Nine best papers published in 2019 selected by cell Journal

January 13, 2020 / BIOON / - -- annual cell best series is finally out On January 6, 2020, cell Journal (the latest impact factor is 36.216) has evaluated 9 "best papers" from the papers published at the end of 2018 and 2019 They are Philipp Keller team of Howard Hughes Medical Research Institute in the United States developed a new intelligent microscope to observe the development of embryos in living mice at the four-dimensional level; predict pre mRNA splicing from the original sequence by using deep learning; Xue Tian group of China University of science and technology used nano technology Technology enables mammals to see infrared rays; transcription factors activate genes through the phase separation ability of their activation domains; thousands of new microbial species have been revealed in the largest study of human microbiome so far; a new generation of immunosuppressive checkpoint inhibitors has been developed: nkg2a antibody; DNA microscopy has been developed; small molecule inhibition blocking crispr-cas9 genome editing has been found for the first time Reconstruction of the long history of population in central and South America 1 Cell: great progress! A new intelligent microscope has been developed to observe the development of embryos in living mice at the four-dimensional level Doi: 10.1016/j.cell.2018.09.031 in a new study, Philipp, a physicist and biologist at jeannia Research Park, Howard Hughes Medical Research Institute, USA Keller and his colleagues adopted a different strategy: they designed a smart microscope that could do all the work The relevant research results were published online in the cell Journal on October 11, 2018, with the title of "in to imaging and reconstruction of post implantation mouse development at the single cell level" Picture from cell, DOI: 10.1016/j.cell.2018.09.031 At the center of the smart microscope, a clear acrylic cube structure holds the embryo imaging chamber Two light sheets illuminate mouse embryos, and two cameras record images These components allow the researchers to peer into the previously invisible world of early organ development, revealing dynamic events in unprecedented high-resolution detail The head of the microscope is equipped with an algorithm to track the position and size of the embryo These algorithms plot how the light moves in the sample, and then find out how to get the best image - keeping the mouse embryo focused in the field of vision and in the middle of it Because mouse embryos are constantly changing, the microscope must constantly adapt to make decisions on hundreds of images at hundreds of different time points in milliseconds Using this smart microscope, Keller's team can now look at live mouse embryos for the first time, and watch the gut begin to form, and the heart cells begin to try to beat for the first time In a crucial 48 hour window - the time when primary organs begin to form - they can track every embryonic cell and determine where they are going, which genes they have turned on, and which cells they encounter on their way 2 Cell: using deep learning to predict pre mRNA splicing from the original sequence doi: 10.1016/j.cell.2018.12.015 exome sequencing changed the clinical diagnosis of patients and family members with rare genetic diseases, but it changed the diagnosis of rare genetic diseases The positive rate is only about 25% - 30%, which makes most of the patients have not been detected, even the combination of exome sequencing and chip testing The noncoding regions of the genome play an important role in gene regulation In the unbiased genome-wide association study of human complex diseases, 90% of the pathogenic loci (causal disease loci) were found in the non coding region Noncoding mutations that disrupt normal splicing patterns of mRNA, also known as cryptic splice variants, have long been considered to play an important role in rare genetic diseases However, the role of recessive splicing mutations in clinical practice has been ignored, mainly because the understanding of splicing codes is not deep enough, which makes it difficult to identify them Picture from cell, DOI: 10.1016/j.cell.2018.12.015 In recent years, RNA sequencing (RNA SEQ) has become a potential method to detect abnormal splicing in Mendel's disease, but so far its application in clinical environment is still limited to a few cases with known cell types and available for biopsy Prediction of splicing of arbitrary precursor mRNA (pre mRNA) sequence can make it possible to accurately predict recessive splicing mutations, thus improving the diagnosis of genetic diseases So far, some progress has been made in modeling the sequence characteristics of core splicing motifs, characterizing exon splicing enhancers and silencers, and predicting cassette exon inclusion However, it is difficult to build a predictive splicing model from the original sequence In a new study, Kyle Kai how FARH and his team developed a deep neural network, which can accurately predict the splice junction of any pre mRNA transcript sequence, so as to accurately predict the noncoding mutations that lead to concealed splicing The related research results were recently published in the journal Cell, and the title of the paper is "predicting spreading from primary sequence with deep learning" Synonymous mutations and intron mutations with predicted splicing change results have been highly verified on RNA SEQ, and have great harm in the population Compared with healthy controls, ab initio mutations with predicted consequences of splicing changes were significantly enriched in patients with autism and mental disorders, and in 28 of these patients, 21 were effectively verified on RNA SEQ The researchers estimate that 9% to 11% of the pathogenic mutations in patients with rare genetic diseases are caused by this previously unrecognized recessive splicing mutation 3 Cell: Xue Tian research group of University of science and technology of China uses nanotechnology to enable mammals to see infrared doi: 10.1016/j.cell.2019.01.038 in a new study, Tian Xue research group of life science and Medicine Department of University of science and technology of China and gang Han research team of Medical College of University of Massachusetts reported that through nano technology Mice with improved vision can see infrared and visible light A single injection of nanoparticles into the eyes of mice can maintain their infrared vision for up to 10 weeks, with the least side effects Infrared light can be seen even in the daytime, and has enough specificity to distinguish different shapes These findings may lead to advances in human infrared vision technology, including potential applications in civil encryption, security, and military operations The relevant research results were published online in the cell Journal on February 28, 2019, and the paper title is "mamma near infrared image vision through injectable and self powered retain nanoantenna" The first authors of this paper are Yuqian Ma, Ph.D student, Department of life science and medicine, University of science and technology of China, Jin Bao, Professor, and Yuanwei Zhang, Ph.D., medical school, University of Massachusetts Picture from cell, 2019, DOI: 10.1016/j.cell.2019.01.038 In this new study, the researchers developed nanoparticles that can play a role in the existing structure of the eye The nanoparticles can only attach to the photoreceptor cells and play the role of micro infrared light sensor When external red light hits the retina, these nanoparticles capture longer infrared wavelengths and emit shorter wavelengths in the visible range Nearby rods and cones absorb these shorter wavelengths and send normal signals to the brain, just as visible light hits the retina "In our experiment, nanoparticles absorb infrared light with a wavelength of about 980 nm and convert it to light that peaked at 535 nm, which makes the infrared look like green light," said Bao The researchers tested the nanoparticles in mice, which, like humans, do not naturally see infrared light Mice injected with nanoparticles showed that they detected unconscious signs of infrared light, such as pupil contraction, while mice injected with buffer alone did not respond to infrared light 4 Cell: transcription factors are controlled by transcription factor (TF) through the phase separation ability of their activation domain to activate gene doi: 10.1016/j.cell.2018.10.042 Transcription factors are composed of DNA binding domain (DBD) and activation domain (AD) DBD has been well described, but little is known about the mechanism of ad affecting gene activation In a new study, researchers from the Whitehead Institute of biomedical research in the United States reported that different ad and mediator coactivator formed phase separated agglomerates Relevant research results were recently published in cell journal, and the title of the paper is "transcription factors activate genes through the phase separation capacity of their activation domains" The researchers found that transcription factors Oct4 and GCN4 can form isolated droplets with mediators in vitro, and their ability to activate genes in vivo depends on the same amino acid residues They also found that for estrogen receptor (ER), estrogen enhanced phase separation from mediators, again associating phase separation with gene activation These results indicate that many transcription factors can interact with the mediators through their phase separation ability of AD, and the agglomerates they form with the mediators participate in gene activation 5 Cell: the largest human microbiome study so far revealed thousands of new microbial species doi: 10.1016/j.cell.2019.01.001 in a new study, Nicola segata and Edoardo from the computational macro genomics Laboratory of the University of Trento, Italy Pasolli and his team have created the largest catalog of bacteria and archaea that has ever been found in humans around the world The related research results were recently published in cell journal, and the title of the paper is "extended unexpected human microbiome diversity revealed by over 150000 genes from metals spanning age, geography, and lifestyle" The picture is from the University of Trento His team's approach to human microbiome is called "computational metagenomics": they study it by analyzing the genetic information of human microbiome They extracted the total DNA from a drop of saliva, a skin swab or a gram of faeces and sequenced the DNA in a high-throughput way A large number of genetic data are analyzed by special software in order to reconstruct the genome of microorganisms in the human microbiome Dr segata introduced some aspects of the new research in detail: "our research results identified nearly 5000 microbial species, reproduced more than 154000 newly reconstructed genomes, and described the human microbiome in different ages, body parts, lifestyles and diseases Each of us is colonized by hundreds of such microbial species However, a large part of it (77%) was previously unknown Many of these microbial species are relatively rare, but some of them are very common in people around the world, and their discovery is to test their autoimmunity