Protein crystal structure obtained at 2.9 ? resolution from injecting bacterial cells into an X-ray free-electron laser beam

It has long been known that toxins produced by Bacillus thuringiensis (Bt) are stored in the bacterial cells in crystalline form. Here we describe the structure determination of the Cry3A toxin found naturally crystallized within Bt cells. When whole Bt cells were streamed into an X-ray free-electron laser beam we found that scattering from other cell components did not obscure diffraction from the crystals. The resolution limits of the best diffraction images collected from cells were the same as from isolated crystals. The integrity of the cells at the moment of diffraction is unclear; however, given the short time (∼5 µs) between exiting the injector to intersecting with the X-ray beam, our result is a 2.9-Å-resolution structure of a crystalline protein as it exists in a living cell. The study suggests that authentic in vivo diffraction studies can produce atomic-level structural information.The advent of X-ray free-electron lasers (XFELs) has made it possible to obtain atomic resolution macromolecular structures from crystals with sizes approximating only 1/60th of the volume of a single red blood cell. Brief, intense pulses of coherent X-rays, focused on a spot of 3-μm diameter, have produced 1.9-Å-resolution diffraction data from a stream of lysozyme crystals, each crystal no bigger than 3 μm³ (1). A stream of crystals, not just one crystal, is required to collect the many tens of thousands of diffraction patterns that compose a complete data set. No single crystal can contribute more than one diffraction pattern because the XFEL beam is so intense and the crystals so small that the crystals are typically vaporized after a single pulse. Impressively, a photosystem I crystal no bigger than 10 unit cells (300 nm) on an edge produced observable subsidiary diffraction peaks between Bragg reflections, details which would be unobservable from conventionally sized crystals (2). With this new ability to collect diffraction patterns from crystals of unprecedentedly small dimensions, it is conceivable that high-resolution diffraction data could be collected from crystals in vivo. The structure obtained in this manner would be unaltered from that occurring naturally in a living cell, free from distortion that might otherwise potentially arise from nonphysiological conditions imposed by recrystallization. A practical advantage would also be gained by eliminating the need for a protein purification step, whether the in vivo grown crystals were naturally, or heterologously expressed (3).The nascent field of serial femtosecond crystallography (SFX) has published results on nine different macromolecular systems since its inception in 2009 (3, 9). The crystals for this study were not grown in artificial crystallization chambers as has been the protocol of conventional macromolecular crystallography since the 1950s. Instead, crystals were grown in cells. Specifically, they were grown in Sf9 insect cells, heterologously expressing Trypanosoma brucei cathepsin B. These in vivo-grown crystals were used for the XFEL diffraction experiment. To this end, the cells were lysed and the crystals were extracted before injecting them in the XFEL beam for data collection. This last purification step seems to be the only major departure from our goal of obtaining high-resolution structural information from crystal inclusions in vivo, without requiring the crystal to be extracted from the cell that assembled it. Here we attempt to go one step further than previous studies—to record diffraction from crystals within living cells.

Table 1.

SFX publications from XFEL sources to date

Longitudinal growth on an everolimus‐ versus an MMF‐based steroid‐free immunosuppressive regimen in paediatric renal transplant recipients

Concerns have been raised that mammalian target of rapamycin inhibitors in pediatric transplant recipients might interfere with longitudinal bone growth by inhibition of growth factor signaling and growth plate chondrocyte proliferation. We therefore undertook a prospective nested, case‐control study on longitudinal growth over 2 years in steroid‐free pediatric renal transplant recipients. Fourteen patients on a steroid‐free maintenance immunosuppressive regimen consisting of low‐dose everolimus (EVR) in conjunction with low‐dose cyclosporine (CsA) were compared to a matched cohort of 14 steroid‐free patients on a standard dose mycophenolate mofetil (MMF) regimen in conjunction with a standard dose calcineurin inhibitor (CNI). The mean change in height standard deviation (SD) score in the first study year was 0.31 ± 0.71 SD score in the EVR group compared to 0.31 ± 0.64 SD score in the MMF group (P = 0.20). For the entire study period of 2 years, the change in height SD score in the EVR group was 0.43 ± 0.81 SDS compared to 0.75 ± 0.85 SDS in the MMF group (P = 0.32). The percentage of prepubertal patients experiencing catch‐up growth, defined as an increase in height SD score ≥0.5 in 2 years, was similar in the EVR group (5/8, 65%) and the MMF group (6/8, 75%; P = 1.00). Longitudinal growth over 2 years in steroid‐free pediatric patients on low‐dose EVR and CsA is not different to that of a matched steroid‐free control group on an immunosuppressive regimen with standard‐dose CNI and MMF. Hence, low‐dose EVR does not appear to negatively impact short‐term growth in pediatric renal transplant recipients.     

Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy

Within artificial intelligence, machine learning (ML) efforts in radiation oncology have augmented the transition from generalized to personalized treatment delivery. Although their impact on quality and safety of radiation therapy has been limited, they are increasingly being used throughout radiation therapy workflows. Various data-driven approaches have been used for outcome prediction, CT simulation, clinical decision support, knowledge-based planning, adaptive radiation therapy, plan validation, machine quality assurance, and process quality assurance; however, there are many challenges that need to be addressed with the creation and usage of ML algorithms as well as the interpretation and dissemination of findings. In this review, the authors present current applications of ML in radiation oncology quality and safety initiatives, discuss challenges faced by the radiation oncology community, and suggest future directions.     

The Effect of the Activation Process and Metal Oxide Addition (CaO,MgO, SrO) on the Catalytic and Physicochemical Properties of Natural Zeolite in Transesterification Reaction

This work provides valuable information about unexplored catalytic systems tested in the transesterification reaction of vegetable oil with methanol. It was demonstrated that natural zeolite treatment leads to enhanced catalytic activity and yield of biodiesel production. The activation of the catalytic material in a mixture of 5% H₂–95% Ar resulted in an improvement of the values of the TG conversion and fatty acid methyl esters (FAME) yield. In addition, it was proven that the incorporation of CaO, MgO and SrO oxides onto the natural zeolite surface improves the TG conversion and FAME yield values in the transesterification reaction.