Major impacts of widespread structural variation on sorghum.

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype-phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

Adhesion energy controls lipid binding-mediated endocytosis.

Several bacterial toxins and viruses can deform membranes through multivalent binding to lipids for clathrin-independent endocytosis. However, it remains unclear, how membrane deformation and endocytic internalization are mechanistically linked. Here we show that many lipid-binding virions induce membrane deformation and clathrin-independent endocytosis, suggesting a common mechanism based on multivalent lipid binding by globular particles. We create a synthetic cellular system consisting of a lipid-anchored receptor in the form of GPI-anchored anti-GFP nanobodies and a multivalent globular binder exposing 180 regularly-spaced GFP molecules on its surface. We show that these globular, 40 nm diameter, particles bind to cells expressing the receptor, deform the plasma membrane upon adhesion and become endocytosed in a clathrin-independent manner. We explore the role of the membrane adhesion energy in endocytosis by using receptors with affinities varying over 7 orders of magnitude. Using this system, we find that once a threshold in adhesion energy is overcome to allow for membrane deformation, endocytosis occurs reliably. Multivalent, binding-induced membrane deformation by globular binders is thus sufficient for internalization to occur and we suggest it is the common, purely biophysical mechanism for lipid-binding mediated endocytosis of toxins and pathogens.

Cortical Thickness Patterns of Cognitive Impairment Phenotypes in Drug-Resistant Temporal Lobe Epilepsy.

OBJECTIVE: In temporal lobe epilepsy (TLE), a taxonomy classifying patients into 3 cognitive phenotypes has been adopted: minimally, focally, or multidomain cognitively impaired (CI). We examined gray matter (GM) thickness patterns of cognitive phenotypes in drug-resistant TLE and assessed potential use for predicting postsurgical cognitive outcomes. METHODS: TLE patients undergoing presurgical evaluation were categorized into cognitive phenotypes. Network edge weights and distances were calculated using type III analysis of variance F-statistics from comparisons of GM regions within each TLE cognitive phenotype and age- and sex-matched healthy participants. In resected patients, logistic regression models (LRMs) based on network analysis results were used for prediction of postsurgical cognitive outcome. RESULTS: A total of 124 patients (63 females, mean age ± standard deviation [SD] = 36.0 ± 12.0 years) and 117 healthy controls (63 females, mean age ± SD = 36.1 ± 12.0 years) were analyzed. In the multidomain CI group (n = 66, 53.2%), 28 GM regions were significantly thinner compared to healthy controls. Focally impaired patients (n = 37, 29.8%) showed 13 regions, whereas minimally impaired patients (n = 21, 16.9%) had 2 significantly thinner GM regions. Regions affected in both multidomain and focally impaired patients included the anterior cingulate cortex, medial prefrontal cortex, medial temporal, and lateral temporal regions. In 69 (35 females, mean age ± SD = 33.6 ± 18.0 years) patients who underwent surgery, LRMs based on network-identified GM regions predicted postsurgical verbal memory worsening with a receiver operating curve area under the curve of 0.70 ± 0.15. INTERPRETATION: A differential pattern of GM thickness can be found across different cognitive phenotypes in TLE. Including magnetic resonance imaging with clinical measures associated with cognitive profiles has potential in predicting postsurgical cognitive outcomes in drug-resistant TLE. ANN NEUROL 2024;95:984-997.

RecA levels modulate biofilm development in Acinetobacter baumannii.

Infections caused by Acinetobacter baumannii, a Gram-negative opportunistic pathogen, are difficult to eradicate due to the bacterium's propensity to quickly gain antibiotic resistances and form biofilms, a protective bacterial multicellular community. The A. baumannii DNA damage response (DDR) mediates the antibiotic resistance acquisition and regulates RecA in an atypical fashion; both RecALow and RecAHigh cell types are formed in response to DNA damage. The findings of this study demonstrate that the levels of RecA can influence formation and dispersal of biofilms. RecA loss results in surface attachment and prominent biofilms, while elevated RecA leads to diminished attachment and dispersal. These findings suggest that the challenge to treat A. baumannii infections may be explained by the induction of the DDR, common during infection, as well as the delicate balance between maintaining biofilms in low RecA cells and promoting mutagenesis and dispersal in high RecA cells. This study underscores the importance of understanding the fundamental biology of bacteria to develop more effective treatments for infections.

Analyzing the cellular plasma membrane by fast and efficient correlative STED and platinum replica EM.

The plasma membrane of mammalian cells links transmembrane receptors, various structural components, and membrane-binding proteins to subcellular processes, allowing inter- and intracellular communication. Therefore, membrane-binding proteins, together with structural components such as actin filaments, modulate the cell membrane in their flexibility, stiffness, and curvature. Investigating membrane components and curvature in cells remains challenging due to the diffraction limit in light microscopy. Preparation of 5-15-nm-thin plasma membrane sheets and subsequent inspection by metal replica transmission electron microscopy (TEM) reveal detailed information about the cellular membrane topology, including the structure and curvature. However, electron microscopy cannot identify proteins associated with specific plasma membrane domains. Here, we describe a novel adaptation of correlative super-resolution light microscopy and platinum replica TEM (CLEM-PREM), allowing the analysis of plasma membrane sheets with respect to their structural details, curvature, and associated protein composition. We suggest a number of shortcuts and troubleshooting solutions to contemporary PREM protocols. Thus, implementation of super-resolution stimulated emission depletion (STED) microscopy offers significant reduction in sample preparation time and reduced technical challenges for imaging and analysis. Additionally, highly technical challenges associated with replica preparation and transfer on a TEM grid can be overcome by scanning electron microscopy (SEM) imaging. The combination of STED microscopy and platinum replica SEM or TEM provides the highest spatial resolution of plasma membrane proteins and their underlying membrane and is, therefore, a suitable method to study cellular events like endocytosis, membrane trafficking, or membrane tension adaptations.

Small leucine-rich proteoglycans inhibit CNS regeneration by modifying the structural and mechanical properties of the lesion environment.

Extracellular matrix (ECM) deposition after central nervous system (CNS) injury leads to inhibitory scarring in humans and other mammals, whereas it facilitates axon regeneration in the zebrafish. However, the molecular basis of these different fates is not understood. Here, we identify small leucine-rich proteoglycans (SLRPs) as a contributing factor to regeneration failure in mammals. We demonstrate that the SLRPs chondroadherin, fibromodulin, lumican, and prolargin are enriched in rodent and human but not zebrafish CNS lesions. Targeting SLRPs to the zebrafish injury ECM inhibits axon regeneration and functional recovery. Mechanistically, we find that SLRPs confer mechano-structural properties to the lesion environment that are adverse to axon growth. Our study reveals SLRPs as inhibitory ECM factors that impair axon regeneration by modifying tissue mechanics and structure, and identifies their enrichment as a feature of human brain and spinal cord lesions. These findings imply that SLRPs may be targets for therapeutic strategies to promote CNS regeneration.

Adhesion energy controls lipid binding-mediated endocytosis.

Several bacterial toxins and viruses can deform membranes through multivalent binding to lipids for clathrin-independent endocytosis. However, it remains unclear, how membrane deformation and endocytic internalization are mechanistically linked. Here we show that many lipid-binding virions induce membrane deformation and clathrin-independent endocytosis, suggesting a common mechanism based on multivalent lipid binding by globular particles. We create a synthetic cellular system consisting of a lipid-anchored receptor in the form of GPI-anchored anti-GFP nanobodies and a multivalent globular binder exposing 180 regularly-spaced GFP molecules on its surface. We show that these globular, 40 nm diameter, particles bind to cells expressing the receptor, deform the plasma membrane upon adhesion and become endocytosed in a clathrin-independent manner. We explore the role of the membrane adhesion energy in endocytosis by using receptors with affinities varying over 7 orders of magnitude. Using this system, we find that once a threshold in adhesion energy is overcome to allow for membrane deformation, endocytosis occurs reliably. Multivalent, binding-induced membrane deformation by globular binders is thus sufficient for internalization to occur and we suggest it is the common, purely biophysical mechanism for lipid-binding mediated endocytosis of toxins and pathogens.

Multimodal analysis of granulocytes, monocytes, and platelets in patients with cystic fibrosis before and after Elexacaftor-Tezacaftor-Ivacaftor treatment.

Cystic fibrosis (CF) is a monogenetic disease caused by an impairment of the cystic fibrosis transmembrane conductance regulator (CFTR). CF affects multiple organs and is associated with acute and chronic inflammation. In 2020, Elexacaftor-Tezacaftor-Ivacaftor (ETI) was approved to enhance and restore the remaining CFTR functionality. This study investigates cellular innate immunity, with a focus on neutrophil activation and phenotype, comparing healthy volunteers with patients with CF before (T1, n = 13) and after six months (T2, n = 11) of ETI treatment. ETI treatment reduced sweat chloride (T1: 95 mmol/l (83|108) vs. T2: 32 mmol/l (25|62), p < 0.01, median, first|third quartile) and significantly improved pulmonal function (FEV1 T1: 2.66 l (1.92|3.04) vs. T2: 3.69 l (3.00|4.03), p < 0.01). Moreover, there was a significant decrease in the biomarker human epididymis protein 4 (T1: 6.2 ng/ml (4.6|6.3) vs. T2: 3.0 ng/ml (2.2|3.7), p < 0.01) and a small but significant decrease in matrix metallopeptidase 9 (T1: 45.5 ng/ml (32.5|140.1) vs. T2: 28.2 ng/ml (18.2|33.6), p < 0.05). Neutrophil phenotype (CD10, CD11b, CD62L, and CD66b) and function (radical oxygen species generation, chemotactic and phagocytic activity) remained largely unaffected by ETI treatment. Likewise, monocyte phenotype and markers of platelet activation were similar at T1 and T2. In summary, the present study confirmed a positive impact on patients with CF after ETI treatment. However, neither beneficial nor harmful effects of ETI treatment on cellular innate immunity could be detected, possibly due to the study population consisting of patients with well-controlled CF.

Correction: Spatial and temporal correlations in human cortex are inherently linked and predicted by functional hierarchy, vigilance state as well as antiepileptic drug load.

[This corrects the article DOI: 10.1371/journal.pcbi.1010919.].

Spatial and temporal correlations in human cortex are inherently linked and predicted by functional hierarchy, vigilance state as well as antiepileptic drug load.

The ability of neural circuits to integrate information over time and across different cortical areas is believed an essential ingredient for information processing in the brain. Temporal and spatial correlations in cortex dynamics have independently been shown to capture these integration properties in task-dependent ways. A fundamental question remains if temporal and spatial integration properties are linked and what internal and external factors shape these correlations. Previous research on spatio-temporal correlations has been limited in duration and coverage, thus providing only an incomplete picture of their interdependence and variability. Here, we use long-term invasive EEG data to comprehensively map temporal and spatial correlations according to cortical topography, vigilance state and drug dependence over extended periods of time. We show that temporal and spatial correlations in cortical networks are intimately linked, decline under antiepileptic drug action, and break down during slow-wave sleep. Further, we report temporal correlations in human electrophysiology signals to increase with the functional hierarchy in cortex. Systematic investigation of a neural network model suggests that these dynamical features may arise when dynamics are poised near a critical point. Our results provide mechanistic and functional links between specific measurable changes in the network dynamics relevant for characterizing the brain's changing information processing capabilities.

Prediction of epilepsy surgery outcome using foramen ovale EEG - A machine learning approach.

INTRODUCTION: Patients with drug-resistant focal epilepsy may benefit from ablative or resective surgery. In presurgical work-up, intracranial EEG markers have been shown to be useful in identification of the seizure onset zone and prediction of post-surgical seizure freedom. However, in most cases, implantation of depth or subdural electrodes is performed, exposing patients to increased risks of complications. METHODS: We analysed EEG data recorded from a minimally invasive approach utilizing foramen ovale (FO) and epidural peg electrodes using a supervised machine learning approach to predict post-surgical seizure freedom. Power-spectral EEG features were incorporated in a logistic regression model predicting one-year post-surgical seizure freedom. The prediction model was validated using repeated 5-fold cross-validation and compared to outcome prediction based on clinical and scalp EEG variables. RESULTS: Forty-seven patients (26 patients with post-surgical 1-year seizure freedom) were included in the study, with 31 having FO and 27 patients having peg onset seizures. The area under the receiver-operating curve for post-surgical seizure freedom (Engel 1A) prediction in patients with FO onset seizures was 0.74 ± 0.23 using electrophysiology features, compared to 0.66 ± 0.22 for predictions based on clinical and scalp EEG variables (p < 0.001). The most important features for prediction were spectral power in the gamma and high gamma ranges. EEG data from peg electrodes was not informative in predicting post-surgical outcomes. CONCLUSION: In this hypothesis-generating study, a data-driven approach based on EEG features derived from FO electrodes recordings outperformed the predictive ability based solely on clinical and scalp EEG variables. Pending validation in future studies, this method may provide valuable post-surgical prognostic information while minimizing risks of more invasive diagnostic approaches.

A new hyperelastic lookup table for RT-DC.

Real-time deformability cytometry (RT-DC) is an established method that quantifies features like size, shape, and stiffness for whole cell populations on a single-cell level in real-time. A lookup table (LUT) disentangles the experimentally derived steady-state cell deformation and the projected area to extract the cell stiffness in the form of the Young's modulus. So far, two lookup tables exist but are limited to simple linear material models and cylindrical channel geometries. Here, we present two new lookup tables for RT-DC based on a neo-Hookean hyperelastic material numerically derived by simulations based on the finite element method in square and cylindrical channel geometries. At the same time, we quantify the influence of the shear-thinning behavior of the surrounding medium on the stationary deformation of cells in RT-DC and discuss the applicability and impact of the proposed LUTs regarding past and future RT-DC data analysis. Additionally, we provide insights about the cell strain and stresses, as well as the influence resulting from the rotational symmetric assumption on the cell deformation and volume estimation. The new lookup tables and the numerical cell shapes are made freely available.

Mastering the game of Stratego with model-free multiagent reinforcement learning.

We introduce DeepNash, an autonomous agent that plays the imperfect information game Stratego at a human expert level. Stratego is one of the few iconic board games that artificial intelligence (AI) has not yet mastered. It is a game characterized by a twin challenge: It requires long-term strategic thinking as in chess, but it also requires dealing with imperfect information as in poker. The technique underpinning DeepNash uses a game-theoretic, model-free deep reinforcement learning method, without search, that learns to master Stratego through self-play from scratch. DeepNash beat existing state-of-the-art AI methods in Stratego and achieved a year-to-date (2022) and all-time top-three ranking on the Gravon games platform, competing with human expert players.

Unbiased retrieval of frequency-dependent mechanical properties from noisy time-dependent signals.

The mechanical response of materials to dynamic loading is often quantified by the frequency-dependent complex modulus. Probing materials directly in the frequency domain faces technical challenges such as a limited range of frequencies, long measurement times, or small sample sizes. Furthermore, many biological samples, such as cells or tissues, can change their properties upon repetitive probing at different frequencies. Therefore, it is common practice to extract the material properties by fitting predefined mechanical models to measurements performed in the time domain. This practice, however, precludes the probing of unique and yet unexplored material properties. In this report, we demonstrate that the frequency-dependent complex modulus can be robustly retrieved in a model-independent manner directly from time-dependent stress-strain measurements. While applying a rolling average eliminates random noise and leads to a reliable complex modulus in the lower frequency range, a Fourier transform with a complex frequency helps to recover the material properties at high frequencies. Finally, by properly designing the probing procedure, the recovery of reliable mechanical properties can be extended to an even wider frequency range. Our approach can be used with many state-of-the-art experimental methods to interrogate the mechanical properties of biological and other complex materials.

Effects of salinity and temperature on seawater dissolution rate of initial detonation agent mercury fulminate.

Mercury fulminate (HgFu) was used as an initial detonator for World War I and II munitions. Its presence in previously discarded and dumped munitions could potentially supply mercury pollution into coastal ecosystems where bygone weaponries reside. There is evidence that historical munitions have already contributed mercury pollution in coastal environments, and millions remain embedded in sediments and subjected to further weakening via corrosion under environmental conditions. Experiments were undertaken assessing HgFu dissolution under varying temperature and salinity conditions to constrain controls on mercury release into marine environments. Our results show that HgFu discharge is strongly temperature dependent, with dissolution rate constants increasing from ∼0.4 mg cm-2 d-1 at 5 °C to ∼2.7 mg cm-2 d-1 at 30 °C. No significant differences were observed between freshwater and seawaters up to 36 psu, except at 5 °C. These experiments provide a basis for modeling HgFu release from underwater munitions and its dynamics in coastal environments.

Diagnostic and prognostic value of EEG patterns recorded on foramen ovale and epidural peg electrodes.

OBJECTIVE: To describe and assess the significance of EEG characteristics recorded during presurgical video-EEG monitoring (VEM) utilizing foramen ovale (FO) and epidural peg electrodes. METHODS: Seizure onset (SOP) and termination pattern morphology and regions, ipsilateral and contralateral latencies, seizure duration, and interictal spike counts were examined in 106 patients (412 seizures). An EEG feature-based logistic regression model predicting one-year post-surgical seizure freedom was assessed using a 5-fold nested cross-validation approach. RESULTS: Four SOPs and five termination patterns were identified. Seventy-one percent of patients had a single unique SOP, the most common being sharp activity ≤ 13 Hz (28.9% of seizures). Seizures recorded by FO electrodes were associated with SOPs ≤ 13 Hz (OR 1.9, p = .008). Focal-to-bilateral tonic-clonic seizures were associated with SOPs > 13 Hz (p = .04) and bilateral spike and wave termination (p < .001). In patients with temporal lobe epilepsy, logistic regression based prediction of post-surgical outcome had a mean area under the curve of 0.69, with the most important features being SOP, right sided interictal epileptic activity, and contralateral latency. CONCLUSIONS: FO and peg recordings yield characteristic EEG patterns. SIGNIFICANCE: EEG features of FO and peg recordings may have diagnostic and prognostic utility in presurgical VEM.

A screening-compatible live cell fluorescence resonance energy transfer-based assay for modulation of Rho GTPase activity.

Rho family GTPases are central regulators of cytoskeletal dynamics controlled by guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). This protocol presents a workflow for a robust high-throughput compatible biosensor assay to analyze changes in Rho GTPase activity by these proteins in the native cellular environment. The procedure can be used for semi-quantitative comparison of GEF/GAP function and extended for analysis of additional modulators. The experimental design is applicable also to other monomolecular ratiometric FRET sensors. For complete details on the use and execution of this protocol, please refer to Müller et al. (2020).

From motor control to team play in simulated humanoid football.

Learning to combine control at the level of joint torques with longer-term goal-directed behavior is a long-standing challenge for physically embodied artificial agents. Intelligent behavior in the physical world unfolds across multiple spatial and temporal scales: Although movements are ultimately executed at the level of instantaneous muscle tensions or joint torques, they must be selected to serve goals that are defined on much longer time scales and that often involve complex interactions with the environment and other agents. Recent research has demonstrated the potential of learning-based approaches applied to the respective problems of complex movement, long-term planning, and multiagent coordination. However, their integration traditionally required the design and optimization of independent subsystems and remains challenging. In this work, we tackled the integration of motor control and long-horizon decision-making in the context of simulated humanoid football, which requires agile motor control and multiagent coordination. We optimized teams of agents to play simulated football via reinforcement learning, constraining the solution space to that of plausible movements learned using human motion capture data. They were trained to maximize several environment rewards and to imitate pretrained football-specific skills if doing so led to improved performance. The result is a team of coordinated humanoid football players that exhibit complex behavior at different scales, quantified by a range of analysis and statistics, including those used in real-world sport analytics. Our work constitutes a complete demonstration of learned integrated decision-making at multiple scales in a multiagent setting.

PNIPAAm microgels with defined network architecture as temperature sensors in optical stretchers.

Stretching individual living cells with light is a standard method to assess their mechanical properties. Yet, heat introduced by the laser light of optical stretchers may unwittingly change the mechanical properties of cells therein. To estimate the temperature induced by an optical trap, we introduce cell-sized, elastic poly(N-isopropylacrylamide) (PNIPAAm) microgels that relate temperature changes to hydrogel swelling. For their usage as a standardized calibration tool, we analyze the effect of free-radical chain-growth gelation (FCG) and polymer-analogous photogelation (PAG) on hydrogel network heterogeneity, micromechanics, and temperature response by Brillouin microscopy and optical diffraction tomography. Using a combination of tailor-made PNIPAAm macromers, PAG, and microfluidic processing, we obtain microgels with homogeneous network architecture. With that, we expand the capability of standardized microgels in calibrating and validating cell mechanics analysis, not only considering cell and microgel elasticity but also providing stimuli-responsiveness to consider dynamic changes that cells may undergo during characterization.

In vivo assessment of mechanical properties during axolotl development and regeneration using confocal Brillouin microscopy.

In processes such as development and regeneration, where large cellular and tissue rearrangements occur, cell fate and behaviour are strongly influenced by tissue mechanics. While most well-established tools probing mechanical properties require an invasive sample preparation, confocal Brillouin microscopy captures mechanical parameters optically with high resolution in a contact-free and label-free fashion. In this work, we took advantage of this tool and the transparency of the highly regenerative axolotl to probe its mechanical properties in vivo for the first time. We mapped the Brillouin frequency shift with high resolution in developing limbs and regenerating digits, the most studied structures in the axolotl. We detected a gradual increase in the cartilage Brillouin frequency shift, suggesting decreasing tissue compressibility during both development and regeneration. Moreover, we were able to correlate such an increase with the regeneration stage, which was undetected with fluorescence microscopy imaging. The present work evidences the potential of Brillouin microscopy to unravel the mechanical changes occurring in vivo in axolotls, setting the basis to apply this technique in the growing field of epimorphic regeneration.