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Photosystem I and II (PSI and PSII) work together to convert solar energy into chemical energy. Whilst a lot of research has been done to unravel variability of PSII fluorescence in response to biotic and abiotic factors, the contribution of PSI to in vivo fluorescence measurements has often been neglected or considered to be constant. Furthermore, little is known about how the absorption and emission properties of PSI from different plant species differ. In this study, we have isolated PSI from five plant species and compared their characteristics using a combination of optical and biochemical techniques. Differences have been identified in the fluorescence emission spectra and at the protein level, whereas the absorption spectra were virtually the same in all cases. In addition, the emission spectrum of PSI depends on temperature over a physiologically relevant range from 280 to 298 K. Combined, our data show a critical comparison of the absorption and emission properties of PSI from various plant species.

Covalent organic frameworks (COFs) are porous materials with high surface areas, making them interesting for a large variety of applications including energy storage, gas separation, photocatalysis, and chemical sensing. Structural variation plays an important role in tuning COF properties. Next to the type of the building block core, bonding directionality, and linking chemistry, substitution of building blocks provides another level of synthetic control. Thorough characterization and comparison of various substitution patterns is relevant for the molecular engineering of COFs via rational design. To this end, we have systematically synthesized and characterized multiple combinations of several methylated and non-methylated building blocks to obtain a series of imine-based COFs. This includes the experimental assignment of the COF structure by solid-state NMR. By comparing the properties of all COFs, the following trends were found: (1) upon methylation of the aldehyde nodes, COFs show increased Brunauer-Emmett-Teller surface areas, reduced pore collapse, blue-shifted absorbance spectra, and ∼0.2 eV increases in their optical band gaps. (2) COFs with dimethylated amine linkers show a lower porosity. (3) In tetramethylated amine linkers, the COF porosity even further decreases, the absorbance spectra are clearly red-shifted, and smaller optical band gaps are obtained. Our study shows that methyl substitution patterns on COF building blocks are a handle to control the UV absorbance of the resulting frameworks.

Nanopores are versatile single-molecule sensors offering a simple label-free readout with great sensitivity. We recently introduced the nanopore electro-osmotic trap (NEOtrap) which can trap and sense single unmodified proteins for long times. The trapping is achieved by the electro-osmotic flow (EOF) generated from a DNA-origami sphere docked onto the pore, but thermal fluctuations of the origami limited the trapping of small proteins. Here, we use site-specific cholesterol functionalization of the origami sphere to firmly link it to the lipid-coated nanopore. We can lock the origami in either a vertical or horizontal orientation which strongly modulates the EOF. The optimized EOF greatly enhances the trapping capacity, yielding reduced noise, reduced measurement heterogeneity, an increased capture rate, and 100-fold extended observation times. We demonstrate the trapping of a variety of single proteins, including small ones down to 14 kDa. The cholesterol functionalization significantly expands the application range of the NEOtrap technology.

Single-molecule localization microscopy (SMLM) is a powerful technique for elucidating structure and dynamics in the life- and material sciences with sub-50 nm spatial resolution. The simultaneous acquisition of spectral information (spectrally resolved SMLM, sSMLM) enables multiplexing using spectrally distinct fluorophores or enable the probing of local chemical environments by using solvachromatic fluorophores such as Nile Red. Until now, the widespread utilisation of sSMLM was hampered by several challenges: an increased complexity of the optical detection pathway, limited software solutions for data analysis, lower accessible emitter densities or smaller field-of-views, and overall compromised spatio-spectral resolution. Here, we present a low-cost implementation of sSMLM that addresses these challenges. Using a blazed, low-dispersion transmission grating positioned close to the image plane here represented by the camera sensor, the +1st diffraction order is minimally elongated compared to the point spread function of the 0th order and can therefore be analysed using common subpixel single-molecule localization algorithms. The distance between both PSFs provides accurate information on the spectral properties of the emitter. The minimal excess width of 1st order PSFs enables a fivefold higher emitter density compared to other sSMLM approaches whilst achieving a spatio-spectral localization accuracy sufficient to discriminate between fluorophores whose peak emission are less than 15 nm apart as demonstrated using dSTORM, DNA-PAINT and smFRET. We provide an ImageJ/Fiji plugin (sSMLMAnalyzer) and suitable Matlab scripts for data analysis. We envision that our approach will find widespread use in super-resolution applications that rely on distinguishing spectrally different fluorophores under low photon conditions.

In chapter 2, we recorded AP shapes and underlying Na+ and K+ currents in human cortical pyramidal neurons and compared them to rodents. We found that not only the AP shape, but also the underlying currents have remarkable stability, even when firing hundreds of consecutive APs at frequencies of 60 Hz. We then argued that biophysical adaptations in voltage-gated sodium and potassium channels must be responsible, and tested this by characterizing the voltage-dependent properties of the Na+ and K+ currents. We find that human Na+ and K+ currents had different biophysical features than their mouse counterparts. Then we used in silico models and found that indeed, the observed gating properties result in more stable APs. Furthermore, the models with human-like channel biophysics were able to reliably encode a larger range of inputs than models with rodent-like biophysics. Based on this we concluded that adaptations in the biophysical gating of Na+ and K+ channels contribute to the computational properties of human neurons. Fast Spiking interneurons (FSINs) are specialized in fast input-to-output conversion. The whole neuron is filled with adaptations that support this fast function. Therefore, this is the perfect neuron to study when interested in the speed limits of neural processing. In the human cortex, neurons are spaced further apart to make space for all the elaborate dendritic and axonal trees, which are much more interconnected than in rodents. This could potentially slow down neural signaling, as signals take time to travel and become weaker and slower over distance. Yet neural signaling seems not to be slow in human neurons. In this chapter, we investigated whether and how human FSINs can retain their fast function. We first characterized the dendritic morphology of these neurons and found that indeed, their dendritic paths are much longer. However, when we made paired recordings we did not find a slowdown of input and output, indicating that some compensatory mechanism must be at play. This could not be explained by sodium channel gating, as we find similar sodium current properties in human and mouse FSINs. Using biophysical modeling we find that a combination of enlarged synaptic inputs, reduced dendritic complexity and fast outputs in human FSINs are responsible for conserving a fast signaling speed even over large distances. In this chapter, we take the concept of cellular properties as important determinant for computational power of neurons and see how that relates to the function of the brain as a whole. Although we know that genetics and thickness of the cortex play an important role in IQ differences between individual humans, we do not know it’s structural and functional basis. In this first-of-its-kind study, we obtained IQ scores as well as cellular measurements from individuals. We find that high IQ score does not only go together with large cortical thickness of the temporal cortex, but also with increased dendritic complexity and fast AP shapes. This provided the first evidence that human intelligence is related to complexity and speed of information exchange between individual neurons. Strikingly, the increase in cortical thickness with IQ was found to be purely specific to layers 2 and 3 of the cortex. Apparently, these cortical layers, which serve as important computational layers between input and output layers, are pivotal for intelligence. We then confirmed that high IQ relates to lower cell density, larger cells, more complex dendrites and faster AP signaling all specifically to the pyramidal neurons in layers 2 and 3. Furthermore, we find that verbal intelligence correlates with all these microstructural and cellular features, but only on left, not right, temporal cortex.

In chapter 2, we recorded AP shapes and underlying Na+ and K+ currents in human cortical pyramidal neurons and compared them to rodents. We found that not only the AP shape, but also the underlying currents have remarkable stability, even when firing hundreds of consecutive APs at frequencies of 60 Hz. We then argued that biophysical adaptations in voltage-gated sodium and potassium channels must be responsible, and tested this by characterizing the voltage-dependent properties of the Na+ and K+ currents. We find that human Na+ and K+ currents had different biophysical features than their mouse counterparts. Then we used in silico models and found that indeed, the observed gating properties result in more stable APs. Furthermore, the models with human-like channel biophysics were able to reliably encode a larger range of inputs than models with rodent-like biophysics. Based on this we concluded that adaptations in the biophysical gating of Na+ and K+ channels contribute to the computational properties of human neurons. Fast Spiking interneurons (FSINs) are specialized in fast input-to-output conversion. The whole neuron is filled with adaptations that support this fast function. Therefore, this is the perfect neuron to study when interested in the speed limits of neural processing. In the human cortex, neurons are spaced further apart to make space for all the elaborate dendritic and axonal trees, which are much more interconnected than in rodents. This could potentially slow down neural signaling, as signals take time to travel and become weaker and slower over distance. Yet neural signaling seems not to be slow in human neurons. In this chapter, we investigated whether and how human FSINs can retain their fast function. We first characterized the dendritic morphology of these neurons and found that indeed, their dendritic paths are much longer. However, when we made paired recordings we did not find a slowdown of input and output, indicating that some compensatory mechanism must be at play. This could not be explained by sodium channel gating, as we find similar sodium current properties in human and mouse FSINs. Using biophysical modeling we find that a combination of enlarged synaptic inputs, reduced dendritic complexity and fast outputs in human FSINs are responsible for conserving a fast signaling speed even over large distances. In this chapter, we take the concept of cellular properties as important determinant for computational power of neurons and see how that relates to the function of the brain as a whole. Although we know that genetics and thickness of the cortex play an important role in IQ differences between individual humans, we do not know it’s structural and functional basis. In this first-of-its-kind study, we obtained IQ scores as well as cellular measurements from individuals. We find that high IQ score does not only go together with large cortical thickness of the temporal cortex, but also with increased dendritic complexity and fast AP shapes. This provided the first evidence that human intelligence is related to complexity and speed of information exchange between individual neurons. Strikingly, the increase in cortical thickness with IQ was found to be purely specific to layers 2 and 3 of the cortex. Apparently, these cortical layers, which serve as important computational layers between input and output layers, are pivotal for intelligence. We then confirmed that high IQ relates to lower cell density, larger cells, more complex dendrites and faster AP signaling all specifically to the pyramidal neurons in layers 2 and 3. Furthermore, we find that verbal intelligence correlates with all these microstructural and cellular features, but only on left, not right, temporal cortex.

In nature, light is never constant, while in the controlled environments used for vertical farming, in vitro propagation, or plant production for scientific research, light intensity is often kept constant during the photoperiod. To investigate the effects on plant growth of varying irradiance during the photoperiod, we grew Arabidopsis thaliana under three irradiance profiles: a square-wave profile, a parabolic profile with gradually increasing and subsequently decreasing irradiance, and a regime comprised of rapid fluctuations in irradiance. The daily integral of irradiance was the same for all three treatments. Leaf area, plant growth rate, and biomass at time of harvest were compared. Plants grown under the parabolic profile had the highest growth rate and biomass. This could be explained by a higher average light-use efficiency for carbon dioxide fixation. Furthermore, we compared the growth of wild type plants with that of the PsbS-deficient mutant npq4. PsbS triggers the fast non-photochemical quenching process (qE) that protects PSII from photodamage during sudden increases in irradiance. Based mainly on field and greenhouse experiments, the current consensus is that npq4 mutants grow more slowly in fluctuating light. However, our data show that this is not the case for several forms of fluctuating light conditions under otherwise identical controlled-climate room conditions.

The work presented in this thesis describes a detailed investigation to understand the mechanism of lipid targeting antibiotics using an array of methods including ssNMR, advanced microscopy techniques, computational analysis, and biophysical and biochemical assays. Together, these methods enable a holistic description of the supramolecular mechanism of lipid-targeting antibiotics such as teixobactin or clovibactin. Chapter 1 introduces the current scenario antimicrobial resistance (AMR) and highlights the studies conducted on teixobactin to date. This chapter introduces the basics of ssNMR and other complimentary techniques. It also lays the foundation for the methodologies used in the following chapters to gain insights into the mechanism of lipid-targeting antibiotics, teixobactin and clovibactin. Chapter 2 is adapted from a study published in Nature Communications in 2020. Here we describe the mechanism of action of synthetic analogues of teixobactin, namely [R4L10] and [L10]. With the help of ssNMR studies, we could solve the structure of the complex formed between [R4L10]-teixobactin and its target, lipid II directly in membranes. Furthermore, we investigated the impact of the membrane composition on the mode of action of [R4L10]- teixobactin and demonstrate that the bacterial cell membrane affects the binding of the drug. Chapter 3 is adapted from a study published in Nature in 2022 where we describe a new dual mode of action for natural teixobactin. In this chapter, we determine the dual mechanism of teixobactin from an atomic to supramolecular scale using ssNMR, HS-AFM, and confocal microscopy. We present an atomically resolved ssNMR structure of the complex and elaborate on its evolution into fibrils and eventually micrometre-sized clusters which ultimately kill the bacteria. Based on our results we show that teixobactin ventures away from the classic 1-drug to 1-target ideology and uses a new type of antimicrobial action. Chapter 4 is adapted from a publication that is currently under review. This chapter emphasizes the discovery of a new antibiotic called clovibactin from the bacterial “dark matter.” We use our established methodology to study and elucidate the novel mechanism of clovibactin and showcase its multi-targeting action. Conclusively in Chapter 5, we showcase some recently acquired and unpublished data on the effect of anionic lipids on teixobactin’s mechanism of action and propose future studies which can be conducted to expand on the role of anionic membranes on the activity of lipid-targeting antibiotics. We also discuss how the efficient methodology developed can be useful in studying lipid-targeting antibiotics at different length scales under varying membrane compositions to provide a complete overview of their mechanism and help in designing better drugs to tackle the problem of AMR.

Arabidopsis thaliana plants were illuminated with far-red or blue light to induce respectively state 1 and state 2. The fluorescence decay kinetics was analysed to see which fraction of the excitation energy went to photosystem I vs photosystem II. Single chloroplasts were imaged in state 1 and state 2 to investigate the redistribution of excitation energy and the thylakoid macro-organisation. Data belonging to Figures 1-4 and SI Figures 1-6 of the article: " See readme for a detailed explanation

In mayonnaise, lipid and protein oxidation are closely related and the interplay between them is critical for understanding the chemical shelf-life stability of mayonnaise. This is in particular the case for comprehending the role of low-density lipoprotein (LDL) particles acting as a main emulsifier. Here, we monitored oxidation and the concomitant aggregation of LDLs by bright-field light microscopy and cryogenic transmission electron microscopy. We further probed the formation of protein radicals and protein oxidation by imaging the accumulation of a water-soluble fluorescent spin trap and protein autofluorescence. The effect of variation of pH and addition of EDTA on the accumulation of the spin trap validated that protein radicals were induced by lipid radicals. Our data suggests two main pathways of oxidative protein radical formation in LDL particles: (1) at the droplet interface, induced by lipid free radicals formed in oil droplets, and (2) in the continuous phase induced by an independent LDL-specific mechanism.

The growing world population and global increases in the standard of living both result in an increasing demand for food, feed and other plant-derived products. In the coming years, plant-based research will be among the major drivers ensuring food security and the expansion of the bio-based economy. Crop productivity is determined by several factors, including the available physical and agricultural resources, crop management, and the resource use efficiency, quality and intrinsic yield potential of the chosen crop. This review focuses on intrinsic yield potential, since understanding its determinants and their biological basis will allow to maximize the plant's potential in food and energy production. Yield potential is determined by a variety of complex traits that integrate strictly regulated processes and their underlying gene regulatory networks. Due to this inherent complexity, numerous potential targets have been identified that could be exploited to increase crop yield. These encompass diverse metabolic and physical processes at the cellular, organ and canopy level. We present an overview of some of the distinct biological processes considered to be crucial for yield determination that could further be exploited to improve future crop productivity.

International audience; To meet the increasing global demand for food, feed, fibre and other plant- derivedproducts, a steep increase in crop productivity is a scientifically and technicallychallenging imperative. The CropBooster- P project, a response to the H2020call ‘Future proofing our plants’, is developing a roadmap for plant research toimprove crops critical for the future of European agriculture by increasing cropyield, nutritional quality, value for non- food applications and sustainability.However, if we want to efficiently improve crop production in Europe and pri-oritize methods for crop trait improvement in the coming years, we need to takeinto account future socio- economic, technological and global developments, in-cluding numerous policy and socio- economic challenges and constraints. Basedon a wide range of possible global trends and key uncertainties, we developedfour extreme future learning scenarios that depict complementary future devel-opments. Here, we elaborate on how the scenarios could inform and direct fu-ture plant research, and we aim to highlight the crop improvement approachesthat could be the most promising or appropriate within each of these four futureworld scenarios. Moreover, we discuss some key plant technology options thatwould need to be developed further to meet the needs of multiple future learningscenarios, such as improving methods for breeding and genetic engineering. Inaddition, other diverse platforms of food production may offer unrealized poten-tial, such as underutilized terrestrial and aquatic species as alternative sources ofnutrition and biomass production. We demonstrate that although several meth-ods or traits could facilitate a more efficient crop production system in some ofthe scenarios, others may offer great potential in all four of the future learningscenarios. Altogether, this indicates that depending on which future we are head-ing toward, distinct plant research fields should be given priority if we are to meetour food, feed and non- food biomass production needs in the coming decades.

Despite research efforts toward improving crop photosynthetic energy conver-sion efficiencies over the past 40 years, photosynthetic efficiencies remain far from their theoretical maxima. A major challenge has been that plant photosyn-thesis is a complex process, controlled by many underlying genetic factors and highly dynamic in response to short- term environmental changes. Recent ap-proaches to improving photosynthesis involved model- based identification of the bottlenecks in photosynthesis followed by their genetic modification (GM). While these approaches were successful and inspirational, their dependency on the use of GM techniques may restrict their implementation in some jurisdictions. We therefore suggest greater research focus on a different, yet complementary, ap-proach to improving photosynthetic efficiency: the exploration and exploitation of natural genetic variation in photosynthesis. A substantial improvement in phe-notyping and genotyping technology over the past decade has highlighted natu-ral variation in photosynthetic sub- traits for crop and model species. However, a comprehensive understanding of all the factors responsible for photosynthetic limitations is still lacking. We therefore propose the use of high photosynthetic capacity species as models for the exploration of the physiological and genetic basis of high photosynthetic efficiency. While most high photosynthetic capacity species are not suitable as models due to complex genetics and evolutionary dis-tance from crops, we have identified Brassicaceae species Hirschfeldia incana (L.) Lagr.- Foss as a promising candidate. In this perspective paper, we describe and advocate the use of H. incana as a model for the exploration of high maximum CO2 assimilation rates (Pmax) found in some C3 species. We describe the basic biology and evolutionary history of the species and report preliminary data on its photosynthetic characteristics. Our findings suggest H. incana is an excellent model species for studies aiming at understanding natural genetic variation in photosynthetic efficiency.

Cyanobacteria carry out photosynthetic light-energy conversion using phycobiliproteins for light harvesting and the chlorophyll-rich photosystems for photochemistry. While most cyanobacteria only absorb visible photons, some of them can acclimate to harvest far-red light (FRL, 700–800 nm) by integrating chlorophyll f and d in their photosystems and producing red-shifted allophycocyanin. Chlorophyll f insertion enables the photosystems to use FRL but slows down charge separation, reducing photosynthetic efficiency. Here we demonstrate with time-resolved fluorescence spectroscopy that on average charge separation in chlorophyll-f-containing Photosystem II becomes faster in the presence of red-shifted allophycocyanin antennas. This is different from all known photosynthetic systems, where additional light-harvesting complexes increase the overall absorption cross section but slow down charge separation. This remarkable property can be explained with the available structural and spectroscopic information. The unique design is probably important for these cyanobacteria to efficiently switch between visible and far-red light.

Oxygenic photosynthesis is driven by light absorption in photosystem I (PSI) and photosystem II (PSII). A balanced excitation pressure between PSI and PSII is required for optimal photosynthetic efficiency. State transitions serve to keep this balance. If PSII is overexcited in plants and green algae, a mobile pool of light-harvesting complex II (LHCII) associates with PSI, increasing its absorption cross-section and restoring the excitation balance. This is called state 2. Upon PSI overexcitation, this LHCII pool moves to PSII, leading to state 1. Whether the association/dissociation of LHCII with the photosystems occurs between thylakoid grana and thylakoid stroma lamellae during state transitions or within the same thylakoid region remains unclear. Furthermore, although state transitions are thought to be accompanied by changes in thylakoid macro-organization, this has never been observed directly in functional leaves. In this work, we used confocal fluorescence lifetime imaging to quantify state transitions in single Arabidopsis (Arabidopsis thaliana) chloroplasts in folio with sub-micrometer spatial resolution. The change in excitation-energy distribution between PSI and PSII was investigated at a range of excitation wavelengths between 475 and 665 nm. For all excitation wavelengths, the PSI/(PSI + PSII) excitation ratio was higher in state 2 than in state 1. We next imaged the local PSI/(PSI + PSII) excitation ratio for single chloroplasts in both states. The data indicated that LHCII indeed migrates between the grana and stroma lamellae during state transitions. Finally, fluorescence intensity images revealed that thylakoid macro-organization is largely unaffected by state transitions. This single chloroplast in folio imaging method will help in understanding how plants adjust their photosynthetic machinery to ever-changing light conditions.

A comprehensive understanding of the time-dependent flow behavior of concentrated oil-in-water emulsions is of considerable industrial importance. Along with conventional rheology measurements, localized flow and structural information are key to gaining insight into the underlying mechanisms causing time variations upon constant shear. In this work, we study the time-dependent flow behavior of concentrated egg-yolk emulsions with (MEY) or without (EY) enzymatic modification and unravel the effects caused by viscous friction during shear. We observe that prolonged shear leads to irreversible and significant loss of apparent viscosity in both emulsion formulations at a mild shear rate. The latter effect is in fact related to a yield stress decay during constant shearing experiments, as indicated by the local flow curve measurements obtained by rheo-MRI. Concurrently, two-dimensional D-T2 NMR measurements revealed a decrease in the T2 NMR relaxation time of the aqueous phase, indicating the release of surface-active proteins from the droplet interface towards the continuous water phase. The combination of an increase in droplet diameter and the concomitant loss of proteins aggregates from the droplet interface leads to a slow decrease in yield stress.

Single-molecule fluorescence detection offers powerful ways to study biomolecules and their complex interactions. Here, nanofluidic devices and camera-based, single-molecule Förster resonance energy transfer (smFRET) detection are combined to study the interactions between plant transcription factors of the auxin response factor (ARF) family and DNA oligonucleotides that contain target DNA response elements. In particular, it is shown that the binding of the unlabeled ARF DNA binding domain (ARF-DBD) to donor and acceptor labeled DNA oligonucleotides can be detected by changes in the FRET efficiency and changes in the diffusion coefficient of the DNA. In addition, this data on fluorescently labeled ARF-DBDs suggest that, at nanomolar concentrations, ARF-DBDs are exclusively present as monomers. In general, the fluidic framework of freely diffusing molecules minimizes potential surface-induced artifacts, enables high-throughput measurements, and proved to be instrumental in shedding more light on the interactions between ARF-DBDs monomers and between ARF-DBDs and their DNA response element.

Aims: Dicarbonyl compounds contribute to the formation of advanced glycation endproducts (AGEs) and the development of insulin resistance and vascular complications. Dicarbonyl stress may already be detrimental in obesity. We evaluated whether diet-induced weight loss can effectively reverse dicarbonyl stress in abdominally obese men.Materials and methods: Plasma samples were collected from lean (n = 25) and abdominally obese men (n = 52) in the fasting state, and during a mixed meal test (MMT). Abdominally obese men were randomized to 8 weeks of dietary weight loss or habitual diet, followed by a second MMT. The a-dicarbonyls methylglyoxal (MGO), glyoxal (GO) and 3-deoxyglucosone (3-DG) and AGEs were measured by UPLC-MS/ MS. Skin autofluorescence (SAF) was measured using the AGE reader. T-tests were used for the crosssectional analysis and ANCOVA to assess the treatment effect.Results: Postprandial glucose, MGO and 3-DG concentrations were higher in obese men as compared to lean men (p < 0.05 for all). Fasting dicarbonyls, AGEs, and SAF were not different between lean and obese men. After the weight loss intervention, fasting MGO levels tended to decrease by 25 nmol/L (95%-CI:-51-0.5; p = 0.054). Postprandial dicarbonyls were decreased after weight loss as compared to the control group: iAUC of MGO decreased by 57% (5280 nmol/L.min; 95%-CI: 33-10526; p = 0.049), of GO by 66% (11,329 nmol/L.min; 95%-CI: 495-22162; p = 0.041), and of 3-DG by 45% (20,175 nmol/L.min; 95%-CI: 5351-35000; p = 0.009). AGEs and SAF did not change significantly after weight loss.Conclusion: Abdominal obesity is characterized by increased postprandial dicarbonyl stress, which can be reduced by a weight loss intervention. (C) 2021 The Authors. Published by Elsevier Ltd.

This protocol describes a signal-to-noise ratio (SNR) calibration and sample preparation method for solenoidal microcoils combined with biological samples, designed for high-resolution magnetic resonance imaging (MRI), also referred to as MR microscopy (MRM). It may be used at pre-clinical MRI spectrometers, demonstrated on Medicago truncatula root samples. Microcoils increase sensitivity by matching the size of the RF resonator to the size of the sample of interest, thereby enabling higher image resolutions in a given data acquisition time. Due to the relatively simple design, solenoidal microcoils are straightforward and cheap to construct and can be easily adapted to the sample requirements. Systematically, we explain how to calibrate new or home-built microcoils, using a reference solution. The calibration steps include: pulse power determination using a nutation curve; estimation of RF-field homogeneity; and calculating a volume-normalized signal-to-noise ratio (SNR) using standard pulse sequences. Important steps in sample preparation for small biological samples are discussed, as well as possible mitigating factors such as magnetic susceptibility differences. The applications of an optimized solenoid coil are demonstrated by high-resolution (13 x 13 x 13 μm3, 2.2 pL) 3D imaging of a root sample.

Chemical feedback between building block synthesis and their subsequent supramolecular self-assembly into nanostructures has profound effects on assembly pathways. Nature harnesses feedback in reaction-assembly networks in a variety of scenarios including virion formation and protein folding. Also in nanomaterial synthesis, reaction-assembly networks have emerged as a promising control strategy to regulate assembly processes. Yet, how chemical feedback affects the fundamental pathways of structure formation remains unclear. Here, we unravel the pathways of a templated reaction-assembly network that couples a covalent polymerization to an electrostatic coassembly process. We show how the supramolecular staging of building blocks at a macromolecular template can accelerate the polymerization reaction and prevent the formation of kinetically trapped structures inherent to the process in the absence of feedback. Finally, we establish a predictive kinetic reaction model that quantitatively describes the pathways underlying these reaction-assembly networks. Our results shed light on the fundamental mechanisms by which chemical feedback can steer self-assembly reactions and can be used to rationally design new nanostructures.

Turbidity poses a major challenge for the microscopic characterization of food systems. Local mismatches in refractive indices, for example, lead to significant image deterioration along sample depth. To mitigate the issue of turbidity and to increase the accessible optical resolution in food microscopy, we added adaptive optics (AO) and flat-field illumination to our previously published open microscopy framework, the miCube. In the detection path, we implemented AO via a deformable mirror to compensate aberrations and to modulate the emission wavefront enabling the engineering of point spread functions (PSFs) for single-molecule localization microscopy (SMLM) in three dimensions. As a model system for a non-transparent food colloid such as mayonnaise, we designed an oil-in-water emulsion containing the ferric ion binding protein phosvitin commonly present in egg yolk. We targeted phosvitin with fluorescently labelled primary antibodies and used PSF engineering to obtain two- and three-dimensional images of phosvitin covered oil droplets with sub 100 nm resolution. Our data indicated that phosvitin is homogeneously distributed at the interface. With the possibility to obtain super-resolved images in depth, our work paves the way for localizing biomacromolecules at heterogeneous colloidal interfaces in food emulsions. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 2)’.

Biomolecular systems, such as proteins, crucially rely on dynamic processes at the nanoscale. Detecting biomolecular nanodynamics is therefore key to obtaining a mechanistic understanding of the energies and molecular driving forces that control biomolecular systems. Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique to observe in real-time how a single biomolecule proceeds through its functional cycle involving a sequence of distinct structural states. Currently, this technique is fundamentally limited by irreversible photobleaching, causing the untimely end of the experiment and thus, a narrow temporal bandwidth of ≤ 3 orders of magnitude. Here, we introduce "DyeCycling", a measurement scheme with which we aim to break the photobleaching limit in smFRET. We introduce the concept of spontaneous dye replacement by simulations, and as an experimental proof-of-concept, we demonstrate the intermittent observation of a single biomolecule for one hour with a time resolution of milliseconds. Theoretically, DyeCycling can provide100-fold more information per single molecule than conventional smFRET. We discuss the experimental implementation of DyeCycling, its current and fundamental limitations, and specific biological use cases. Given its general simplicity and versatility, DyeCycling has the potential to revolutionize the field of time-resolved smFRET, where it may serve to unravel a wealth of biomolecular dynamics by bridging from milliseconds to the hour range.Supplementary material is available for this article at 10.1007/s12274-022-4420-5 and is accessible for authorized users.

Lipid oxidation is one of the main causes of degradation in food emulsions. It leads to the generation of off-flavors and a concomitant reduction in shelf-life of the food products. The multiscale complexity of lipid oxidation reactions in food emulsions has raised the need to develop new methodological approaches. In this chapter, we will discuss how the recent analytical advancements have opened new avenues for the identification and quantification of multiple key oxidation products and for the spatio-temporal resolution of the reactions. After shortly introducing the challenges related to lipid extraction prior to analysis, we will first focus on the use of electron spin resonance for the early assessment and of nuclear magnetic resonance for the simultaneous analysis of multiple oxidation products. Then, we will discuss the potential of chromatographic and mass spectrometry approaches to monitor non-volatile and volatile oxidation products and assess the contribution of minor surface-active lipid species. Finally, the recent developments in electron and fluorescence microscopy to monitor the structural changes associated with lipid oxidation and the localization of the reaction sites in emulsions will be discussed.

This chapter describes what photosynthetic light harvesting is, why it is needed, and how it works. Light absorption by two types of photosystems drives oxygenic photosynthesis. The light-harvesting capacity and efficiency of these photosystems depend on their structure, pigment composition, and number of pigments per photosystem. The structures of the photosystems are highly conserved throughout evolution. On the contrary, the antenna complexes, which are pigment-protein complexes that increase the light absorption, can be very different for different species. Light harvested by antenna pigments needs to be transferred from one pigment to the other to finally reach the reaction centre of the photosystem where the energy is used to drive charge separation. The rate of energy transfer depends on the distance, energy levels, and relative orientations of the pigments involved. The transfer of energy to the reaction centre competes with other excited-state decay processes in the pigment. As such, the quantum efficiency of excitation energy trapping is high when the transfer rate to the reaction centre is high, while the intrinsic decay rate of the pigment is low.

Photosynthesis powers nearly all life on Earth. Light absorbed by photosystems drives the conversion of water and carbon dioxide into sugars. In plants, photosystem I (PSI) and photosystem II (PSII) work in series to drive the electron transport from water to NADP+. As both photosystems largely work in series, a balanced excitation pressure is required for optimal photosynthetic performance. Both photosystems are composed of a core and light-harvesting complexes (LHCI) for PSI and LHCII for PSII. When the light conditions favor the excitation of one photosystem over the other, a mobile pool of trimeric LHCII moves between both photosystems thus tuning their antenna cross-section in a process called state transitions. When PSII is overexcited multiple LHCIIs can associate with PSI. A trimeric LHCII binds to PSI at the PsaH/L/O site to form a well-characterized PSI–LHCI–LHCII supercomplex. The binding site(s) of the “additional” LHCII is still unclear, although a mediating role for LHCI has been proposed. In this work, we measured the PSI antenna size and trapping kinetics of photosynthetic membranes from Arabidopsis (Arabidopsis thaliana) plants. Membranes from wild-type (WT) plants were compared to those of the ΔLhca mutant that completely lacks the LHCI antenna. The results showed that “additional” LHCII complexes can transfer energy directly to the PSI core in the absence of LHCI. However, the transfer is about two times faster and therefore more efficient, when LHCI is present. This suggests LHCI mediates excitation energy transfer from loosely bound LHCII to PSI in WT plants.

The repository contains the smFRET and SAXS data presented in the preprint https://doi.org/10.1101/2022.11.16.516730 (BioRxiv)

Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction.

The realisation of the full objectives of international policies targeting global food security and climate change mitigation, including the European Green Deal, United Nation’s Sustainable Development Goals (SDGs), the Paris Climate Agreement COP21 and transition away from a fossil-carbon industrial base to one that is more bio-based, requires that we (i) sustainably increase the yield, nutritional quality, and biodiversity of major crop species, (ii) select climate-ready crops that are adapted to future weather dynamic and (iii) increase the resource use efficiency of crops to preserve natural resources, such as fresh water and phosphate and reducing the environmental burden arising from the application of nitrogenous fertiliser. Advanced scientific knowledge and tools for research and crop breeding already provide an excellent platform to build on. A long-term Strategic Research Agenda now needs to be agreed and priorities set to deliver blueprints for climate resilient future-proofed crops. This strategy should then be implemented through an innovative collaborative approach that combines the joint knowledge base of the research and industrial communities, with multi-stakeholder involvement and strong support from policy makers. This white paper has been compiled from contributions from several experts across the field of plant sciences. The CropBooster-P project has developed this strategic research agenda for a crop improvement programme that will provide the genetic innovation to improve and future proof our crop plants. It builds a strong collaboration between plant scientists and modellers, physicists, soil scientists, engineers and coders, biomathematicians, agronomists, plant breeders and farmers. The goal is to exploit the largely untapped genetic diversity that exists within the wild relatives and ancient and heirloom varieties of our crop plants to improve our crops so they will be more resilient, high yielding, resource efficient, nutritious, and ready for the future climate of Europe. The knowledge and technology to reach this goal springs from the transformative developments that have occurred in the last 20 years in genomics, phenomics, crop sciences, molecular plant sciences, agronomy, and plant breeding.

Raw data for our publication "Non-Invasive Rheo-MRI Study of Egg Yolk-Stabilized Emulsions: Yield Stress Decay and Protein Release", including MRI (Paravision) and D-T2 maps (Topspin) datasets, rheological measurements (ASCII) and MATLAB scripts organised corresponding to each figure in the paper.

Light absorbed by chlorophylls of Photosystems II and I drives oxygenic photosynthesis. Light-harvesting complexes increase the absorption cross-section of these photosystems. Furthermore, these complexes play a central role in photoprotection by dissipating the excess of absorbed light energy in an inducible and regulated fashion. In higher plants, the main light-harvesting complex is trimeric LHCII. In this work, we used CRISPR/Cas9 to knockout the five genes encoding LHCB1, which is the major component of LHCII. In absence of LHCB1, the accumulation of the other LHCII isoforms was only slightly increased, thereby resulting in chlorophyll loss, leading to a pale green phenotype and growth delay. The Photosystem II absorption cross-section was smaller, while the Photosystem I absorption cross-section was unaffected. This altered the chlorophyll repartition between the two photosystems, favoring Photosystem I excitation. The equilibrium of the photosynthetic electron transport was partially maintained by lower Photosystem I over Photosystem II reaction center ratio and by the dephosphorylation of LHCII and Photosystem II. Loss of LHCB1 altered the thylakoid structure, with less membrane layers per grana stack and reduced grana width. Stable LHCB1 knockout lines allow characterizing the role of this protein in light harvesting and acclimation and pave the way for future in vivo mutational analyses of LHCII.

Raw data

The overall process of photosynthesis requires the integrated activity of a network of subprocesses. Efficient and effective integration is important because carbon dioxide fixation, perhaps the most crucial activity of photosynthesis, arises from the combined activity of linked reactions in the thylakoid membranes and chloroplast stroma. Understanding how the various constituent processes of photosynthesis work together is important is not only an important question in plant physiology but is also at the heart of understanding the overall light-use efficiency of photosynthesis and the diversity of photosynthetic activities encountered in nature. There is no one single rate or activity of photosynthesis. Rather the process is very variable and highly responsive to the environment. This variability is part of ecological specialisation and optimisation, and the environmental dependence of photosynthesis (something which is still 'work in progress' seems to reflect compromises between maximising the light (and other resource) efficiencies of photosynthesis on the one hand, and protecting photosynthesis from damage largely due to the formation of reactive oxygen species. It is now widely recognised that how photosynthesis responds to environmental fluctuations is an essential part of operation. The physical environment of the plant and its leaves (e.g. temperature, humidity, carbon dioxide levels, and especially irradiance-this is not a complete list) changes over many time scales. These fluctuations are now seen to be the cause of increases in photosynthetic inefficiency beyond that encountered when photosynthesis is allowed to adjust and reach a steady-state optimum. Responses to rapid fluctuations in irradiance, which are physiological in nature, are because of their relative slowness in comparison to the speed at which irradiance can change now seen to be major source of increased short-term photosynthetic inefficiency in the field. Consequently, it is now widely considered that a complete understanding of the operation and regulation of photosynthesis must take into account the regulation of photosynthesis in response to environmental fluctuations. In this chapter, we will introduce something of the regulation of photosynthesis that occurs in response to changes in irradiance.The complexity of photosynthesis is best encapsulated by means of modes, and we will also introduce the use of models in photosynthesis.

Model-free phasor image analysis, well established in fluorescence lifetime imaging and only recently applied to qMRI $${T}_{2}$$ T 2 data processing, is here adapted and validated for myocardial qMRI $${T}_{1}$$ T 1 mapping. Contrarily to routine mono-exponential fitting procedures, phasor enables mapping the lifetime information from all image voxels to a single plot, without resorting to any regression fitting analysis, and describing multi-exponential qMRI decays without biases due to violated modelling assumptions. In this feasibility study, we test the performance of our recently developed full-harmonics phasor method for unravelling partial-volume effects, motion or pathological tissue alteration, respectively on a numerically-simulated dataset, a healthy subject scan, and two pilot patient datasets. Our results show that phasor analysis can be used, as alternative method to fitting analysis or other model-free approaches, to identify motion artifacts or partial-volume effects at the myocardium-blood interface as characteristic deviations, or delineations of scar and remote myocardial tissue in patient data.

Photosynthesis is one of the last plant traits in which there is significant room for further improvement in staple food crops. In the past decade, an increasing number of studies report that natural genetic variation is a promising route to improve photosynthesis traits in a large number of plant species. Most of these studies involve the use of analysing the genetic architecture of photosynthesis in diversity panels through genome-wide association studies. These are collections of model plant accessions exhibiting high diversity. However, as thousands of genes encode for proteins that locate to the chloroplasts alone, determining the exact alleles that can be used to breed for improved traits is difficult. This makes photosynthesis a highly complex trait to decipher. Bi-parental mapping populations derived from parental genotypes exhibiting contrasting phenotypes offer a simplified genetic architecture over diversity panels. Such populations also offer a good starting point to test novel photosynthesis traits and quantitative trait loci in isogenic backgrounds. In addition, chromosome substitution line (CSL-)populations are a novel type of bi-parental population with potential for high mapping power. In this work, three different bi-parental mapping populations, a RIL, an F2 and a CSL-population were used to study a variety of photosynthesis traits under various (fluctuating) light- and environmental conditions. The scientific model plant Arabidopsis thaliana was used here, because of its compact leaf architecture, fast growth architecture and ease of generating new genetic mapping populations. This study highlights a role for copy number variation in sterol biosynthesis genes to affect photosynthesis, presents the discovery and utility of large effect size QTLs for photosynthetic acclimation under high light conditions and describes a novel approach to screening mapping populations for productivity under fluctuating light conditions. Additionally, as CSL-populations are a novel genetic mapping type, developmental and analytical strategies have been developed to efficiently use them. Together, this study demonstrates the high QTL detection power of bi-parental mapping populations to explore genes and methodology to increase photosynthesis efficiency in plants. The genes and methods as described in this work should aid those interested in seeking ways to further enhance photosynthesis in crops, as well as provide a strategic framework to efficiently make use of chromosome substitution lines in plant breeding and quantitative genetic analyses.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

The data in this dataset accompanies the various figures present in the publication 'Enabling spectrally resolved single-molecule localization microscopy at high emitter densities'. Contained are tiff files used to create the figures 2-4 and Supplementary figures 1 and 2, as well as csvs after processed with the steps described in the paper (and contained in protocol text files).

A microscope includes a light source, a sample holder, an optical imaging system and a digital image sensor. The sample holder is arranged for holding a sample containing spectral emitters with specific emission profiles. The light source is configured for emitting a light beam for excitation of emitters in the sample. The optical imaging system is arranged for collecting radiation from emitters in the sample and imaging an emitters' image from the collected radiation through the optical imaging system on the digital image sensor. The microscope includes a diffractive optical element mounted directly in front of the digital image sensor at a first distance. The diffractive optical element is configured for receiving the emitters' image and creating a diffraction pattern thereof of at least two beams of different order. The first distance is chosen such that the at least two beams are directly projected on the digital image sensor.

Source data used in the manuscript: Orientation-locked DNA origami improves single-protein trapping in the NEOtrap The measurements were implemented in 600 KHM buffer under the bias voltage of 100 mV. Names of these files specify the trapped protein's name with corresponding measurement conditions, i.e., bare origami sphere, Cholesterol functionalized sphere in vertical configuration, and Cholesterol functionalized sphere in horizontal configuration.

International audience; The world needs more than double its current agricultural productivity by 2050 to produce enough food and feed, as well as to provide feedstock for the bioeconomy. These future increases will not only need to be sustainable but also need to compromise the nutritional quality, and ideally also need to decrease greenhouse gas emissions and increase carbon sequestration to help mitigate the consequences of global climate change. These challenges could be tackled by developing and integrating new future-proof crops into our food system. The H2020 CropBooster-P project sets out plant-centered breeding approaches guided by a broad socioeconomic and societal support. First, the potential approaches for breeding crops with sustainably increased yields adapted to the future climate of Europe are identified. These crop-breeding options are subsequently prioritized and their adoption considered by experts across the agri-food system and the wider public, taking into account environmental, economic and other technical criteria. In this way, a specific research agenda to future-proof our crops was developed, supported by an eventual implementation plan.

Identifying genomic variants that influence photosynthetic rate is challenging, due to a lack of genomic resources for suitable plants models. We aimed to solve this need by sequencing and assembling the genome of the plant Hirschfeldia incana. This species has shown high photosynthetic efficiency at high levels of irradiance and is a member of the well-studied Brassicaceae family, for which extensive genetic and genomic resources are available. Assembling a high-quality reference genome of H. incana allows comparative genomics to elucidate the genomic nature of photosynthetic efficiency.

Biomolecular systems, such as proteins, crucially rely on dynamic processes at the nanoscale. Detecting biomolecular nanodynamics is therefore key to obtaining a mechanistic understanding of the energies and molecular driving forces that control biomolecular systems. Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique to observe in real-time how a single biomolecule proceeds through its functional cycle involving a sequence of distinct structural states. Currently, this technique is fundamentally limited by irreversible photobleaching, causing the untimely end of the experiment and thus, a prohibitively narrow temporal bandwidth of ≤ 3 orders of magnitude. Here, we introduce ‘DyeCycling’, a measurement scheme with which we aim to break the photobleaching limit in single-molecule FRET. We introduce the concept of spontaneous dye replacement by simulations, and as an experimental proof-of-concept, we demonstrate the intermittent observation of a single biomolecule for one hour with a time resolution of milliseconds. Theoretically, DyeCycling can provide >100-fold more information per single molecule than conventional smFRET. We discuss the experimental implementation of DyeCycling, its current and fundamental limitations, and specific biological use cases. Given its general simplicity and versatility, DyeCycling has the potential to revolutionize the field of time-resolved smFRET, where it may serve to unravel a wealth of biomolecular dynamics by bridging from milliseconds to the hour range.

The CropBooster Program proposes an exciting strategic Research and Innovation Roadmap that builds on current advances in plant science and crop research. This will combine research excellence distributed within the European Research Area with professional expertise from plant breeders, growers and the Bioeconomy value chains. The Program will deliver breakthrough translational research and deliver blueprints for future-proofed crops designed to address emerging environmental threats to crop production and improve food security and the sustainable supply of plant-based materials. The CropBooster Program science-based “blueprints” for improved crop plants will address key critical challenges including: More efficient use of resources or inputs in agriculture (in the case of CropBooster the primary resources are water, and nutrients (e.g. Nitrogen and Phosphorus) Increasing crop yields to provide sufficient food for the growing global population. This population is expected to have an increased per capita food demand, estimates suggest crop production may need to increase by up to 110% Transitioning to a more sustainable bioeconomy to meet increasing demands for biobased materials and products. New feedstock crops and cell factories will be better designed to meet the needs of processors and end users. The adaptation of crops to be resilient to climate change: this will affect different regions in Europe differently including changes in average climate and increasing weather extremes. Increasing the nutritional value and other quality parameters of future crops. The mitigation of greenhouse gases. Carbon dioxide, fixed by photosynthesis, can be sequestered within plants or below ground as soil organic carbon. The need to reserve space for natural ecosystems and therefore to increase yields and sustainability without any expansion of the area of croplands., This document has benefited from contributions from multiple experts – the authoring team and main contributors are listed in Section 12.1. This document would not have been possible without their generous support and contributions.

Processing of milk involves heating, which can modify the structure and digestibility of its proteins. In vitro models are useful for studying protein digestion. However, validating these models with in vivo data is challenging. Here, we non-invasively monitor in vitro gastric milk protein digestion by protein-water chemical exchange detected by 1H nuclear magnetic resonance (NMR) magnetization transfer (MT). We obtained either a fitted composite exchange rate (CER) with a relative standard error of ≤10% or the MT ratio (MTR) of the intensity without or with an off-resonance saturation pulse, from just a single spectral acquisition. Both CER and MTR, affected by the variation in the amount of semi-solid protons, decreased during in vitro gastric digestion in agreement with standard protein content analyses. The decrease was slower in heated milk, indicating slower breakdown of the coagulum. Our results open the way to future quantification of protein digestion in vivo by MRI.