| 1. |
- Ayyer, Kartik, et al.
(författare)
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3D diffractive imaging of nanoparticle ensembles using an x-ray laser
- 2021
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Ingår i: Optica. - : Optical Society of America. - 2334-2536. ; 8:1, s. 15-23
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Tidskriftsartikel (refereegranskat)abstract
- Single particle imaging at x-ray free electron lasers (XFELs) has the potential to determine the structure and dynamics of single biomolecules at room temperature. Two major hurdles have prevented this potential from being reached, namely, the collection of sufficient high-quality diffraction patterns and robust computational purification to overcome structural heterogeneity. We report the breaking of both of these barriers using gold nanoparticle test samples, recording around 10 million diffraction patterns at the European XFEL and structurally and orientationally sorting the patterns to obtain better than 3-nm-resolution 3D reconstructions for each of four samples. With these new developments, integrating advancements in x-ray sources, fast-framing detectors, efficient sample delivery, and data analysis algorithms, we illuminate the path towards sub-nano meter biomolecular imaging. The methods developed here can also be extended to characterize ensembles that are inherently diverse to obtain their full structural landscape. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License.
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| 2. |
- Barty, A., et al.
(författare)
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Self-terminating diffraction gates femtosecond X-ray nanocrystallography measurements
- 2012
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Ingår i: Nature Photonics. - 1749-4885 .- 1749-4893. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- X-ray free-electron lasers have enabled new approaches to the structural determination of protein crystals that are too small or radiation-sensitive for conventional analysis1. For sufficiently short pulses, diffraction is collected before significant changes occur to the sample, and it has been predicted that pulses as short as 10 fs may be required to acquire atomic-resolution structural information1, 2, 3, 4. Here, we describe a mechanism unique to ultrafast, ultra-intense X-ray experiments that allows structural information to be collected from crystalline samples using high radiation doses without the requirement for the pulse to terminate before the onset of sample damage. Instead, the diffracted X-rays are gated by a rapid loss of crystalline periodicity, producing apparent pulse lengths significantly shorter than the duration of the incident pulse. The shortest apparent pulse lengths occur at the highest resolution, and our measurements indicate that current X-ray free-electron laser technology5 should enable structural determination from submicrometre protein crystals with atomic resolution.
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| 3. |
- Bellisario, Alfredo
(författare)
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Deep learning assisted phase retrieval and computational methods in coherent diffractive imaging
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, advances in Artificial Intelligence and experimental techniques have revolutionized the field of structural biology. X-ray crystallography and Cryo-EM have provided unprecedented insights into the structures of biomolecules, while the unexpected success of AlphaFold has opened up new avenues of investigation. However, studying the dynamics of proteins at high resolution remains a significant obstacle, especially for fast dynamics. Single-particle imaging (SPI) or Flash X-ray Imaging (FXI) is an emerging technique that may enable the mapping of the conformational landscape of biological molecules at high resolution and fast time scale. This thesis discusses the potential of SPI/FXI, its challenges, recent experimental successes, and the advancements driving its development. In particular, machine learning and neural networks could play a vital role in fostering data analysis and improving SPI/FXI data processing. In Paper I, we discuss the problem of noise and detector masks in collecting FXI data. I simulated a dataset of diffraction patterns and used it to train a Convolutional Neural Network (U-Net) to restore data by denoising and filling in detector masks. As a natural continuation of this work, I trained another machine learning model in Paper II to estimate 2D protein densities from diffraction intensities. In the final chapter, corresponding to Paper III, we discuss another experimental method, time-resolved Small Angle X-ray Scattering (SAXS), and a new algorithm recently developed for SAXS data, the DENsity from Solution Scattering (DENSS) algorithm. I discuss the potential of DENSS in time-resolved SAXS and its application for structural fitting of AsLOV2, a Light-Oxygen-Voltage (LOV) protein domain from Avena sativa.
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| 4. |
- Bellisario, Alfredo, et al.
(författare)
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Deep learning phase retrieval in X-ray single-particle imaging and object support from autocorrelations
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Phase retrieval is an important optimization problem that occurs, for example, in the analysis of coherent diffraction patterns from isolated proteins. All iterative algorithms employed for phase retrieval in this context require some a priori knowledge of the object, usually in the form of a support that describes the extent of the particle. Phase retrieval is a time-consuming task that can often fail, particularly if the support is too loose or of bad quality. In this paper, we present a neural network that can produce low-resolution estimates of the phased object in a fraction of the time that it takes for a full phase retrieval and that can also successfully be used as support for further analysis. Our network is trained on simulated data from biological macromolecules and is thus tailored to the type of data seen in a typical CDI experiment. Other approaches to support finding either require very accurate data without missing regions or require the full phase-retrieval algorithm to be run for a long time. Our network could both speed up off-line analysis, and provide real-time feedback during data collection.
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| 5. |
- Bellisario, Alfredo, et al.
(författare)
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Noise reduction and mask removal neural network for X-ray single-particle imaging
- 2022
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Ingår i: Journal of applied crystallography. - : International Union of Crystallography (IUCr). - 0021-8898 .- 1600-5767. ; 55, s. 122-132
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Tidskriftsartikel (refereegranskat)abstract
- Free-electron lasers could enable X-ray imaging of single biological macro-molecules and the study of protein dynamics, paving the way for a powerful new imaging tool in structural biology, but a low signal-to-noise ratio and missing regions in the detectors, colloquially termed 'masks', affect data collection and hamper real-time evaluation of experimental data. In this article, the challenges posed by noise and masks are tackled by introducing a neural network pipeline that aims to restore diffraction intensities. For training and testing of the model, a data set of diffraction patterns was simulated from 10 900 different proteins with molecular weights within the range of 10-100 kDa and collected at a photon energy of 8 keV. The method is compared with a simple low-pass filtering algorithm based on autocorrelation constraints. The results show an improvement in the mean-squared error of roughly two orders of magnitude in the presence of masks compared with the noisy data. The algorithm was also tested at increasing mask width, leading to the conclusion that demasking can achieve good results when the mask is smaller than half of the central speckle of the pattern. The results highlight the competitiveness of this model for data processing and the feasibility of restoring diffraction intensities from unknown structures in real time using deep learning methods. Finally, an example is shown of this preprocessing making orientation recovery more reliable, especially for data sets containing very few patterns, using the expansion-maximization-compression algorithm.
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| 6. |
- Daurer, Benedikt J., et al.
(författare)
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Ptychographic wavefront characterization for single-particle imaging at x-ray lasers
- 2021
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Ingår i: Optica. - : Optical Society of America. - 2334-2536. ; 8:4, s. 551-562
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Tidskriftsartikel (refereegranskat)abstract
- A well-characterized wavefront is important for many x-ray free-electron laser (XFEL) experiments, especially for single-particle imaging (SPI), where individual biomolecules randomly sample a nanometer region of highly focused femtosecond pulses. We demonstrate high-resolution multiple-plane wavefront imaging of an ensemble of XFEL pulses, focused by Kirkpatrick–Baez mirrors, based on mixed-state ptychography, an approach letting us infer and reduce experimental sources of instability. From the recovered wavefront profiles, we show that while local photon fluence correction is crucial and possible for SPI, a small diversity of phase tilts likely has no impact. Our detailed characterization will aid interpretation of data from past and future SPI experiments and provides a basis for further improvements to experimental design and reconstruction algorithms.
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| 7. |
- Ekeberg, Tomas, 1983-, et al.
(författare)
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Data requirements for single-particle diffractive imaging
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Single-shot diffractive imaging with ultra-short and very intense coherent X-ray pulses has become a routine experimental technique at new free-electron-laser facilities. Extension to three-dimensional imaging requires many diffraction pat- terns from identical objects captured in different orientations. These can then be combined into a full three-dimensional Fourier transform of the object. The ori- entation of the particle intercepted by the pulsed X-ray beam is usually unknown. This makes it hard to predict the number of patterns required to fully cover the Fourier space. In this paper we provide formulae to estimate the number of expo- sures required to achieve a given coverage of Fourier space as a function of parti- cle size, resolution and shot noise.
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| 8. |
- Ekeberg, Tomas, 1983-
(författare)
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Flash Diffractive Imaging in Three Dimensions
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- During the last years we have seen the birth of free-electron lasers, a new type of light source ten billion times brighter than syncrotrons and able to produce pulses only a few femtoseconds long. One of the main motivations for building these multi-million dollar machines was the prospect of imaging biological samples such as proteins and viruses in 3D without the need for crystallization or staining. This thesis contains some of the first biological results from free-electron lasers.These results include 2D images, both of whole cells and of the giant mimivirus and also con- tains a 3D density map of the mimivirus assembled from diffraction patterns from many virus particles. These are important proof-of-concept experiments but they also mark the point where free-electron lasers start to produce biologically relevant results. The most noteworthy of these results is the unexpectedly non-uniform density distribution of the internals of the mimivirus.We also present Hawk, the only open-source software toolkit for analysing single particle diffraction data. The Uppsala-developed program suite supports a wide range fo algorithms and takes advantage of Graphics Processing Units which makes it very computationally efficient.Last, the problem introduced by structural variability in samples is discussed. This includes a description of the problem and how it can be overcome, and also how it could be turned into an advantage that allows us to image samples in all of their conformational states.
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| 9. |
- Ekeberg, Tomas, 1983-, et al.
(författare)
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Observation of a single protein by ultrafast X-ray diffraction
- 2024
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Ingår i: Light. - : Springer Nature. - 2095-5545 .- 2047-7538. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- The idea of using ultrashort X-ray pulses to obtain images of single proteins frozen in time has fascinated and inspired many. It was one of the arguments for building X-ray free-electron lasers. According to theory, the extremely intense pulses provide sufficient signal to dispense with using crystals as an amplifier, and the ultrashort pulse duration permits capturing the diffraction data before the sample inevitably explodes. This was first demonstrated on biological samples a decade ago on the giant mimivirus. Since then, a large collaboration has been pushing the limit of the smallest sample that can be imaged. The ability to capture snapshots on the timescale of atomic vibrations, while keeping the sample at room temperature, may allow probing the entire conformational phase space of macromolecules. Here we show the first observation of an X-ray diffraction pattern from a single protein, that of Escherichia coli GroEL which at 14 nm in diameter is the smallest biological sample ever imaged by X-rays, and demonstrate that the concept of diffraction before destruction extends to single proteins. From the pattern, it is possible to determine the approximate orientation of the protein. Our experiment demonstrates the feasibility of ultrafast imaging of single proteins, opening the way to single-molecule time-resolved studies on the femtosecond timescale.
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| 10. |
- Ekeberg, Tomas, 1983-, et al.
(författare)
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Three-dimensional structure determination with an X-ray laser
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Three-dimensional structure determination of a non-crystalline virus has been achieved from a set of randomly oriented continuous diffraction patterns captured with an X-ray laser. Intense, ultra-short X-ray pulses intercepted a beam of single mimivirus particles, producing single particle X-ray diffraction patterns that are assembled into a three-dimensional amplitude distribution based on statistical consistency. Phases are directly retrieved from the assembled Fourier distribution to synthesize a three-dimensional image. The resulting electron density reveals a pseudo-icosahedral asymmetric virion structure with a compartmentalized interior, within which the DNA genome occupies only about a fifth of the volume enclosed by the capsid. Additional electron microscopy data indicate the genome has a chromatin-like fiber structure that has not previously been observed in a virus.
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