence (mIF) allows the simultaneous analysis of multiple markers, but image-based analysis is time-consuming and often inconsistent among analysts. In this work, we evaluated several machine learning (ML) algorithms and established a workflow of nine-parameter image analysis that allowed us to study cDC1s in a reproducible and accessible manner. Using this workflow, we compared melanoma samples between disease-free and metastatic patients at diagnosis. We observed that cDC1s are more abundant in the tumor infiltrate of the former. Furthermore, cDC1s in disease-free patients exhibit an expression profile more congruent with an activator function: CD40highPD-L1low CD86+IL-12+. Although disease-free patients were also enriched with CD40-PD-L1+ cDC1s, these cells were also more compatible with an activator phenotype. The opposite was true for metastatic patients at diagnosis who were enriched for cDC1s with a more tolerogenic phenotype (CD40lowPD-L1highCD86-IL-12-IDO+). ML-based workflows like the one developed here can be used to analyze complex phenotypes of other immune cells and can be brought to laboratories with standard expertise and computer capacity.

3D+t feature-based descriptor for unsupervised flagellar human sperm beat classification.

Human spermatozoa must swim through the female reproductive tract, where they undergo a series of biochemical and biophysical reactions called capacitation, a necessary step to fertilize the egg. Capacitation promotes changes in the motility pattern. Historically, a two-dimensional analysis has been used to classify sperm motility and clinical fertilization studies. Nevertheless, in a natural environment sperm motility is three-dimensional (3D). Imaging flagella of freely swimming sperm is a difficult task due to their high beating frequency of up to 25 Hz. Very recent studies have described several sperm flagellum 3D beating features (curvature, torsion, asymmetries, etc.). However, up to date, the 3D motility pattern of hyperactivated spermatozoa has not been characterized. The main difficulty in classifying these patterns in 3D is the lack of a ground truth reference since differences in flagellar beat patterns are very difficult to assess visually. Moreover, only around 10-20% of induced to capacitate spermatozoa are truly capacitated, i.e., hyperactivated. We used an image acquisition system that can acquire, segment, and track spermatozoa flagella in 3D+t. In this work, we propose an original three-dimensional feature vector formed by ellipses describing the envelope of the 3D+t spatio-temporal flagellar sperm motility patterns. These features allowed compressing an unlabeled 3D+t dataset to separate hyperactivated cells from others (capacitated from non-capacitated cells) using unsupervised hierarchical clustering. Preliminary results show three main clusters of flagellar motility patterns. The first principal component of these 3D flagella measurements correlated with 2D OpenCASA head determinations as a first approach to validate the unsupervised classification, showing a reasonable correlation coefficient near to 0.7. Clinical relevance- The novelty of this work is defining a 3D+t feature-based descriptor consisting of a set of ellipses enveloping the flagellar motion of human sperm for its unsu-pervised classification. This is a new promising tool to determine the viability of human sperm to fertilize the egg.

Fluorescence fluctuation-based super-resolution microscopy: Basic concepts for an easy start.

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of approximately half of the wavelength of visible light, that is, within the range of 200 to 350 nm. Fluorescence fluctuation-based super-resolution microscopy (FF-SRM) is a term used to encompass a collection of image analysis techniques that rely on the statistical processing of temporal variations of the fluorescence signal. FF-SRM aims to reduce the uncertainty of the location of fluorophores within an image, often improving spatial resolution by several tens of nanometers. FF-SRM is suitable for live-cell imaging due to its compatibility with most fluorescent probes and relatively simple instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are described. Their operational parameters are explained and guidance for their selection is provided.

Due to light's wave nature, an optical microscope's resolution range is 200 to 350 nanometers. Several techniques enhance resolution; this work encompasses several fluorescence fluctuation super-resolution (FF-SMR) methods capable of achieving nanoscopic scales. FF-SRM is known to be suitable for fixed or live-cell imaging and compatible with most conventional microscope setups found in a laboratory. However, each FF-SRM approach has its strengths and weaknesses, which depend directly on the underlying principles through which enhanced spatial resolution is achieved. Therefore, the basic concepts and principles behind diverse FF-SRM methods are revisited in this review. In addition, their operational parameters are explained, and guidance for their selection is provided for microscopists interested in FF-SRM.

Live Plant Cell Tracking: Fiji plugin to analyze cell proliferation dynamics and understand morphogenesis.

Arabidopsis (Arabidopsis thaliana) primary and lateral roots (LRs) are well suited for 3D and 4D microscopy, and their development provides an ideal system for studying morphogenesis and cell proliferation dynamics. With fast-advancing microscopy techniques used for live-imaging, whole tissue data are increasingly available, yet present the great challenge of analyzing complex interactions within cell populations. We developed a plugin "Live Plant Cell Tracking" (LiPlaCeT) coupled to the publicly available ImageJ image analysis program and generated a pipeline that allows, with the aid of LiPlaCeT, 4D cell tracking and lineage analysis of populations of dividing and growing cells. The LiPlaCeT plugin contains ad hoc ergonomic curating tools, making it very simple to use for manual cell tracking, especially when the signal-to-noise ratio of images is low or variable in time or 3D space and when automated methods may fail. Performing time-lapse experiments and using cell-tracking data extracted with the assistance of LiPlaCeT, we accomplished deep analyses of cell proliferation and clonal relations in the whole developing LR primordia and constructed genealogical trees. We also used cell-tracking data for endodermis cells of the root apical meristem (RAM) and performed automated analyses of cell population dynamics using ParaView software (also publicly available). Using the RAM as an example, we also showed how LiPlaCeT can be used to generate information at the whole-tissue level regarding cell length, cell position, cell growth rate, cell displacement rate, and proliferation activity. The pipeline will be useful in live-imaging studies of roots and other plant organs to understand complex interactions within proliferating and growing cell populations. The plugin includes a step-by-step user manual and a dataset example that are available at https://www.ibt.unam.mx/documentos/diversos/LiPlaCeT.zip.

Role of calcium oscillations in sperm physiology.

Intracellular Ca2+ is a key regulator of cell signaling and sperm are not the exception. Cells often use cytoplasmic Ca2+ concentration ([Ca2+]i) oscillations as a means to decodify external and internal information. [Ca2+]i oscillations faster than those usually found in other cells and correlated with flagellar beat were the first to be described in sperm in 1993 by Susan Suarez, in the boar. More than 20 years passed before similar [Ca2+]i oscillations were documented in human sperm, simultaneously examining their flagellar beat in three dimensions by Corkidi et al. 2017. On the other hand, 10 years after the discovery of the fast boar [Ca2+]i oscillations, slower ones triggered by compounds from the egg external envelope were found to regulate cell motility and chemotaxis in sperm from marine organisms. Today it is known that sperm display fast and slow spontaneous and agonist triggered [Ca2+]i oscillations. In mammalian sperm these Ca2+ transients may act like a multifaceted tool that regulates fundamental functions such as motility and acrosome reaction. This review covers the main sperm species and experimental conditions where [Ca2+]i oscillations have been described and discusses what is known about the transporters involved, their regulation and the physiological purpose of these oscillations. There is a lot to be learned regarding the origin, regulation and physiological relevance of these Ca2+ oscillations.

Long-term segmentation-free assessment of head-flagellum movement and intracellular calcium in swimming human sperm.

Human spermatozoa are the archetype of long-term self-organizing transport in nature and are critical for reproductive success. They utilize coordinated head and flagellar movements to swim long distances within the female reproductive tract in order to find and fertilize the egg. However, to date, long-term analysis of the sperm head-flagellar movements, or indeed those of other flagellated microorganisms, remains elusive due to limitations in microscopy and flagellar-tracking techniques. Here, we present a novel methodology based on local orientation and isotropy of bio-images to obtain long-term kinematic and physiological parameters of individual free-swimming spermatozoa without requiring image segmentation (thresholding). This computer-assisted segmentation-free method evaluates, for the first time, characteristics of the head movement and flagellar beating for up to 9.2 min. We demonstrate its powerful use by showing how releasing Ca2+ from internal stores significantly alters long-term sperm behavior. The method allows for straightforward generalization to other bio-imaging applications, such as studies of bull sperm and Trypanosoma, or indeed of other flagellated microorganisms - appealing to communities other than those investigating sperm biology.

From one cell to many: Morphogenetic field of lateral root founder cells in Arabidopsis thaliana is built by gradual recruitment.

The reiterative process of lateral root (LR) formation is widespread and underlies root system formation. However, early LR primordium (LRP) morphogenesis is not fully understood. In this study, we conducted both a clonal analysis and time-lapse experiments to decipher the pattern and sequence of pericycle founder cell (FC) participation in LR formation. Most commonly, LRP initiation starts with the specification of just one FC longitudinally. Clonal and anatomical analyses suggested that a single FC gradually recruits neighboring pericycle cells to become FCs. This conclusion was validated by long-term time-lapse live-imaging experiments. Once the first FC starts to divide, its immediate neighbors, both lengthwise and laterally, are recruited within the hour, after which they recruit their neighboring cells within a few hours. Therefore, LRP initiation is a gradual, multistep process. FC recruitment is auxin-dependent and is abolished by treatment with a polar auxin transport inhibitor. Furthermore, FC recruitment establishes a morphogenetic field where laterally peripheral cells have a lower auxin response, which is associated with a lower proliferation potential, compared to centrally located FCs. The lateral boundaries of the morphogenetic field are determined by phloem-adjacent pericycle cells, which are the last cells to be recruited as FCs. The proliferation potential of these cells is limited, but their recruitment is essential for root system formation, resulting in the formation of a new vascular connection between the nascent and parent root, which is crucial for establishing a continuous and efficient vascular system.

Human sperm uses asymmetric and anisotropic flagellar controls to regulate swimming symmetry and cell steering.

Flagellar beating drives sperm through the female reproductive tract and is vital for reproduction. Flagellar waves are generated by thousands of asymmetric molecular components; yet, paradoxically, forward swimming arises via symmetric side-to-side flagellar movement. This led to the preponderance of symmetric flagellar control hypotheses. However, molecular asymmetries must still dictate the flagellum and be manifested in the beat. Here, we reconcile molecular and microscopic observations, reconnecting structure to function, by showing that human sperm uses asymmetric and anisotropic controls to swim. High-speed three-dimensional (3D) microscopy revealed two coactive transversal controls: An asymmetric traveling wave creates a one-sided stroke, and a pulsating standing wave rotates the sperm to move equally on all sides. Symmetry is thus achieved through asymmetry, creating the optical illusion of bilateral symmetry in 2D microscopy. This shows that the sperm flagellum is asymmetrically controlled and anisotropically regularized by fast-signal transduction. This enables the sperm to swim forward.

3-D Human Sperm Flagellum Tracing in Low SNR Fluorescence Images.

Tracing tubular structures from biomedical images is important for a wide range of applications. Particularly, the spermatozoon is an essential cell whose flagella have a tubular form. Its main function is to fertilize the egg, and the flagellum is fundamental to achieve this task which depends importantly on the dynamics of intracellular calcium ([Ca2+]i). Measuring [Ca2+]i along the flagellum in 3-D is not a simple matter since it requires: 1) sophisticated fluorescence imaging techniques dealing with low intensity and signal to noise ratio (SNR) and 2) tracing the flagellum's centerline. Most of the algorithms proposed to trace tubular structures have been developed for multi-branch structures not being adequate for single tubular structures with low SNR. Taking into account the prior knowledge that the flagellum is constituted by a single tubular structure, we propose an automatic method to trace and track multiple single tubular structures from 3-D images. First, an algorithm based on one-class classification allows enhancement of the flagellum. This enhanced 3-D image permits guiding an iterative centerline algorithm toward the flagellum's centerline. Each sperm is assigned an ID to keep track of it in 3-D . Our algorithm was quantitatively evaluated using a ground truth 564 semi-manual traces (six 3-D image stacks) comparing them to those obtained from state-of-the-art tubular structure centerline extraction algorithms. The qualitative and quantitative results show that our algorithm is extracting similar traces as compared with ground truth, and it is more robust and accurate to trace the flagellum's centerline than multi-branch algorithms.

Multi-scale segmentation of neurons based on one-class classification.

BACKGROUND: High resolution multiphoton and confocal microscopy has allowed the acquisition of large amounts of data to be analyzed by neuroscientists. However, manual processing of these images has become infeasible. Thus, there is a need to create automatic methods for the morphological reconstruction of 3D neuronal image stacks. NEW METHOD: An algorithm to extract the 3D morphology from a neuron is presented. The main contribution of the paper is the segmentation of the neuron from the background. Our segmentation method is based on one-class classification where the 3D image stack is analyzed at different scales. First, a multi-scale approach is proposed to compute the Laplacian of the 3D image stack. The Laplacian is used to select a training set consisting of background points. A decision function is learned for each scale from the training set that allows determining how similar an unlabeled point is to the points in the background class. Foreground points (dendrites and axons) are assigned as those points that are rejected as background. Finally, the morphological reconstruction of the neuron is extracted by applying a state-of-the-art centerline tracing algorithm on the segmentation. RESULTS: Quantitative and qualitative results on several datasets demonstrate the ability of our algorithm to accurately and robustly segment and trace neurons. COMPARISON WITH EXISTING METHOD(S): Our method was compared to state-of-the-art neuron tracing algorithms. CONCLUSIONS: Our approach allows segmentation of thin and low contrast dendrites that are usually difficult to segment. Compared to our previous approach, this algorithm is more accurate and much faster.

Automatic Morphological Reconstruction of Neurons from Multiphoton and Confocal Microscopy Images Using 3D Tubular Models.

The challenges faced in analyzing optical imaging data from neurons include a low signal-to-noise ratio of the acquired images and the multiscale nature of the tubular structures that range in size from hundreds of microns to hundreds of nanometers. In this paper, we address these challenges and present a computational framework for an automatic, three-dimensional (3D) morphological reconstruction of live nerve cells. The key aspects of this approach are: (i) detection of neuronal dendrites through learning 3D tubular models, and (ii) skeletonization by a new algorithm using a morphology-guided deformable model for extracting the dendritic centerline. To represent the neuron morphology, we introduce a novel representation, the Minimum Shape-Cost (MSC) Tree that approximates the dendrite centerline with sub-voxel accuracy and demonstrate the uniqueness of such a shape representation as well as its computational efficiency. We present extensive quantitative and qualitative results that demonstrate the accuracy and robustness of our method.