Floating perovskite-BiVO4 devices for scalable solar fuel production.

Photoelectrochemical (PEC) artificial leaves hold the potential to lower the costs of sustainable solar fuel production by integrating light harvesting and catalysis within one compact device. However, current deposition techniques limit their scalability1, whereas fragile and heavy bulk materials can affect their transport and deployment. Here we demonstrate the fabrication of lightweight artificial leaves by employing thin, flexible substrates and carbonaceous protection layers. Lead halide perovskite photocathodes deposited onto indium tin oxide-coated polyethylene terephthalate achieved an activity of 4,266 µmol H2 g-1 h-1 using a platinum catalyst, whereas photocathodes with a molecular Co catalyst for CO2 reduction attained a high CO:H2 selectivity of 7.2 under lower (0.1 sun) irradiation. The corresponding lightweight perovskite-BiVO4 PEC devices showed unassisted solar-to-fuel efficiencies of 0.58% (H2) and 0.053% (CO), respectively. Their potential for scalability is demonstrated by 100 cm2 stand-alone artificial leaves, which sustained a comparable performance and stability (of approximately 24 h) to their 1.7 cm2 counterparts. Bubbles formed under operation further enabled 30-100 mg cm-2 devices to float, while lightweight reactors facilitated gas collection during outdoor testing on a river. This leaf-like PEC device bridges the gulf in weight between traditional solar fuel approaches, showcasing activities per gram comparable to those of photocatalytic suspensions and plant leaves. The presented lightweight, floating systems may enable open-water applications, thus avoiding competition with land use.

Pleiotropic hubs drive bacterial surface competition through parallel changes in colony composition and expansion.

Bacteria commonly adhere to surfaces where they compete for both space and resources. Despite the importance of surface growth, it remains largely elusive how bacteria evolve on surfaces. We previously performed an evolution experiment where we evolved distinct Bacilli populations under a selective regime that favored colony spreading. In just a few weeks, colonies of Bacillus subtilis showed strongly advanced expansion rates, increasing their radius 2.5-fold relative to that of the ancestor. Here, we investigate what drives their rapid evolution by performing a uniquely detailed analysis of the evolutionary changes in colony development. We find mutations in diverse global regulators, RicT, RNAse Y, and LexA, with strikingly similar pleiotropic effects: They lower the rate of sporulation and simultaneously facilitate colony expansion by either reducing extracellular polysaccharide production or by promoting filamentous growth. Combining both high-throughput flow cytometry and gene expression profiling, we show that regulatory mutations lead to highly reproducible and parallel changes in global gene expression, affecting approximately 45% of all genes. This parallelism results from the coordinated manner by which regulators change activity both during colony development-in the transition from vegetative growth to dormancy-and over evolutionary time. This coordinated activity can however also break down, leading to evolutionary divergence. Altogether, we show how global regulators function as major pleiotropic hubs that drive rapid surface adaptation by mediating parallel changes in both colony composition and expansion, thereby massively reshaping gene expression.

Planet-compatible pathways for transitioning the chemical industry.

Chemical products, such as plastics, solvents, and fertilizers, are essential for supporting modern lifestyles. Yet, producing, using, and disposing of chemicals creates adverse environmental impacts which threaten the industry's license to operate. This study presents seven planet-compatible pathways toward 2050 employing demand-side and supply-side interventions with cumulative total investment costs of US$1.2-3.7 trillion. Resource efficiency and circularity interventions reduce global chemicals demand by 23 to 33% and are critical for mitigating risks associated with using fossil feedstocks and carbon capture and sequestration, and constraints on available biogenic and recyclate feedstocks. Replacing fossil feedstocks with biogenic/air-capture sources, shifting carbon destinations from the atmosphere to ground, and electrifying/decarbonizing energy supply for production technologies could enable net negative emissions of 0.5 GtCO2eq y-1 across non-ammonia chemicals, while still delivering essential chemical-based services to society.

Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.

MOTIVATION: Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitness needs to be measured for any one protein. Deep learning may help to predict the fitness of many genotypes from a smaller neural network training sample of genotypes with experimentally measured fitness. Here I use a recently published experimentally mapped fitness landscape of more than 260 000 protein genotypes to ask how such sampling is best performed. RESULTS: I show that multilayer perceptrons, recurrent neural networks, convolutional networks, and transformers, can explain more than 90% of fitness variance in the data. In addition, 90% of this performance is reached with a training sample comprising merely ≈103 sequences. Generalization to unseen test data is best when training data is sampled randomly and uniformly, or sampled to minimize the number of synonymous sequences. In contrast, sampling to maximize sequence diversity or codon usage bias reduces performance substantially. These observations hold for more than one network architecture. Simple sampling strategies may perform best when training deep learning neural networks to map fitness landscapes from experimental data. AVAILABILITY AND IMPLEMENTATION: The fitness landscape data analyzed here is publicly available as described previously (Papkou et al. 2023). All code used to analyze this landscape is publicly available at https://github.com/andreas-wagner-uzh/fitness_landscape_sampling.

The causes of evolvability and their evolution.

Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.

Not Quite Lost in Translation: Mistranslation Alters Adaptive Landscape Topography and the Dynamics of Evolution.

Mistranslation-the erroneous incorporation of amino acids into nascent proteins-is a source of protein variation that is orders of magnitude more frequent than DNA mutation. Like other sources of nongenetic variation, it can affect adaptive evolution. We study the evolutionary consequences of mistranslation with experimental data on mistranslation rates applied to three empirical adaptive landscapes. We find that mistranslation generally flattens adaptive landscapes by reducing the fitness of high fitness genotypes and increasing that of low fitness genotypes, but it does not affect all genotypes equally. Most importantly, it increases genetic variation available to selection by rendering many neutral DNA mutations nonneutral. Mistranslation also renders some beneficial mutations deleterious and vice versa. It increases the probability of fixation of 3-8% of beneficial mutations. Even though mistranslation increases the incidence of epistasis, it also allows populations evolving on a rugged landscape to evolve modestly higher fitness. Our observations show that mistranslation is an important source of nongenetic variation that can affect adaptive evolution on fitness landscapes in multiple ways.

Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation.

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.

Meso- and thermophilic posttreatment of press water coming from a thermophilic municipal solid waste digester.

An efficient biogas production out of organic (waste) materials is important to contribute to a carbon-neutral future. In this study, thermophilic press water (PW) coming from an organic fraction of the municipal solid waste digester was further digested in a thermo- and mesophilic posttreatment approach using two semicontinuous 14 L digesters. The results showed that the PW can still have considerable high biogas potential-at least during the touristic high season in central Europe. The change in temperature led to an increase in volatile fatty acid concentrations and a decrease in biogas production in the mesophilic approach in the first days. However, the losses in biogas production at the beginning could be compensated thus there were no considerable differences in biogas production between thermo- and mesophilic posttreatment at the end of incubation. This can most probably be contributed to a change in the microbial community, and potentially problematic intermediates like valerate could be better degraded in the mesophilic reactor. Especially the abundance of representatives of the phylum Bacteroidota, like Fermentimonas spp., increased during mesophilic anaerobic digestion.

Cryptic surface-associated multicellularity emerges through cell adhesion and its regulation.

The repeated evolution of multicellularity led to a wide diversity of organisms, many of which are sessile, including land plants, many fungi, and colonial animals. Sessile organisms adhere to a surface for most of their lives, where they grow and compete for space. Despite the prevalence of surface-associated multicellularity, little is known about its evolutionary origin. Here, we introduce a novel theoretical approach, based on spatial lineage tracking of cells, to study this origin. We show that multicellularity can rapidly evolve from two widespread cellular properties: cell adhesion and the regulatory control of adhesion. By evolving adhesion, cells attach to a surface, where they spontaneously give rise to primitive cell collectives that differ in size, life span, and mode of propagation. Selection in favor of large collectives increases the fraction of adhesive cells until a surface becomes fully occupied. Through kin recognition, collectives then evolve a central-peripheral polarity in cell adhesion that supports a division of labor between cells and profoundly impacts growth. Despite this spatial organization, nascent collectives remain cryptic, lack well-defined boundaries, and would require experimental lineage tracking technologies for their identification. Our results suggest that cryptic multicellularity could readily evolve and originate well before multicellular individuals become morphologically evident.

Prospective Observational Study of Volatile Sedation with Sevoflurane After Aneurysmal Subarachnoid Hemorrhage Using the Sedaconda Anesthetic Conserving Device.

BACKGROUND: Volatile sedation is still used with caution in patients with acute brain injury because of safety concerns. We analyzed the effects of sevoflurane sedation on systemic and cerebral parameters measured by multimodal neuromonitoring in patients after aneurysmal subarachnoid hemorrhage (aSAH) with normal baseline intracranial pressure (ICP). METHODS: In this prospective observational study, we analyzed a 12-h period before and after the switch from intravenous to volatile sedation with sevoflurane using the Sedaconda Anesthetic Conserving Device with a target Richmond Agitation Sedation Scale score of - 5 to - 4. ICP, cerebral perfusion pressure (CPP), brain tissue oxygenation (PBrO2), metabolic values of cerebral microdialysis, systemic cardiopulmonary parameters, and the administered drugs before and after the sedation switch were analyzed. RESULTS: We included 19 patients with a median age of 61 years (range 46-78 years), 74% of whom presented with World Federation of Neurosurgical Societies grade 4 or 5 aSAH. We observed no significant changes in the mean ICP (9.3 ± 4.2 vs. 9.7 ± 4.2 mm Hg), PBrO2 (31.0 ± 13.2 vs. 32.2 ± 12.4 mm Hg), cerebral lactate (5.0 ± 2.2 vs. 5.0 ± 1.9 mmol/L), pyruvate (136.6 ± 55.9 vs. 134.1 ± 53.6 µmol/L), and lactate/pyruvate ratio (37.4 ± 8.7 vs. 39.8 ± 9.2) after the sedation switch to sevoflurane. We found a significant decrease in mean arterial pressure (MAP) (88.6 ± 7.6 vs. 86.3 ± 5.8 mm Hg) and CPP (78.8 ± 8.5 vs. 76.6 ± 6.6 mm Hg) after the initiation of sevoflurane, but the decrease was still within the physiological range requiring no additional hemodynamic support. CONCLUSIONS: Sevoflurane appears to be a feasible alternative to intravenous sedation in patients with aSAH without intracranial hypertension, as our study did not show negative effects on ICP, cerebral oxygenation, or brain metabolism. Nevertheless, the risk of a decrease of MAP leading to a consecutive CPP decrease should be considered.

Multiple Novel Traits without Immediate Benefits Originate in Bacteria Evolving on Single Antibiotics.

How new traits originate in evolution is a fundamental question of evolutionary biology. When such traits arise, they can either be immediately beneficial in their environment of origin, or they may become beneficial only in a future environment. Compared to immediately beneficial novel traits, novel traits without immediate benefits remain poorly studied. Here we use experimental evolution to study novel traits that are not immediately beneficial but that allow bacteria to survive in new environments. Specifically, we evolved multiple E. coli populations in five antibiotics with different mechanisms of action, and then determined their ability to grow in more than 200 environments that are different from the environment in which they evolved. Our populations evolved viability in multiple environments that contain not just clinically relevant antibiotics, but a broad range of antimicrobial molecules, such as surfactants, organic and inorganic salts, nucleotide analogues and pyridine derivatives. Genome sequencing of multiple evolved clones shows that pleiotropic mutations are important for the origin of these novel traits. Our experiments, which lasted fewer than 250 generations, demonstrate that evolution can readily create an enormous reservoir of latent traits in microbial populations. These traits can facilitate adaptive evolution in a changing world.

GroEL/S Overexpression Helps to Purge Deleterious Mutations and Reduce Genetic Diversity during Adaptive Protein Evolution.

Chaperones are proteins that help other proteins fold. They also affect the adaptive evolution of their client proteins by buffering the effect of deleterious mutations and increasing the genetic diversity of evolving proteins. We study how the bacterial chaperone GroE (GroEL+GroES) affects the evolution of green fluorescent protein (GFP). To this end, we subjected GFP to multiple rounds of mutation and selection for its color phenotype in four replicate Escherichia coli populations, and studied its evolutionary dynamics through high-throughput sequencing and mutant engineering. We evolved GFP both under stabilizing selection for its ancestral (green) phenotype, and to directional selection for a new (cyan) phenotype. We did so both under low and high expression of the chaperone GroE. In contrast to previous work, we observe that GroE does not just buffer but also helps purge deleterious (fluorescence reducing) mutations from evolving populations. In doing so, GroE helps reduce the genetic diversity of evolving populations. In addition, it causes phenotypic heterogeneity in mutants with the same genotype, helping to enhance their fluorescence in some cells, and reducing it in others. Our observations show that chaperones can affect adaptive evolution in more than one way.

Aquaporin-4 expression in the human choroid plexus.

The choroid plexus (CP) consists of specialized ependymal cells and underlying blood vessels and stroma producing the bulk of the cerebrospinal fluid (CSF). CP epithelial cells are considered the site of the internal blood-cerebrospinal fluid barrier, show epithelial characteristics (basal lamina, tight junctions), and express aquaporin-1 (AQP1) apically. In this study, we analyzed the expression of aquaporins in the human CP using immunofluorescence and qPCR. As previously reported, AQP1 was expressed apically in CP epithelial cells. Surprisingly, and previously unknown, many cells in the CP epithelium were also positive for aquaporin-4 (AQP4), normally restricted to ventricle-lining ependymal cells and astrocytes in the brain. Expression of AQP1 and AQP4 was found in the CP of all eight body donors investigated (3 males, 5 females; age 74-91). These results were confirmed by qPCR, and by electron microscopy detecting orthogonal arrays of particles. To find out whether AQP4 expression correlated with the expression pattern of relevant transport-related proteins we also investigated expression of NKCC1, and Na/K-ATPase. Immunostaining with NKCC1 was similar to AQP1 and revealed no particular pattern related to AQP4. Co-staining of AQP4 and Na/K-ATPase indicated a trend for an inverse correlation of their expression. We hypothesized that AQP4 expression in the CP was caused by age-related changes. To address this, we investigated mouse brains from young (2 months), adult (12 months) and old (30 months) mice. We found a significant increase of AQP4 on the mRNA level in old mice compared to young and adult animals. Taken together, we provide evidence for AQP4 expression in the CP of the aging brain which likely contributes to the water flow through the CP epithelium and CSF production. In two alternative hypotheses, we discuss this as a beneficial compensatory, or a detrimental mechanism influencing the previously observed CSF changes during aging.

Comparative lipid profiling of murine and human atherosclerotic plaques using high-resolution MALDI MSI.

The distribution of atherosclerotic lesions in the aorta and its branches of ApoE knockout (ApoE-/-) mice is like that of patients with atherosclerosis. By using high-resolution MALDI mass spectrometry imaging (MSI), we aimed at characterizing universally applicable physiological biomarkers by comparing the murine lipid marker profile with that of human atherosclerotic arteries. Therefore, the aorta or carotid artery of male ApoE-/- mice at different ages, human arteries with documented atherosclerotic changes originated from amputated limbs, and corresponding controls were analysed. Obtained data were subjected to multivariate statistical analysis to identify potential biomarkers. Thirty-one m/z values corresponding to individual lipid species of cholesterol esters, lysophosphatidylcholines, lysophosphatidylethanolamines, and cholesterol derivatives were found to be specific in aortic atherosclerotic plaques of old ApoE-/- mice. The lipid composition at related vessel positions of young ApoE-/- mice was more comparable with wild-type mice. Twenty-six m/z values of the murine lipid markers were found in human atherosclerotic peripheral arteries but also control vessels and showed a more patient-dependent diverse distribution. Extensive data analysis without marker preselection based on mouse data revealed lysophosphatidylcholine and glucosylated cholesterol species, the latter not being detected in the murine atherosclerotic tissue, as specific potential novel human atherosclerotic vessel markers. Despite the heterogeneous lipid profile of atherosclerotic peripheral arteries derived from human patients, we identified lipids specifically colocalized to atherosclerotic human tissue and plaques in ApoE-/- mice. These data highlight species-dependent differences in lipid profiles between peripheral artery disease and aortic atherosclerosis.

Natural Selection on the Phase-Separation Properties of FUS during 160 My of Mammalian Evolution.

Protein phase separation can help explain the formation of many nonmembranous organelles. However, we know little about its ability to change in evolution. Here we studied the evolution of the mammalian RNA-binding protein Fused in Sarcoma (FUS), a protein whose prion-like domain (PLD) contributes to the formation of stress granules through liquid-liquid phase separation. Although the PLD evolves three times as rapidly as the remainder of FUS, it harbors absolutely conserved tyrosine residues that are crucial for phase separation. Ancestral reconstruction shows that the phosphorylation sites within the PLD are subject to stabilizing selection. They toggle among a small number of amino acid states. One exception to this pattern is primates, where the number of such phosphosites has increased through positive selection. In addition, we find frequent glutamine to proline changes that help maintain the unstructured state of FUS that is necessary for phase separation. Our work provides evidence that natural selection has stabilized the liquid forming potential of FUS and minimized the propensity of cytotoxic liquid-to-solid phase transitions during 160 My of mammalian evolution.

Mistranslation Reduces Mutation Load in Evolving Proteins through Negative Epistasis with DNA Mutations.

Translational errors during protein synthesis cause phenotypic mutations that are several orders of magnitude more frequent than DNA mutations. Such phenotypic mutations may affect adaptive evolution through their interactions with DNA mutations. To study how mistranslation may affect the adaptive evolution of evolving proteins, we evolved populations of green fluorescent protein (GFP) in either high-mistranslation or low-mistranslation Escherichia coli hosts. In both hosts, we first evolved GFP under purifying selection for the ancestral phenotype green fluorescence, and then under directional selection toward the new phenotype yellow fluorescence. High-mistranslation populations evolved modestly higher yellow fluorescence during each generation of evolution than low-mistranslation populations. We demonstrate by high-throughput sequencing that elevated mistranslation reduced the accumulation of deleterious DNA mutations under both purifying and directional selection. It did so by amplifying the fitness effects of deleterious DNA mutations through negative epistasis with phenotypic mutations. In contrast, mistranslation did not affect the incidence of beneficial mutations. Our findings show that phenotypic mutations interact epistatically with DNA mutations. By reducing a population's mutation load, mistranslation can affect an important determinant of evolvability.

Defect Nanostructure and its Impact on Magnetism of α-Cr2 O3 Thin Films.

Thin films of the magnetoelectric insulator α-Cr2 O3 are technologically relevant for energy-efficient magnetic memory devices controlled by electric fields. In contrast to single crystals, the quality of thin Cr2 O3 films is usually compromised by the presence of point defects and their agglomerations at grain boundaries, putting into question their application potential. Here, the impact of the defect nanostructure, including sparse small-volume defects and their complexes is studied on the magnetic properties of Cr2 O3 thin films. By tuning the deposition temperature, the type, size, and relative concentration of defects is tailored, which is analyzed using the positron annihilation spectroscopy complemented with electron microscopy studies. The structural characterization is correlated with magnetotransport measurements and nitrogen-vacancy microscopy of antiferromagnetic domain patterns. Defects pin antiferromagnetic domain walls and stabilize complex multidomain states with a domain size in the sub-micrometer range. Despite their influence on the domain configuration, neither small open-volume defects nor grain boundaries in Cr2 O3 thin films affect the Néel temperature in a broad range of deposition parameters. The results pave the way toward the realization of spin-orbitronic devices where magnetic domain patterns can be tailored based on defect nanostructures without affecting their operation temperature.

Adaptive evolvability through direct selection instead of indirect, second-order selection.

Can evolvability itself be the product of adaptive evolution? To answer this question is challenging, because any DNA mutation that alters only evolvability is subject to indirect, "second order" selection on the future effects of this mutation. Such indirect selection is weaker than "first-order" selection on mutations that alter fitness, in the sense that it can operate only under restrictive conditions. Here I discuss a route to adaptive evolvability that overcomes this challenge. Specifically, a recent evolution experiment showed that some mutations can enhance both fitness and evolvability through a combination of direct and indirect selection. Unrelated evidence from gene duplication and the evolution of gene regulation suggests that mutations with such dual effects may not be rare. Through such mutations, evolvability may increase at least in part because it provides an adaptive advantage. These observations suggest a research program on the adaptive evolution of evolvability, which aims to identify such mutations and to disentangle their direct fitness effects from their indirect effects on evolvability. If evolvability is itself adaptive, Darwinian evolution may have created more than life's diversity. It may also have helped create the very conditions that made the success of Darwinian evolution possible.

Competition for nutrients increases invasion resistance during assembly of microbial communities.

The assembly of microbial communities through sequential invasions of microbial species is challenging to study experimentally. Here, I used genome-scale metabolic models of multiple species to model community assembly. Each such model represents all known biochemical reactions that a species uses to build biomass from nutrients in the environment. Species interactions in such models emerge from first biochemical principles, either through competition for environmental nutrients, or through cross-feeding on metabolic by-products excreted by resident species. I used these models to study 250 community assembly sequences. In each such sequence, a community changes through successive species invasions. During the 250 assembly sequences, communities become more species-rich and invasion-resistant. Resistance against both constructive and destructive invasions - those that entail species extinction - is associated with high community productivity, high biomass, and low concentrations of unused carbon. Competition for nutrients outweighs the influence of cross-feeding on the growth rate of individual species. In a community assembly network of all communities that arise during the 250 assembly sequences, some communities occur more often than expected by chance. These include invasion resistant "attractor" communities with high biomass that arise late in community assembly and persist preferentially because of their invasion resistance. Genome-scale metabolic models can reveal generic properties of microbial communities that are independent of the resident species and the environment.