PARP1 expression predicts PARP inhibitor sensitivity and correlates with metastatic potential and overall survival in melanoma

Metastatic melanoma is still a difficult-to-treat cancer type owing to its frequent resistance mechanisms to targeted and immunotherapy. Therefore, we aimed to unravel novel therapeutic strategies for melanoma patients. Preclinical and clinical studies show that melanoma patients may benefit from a treatment with poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi). In this study, we focus on PARP1 as a potential biomarker to predict the response of melanoma cells to PARPi therapy. We found that melanoma cells with high basal PARP1 expression exhibit significantly increased cell death after PARPi treatment owing to higher PARP1 trapping compared with melanoma cells with low PARP1 expression. In addition, we could demonstrate that PARP1 expression levels are low in nonmalignant skin cells, and metastatic melanomas show considerably higher PARP1 levels compared with primary melanomas. Most strikingly, we found that high PARP1 levels correlate with worse overall survival of late stage metastasized melanoma patients. In conclusion, we show that PARP1 might act as a biomarker to predict the response to PARPi therapy, and that in particular the late stage metastasized melanoma patients are especially sensitive to PARPi therapy owing to elevated PARP1 expression. Our data suggest that the PARPi cytotoxicity primarily will affect the high PARP1 expressing melanoma cells, rather than the low PARP1 expressing nonmalignant skin cells resulting in only low side effects.

Infrared spectroscopy across scales in length and time at BESSY II

The infrared beamline at BESSY II storage ring was upgraded recently to extend the capabilities of infrared microscopy. The endstations available at the beamline are now facilitating improved characterization of molecules and materials at different length scales and time resolutions. Here, the current outline of the beamline is reported and an overview of the endstations available is given. In particular, the first results obtained by using a new microscope for nano-spectroscopy that was implemented are presented. The capabilities of the scattering-type near-field optical microscope (s-SNOM) are demonstrated by investigating cellulose microfibrils, representing nanoscopic objects of a hierarchical structure. It is shown that the s-SNOM coupled to the beamline allows imaging to be performed with a spatial resolution of less than 30 nm and infrared spectra to be collected from an effective volume of less than 30 nm × 30 nm × 12 nm. Potential steps for further optimization of the beamline performance are discussed.

Photoswitchable Endocytosis of Biomolecular Condensates in Giant Vesicles

Interactions between membranes and biomolecular condensates can give rise to complex phenomena such as wetting transitions, mutual remodeling, and endocytosis. In this study, light-triggered manipulation of condensate engulfment is demonstrated using giant vesicles containing photoswitchable lipids. UV irradiation increases the membrane area, which can be stored in nanotubes. When in contact with a condensate droplet, the UV light triggers rapid condensate endocytosis, which can be reverted by blue light. The affinity of the protein-rich condensates to the membrane and the reversibility of the engulfment processes is quantified from confocal microscopy images. The degree of photo-induced engulfment, whether partial or complete, depends on the vesicle excess area and the relative sizes of vesicles and condensates. Theoretical estimates suggest that utilizing the light-induced excess area to increase the vesicle-condensate adhesion interface is energetically more favorable than the energy gain from folding the membrane into invaginations and tubes. The overall findings demonstrate that membrane-condensate interactions can be easily and quickly modulated via light, providing a versatile system for building platforms to control cellular events and design intelligent drug delivery systems for cell repair.

Prebiotic Vitamin B3 Synthesis in Carbonaceous Planetesimals

Aqueous chemistry within carbonaceous planetesimals is promising for synthesizing prebiotic organic matter essential to all life. Meteorites derived from these planetesimals delivered these life building blocks to the early Earth, potentially facilitating the origins of life. Here, we studied the formation of vitamin B3 as it is an important precursor of the coenzyme NAD(P)(H), which is essential for the metabolism of all life as we know it. We propose a new reaction mechanism based on known experiments in the literature that explains the synthesis of vitamin B3. It combines the sugar precursors glyceraldehyde or dihydroxyacetone with the amino acids aspartic acid or asparagine in aqueous solution without oxygen or other oxidizing agents. We performed thermochemical equilibrium calculations to test the thermodynamic favorability. The predicted vitamin B3 abundances resulting from this new pathway were compared with measured values in asteroids and meteorites. We conclude that competition for reactants and decomposition by hydrolysis are necessary to explain the prebiotic content of meteorites. In sum, our model fits well into the complex network of chemical pathways active in this environment.

Towards understanding the crystallization of photosystem II: influence of poly(ethylene glycol) of various molecular sizes on the micelle formation of alkyl maltosides

The influence of poly(ethylene glycol) (PEG) polymers H-(O-CH2-CH2)p-OH with different average molecular sizes p on the micelle formation of n-alkyl-β-D-maltoside detergents with the number of carbon atoms in the alkyl chain ranging from 10 to 12 is investigated with the aim to learn more about the detergent behavior under conditions suitable for the crystallization of the photosynthetic pigment-protein complex photosystem II. PEG is shown to increase the critical micelle concentration (CMC) of all three detergents in the crystallization buffer in a way that the free energy of micelle formation increases linearly with the concentration of oxyethylene units (O-CH2-CH2) irrespective of the actual molecular weight of the polymer. The CMC shift is modeled by assuming for simplicity that it is dominated by the interaction between PEG and detergent monomers and is interpreted in terms of an increase of the transfer free energy of a methylene group of the alkyl chain by 0.2 kJ mol-1 per 1 mol L-1 increase of the concentration of oxyethylene units at 298 K. Implications of this effect for the solubilization and crystallization of protein-detergent complexes as well as detergent extraction from crystals are discussed.

Nuclear actin dynamics and functions at a glance

Actin is well known for its cytoskeletal functions, where it helps to control and maintain cell shape and architecture, as well as regulating cell migration and intracellular cargo transport, among others. However, actin is also prevalent in the nucleus, where genome-regulating roles have been described, including it being part of chromatin-remodeling complexes. More recently, with the help of advances in microscopy techniques and specialized imaging probes, direct visualization of nuclear actin filament dynamics has helped elucidate new roles for nuclear actin, such as in cell cycle regulation, DNA replication and repair, chromatin organization and transcriptional condensate formation. In this Cell Science at a Glance article, we summarize the known signaling events driving the dynamic assembly of actin into filaments of various structures within the nuclear compartment for essential genome functions. Additionally, we highlight the physiological role of nuclear F-actin in meiosis and early embryonic development.

The role of metabolomics in informing strategies for improving photosynthesis

Photosynthesis plays a vital role in acclimating to and mitigating climate change, providing food and energy security for a population that is constantly growing, and achieving an economy with zero carbon emissions. A thorough comprehension of the dynamics of photosynthesis, including its molecular regulatory network and limitations, is essential for utilizing it as a tool to boost plant growth, enhance crop yields, and support the production of plant biomass for carbon storage. Photorespiration constrains photosynthetic efficiency and contributes significantly to carbon loss. Therefore, modulating or circumventing photorespiration presents opportunities to enhance photosynthetic efficiency. Over the past eight decades, substantial progress has been made in elucidating the molecular basis of photosynthesis, photorespiration, and the key regulatory mechanisms involved, beginning with the discovery of the canonical Calvin-Benson-Bassham cycle. Advanced chromatographic and mass spectrometric technologies have allowed a comprehensive analysis of the metabolite patterns associated with photosynthesis, contributing to a deeper understanding of its regulation. In this review, we summarize the results of metabolomics studies that shed light on the molecular intricacies of photosynthetic metabolism. We also discuss the methodological requirements essential for effective analysis of photosynthetic metabolism, highlighting the value of this technology in supporting strategies aimed at enhancing photosynthesis.

Intermetallic Cobalt Indium Nanoparticles as Oxygen Evolution Reaction Precatalyst: A Non-Leaching p-Block Element

Merely all transition-metal-based materials reconstruct into similar oxyhydroxides during the electrocatalytic oxygen evolution reaction (OER), severely limiting the options for a tailored OER catalyst design. In such reconstructions, initial constituent p-block elements take a sacrificial role and leach into the electrolyte as oxyanions, thereby losing the ability to tune the catalyst's properties systematically. From a thermodynamic point of view, indium is expected to behave differently and should remain in the solid phase under alkaline OER conditions. However, the structural behavior of transition metal indium phases during the OER remains unexplored. Herein, are synthesized intermetallic cobalt indium (CoIn3 ) nanoparticles and revealed by in situ X-ray absorption spectroscopy and scanning transmission microscopy that they undergo phase segregation to cobalt oxyhydroxide and indium hydroxide. The obtained cobalt oxyhydroxide outperforms a metallic-cobalt-derived one due to more accessible active sites. The observed phase segregation shows that indium behaves distinctively differently from most p-block elements and remains at the electrode surface, where it can form lasting interfaces with the active metal oxo phases.

A Dynamic Water Channel Affects O2 Stability in [FeFe]-Hydrogenases

[FeFe]-hydrogenases are capable of reducing protons at a high rate. However, molecular oxygen (O2 ) induces the degradation of their catalytic cofactor, the H-cluster, which consists of a cubane [4Fe4S] subcluster (4FeH ) and a unique diiron moiety (2FeH ). Previous attempts to prevent O2 -induced damage have focused on enhancing the protein's sieving effect for O2 by blocking the hydrophobic gas channels that connect the protein surface and the 2FeH . In this study, we aimed to block an O2 diffusion pathway and shield 4FeH instead. Molecular dynamics (MD) simulations identified a novel water channel (WH ) surrounding the H-cluster. As this hydrophilic path may be accessible for O2 molecules we applied site-directed mutagenesis targeting amino acids along WH in proximity to 4FeH to block O2 diffusion. Protein film electrochemistry experiments demonstrate increased O2 stabilities for variants G302S and S357T, and MD simulations based on high-resolution crystal structures confirmed an enhanced local sieving effect for O2 in the environment of the 4FeH in both cases. The results strongly suggest that, in wild type proteins, O2 diffuses from the 4FeH to the 2FeH . These results reveal new strategies for improving the O2 stability of [FeFe]-hydrogenases by focusing on the O2 diffusion network near the active site.

Interrogating two extensively self-targeting Type I CRISPR-Cas systems in Xanthomonas albilineans reveals distinct anti-CRISPR proteins that block DNA degradation

CRISPR-Cas systems store fragments of invader DNA as spacers to recognize and clear those same invaders in the future. Spacers can also be acquired from the host's genomic DNA, leading to lethal self-targeting. While self-targeting can be circumvented through different mechanisms, natural examples remain poorly explored. Here, we investigate extensive self-targeting by two CRISPR-Cas systems encoding 24 self-targeting spacers in the plant pathogen Xanthomonas albilineans. We show that the native I-C and I-F1 systems are actively expressed and that CRISPR RNAs are properly processed. When expressed in Escherichia coli, each Cascade complex binds its PAM-flanked DNA target to block transcription, while the addition of Cas3 paired with genome targeting induces cell killing. While exploring how X. albilineans survives self-targeting, we predicted putative anti-CRISPR proteins (Acrs) encoded within the bacterium's genome. Screening of identified candidates with cell-free transcription-translation systems and in E. coli revealed two Acrs, which we named AcrIC11 and AcrIF12Xal, that inhibit the activity of Cas3 but not Cascade of the respective system. While AcrF12Xal is homologous to AcrIF12, AcrIC11 shares sequence and structural homology with the anti-restriction protein KlcA. These findings help explain tolerance of self-targeting through two CRISPR-Cas systems and expand the known suite of DNA degradation-inhibiting Acrs.

Eating After Acute Psychosocial Stress in Healthy Men and Women: Sex Differences and Endocrine Mechanisms

CONTEXT

Overweight and obesity have become a major health burden with a higher prevalence of obesity in women than in men. Mental stress has been discussed to play a role in this context.

OBJECTIVE

We investigated endocrine mechanisms underlying eating after acute psychosocial stress and potential sex differences therein.

METHODS

A total of 32 male and 31 female healthy participants underwent the Trier Social Stress Test before they tasted ice cream in a bogus taste test 15 minutes after stress. We repeatedly assessed the stress hormone cortisol and the satiety hormone cholecystokinin (CCK) in saliva as well as perceived hunger before and up to 1 hour after stress.

RESULTS

Lower immediate total cortisol stress reactivity predicted higher hunger (Ps ≤ .004), but was not associated with food intake (Ps ≥ .90) or total CCK release (Ps ≥ .84). As compared to men, women ate less after stress (Ps < .001) and had consistently lower levels of hunger (Ps ≤ .024) and cortisol (Ps ≤ .008) as well as a lower immediate total cortisol stress reactivity (Ps = .002). Further, they differed in the kinetics of CCK over the total experimental procedure (Ps ≤ .011), in immediate reaction to stress (Ps ≤ .038), and after eating (Ps ≤ .072), with women's CCK levels continuously decreasing while men's CCK levels were reactive.

CONCLUSION

We found evidence for lower immediate total cortisol stress reactivity relating to higher perceived hunger, with lower cortisol levels in women. Unlike in men, CCK levels in women were not reactive to acute stress and eating and decreased continuously. Our results may suggest a higher risk for stress-induced eating in women.

Alpha/beta oscillations reveal cognitive and affective brain states associated with role taking in a dyadic cooperative game

Social cooperation often requires taking different roles in order to reach a shared goal. By defining individual tasks, these roles dictate processing demands of the collaborators. The main aim of the present study was to examine the hypothesis that induced alpha and lower beta oscillations provide insights into affective and cognitive brain states during social cooperation. Toward this end, an experimental game was used in which participants had to navigate a Pacman figure through a maze by sending and receiving information about the correct moving direction. Supporting our hypotheses, individual roles taken by the collaborators during gameplay were associated with significant changes in alpha and lower beta power. Furthermore, effects were similar when participants played the Pacman Game with human or computer partners. Findings are discussed from the perspective of the information-via-desynchronization hypothesis proposing that alpha and lower beta power decreases reflect states of enhanced cortical information representation. Overall, experimental games are a useful tool for extending basic research on brain oscillations to the domain of naturalistic social interaction as emphasized by the second-person neuroscience perspective.

Aggregation and beyond: alpha-synuclein-based biomarkers in synucleinopathies

Parkinson's disease is clinically known for the loss of dopaminergic neurons in the substantia nigra pars compacta and accumulation of intraneuronal cytoplasmic inclusions rich in alpha-synuclein called 'Lewy bodies' and 'Lewy neurites'. Together with dementia with Lewy bodies and multiple system atrophy, Parkinson's disease is part of a group of disorders called synucleinopathies. Currently, diagnosis of synucleinopathies is based on the clinical assessment which often takes place in advanced disease stages. While the causal role of alpha-synuclein aggregates in these disorders is still debatable, measuring the levels, types or seeding properties of different alpha-synuclein species hold great promise as biomarkers. Recent studies indicate significant differences in peptide, protein and RNA levels in blood samples from patients with Parkinson's disease. Seed amplification assays using CSF, blood, skin biopsy, olfactory swab samples show great promise for detecting synucleinopathies and even for discriminating between different synucleinopathies. Interestingly, small extracellular vesicles, such as exosomes, display differences in their cargoes in Parkinson's disease patients versus controls. In this update, we focus on alpha-synuclein aggregation and possible sources of disease-related species released in extracellular vesicles, which promise to revolutionize the diagnosis and the monitoring of disease progression.

Brassicaceae display variation in efficiency of photorespiratory carbon-recapturing mechanisms

Carbon-concentrating mechanisms enhance the carboxylase efficiency of Rubisco by providing supra-atmospheric concentrations of CO2 in its surroundings. Beside the C4 photosynthesis pathway, carbon concentration can also be achieved by the photorespiratory glycine shuttle which requires fewer and less complex modifications. Plants displaying CO2 compensation points between 10 ppm and 40 ppm are often considered to utilize such a photorespiratory shuttle and are termed 'C3-C4 intermediates'. In the present study, we perform a physiological, biochemical, and anatomical survey of a large number of Brassicaceae species to better understand the C3-C4 intermediate phenotype, including its basic components and its plasticity. Our phylogenetic analysis suggested that C3-C4 metabolism evolved up to five times independently in the Brassicaceae. The efficiency of the pathway showed considerable variation. Centripetal accumulation of organelles in the bundle sheath was consistently observed in all C3-C4-classified taxa, indicating a crucial role for anatomical features in CO2-concentrating pathways. Leaf metabolite patterns were strongly influenced by the individual species, but accumulation of photorespiratory shuttle metabolites glycine and serine was generally observed. Analysis of phosphoenolpyruvate carboxylase activities suggested that C4-like shuttles have not evolved in the investigated Brassicaceae. Convergent evolution of the photorespiratory shuttle indicates that it represents a distinct photosynthesis type that is beneficial in some environments.

pyPESTO: a modular and scalable tool for parameter estimation for dynamic models

SUMMARY

Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. pyPESTO is a modular framework for systematic parameter estimation, with scalable algorithms for optimization and uncertainty quantification. While tailored to ordinary differential equation problems, pyPESTO is broadly applicable to black-box parameter estimation problems. Besides own implementations, it provides a unified interface to various popular simulation and inference methods.

AVAILABILITY AND IMPLEMENTATION

pyPESTO is implemented in Python, open-source under a 3-Clause BSD license. Code and documentation are available on GitHub (https://github.com/icb-dcm/pypesto).

Photomanipulation of Minimal Synthetic Cells: Area Increase, Softening, and Interleaflet Coupling of Membrane Models Doped with Azobenzene-Lipid Photoswitches

Light can effectively interrogate biological systems in a reversible and physiologically compatible manner with high spatiotemporal precision. Understanding the biophysics of photo-induced processes in bio-systems is crucial for achieving relevant clinical applications. Employing membranes doped with the photolipid azobenzene-phosphatidylcholine (azo-PC), a holistic picture of light-triggered changes in membrane kinetics, morphology, and material properties obtained from correlative studies on cell-sized vesicles, Langmuir monolayers, supported lipid bilayers, and molecular dynamics simulations is provided. Light-induced membrane area increases as high as ≈25% and a ten-fold decrease in the membrane bending rigidity is observed upon trans-to-cis azo-PC isomerization associated with membrane leaflet coupling and molecular curvature changes. Vesicle electrodeformation measurements and atomic force microscopy reveal that trans azo-PC bilayers are thicker than palmitoyl-oleoyl phosphatidylcholine (POPC) bilayers but have higher specific membrane capacitance and dielectric constant suggesting an increased ability to store electric charges across the membrane. Lastly, incubating POPC vesicles with azo-PC solutions results in the insertion of azo-PC in the membrane enabling them to become photoresponsive. All these results demonstrate that light can be used to finely manipulate the shape, mechanical and electric properties of photolipid-doped minimal cell models, and liposomal drug carriers, thus, presenting a promising therapeutic alternative for the repair of cellular disorders.

FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes

MOTIVATION

Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyse and understand the processes determining tissue dynamics. These models usually depend on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as approximate Bayesian computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes.

RESULTS

Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology.

AVAILABILITY AND IMPLEMENTATION

FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit.

PYRIDOX(AM)INE 5'-PHOSPHATE OXIDASE3 of Arabidopsis thaliana maintains carbon/nitrogen balance in distinct environmental conditions

The identification of factors that regulate C/N utilization in plants can make a substantial contribution to optimization of plant health. Here, we explored the contribution of pyridox(am)ine 5'-phosphate oxidase3 (PDX3), which regulates vitamin B6 homeostasis, in Arabidopsis (Arabidopsis thaliana). Firstly, N fertilization regimes showed that ammonium application rescues the leaf morphological phenotype of pdx3 mutant lines but masks the metabolite perturbance resulting from impairment in utilizing soil nitrate as a source of N. Without fertilization, pdx3 lines suffered a C/N imbalance and accumulated nitrogenous compounds. Surprisingly, exploration of photorespiration as a source of endogenous N driving this metabolic imbalance, by incubation under high CO2, further exacerbated the pdx3 growth phenotype. Interestingly, the amino acid serine, critical for growth and N management, alleviated the growth phenotype of pdx3 plants under high CO2, likely due to the requirement of pyridoxal 5'-phosphate for the phosphorylated pathway of serine biosynthesis under this condition. Triggering of thermomorphogenesis by growth of plants at 28 °C (instead of 22 °C) did not appear to require PDX3 function, and we observed that the consequent drive toward C metabolism counters the C/N imbalance in pdx3. Further, pdx3 lines suffered a salicylic acid-induced defense response, probing of which unraveled that it is a protective strategy mediated by nonexpressor of pathogenesis related1 (NPR1) and improves fitness. Overall, the study demonstrates the importance of vitamin B6 homeostasis as managed by the salvage pathway enzyme PDX3 to growth in diverse environments with varying nutrient availability and insight into how plants reprogram their metabolism under such conditions.

Electrochemical Aldehyde Oxidation at Gold Electrodes: gem-Diol, non-Hydrated Aldehyde, and Diolate as Electroactive Species

To date the electroactive species of selective aldehyde oxidation to carboxylates at gold electrodes is usually assumed to be the diolate. It forms with high concentration only in very alkaline electrolytes, when OH- binds to the carbonyl carbon atom. Accordingly, the electrochemical upgrading of biomass-derived aldehydes to carboxylates is believed to be limited to very alkaline electrolytes at many electrode materials. However, OH- -induced aldehyde decomposition in these electrolytes prevents application of electrochemical aldehyde oxidation for the sustainable upgrading of biomass to value-added chemicals at industrial scale. Here, we demonstrate the successful oxidation of aliphatic aldehydes at a rotating gold electrode at pH 12, where only 1 % of the aldehyde resides as the diolate species. This concentration is too small to account for the observed current, which shows that also other aldehyde species (i. e., the geminal diol and the non-hydrated aldehyde) are electroactive. This insight allows developing strategies to omit aldehyde decomposition while achieving high current densities for the selective aldehyde oxidation, making its future industrial application viable.

Genetic factors inherited from both diploid parents interact to affect genome stability and fertility in resynthesized allotetraploid Brassica napus

Established allopolyploids are known to be genomically stable and fertile. However, in contrast, most newly resynthesized allopolyploids are infertile and meiotically unstable. Identifying the genetic factors responsible for genome stability in newly formed allopolyploid is key to understanding how 2 genomes come together to form a species. One hypothesis is that established allopolyploids may have inherited specific alleles from their diploid progenitors which conferred meiotic stability. Resynthesized Brassica napus lines are often unstable and infertile, unlike B. napus cultivars. We tested this hypothesis by characterizing 41 resynthesized B. napus lines produced by crosses between 8 Brassica rapa and 8 Brassica oleracea lines for copy number variation resulting from nonhomologous recombination events and fertility. We resequenced 8 B. rapa and 5 B. oleracea parent accessions and analyzed 19 resynthesized lines for allelic variation in a list of meiosis gene homologs. SNP genotyping was performed using the Illumina Infinium Brassica 60K array for 3 individuals per line. Self-pollinated seed set and genome stability (number of copy number variants) were significantly affected by the interaction between both B. rapa and B. oleracea parental genotypes. We identified 13 putative meiosis gene candidates which were significantly associated with frequency of copy number variants and which contained putatively harmful mutations in meiosis gene haplotypes for further investigation. Our results support the hypothesis that allelic variants inherited from parental genotypes affect genome stability and fertility in resynthesized rapeseed.

The impossible challenge of estimating non-existent moments of the Chemical Master Equation

MOTIVATION

The Chemical Master Equation (CME) is a set of linear differential equations that describes the evolution of the probability distribution on all possible configurations of a (bio-)chemical reaction system. Since the number of configurations and therefore the dimension of the CME rapidly increases with the number of molecules, its applicability is restricted to small systems. A widely applied remedy for this challenge is moment-based approaches which consider the evolution of the first few moments of the distribution as summary statistics for the complete distribution. Here, we investigate the performance of two moment-estimation methods for reaction systems whose equilibrium distributions encounter fat-tailedness and do not possess statistical moments.

RESULTS

We show that estimation via stochastic simulation algorithm (SSA) trajectories lose consistency over time and estimated moment values span a wide range of values even for large sample sizes. In comparison, the method of moments returns smooth moment estimates but is not able to indicate the non-existence of the allegedly predicted moments. We furthermore analyze the negative effect of a CME solution's fat-tailedness on SSA run times and explain inherent difficulties. While moment-estimation techniques are a commonly applied tool in the simulation of (bio-)chemical reaction networks, we conclude that they should be used with care, as neither the system definition nor the moment-estimation techniques themselves reliably indicate the potential fat-tailedness of the CME's solution.

PlasmoFAB: a benchmark to foster machine learning for Plasmodium falciparum protein antigen candidate prediction

MOTIVATION

Machine learning methods can be used to support scientific discovery in healthcare-related research fields. However, these methods can only be reliably used if they can be trained on high-quality and curated datasets. Currently, no such dataset for the exploration of Plasmodium falciparum protein antigen candidates exists. The parasite P.falciparum causes the infectious disease malaria. Thus, identifying potential antigens is of utmost importance for the development of antimalarial drugs and vaccines. Since exploring antigen candidates experimentally is an expensive and time-consuming process, applying machine learning methods to support this process has the potential to accelerate the development of drugs and vaccines, which are needed for fighting and controlling malaria.

RESULTS

We developed PlasmoFAB, a curated benchmark that can be used to train machine learning methods for the exploration of P.falciparum protein antigen candidates. We combined an extensive literature search with domain expertise to create high-quality labels for P.falciparum specific proteins that distinguish between antigen candidates and intracellular proteins. Additionally, we used our benchmark to compare different well-known prediction models and available protein localization prediction services on the task of identifying protein antigen candidates. We show that available general-purpose services are unable to provide sufficient performance on identifying protein antigen candidates and are outperformed by our models that were trained on this tailored data.

AVAILABILITY AND IMPLEMENTATION

PlasmoFAB is publicly available on Zenodo with DOI 10.5281/zenodo.7433087. Furthermore, all scripts that were used in the creation of PlasmoFAB and the training and evaluation of machine learning models are open source and publicly available on GitHub here: https://github.com/msmdev/PlasmoFAB.

Reliable genotyping of recombinant genomes using a robust hidden Markov model

Meiotic recombination is an essential mechanism during sexual reproduction and includes the exchange of chromosome segments between homologous chromosomes. New allelic combinations are transmitted to the new generation, introducing novel genetic variation in the offspring genomes. With the improvement of high-throughput whole-genome sequencing technologies, large numbers of recombinant individuals can now be sequenced with low sequencing depth at low costs, necessitating computational methods for reconstructing their haplotypes. The main challenge is the uncertainty in haplotype calling that arises from the low information content of a single genomic position. Straightforward sliding window-based approaches are difficult to tune and fail to place recombination breakpoints precisely. Hidden Markov model (HMM)-based approaches, on the other hand, tend to over-segment the genome. Here, we present RTIGER, an HMM-based model that exploits in a mathematically precise way the fact that true chromosome segments typically have a certain minimum length. We further separate the task of identifying the correct haplotype sequence from the accurate placement of haplotype borders, thereby maximizing the accuracy of border positions. By comparing segmentations based on simulated data with known underlying haplotypes, we highlight the reasons for RTIGER outperforming traditional segmentation approaches. We then analyze the meiotic recombination pattern of segregants of 2 Arabidopsis (Arabidopsis thaliana) accessions and a previously described hyper-recombining mutant. RTIGER is available as an R package with an efficient Julia implementation of the core algorithm.

On the accuracy of the epigenetic copy machine: comprehensive specificity analysis of the DNMT1 DNA methyltransferase

The specificity of DNMT1 for hemimethylated DNA is a central feature for the inheritance of DNA methylation. We investigated this property in competitive methylation kinetics using hemimethylated (HM), hemihydroxymethylated (OH) and unmethylated (UM) substrates with single CpG sites in a randomized sequence context. DNMT1 shows a strong flanking sequence dependent HM/UM specificity of 80-fold on average, which is slightly enhanced on long hemimethylated DNA substrates. To explain this strong effect of a single methyl group, we propose a novel model in which the presence of the 5mC methyl group changes the conformation of the DNMT1-DNA complex into an active conformation by steric repulsion. The HM/OH preference is flanking sequence dependent and on average only 13-fold, indicating that passive DNA demethylation by 5hmC generation is not efficient in many flanking contexts. The CXXC domain of DNMT1 has a moderate flanking sequence dependent contribution to HM/UM specificity during DNA association to DNMT1, but not if DNMT1 methylates long DNA molecules in processive methylation mode. Comparison of genomic methylation patterns from mouse ES cell lines with various deletions of DNMTs and TETs with our data revealed that the UM specificity profile is most related to cellular methylation patterns, indicating that de novo methylation activity of DNMT1 shapes the DNA methylome in these cells.

Microglia actively remove NR1 autoantibody-bound NMDA receptors and associated post-synaptic proteins in neuron microglia co-cultures

Autoantibodies against the NR1 subunit of NMDA receptors (NMDARs) have been shown to promote crosslinking and internalization of bound receptors in NMDAR encephalitis (NMDARE). This internalization-mediated loss of NMDARs is thought to be the major mechanism leading to pathogenic outcomes in patients. However, the role of bound autoantibody in engaging the resident immune cells, microglia, remains poorly understood. Here, using a patient-derived monoclonal NR1 autoantibody (hNR1-mAb) and a co-culture system of microglia and neurons, we could show that hNR1-mAb bound to hippocampal neurons led to microglia-mediated removal of hNR1-mAb bound NMDARs. These complexes were found to accumulate inside endo-lysosomal compartments of microglia. Utilizing another patient isolated monoclonal autoantibody, against the α1-subunit of GABA_A receptors (α1-GABA_A -mAb), such removal of receptors was found to be specific to the antibody-bound receptor targets. Interestingly, along with receptor removal, we also observed a reduction in synapse number, more specifically in the numbers of post-synaptic proteins like PSD95 and Homer 1, when microglia were present in the culture. Importantly, mutations in the Fc region of hNR1-mAb, blocking its Fcγ receptor (FcγR) and complement binding, attenuated hNR1-mAb driven loss of NMDARs and synapses, indicating that microglia engagement by bound hNR1-mAb is critical for receptor and synapse loss. Our data argues for an active involvement of microglia in removal of NMDARs and other receptors in individuals with autoimmune encephalitis, thereby contributing to the etiology of these diseases.

Mutations in plasticity-related-gene-1 (PRG-1) protein contribute to hippocampal seizure susceptibility and modify epileptic phenotype

The Phospholipid Phosphatase Related 4 gene (PLPPR4,  *607813) encodes the Plasticity-Related-Gene-1 (PRG-1) protein. This cerebral synaptic transmembrane-protein modulates cortical excitatory transmission on glutamatergic neurons. In mice, homozygous Prg-1 deficiency causes juvenile epilepsy. Its epileptogenic potential in humans was unknown. Thus, we screened 18 patients with infantile epileptic spasms syndrome (IESS) and 98 patients with benign familial neonatal/infantile seizures (BFNS/BFIS) for the presence of PLPPR4 variants. A girl with IESS had inherited a PLPPR4-mutation (c.896C > G, NM_014839; p.T299S) from her father and an SCN1A-mutation from her mother (c.1622A > G, NM_006920; p.N541S). The PLPPR4-mutation was located in the third extracellular lysophosphatidic acid-interacting domain and in-utero electroporation (IUE) of the Prg-1p.T300S construct into neurons of Prg-1 knockout embryos demonstrated its inability to rescue the electrophysiological knockout phenotype. Electrophysiology on the recombinant SCN1Ap.N541S channel revealed partial loss-of-function. Another PLPPR4 variant (c.1034C > G, NM_014839; p.R345T) that was shown to result in a loss-of-function aggravated a BFNS/BFIS phenotype and also failed to suppress glutamatergic neurotransmission after IUE. The aggravating effect of Plppr4-haploinsufficiency on epileptogenesis was further verified using the kainate-model of epilepsy: double heterozygous Plppr4-/+|Scn1awt|p.R1648H mice exhibited higher seizure susceptibility than either wild-type, Plppr4-/+, or Scn1awt|p.R1648H littermates. Our study shows that a heterozygous PLPPR4 loss-of-function mutation may have a modifying effect on BFNS/BFIS and on SCN1A-related epilepsy in mice and humans.

Isotropic three-dimensional dual-color super-resolution microscopy with metal-induced energy transfer

Over the past two decades, super-resolution microscopy has seen a tremendous development in speed and resolution, but for most of its methods, there exists a remarkable gap between lateral and axial resolution, which is by a factor of 2 to 3 worse. One recently developed method to close this gap is metal-induced energy transfer (MIET) imaging, which achieves an axial resolution down to nanometers. It exploits the distance-dependent quenching of fluorescence when a fluorescent molecule is brought close to a metal surface. In the present manuscript, we combine the extreme axial resolution of MIET imaging with the extraordinary lateral resolution of single-molecule localization microscopy, in particular with direct stochastic optical reconstruction microscopy (dSTORM). This combination allows us to achieve isotropic three-dimensional super-resolution imaging of subcellular structures. Moreover, we used spectral demixing for implementing dual-color MIET-dSTORM that allows us to image and colocalize, in three dimensions, two different cellular structures simultaneously.

The effects of substrate porosity, mechanical substrate properties and loading conditions on the attachment performance of the Mediterranean medicinal leech (Hirudo verbana)

The ectoparasitic lifestyle of the Mediterranean medicinal leech (Hirudo verbana) requires reliable functioning of its attachment organs (i.e. anterior and posterior suction discs) on multiple habitat- and host-specific surfaces under both normal and shear stresses. In addition to some intrinsic properties of the attachment devices, however, only a few extrinsic factors (e.g. substrate roughness and porosity) have been considered in previous studies on leech suckers. Using centrifugal force experiments, we analysed the attachment performance of H. verbana under different types of loading on artificial substrates differing in porosity and their mechanical properties. Whereas the substrate porosity significantly influenced leech attachment under normal and shear loading, the different mechanical properties did not noticeably affect attachment within the considered parameter limits. Furthermore, suction was confirmed to be the primary attachment mechanism independent of the prevailing loading condition. The question of whether the suction cups of H. verbana are adapted to a specific loading condition could not be answered. In any case, our results again highlight the high functional resilience of leech suckers guaranteeing a successful ectoparasitic lifestyle.

Bo-NO-bouba-kiki: picture-word mapping but no spontaneous sound symbolic speech-shape mapping in a language trained bonobo

Humans share the ability to intuitively map 'sharp' or 'round' pseudowords, such as 'bouba' versus 'kiki', to abstract edgy versus round shapes, respectively. This effect, known as sound symbolism, appears early in human development. The phylogenetic origin of this phenomenon, however, is unclear: are humans the only species capable of experiencing correspondences between speech sounds and shapes, or could similar effects be observed in other animals? Thus far, evidence from an implicit matching experiment failed to find evidence of this sound symbolic matching in great apes, suggesting its human uniqueness. However, explicit tests of sound symbolism have never been conducted with nonhuman great apes. In the present study, a language-competent bonobo completed a cross-modal matching-to-sample task in which he was asked to match spoken English words to pictures, as well as 'sharp' or 'round' pseudowords to shapes. Sound symbolic trials were interspersed among English words. The bonobo matched English words to pictures with high accuracy, but did not show any evidence of spontaneous sound symbolic matching. Our results suggest that speech exposure/comprehension alone cannot explain sound symbolism. This lends plausibility to the hypothesis that biological differences between human and nonhuman primates could account for the putative human specificity of this effect.

Population size impacts host-pathogen coevolution

Ongoing host-pathogen interactions are characterized by rapid coevolutionary changes forcing species to continuously adapt to each other. The interacting species are often defined by finite population sizes. In theory, finite population size limits genetic diversity and compromises the efficiency of selection owing to genetic drift, in turn constraining any rapid coevolutionary responses. To date, however, experimental evidence for such constraints is scarce. The aim of our study was to assess to what extent population size influences the dynamics of host-pathogen coevolution. We used Caenorhabditus elegans and its pathogen Bacillus thuringiensis as a model for experimental coevolution in small and large host populations, as well as in host populations which were periodically forced through a bottleneck. By carefully controlling host population size for 23 host generations, we found that host adaptation was constrained in small populations and to a lesser extent in the bottlenecked populations. As a result, coevolution in large and small populations gave rise to different selection dynamics and produced different patterns of host-pathogen genotype-by-genotype interactions. Our results demonstrate a major influence of host population size on the ability of the antagonists to co-adapt to each other, thereby shaping the dynamics of antagonistic coevolution.

Preclinical evidence for the therapeutic value of TBX5 normalization in arrhythmia control

AIMS

Arrhythmias and sudden cardiac death (SCD) occur commonly in patients with heart failure. We found T-box 5 (TBX5) dysregulated in ventricular myocardium from heart failure patients and thus we hypothesized that TBX5 reduction contributes to arrhythmia development in these patients. To understand the underlying mechanisms, we aimed to reveal the ventricular TBX5-dependent transcriptional network and further test the therapeutic potential of TBX5 level normalization in mice with documented arrhythmias.

METHODS AND RESULTS

We used a mouse model of TBX5 conditional deletion in ventricular cardiomyocytes. Ventricular (v) TBX5 loss in mice resulted in mild cardiac dysfunction and arrhythmias and was associated with a high mortality rate (60%) due to SCD. Upon angiotensin stimulation, vTbx5KO mice showed exacerbated cardiac remodelling and dysfunction suggesting a cardioprotective role of TBX5. RNA-sequencing of a ventricular-specific TBX5KO mouse and TBX5 chromatin immunoprecipitation was used to dissect TBX5 transcriptional network in cardiac ventricular tissue. Overall, we identified 47 transcripts expressed under the control of TBX5, which may have contributed to the fatal arrhythmias in vTbx5KO mice. These included transcripts encoding for proteins implicated in cardiac conduction and contraction (Gja1, Kcnj5, Kcng2, Cacna1g, Chrm2), in cytoskeleton organization (Fstl4, Pdlim4, Emilin2, Cmya5), and cardiac protection upon stress (Fhl2, Gpr22, Fgf16). Interestingly, after TBX5 loss and arrhythmia development in vTbx5KO mice, TBX5 protein-level normalization by systemic adeno-associated-virus (AAV) 9 application, re-established TBX5-dependent transcriptome. Consequently, cardiac dysfunction was ameliorated and the propensity of arrhythmia occurrence was reduced.

CONCLUSIONS

This study uncovers a novel cardioprotective role of TBX5 in the adult heart and provides preclinical evidence for the therapeutic value of TBX5 protein normalization in the control of arrhythmia.

The G127V variant of the prion protein interferes with dimer formation in vitro but not in cellulo

Scrapie prion, PrPSc, formation is the central event of all types of transmissible spongiform encephalopathies (TSEs), while the pathway with possible intermediates and their mechanism of formation from the normal isoform of prion (PrP), remains not fully understood. Recently, the G127V variant of the human PrP is reported to render the protein refractory to transmission of TSEs, via a yet unknown mechanism. Molecular dynamics studies suggested that this mutation interferes with the formation of PrP dimers. Here we analyze the dimerization of 127G and 127VPrP, in both in vitro and a mammalian cell culture system. Our results show that while molecular dynamics may capture the features affecting dimerization in vitro, G127V inhibiting dimer formation of PrP, these are not evidenced in a more complex cellular system.

Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects

We point out an instantiation of Simpson's paradox in COVID-19 case fatality rates (cfrs): comparing a large-scale study from China (February 17) with early reports from Italy (March 9), we find that cfrs are lower in Italy for every age group, but higher overall. This phenomenon is explained by a stark difference in case demographic between the two countries. Using this as a motivating example, we introduce basic concepts from mediation analysis and show how these can be used to quantify different direct and indirect effects when assuming a coarse-grained causal graph involving country, age, and case fatality. We curate an age-stratified cfr dataset with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$>$\end{document}750 k cases and conduct a case study, investigating total, direct, and indirect (age-mediated) causal effects between different countries and at different points in time. This allows us to separate age-related effects from others unrelated to age and facilitates a more transparent comparison of cfrs across countries at different stages of the COVID-19 pandemic. Using longitudinal data from Italy, we discover a sign reversal of the direct causal effect in mid-March, which temporally aligns with the reported collapse of the healthcare system in parts of the country. Moreover, we find that direct and indirect effects across 132 pairs of countries are only weakly correlated, suggesting that a country's policy and case demographic may be largely unrelated. We point out limitations and extensions for future work, and finally, discuss the role of causal reasoning in the broader context of using AI to combat the COVID-19 pandemic.

Impact Statement—During a global pandemic, understanding the causal effects of risk factors such as age on COVID-19 fatality is an important scientific question. Since randomised controlled trials are typically infeasible or unethical in this context, causal investigations based on observational data—such as the one carried out in this article—will, therefore, be crucial in guiding our understanding of the available data. Causal inference, in particular mediation analysis, can be used to resolve apparent statistical paradoxes; help educate the public and decision-makers alike; avoid unsound comparisons; and answer a range of causal questions pertaining to the pandemic, subject to transparently stated assumptions. Our exposition helps clarify how mediation analysis can be used to investigate direct and indirect effects along different causal paths and thus serves as a stepping stone for future studies of other important risk factors for COVID-19 besides age.

NCX1 represents an ionic Na+ sensing mechanism in macrophages

Inflammation and infection can trigger local tissue Na+ accumulation. This Na+-rich environment boosts proinflammatory activation of monocyte/macrophage-like cells (MΦs) and their antimicrobial activity. Enhanced Na+-driven MΦ function requires the osmoprotective transcription factor nuclear factor of activated T cells 5 (NFAT5), which augments nitric oxide (NO) production and contributes to increased autophagy. However, the mechanism of Na+ sensing in MΦs remained unclear. High extracellular Na+ levels (high salt [HS]) trigger a substantial Na+ influx and Ca2+ loss. Here, we show that the Na+/Ca2+ exchanger 1 (NCX1, also known as solute carrier family 8 member A1 [SLC8A1]) plays a critical role in HS-triggered Na+ influx, concomitant Ca2+ efflux, and subsequent augmented NFAT5 accumulation. Moreover, interfering with NCX1 activity impairs HS-boosted inflammatory signaling, infection-triggered autolysosome formation, and subsequent antibacterial activity. Taken together, this demonstrates that NCX1 is able to sense Na+ and is required for amplifying inflammatory and antimicrobial MΦ responses upon HS exposure. Manipulating NCX1 offers a new strategy to regulate MΦ function.

A Low-Temperature Molecular Precursor Approach to Copper-Based Nano-Sized Digenite Mineral for Efficient Electrocatalytic Oxygen Evolution Reaction

In the urge of designing noble metal-free and sustainable electrocatalysts for oxygen evolution reaction (OER), herein, a mineral Digenite Cu9 S5 has been prepared from a molecular copper(I) precursor, [{(PyHS)2 CuI (PyHS)}2 ](OTf)2 (1), and utilized as an anode material in electrocatalytic OER for the first time. A hot injection of 1 yielded a pure phase and highly crystalline Cu9 S5 , which was then electrophoretically deposited (EPD) on a highly conducting nickel foam (NF) substrate. When assessed as an electrode for OER, the Cu9 S5 /NF displayed an overpotential of merely 298±3 mV at a current density of 10 mA cm-2 in alkaline media. The overpotential recorded here supersedes the value obtained for the best reported Cu-based as well as the benchmark precious-metal-based RuO2 and IrO2 electrocatalysts. In addition, the choronoamperometric OER indicated the superior stability of Cu9 S5 /NF, rendering its suitability as the sustainable anode material for practical feasibility. The excellent catalytic activity of Cu9 S5 can be attributed to the formation of a crystalline CuO overlayer on the conductive Cu9 S5 that behaves as active species to facilitate OER. This study delivers a distinct molecular precursor approach to produce highly active copper-based catalysts that could be used as an efficient and durable OER electro(pre)catalysts relying on non-precious metals.