Integrated intracellular organization and its variations in human iPS cells.

Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours that they determine1,2. Here we reduced this complexity by focusing on cellular organization-a key readout and driver of cell behaviour3,4-at the level of major cellular structures that represent distinct organelles and functional machines, and generated the WTC-11 hiPSC Single-Cell Image Dataset v1, which contains more than 200,000 live cells in 3D, spanning 25 key cellular structures. The scale and quality of this dataset permitted the creation of a generalizable analysis framework to convert raw image data of cells and their structures into dimensionally reduced, quantitative measurements that can be interpreted by humans, and to facilitate data exploration. This framework embraces the vast cell-to-cell variability that is observed within a normal population, facilitates the integration of cell-by-cell structural data and allows quantitative analyses of distinct, separable aspects of organization within and across different cell populations. We found that the integrated intracellular organization of interphase cells was robust to the wide range of variation in cell shape in the population; that the average locations of some structures became polarized in cells at the edges of colonies while maintaining the 'wiring' of their interactions with other structures; and that, by contrast, changes in the location of structures during early mitotic reorganization were accompanied by changes in their wiring.

Methods for imaging mammalian mitochondrial morphology: A prospective on MitoGraph.

Mitochondria are found in a variety of shapes, from small round punctate structures to a highly interconnected web. This morphological diversity is important for function, but complicates quantification. Consequently, early quantification efforts relied on various qualitative descriptors that understandably reduce the complexity of the network leading to challenges in consistency across the field. Recent application of state-of-the-art computational tools have resulted in more quantitative approaches. This prospective highlights the implementation of MitoGraph, an open-source image analysis platform for measuring mitochondrial morphology initially optimized for use with Saccharomyces cerevisiae. Here Mitograph was assessed on five different mammalian cells types, all of which were accurately segmented by MitoGraph analysis. MitoGraph also successfully differentiated between distinct mitochondrial morphologies that ranged from entirely fragmented to hyper-elongated. General recommendations are also provided for confocal imaging of labeled mitochondria (using mito-YFP, MitoTracker dyes and immunostaining parameters). Widespread adoption of MitoGraph will help achieve a long-sought goal of consistent and reproducible quantification of mitochondrial morphology.

Effects of stereochemistry, saturation, and hydrocarbon chain length on the ability of synthetic constrained azacyclic sphingolipids to trigger nutrient transporter down-regulation, vacuolation, and cell death.

Constrained analogs containing a 2-hydroxymethylpyrrolidine core of the natural sphingolipids sphingosine, sphinganine, N,N-dimethylsphingosine and N-acetyl variants of sphingosine and sphinganine (C2-ceramide and dihydro-C2-ceramide) were synthesized and evaluated for their ability to down-regulate nutrient transporter proteins and trigger cytoplasmic vacuolation in mammalian cells. In cancer cells, the disruptions in intracellular trafficking produced by these sphingolipids lead to cancer cell death by starvation. Structure activity studies were conducted by varying the length of the hydrocarbon chain, the degree of unsaturation and the presence or absence of an aryl moiety on the appended chains, and stereochemistry at two stereogenic centers. In general, cytotoxicity was positively correlated with nutrient transporter down-regulation and vacuolation. This study was intended to identify structural and functional features in lead compounds that best contribute to potency, and to develop chemical biology tools that could be used to isolate the different protein targets responsible for nutrient transporter loss and cytoplasmic vacuolation. A molecule that produces maximal vacuolation and transporter loss is expected to have the maximal anti-cancer activity and would be a lead compound.

Unraveling climatic niche evolution: Insights into the geographical distribution of the neotropical social wasp genus Synoeca (Hymenoptera, Vespidae, Epiponini).

Niche evolution refers to the process by which species undergo changes in ecological interactions, as well as their ability to disperse over time. Our study focuses on the widely distributed neotropical genus of social wasps, Synoeca (Hymenoptera, Vespidae, Epiponini). We use ecological niche modeling to investigate the niche evolution of this insects, to explore how species have evolved within and across distinct environmental boundaries, as well as to explore the overlap, equivalence, and similarity between their niches. Our analysis of Predicted Niche Occupancy reveals that species occupy heterogeneous niches in relation to temperature, precipitation, and altitude, similar to the patterns observed in the analysis of the evolutionary history of climate tolerances, which shows that species have evolved to occupy distinct niche ranges. In addition, our niche comparisons indicate that the species do not share similar niches with each other. All these results suggest that Phylogenetic Niche Conservatism may be playing a significant role as a process contributing to the allopatric pattern observed in this genus. This study represents the first investigation of niche evolution in Vespidae, providing valuable insights for future research into the evolutionary dynamics of insects.

Mitochondrial protein heterogeneity stems from the stochastic nature of co-translational protein targeting in cell senescence.

A decline in mitochondrial function is a hallmark of aging and neurodegenerative diseases. It has been proposed that changes in mitochondrial morphology, including fragmentation of the tubular mitochondrial network, can lead to mitochondrial dysfunction, yet the mechanism of this loss of function is unclear. Most proteins contained within mitochondria are nuclear-encoded and must be properly targeted to the mitochondria. Here, we report that sustained mRNA localization and co-translational protein delivery leads to a heterogeneous protein distribution across fragmented mitochondria. We find that age-induced mitochondrial fragmentation drives a substantial increase in protein expression noise across fragments. Using a translational kinetic and molecular diffusion model, we find that protein expression noise is explained by the nature of stochastic compartmentalization and that co-translational protein delivery is the main contributor to increased heterogeneity. We observed that cells primarily reduce the variability in protein distribution by utilizing mitochondrial fission-fusion processes rather than relying on the mitophagy pathway. Furthermore, we are able to reduce the heterogeneity of the protein distribution by inhibiting co-translational protein targeting. This research lays the framework for a better understanding of the detrimental impact of mitochondrial fragmentation on the physiology of cells in aging and disease.

Interpretable representation learning for 3D multi-piece intracellular structures using point clouds.

A key challenge in understanding subcellular organization is quantifying interpretable measurements of intracellular structures with complex multi-piece morphologies in an objective, robust and generalizable manner. Here we introduce a morphology-appropriate representation learning framework that uses 3D rotation invariant autoencoders and point clouds. This framework is used to learn representations of complex multi-piece morphologies that are independent of orientation, compact, and easy to interpret. We apply our framework to intracellular structures with punctate morphologies (e.g. DNA replication foci) and polymorphic morphologies (e.g. nucleoli). We systematically compare our framework to image-based autoencoders across several intracellular structure datasets, including a synthetic dataset with pre-defined rules of organization. We explore the trade-offs in the performance of different models by performing multi-metric benchmarking across efficiency, generative capability, and representation expressivity metrics. We find that our framework, which embraces the underlying morphology of multi-piece structures, facilitates the unsupervised discovery of sub-clusters for each structure. We show how our approach can also be applied to phenotypic profiling using a dataset of nucleolar images following drug perturbations. We implement and provide all representation learning models using CytoDL, a python package for flexible and configurable deep learning experiments.

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Establishment and Expansion Scenario of Drosophila suzukii (Diptera: Drosophilidae) in Central Brazil.

Drosophila suzukii Matsumura (Diptera: Drosophilidae), also known as spotted wing drosophila (SWD), is an important pest that damages various wild and cultivated soft fruits worldwide, especially in the Northern Hemisphere. In Brazil, it occurs mainly in the subtropical climates of the southern and southeastern regions. However, SWD has also been sporadically found in the central region of the country in the natural vegetation of the tropical Brazilian Savanna. In this study, we investigated the occurrence of SWD at the northern limit of its range in South America - the central region of Brazil - by monitoring an established drosophilid community in an orchard located in the Brazilian Federal District. We also investigated the current geographical distribution of this pest in Brazil and its potential geographical distribution using species distribution models under two different future shared socioeconomic pathways scenarios (2040 and 2060, optimist and pessimist). Twenty drosophilid species were detected among the 6,396 captured specimens, most of which are exotic in the Neotropical region. The fly community greatly fluctuated throughout the year, and the highest abundance of SWD (3.5% relative abundance and 1.38 flies/trap/day) was recorded in April during the rainy season. Potential distribution models indicate that suitable areas for SWD spread will decrease in the south and southeast but increase in the central region of Brazil. We recommend continuous SWD monitoring and improving bioclimatic forecast models for mitigating damage to local fruit production.

Mesoscale molecular assembly is favored by the active, crowded cytoplasm.

The mesoscale organization of molecules into membraneless biomolecular condensates is emerging as a key mechanism of rapid spatiotemporal control in cells1. Principles of biomolecular condensation have been revealed through in vitro reconstitution2. However, intracellular environments are much more complex than test-tube environments: They are viscoelastic, highly crowded at the mesoscale, and are far from thermodynamic equilibrium due to the constant action of energy-consuming processes3. We developed synDrops, a synthetic phase separation system, to study how the cellular environment affects condensate formation. Three key features enable physical analysis: synDrops are inducible, bioorthogonal, and have well-defined geometry. This design allows kinetic analysis of synDrop assembly and facilitates computational simulation of the process. We compared experiments and simulations to determine that macromolecular crowding promotes condensate nucleation but inhibits droplet growth through coalescence. ATP-dependent cellular activities help overcome the frustration of growth. In particular, actomyosin dynamics potentiate droplet growth by reducing confinement and elasticity in the mammalian cytoplasm, thereby enabling synDrop coarsening. Our results demonstrate that mesoscale molecular assembly is favored by the combined effects of crowding and active matter in the cytoplasm. These results move toward a better predictive understanding of condensate formation in vivo.

Benefits of intraoperative music on orthopedic surgeries under spinal anesthesia: A randomized clinical trial.

OBJECTIVE: To determine whether instrumental music influences the anxiety status and intraoperative sedative requirements of a patient DESIGN: A single center, prospective, randomized controlled trial SETTING: Patients between 18 and 65 years, physical status of American Society of Anesthesiologists (ASA I or II) who underwent lower limb orthopedic surgery under spinal anesthesia. INTERVENTIONS: Patients were assigned to one of two groups: (1) Music Group: patients hearing instrumental music through a headset during the entire procedure or (2) No Music Group: patients wearing headphones without music MAIN OUTCOME MEASURES: Before and after the procedure, the anxiety status of the patient was assessed using the State-Trait Anxiety Inventory, and intraoperative sedative drug consumption was quantified. RESULTS: A total of 107 patients were analyzed. A significant reduction in anxiety in the Music Group patients after surgery (p = 0.023) was found. Patients in this group also required less additional medication for intraoperative sedation (p = 0.004), and 88.9% of Music Group patients self-reported that music helped them remain calm during the procedure. Most patients in both groups agreed that music should be used during surgical procedures (98.2% and 94.3% in Music and No Music Groups, respectively) CONCLUSIONS: This study showed that listening to instrumental music during lower limb orthopedic surgery caused a reduction in anxiety and sedative requirements. Patients also self-reported a positive music-related experience.

Cell states beyond transcriptomics: Integrating structural organization and gene expression in hiPSC-derived cardiomyocytes.

Although some cell types may be defined anatomically or by physiological function, a rigorous definition of cell state remains elusive. Here, we develop a quantitative, imaging-based platform for the systematic and automated classification of subcellular organization in single cells. We use this platform to quantify subcellular organization and gene expression in >30,000 individual human induced pluripotent stem cell-derived cardiomyocytes, producing a publicly available dataset that describes the population distributions of local and global sarcomere organization, mRNA abundance, and correlations between these traits. While the mRNA abundance of some phenotypically important genes correlates with subcellular organization (e.g., the beta-myosin heavy chain, MYH7), these two cellular metrics are heterogeneous and often uncorrelated, which suggests that gene expression alone is not sufficient to classify cell states. Instead, we posit that cell state should be defined by observing full distributions of quantitative, multidimensional traits in single cells that also account for space, time, and function.

Mitochondrial Fission and Fusion Dynamics Generate Efficient, Robust, and Evenly Distributed Network Topologies in Budding Yeast Cells.

The simplest configuration of mitochondria in a cell is as small separate organellar units. Instead, mitochondria often form a dynamic, intricately connected network. A basic understanding of the topological properties of mitochondrial networks, and their influence on cell function is lacking. We performed an extensive quantitative analysis of mitochondrial network topology, extracting mitochondrial networks in 3D from live-cell microscopic images of budding yeast cells. In the presence of fission and fusion, mitochondrial network structures exhibited certain topological properties similar to other real-world spatial networks. Fission and fusion dynamics were required to efficiently distribute mitochondria throughout the cell and generate highly interconnected networks that can facilitate efficient diffusive search processes. Thus, mitochondrial fission and fusion combine to regulate the underlying topology of mitochondrial networks, which may independently impact cell function.

Mitochondrial volume fraction and translation duration impact mitochondrial mRNA localization and protein synthesis.

Mitochondria are dynamic organelles that must precisely control their protein composition according to cellular energy demand. Although nuclear-encoded mRNAs can be localized to the mitochondrial surface, the importance of this localization is unclear. As yeast switch to respiratory metabolism, there is an increase in the fraction of the cytoplasm that is mitochondrial. Our data point to this change in mitochondrial volume fraction increasing the localization of certain nuclear-encoded mRNAs to the surface of the mitochondria. We show that mitochondrial mRNA localization is necessary and sufficient to increase protein production to levels required during respiratory growth. Furthermore, we find that ribosome stalling impacts mRNA sensitivity to mitochondrial volume fraction and counterintuitively leads to enhanced protein synthesis by increasing mRNA localization to mitochondria. This points to a mechanism by which cells are able to use translation elongation and the geometric constraints of the cell to fine-tune organelle-specific gene expression through mRNA localization.

Revised criteria for diagnosis of NIFTP reveals a better correlation with tumor biological behavior.

The recent reclassification of a follicular variant of papillary thyroid carcinoma (FVPTC), subset as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), aims to avoid overtreatment of patients with an indolent lesion. The diagnosis of NIFTP has recently been revisited using more rigid criteria. This study presents histological and molecular findings and a long clinical follow-up of 94 FVPTC, 40 cases of follicular adenoma (FTA) and 22 cases of follicular carcinoma (FTC) that were classified before the advent of the NIFTP reclassification. All slides were reviewed using these rigid criteria and analysis of numerous sections of paraffin blocks and reclassified as 7 NIFTPs, 2 EFVPTCs, 29 infiltrative FVPTC (IFVPTCs), 57 invasive EFVPTC (I-EFVPTCs), 39 FTAs and 22 FTCs. Remarkably, EFVPTC and NIFTP patients were all free of disease at the end of follow-up and showed no BRAF mutation. Only one NIFTP sample harbored mutations, an NRAS Q61R. PAX8/PPARG fusion was found in I-EFVPTCs and FTC. Although additional studies are needed to identify a specific molecular profile to aid in the diagnosis of lesions with borderline morphological characteristics, we confirmed that the BRAF V600E mutation is an important tool to exclude the diagnosis of NIFTP. We also show that rigorous histopathological criteria should be strongly followed to avoid missing lesions in which more aggressive behavior is present, mainly via the analysis of capsule or vascular invasion and the presence of papillary structures.

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor proliferation assessment by image analysis only focused on mitosis detection in predefined tumor regions. However, in a real-world scenario, automatic mitosis detection should be performed in whole-slide images (WSIs) and an automatic method should be able to produce a tumor proliferation score given a WSI as input. To address this, we organized the TUmor Proliferation Assessment Challenge 2016 (TUPAC16) on prediction of tumor proliferation scores from WSIs. The challenge dataset consisted of 500 training and 321 testing breast cancer histopathology WSIs. In order to ensure fair and independent evaluation, only the ground truth for the training dataset was provided to the challenge participants. The first task of the challenge was to predict mitotic scores, i.e., to reproduce the manual method of assessing tumor proliferation by a pathologist. The second task was to predict the gene expression based PAM50 proliferation scores from the WSI. The best performing automatic method for the first task achieved a quadratic-weighted Cohen's kappa score of κ = 0.567, 95% CI [0.464, 0.671] between the predicted scores and the ground truth. For the second task, the predictions of the top method had a Spearman's correlation coefficient of r = 0.617, 95% CI [0.581 0.651] with the ground truth. This was the first comparison study that investigated tumor proliferation assessment from WSIs. The achieved results are promising given the difficulty of the tasks and weakly-labeled nature of the ground truth. However, further research is needed to improve the practical utility of image analysis methods for this task.

Three-dimensional description and mathematical characterization of the parasellar internal carotid artery in human infants.

Inside the 'cavernous sinus' or 'parasellar region' the human internal carotid artery takes the shape of a siphon that is twisted and torqued in three dimensions and surrounded by a network of veins. The parasellar section of the internal carotid artery is of broad biological and medical interest, as its peculiar shape is associated with temperature regulation in the brain and correlated with the occurrence of vascular pathologies. The present study aims to provide anatomical descriptions and objective mathematical characterizations of the shape of the parasellar section of the internal carotid artery in human infants and its modifications during ontogeny. Three-dimensional (3D) computer models of the parasellar section of the internal carotid artery of infants were generated with a state-of-the-art 3D reconstruction method and analysed using both traditional morphometric methods and novel mathematical algorithms. We show that four constant, demarcated bends can be described along the infant parasellar section of the internal carotid artery, and we provide measurements of their angles. We further provide calculations of the curvature and torsion energy, and the total complexity of the 3D skeleton of the parasellar section of the internal carotid artery, and compare the complexity of this in infants and adults. Finally, we examine the relationship between shape parameters of the parasellar section of the internal carotid artery in infants, and the occurrence of intima cushions, and evaluate the reliability of subjective angle measurements for characterizing the complexity of the parasellar section of the internal carotid artery in infants. The results can serve as objective reference data for comparative studies and for medical imaging diagnostics. They also form the basis for a new hypothesis that explains the mechanisms responsible for the ontogenetic transformation in the shape of the parasellar section of the internal carotid artery.

Mapping road network communities for guiding disease surveillance and control strategies.

Human mobility is increasing in its volume, speed and reach, leading to the movement and introduction of pathogens through infected travelers. An understanding of how areas are connected, the strength of these connections and how this translates into disease spread is valuable for planning surveillance and designing control and elimination strategies. While analyses have been undertaken to identify and map connectivity in global air, shipping and migration networks, such analyses have yet to be undertaken on the road networks that carry the vast majority of travellers in low and middle income settings. Here we present methods for identifying road connectivity communities, as well as mapping bridge areas between communities and key linkage routes. We apply these to Africa, and show how many highly-connected communities straddle national borders and when integrating malaria prevalence and population data as an example, the communities change, highlighting regions most strongly connected to areas of high burden. The approaches and results presented provide a flexible tool for supporting the design of disease surveillance and control strategies through mapping areas of high connectivity that form coherent units of intervention and key link routes between communities for targeting surveillance.

Author Correction: Mapping road network communities for guiding disease surveillance and control strategies.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Accurate concentration control of mitochondria and nucleoids.

All cellular materials are partitioned between daughters at cell division, but by various mechanisms and with different accuracy. In the yeast Schizosaccharomyces pombe, the mitochondria are pushed to the cell poles by the spindle. We found that mitochondria spatially reequilibrate just before division, and that the mitochondrial volume and DNA-containing nucleoids instead segregate in proportion to the cytoplasm inherited by each daughter. However, nucleoid partitioning errors are suppressed by control at two levels: Mitochondrial volume is actively distributed throughout a cell, and nucleoids are spaced out in semiregular arrays within mitochondria. During the cell cycle, both mitochondria and nucleoids appear to be produced without feedback, creating a net control of fluctuations that is just accurate enough to avoid substantial growth defects.