Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.

Epstein-Barr Virus BGLF2 commandeers RISC to interfere with cellular miRNA function

The Epstein-Barr virus (EBV) BGLF2 protein is a tegument protein with multiple effects on the cellular environment, including induction of SUMOylation of cellular proteins. Using affinity-purification coupled to mass-spectrometry, we identified the miRNA-Induced Silencing Complex (RISC), essential for miRNA function, as a top interactor of BGLF2. We confirmed BGLF2 interaction with the Ago2 and TNRC6 components of RISC in multiple cell lines and their co-localization in cytoplasmic bodies that also contain the stress granule marker G3BP1. In addition, BGLF2 expression led to the loss of processing bodies in multiple cell types, suggesting disruption of RISC function in mRNA regulation. Consistent with this observation, BGLF2 disrupted Ago2 association with multiple miRNAs. Using let-7 miRNAs as a model, we tested the hypothesis that BGLF2 interfered with the function of RISC in miRNA-mediated mRNA silencing. Using multiple reporter constructs with 3’UTRs containing let-7a regulated sites, we showed that BGLF2 inhibited let-7a miRNA activity dependent on these 3’UTRs, including those from SUMO transcripts which are known to be regulated by let-7 miRNAs. In keeping with these results, we showed that BGLF2 increased the cellular level of unconjugated SUMO proteins without affecting the level of SUMO transcripts. Such an increase in free SUMO is known to drive SUMOylation and would account for the effect of BGLF2 in inducing SUMOylation. We further showed that BGLF2 expression inhibited the loading of let-7 miRNAs into Ago2 proteins, and conversely, that lytic infection with EBV lacking BGLF2 resulted in increased interaction of let-7a and SUMO transcripts with Ago2, relative to WT EBV infection. Therefore, we have identified a novel role for BGLF2 as a miRNA regulator and shown that one outcome of this activity is the dysregulation of SUMO transcripts that leads to increased levels of free SUMO proteins and SUMOylation.

Advanced Microfluidic Technologies for Lipid Nano-Microsystems from Synthesis to Biological Application

Microfluidics is an emerging technology that can be employed as a powerful tool for designing lipid nano-microsized structures for biological applications. Those lipid structures can be used as carrying vehicles for a wide range of drugs and genetic materials. Microfluidic technology also allows the design of sustainable processes with less financial demand, while it can be scaled up using parallelization to increase production. From this perspective, this article reviews the recent advances in the synthesis of lipid-based nanostructures through microfluidics (liposomes, lipoplexes, lipid nanoparticles, core-shell nanoparticles, and biomimetic nanovesicles). Besides that, this review describes the recent microfluidic approaches to produce lipid micro-sized structures as giant unilamellar vesicles. New strategies are also described for the controlled release of the lipid payloads using microgels and droplet-based microfluidics. To address the importance of microfluidics for lipid-nanoparticle screening, an overview of how microfluidic systems can be used to mimic the cellular environment is also presented. Future trends and perspectives in designing novel nano and micro scales are also discussed herein.

Nucleus-cytoskeleton communication impacts on OCT4-chromatin interactions in embryonic stem cells

Background The cytoskeleton is a key component of the system responsible for transmitting mechanical cues from the cellular environment to the nucleus, where they trigger downstream responses. This communication is particularly relevant in embryonic stem (ES) cells since forces can regulate cell fate and guide developmental processes. However, little is known regarding cytoskeleton organization in ES cells, and thus, relevant aspects of nuclear-cytoskeletal interactions remain elusive. Results We explored the three-dimensional distribution of the cytoskeleton in live ES cells and show that these filaments affect the shape of the nucleus. Next, we evaluated if cytoskeletal components indirectly modulate the binding of the pluripotency transcription factor OCT4 to chromatin targets. We show that actin depolymerization triggers OCT4 binding to chromatin sites whereas vimentin disruption produces the opposite effect. In contrast to actin, vimentin contributes to the preservation of OCT4-chromatin interactions and, consequently, may have a pro-stemness role. Conclusions Our results suggest roles of components of the cytoskeleton in shaping the nucleus of ES cells, influencing the interactions of the transcription factor OCT4 with the chromatin and potentially affecting pluripotency and cell fate.

A Road towards 6G Communication—A Review of 5G Antennas, Arrays, and Wearable Devices

Next-generation communication systems and wearable technologies aim to achieve high data rates, low energy consumption, and massive connections because of the extensive increase in the number of Internet-of-Things (IoT) and wearable devices. These devices will be employed for many services such as cellular, environment monitoring, telemedicine, biomedical, and smart traffic, etc. Therefore, it is challenging for the current communication devices to accommodate such a high number of services. This article summarizes the motivation and potential of the 6G communication system and discusses its key features. Afterward, the current state-of-the-art of 5G antenna technology, which includes existing 5G antennas and arrays and 5G wearable antennas, are summarized. The article also described the useful methods and techniques of exiting antenna design works that could mitigate the challenges and concerns of the emerging 5G and 6G applications. The key features and requirements of the wearable antennas for next-generation technology are also presented at the end of the paper.

Unraveling membrane properties at the organelle-level with LipidDyn

Cellular membranes are formed from many different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and their alterations are linked to several diseases, including cancer. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins, profoundly impacting each other. Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and at varying levels of resolution. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. The community needs computational tools for lipidomics and simulation data effectively interacting to better understand how changes in lipid compositions impact membrane function and structure. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data to understand how membrane properties and membrane-protein interactions are changing in the different conditions. In this context, we developed LipidDyn, an in silico pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, diffusion motions, the density of lipid bilayers, and lipid enrichment/depletion. The calculations exploit parallelization and the pipelines include graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is implemented in Python and relies on open-source libraries. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.

A systematic characterization of intrinsically formed microglia-like cells during retinal organoid differentiation.

Brain organoids differentiated from human induced pluripotent stem cells provide a unique opportunity to investigate the development, organization and connectivity of neurons in a complex cellular environment. However, organoids usually lack microglia, brain-resident immune cells which are both present in the early human embryonic brain and participate in neuronal circuit development. Here, we find that microglia innately develop in unguided retinal organoid differentiation between week 3 and 4 in 2.5D culture and appear later in floating, non-pigmented, 3D-cystic compartments. We enriched for cystic structures using a low-dosed BMP4 application and performed mass spectrometry, thus defining the protein composition of microglia-containing compartments. We found that cystic compartments expressed both mesenchymal and epithelial markers with microglia enriched in the mesenchymal region. Interestingly, microglia-like cells started to express the border-associated macrophage marker CD163. The preferential localization of human microglia to a mesenchymal compartment provides insight into the behavior and migration of microglia. The model will ultimately allow detailed study of these enigmatic cells and how they enter and distribute within the human brain.

The Effect of Aerobic Exercise on Deteriorating VO2max and Diminished Mitochondrial Biogenesis During Aging

Aging seems to be inevitable and gradual loss of physical activity is associated with frailty and many age-related disorders. Exercise is the way of keeping a healthy life and delaying aging process. Deterioration in pulmonary vital capacity is inevitable, and mitochondrial biogenesis also diminishes with aging. Regular aerobic exercise alleviates the diminishing vital capacity while increasing mitochondrial biogenesis in aging. Peroxisome proliferator-activated receptor c coactivator 1 alpha (PGC-1a), which is the master regulator of mitochondrial biogenesis, is activated by reactive oxygen species (ROS). Exercise-induced lactate leads to formation of ROS and synthesis of nitric oxide (NO) at physiological level. PGC1a regulation by NO seems to be controversial. Over the physiological limit of ROS and NO has toxic effects in cellular environment with reduced antioxidant activities in aging. Overall, exercise seems to be beneficial option to alleviate reduction rate of vital capacity and to enhance mitochondrial biogenesis via lactate-induced ROS formation. Keywords: Aging, Exercise, Maximum oxygen consumption rate, Lungs vital capacity, Mitochondria Biogenesis.

Impact of Alcohol Consumption on Male Fertility Potential: A Narrative Review

Alcohol abuse disorder is a serious condition, implicating more than 15 million people aged 12 years and older in 2019 in the United States. Ethanol (or ethyl alcohol) is mainly oxidized in the liver, resulting in the synthesis of acetaldehyde and acetate, which are toxic and carcinogenic metabolites, as well as in the generation of a reductive cellular environment. Moreover, ethanol can interact with lipids, generating fatty acid ethyl esters and phosphatidylethanol, which interfere with physiological cellular pathways. This narrative review summarizes the impact of excessive alcohol consumption on male fertility by describing its metabolism and how ethanol consumption may induce cellular damage. Furthermore, the impact of alcohol consumption on hormonal regulation, semen quality, and genetic and epigenetic regulations is discussed based on evidence from animal and human studies, focusing on the consequences on the offspring. Finally, the limitations of the current evidence are discussed. Our review highlights the association between chronic alcohol consumption and poor semen quality, mainly due to the development of oxidative stress, as well as its genotoxic impact on hormonal regulation and DNA integrity, affecting the offspring’s health. New landscapes of investigation are proposed for the identification of molecular markers for alcohol-associated infertility, with a focus on advanced OMICS-based approaches applied to the analysis of semen samples.

SpaceX: Gene Co-expression Network Estimation for Spatial Transcriptomics

Motivation: The analysis of spatially-resolved transcriptome enables the understanding of the spatial interactions between the cellular environment and transcriptional regulation. In particular, the characterization of the gene-gene co-expression at distinct spatial locations or cell types in the tissue enables delineation of spatial co-regulatory patterns as opposed to standard differential single gene analyses. To enhance the ability and potential of spatial transcriptomics technologies to drive biological discovery, we develop a statistical framework to detect gene co-expression patterns in a spatially structured tissue consisting of different clusters in the form of cell classes or tissue domains. Results: We develop SpaceX (spatially dependent gene co-expression network), a Bayesian methodology to identify both shared and cluster-specific co-expression network across genes. SpaceX uses an over-dispersed spatial Poisson model coupled with a high-dimensional factor model which is based on a dimension reduction technique for computational efficiency. We show via simulations, accuracy gains in co-expression network estimation and structure by accounting for (increasing) spatial correlation and appropriate noise distributions. In-depth analysis of two spatial transcriptomics datasets in mouse hypothalamus and human breast cancer using SpaceX, detected multiple hub genes which are related to cognitive abilities for the hypothalamus data and multiple cancer genes (e.g. collagen family) from the tumor region for the breast cancer data.