Global S&T Development Trend Analysis Platform of Resources and Environment
Light-driven sodium pumps actively transport small cations across cellular membranes(1). These pumps are used by microorganisms to convert light into membrane potential and have become useful optogenetic tools with applications in neuroscience. Although the resting state structures of the prototypical sodium pump Krokinobacter eikastus rhodopsin 2 (KR2) have been solved(2,3), it is unclear how structural alterations overtime allow sodium to be translocated against a concentration gradient. Here, using the Swiss X-ray Free Electron Laser(4), we have collected serial crystallographic data at ten pump-probe delays from femtoseconds to milliseconds. High-resolution structural snapshots throughout the KR2 photocycle show how retinal isomerization is completed on the femtosecond timescale and changes the local structure of the binding pocket in the early nanoseconds. Subsequent rearrangements and deprotonation of the retinal Schiff base open an electrostatic gate in microseconds. Structural and spectroscopic data, in combination with quantum chemical calculations, indicate that a sodium ion bind stransiently close to the retinal within one millisecond. In the last structural intermediate, at 20 milliseconds after activation, we identified a potential second sodium-binding site close to the extracellular exit. These results provide direct molecular insight into the dynamics of active cation transport across biological membranes.
Reverse genetics has been an indispensable tool to gain insights into viral pathogenesis and vaccine development. The genomes of large RNA viruses, such as those from coronaviruses, are cumbersome to clone and manipulate inEscherichia coliowing to the size and occasional instability of the genome(1-3). Therefore, an alternative rapid and robust reverse-genetics platform for RNA viruses would benefit the research community. Here we show the full functionality of a yeast-based synthetic genomics platform to genetically reconstruct diverse RNA viruses, including members of theCoronaviridae,FlaviviridaeandPneumoviridaefamilies. Viral subgenomic fragments were generated using viral isolates, cloned viral DNA, clinical samples or synthetic DNA, and these fragments were then reassembled in one step inSaccharomyces cerevisiaeusing transformation-associated recombination cloning to maintain the genome as a yeast artificial chromosome. T7 RNA polymerase was then used to generate infectious RNA to rescue viable virus. Using this platform, we were able to engineer and generate chemically synthesized clones of the virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)(4), which has caused the recent pandemic of coronavirus disease (COVID-19), in only a week after receipt of the synthetic DNA fragments. The technical advance that we describe here facilitates rapid responses to emerging viruses as it enables the real-time generation and functional characterization of evolving RNA virus variants during an outbreak.
A yeast-based synthetic genomics platform is used to reconstruct and characterize large RNA viruses from synthetic DNA fragments
Ultrahot giant exoplanets receive thousands of times Earth'
Absorption lines of iron in the dayside atmosphere of an ultrahot giant exoplanet disappear after travelling across the nightside, showing that the iron has condensed during its travel.
Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.
Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions(1-10), we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas(11) (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma