Biology subjects

Hu, Z.

Publications and source records attributed to Hu, Z..

At least 217 records · Page 12Linked to original sources

bioRxiv2023

The "replacing surgery" of cpDNA: de novo chemical synthesis and in vivo functional testing of Chlamydomonas chloroplast genome

We have successfully designed and synthesized the 221,372-bp cpDNA SynCpV1.0 with the native cpDNA of Chlamydomonas reinhardtii as the template. Homoplasmic SynCpv1.0-harboring algal strains were obtained by biolistic transformation and selected with an ascending gradient of antibiotic pressure. Meanwhile, we were pleasantly surprised to find that SynCpV1.0 was able to re-introduce and replicate normally after the total DNA of transplastomic algal strains were transformed to Escherichia coli, it indicated that SynCpV1.0 was able to shuttle between C. reinhardtii and E. coli. Finally, we analyzed the photosynthetic properties of SynCpV1.0-harboring transplastomic strains, the results showed that they exhibited the same photosynthetic efficiency as the wild strain of C. reinhardtii CC125, and could rescue the photosynthetic defect in mutant strain of C. reinhardtii CC5168. Herein, we have performed the "replacing surgery" of cpDNA and established an ideal platform to complete multiple cycles of "Design-Build-Test" for optimizing the cpDNA of photosynthetic organisms. HighlightO_LIAn artificial cpDNA SynCpV1.0 is constructed by de novo chemical synthesis. C_LIO_LIThe "replacing surgery" of cpDNA was performed in the chloroplast of C. reinhardtii C_LIO_LIIt is found that artificial cpDNA was able to shuttle between Chlamydomonas chloroplast and E. coli. C_LIO_LIEstablish an ideal platform to complete multiple cycles of "Design-Build-Test" for optimizing the cpDNA. C_LI One-Sentence SummaryThe chloroplast genome can be replaced by a complete synthesized genome and performs the designed biological function in C. reinhardtii.

molecular biology↗

bioRxiv2022

PhyloAcc-GT: A Bayesian method for inferringpatterns of substitution rate shifts and associations with binary traits under gene tree discordance

An important goal of evolutionary genomics is to identify genomic regions whose substitution rates differ among lineages. For example, genomic regions experiencing accelerated molecular evolution in some lineages may provide insight into links between genotype to phenotype. Several comparative genomics methods have been developed to identify genomic accelerations between species, including a Bayesian method called PhyloAcc, which models shifts in substitution rate in multiple target lineages on a phylogeny. However, few methods consider the possibility of discordance between the trees of individual loci and the species tree due to incomplete lineage sorting, which might cause false positives. Here we present PhyloAcc-GT, which extends PhyloAcc by modeling gene tree heterogeneity to detect rate shifts across genomic regions. Given a species tree, we adopt the multispecies coalescent model as the prior distribution of gene trees, use Markov chain Monte Carlo (MCMC) for inference, and design novel MCMC moves to sample gene trees efficiently. Through extensive simulations, we show that PhyloAcc-GT outperforms PhyloAcc and other methods in identifying target-lineage-specific accelerations and detecting complex patterns of rate shifts, and is robust to specification of population size parameters. We apply PhyloAcc-GT to two examples of convergent evolution: flightlessness in ratites and marine mammal adaptations. PhyloAcc-GT is usually more conservative than PhyloAcc in calling convergent rate shifts because it identifies more accelerations on ancestral than on terminal branches. In summary, PhyloAcc-GT is a useful tool to identify shifts in substitution rate associated with specific target lineages while accounting for incomplete lineage sorting.

evolutionary biology↗

bioRxiv2022

Structural basis for the assembly of the DNA polymerase holoenzyme from a monkeypox virus variant

The ongoing pandemic caused by a monkeypox virus (MPXV) variant has spread all over the world and raised great public health concerns. The DNA polymerase F8 of MPXV, associated with its processivity factors A22 and E4, is responsible for viral genome replication in the perinuclear sites of the infected cells as well as a critical target for developing antiviral drugs. However, the assembly and working mechanism for the DNA polymerase holoenzyme of MPXV remains elusive. Here, we present the cryo-EM structure of the DNA polymerase holoenzyme F8/A22/E4 from the 2022 West African strain at an overall resolution of 3.5 [A] and revealed the precise spatial arrangement. Surprisingly, unlike any other previously reported B-family DNA polymerase, the holoenzyme complex is assembled as a dimer of heterotrimers, of which the extra interface between the thumb domain of F8 and A22 shows a clash between A22 and substrate DNA, suggesting an auto-inhibition state. Supplying an exogenous double-stranded DNA could notably shift the hexameric form into a trimeric form, which exposes the DNA binding site of thumb domain and might represent a more active state. The structures provide a molecular basis for the design of new antiviral therapeutics that target the MPXV DNA polymerase holoenzyme.

biochemistry↗

bioRxiv2022

ClpP/ClpX deficiency impairs mitochondrial functions and mTORC1 signaling during spermatogenesis and meiosis

Caseinolytic protease proteolytic subunit (ClpP) and caseinolytic protease X (ClpX) are mitochondrial matrix peptidases that activate mitochondrial unfolded protein response to maintain protein homeostasis in the mitochondria. However, the role of ClpP and ClpX in spermatogenesis remains largely unknown. In this study, we demonstrated the importance of ClpP/ClpX for meiosis and spermatogenesis with two conditional knockout (cKO) mouse models. We found that ClpP/ClpX deficiency reduced mitochondrial functions and quantity in spermatocytes, affected energy supply during meiosis and attenuated zygotene-pachytene transformation of the male germ cells. The dysregulated spermatocytes finally underwent apoptosis resulting in decreased testicular size and vacuolar structures within the seminiferous tubules. We found mTORC1 pathway was over-activated after deletion of ClpP/ClpX in spermatocytes. Long-term inhibition of the mTORC1 signaling via rapamycin treatment in vivo partially rescue spermatogenesis. The data reveal the novel roles of ClpP and ClpX in regulating meiosis and spermatogenesis. One-Sentence SummaryClpP/ClpX is required for maintaining mitochondrial functions in spermatocytes during meiosis and spermatogenesis.

developmental biology↗

bioRxiv2022

Dynamic Interaction Learning and MultimodalRepresentation for Drug Response Prediction

Mining multimodal pharmaceutical data is crucial for in-silico drug candidate screening and discovery. A daunting challenge of integrating multimodal data is to enable dynamic feature modeling generalizable for real-world applications. Unlike conventional approaches using a simple concatenation with fixed parameters, in this paper, we develop a dynamic interaction learning network to adaptively integrate drug and different reactants on multimodal tasks towards robust drug response prediction. The primary objective of dynamic learning falls into two key aspects: at micro-level, we aim to dynamically search specific relational patterns on the whole reactant range for each drug-reactant pair; at macro-level, drug features can be used to adaptively correlate with different reactants. Extensive experiments demonstrate the validity of our approach in both drug protein interaction (DPI) and cancer drug response (CDR) tasks. Our approach achieves superior performance on both DPI (AUC = 0.967) and CDR (AUC = 0.932) tasks, outperforming competitive baselines from four real-world, drug-outcome datasets. In addition, the performance on the challenging blind subsets is remarkably improved, where AUC value increases from 0.843 to 0.937 on blind protein set of DPI task, and Pearsons correlation value increases from 0.516 to 0.566 on blind drug set of CDR task. A series of case studies highlight the potential generalization and interpretability of dynamic learning in the in-silico drug response assessment.

bioinformatics↗

bioRxiv2022

Running ahead of evolution - AI based simulation for predicting future high-risk SARS-CoV-2 variants

The never-ending emergence of SARS-CoV-2 variations of concern (VOCs) has challenged the whole world for pandemic control. In order to develop effective drugs and vaccines, one needs to efficiently simulate SARS-CoV-2 spike receptor binding domain (RBD) mutations and identify high-risk variants. We pretrain a large protein language model with approximately 408 million protein sequences and construct a high-throughput screening for the prediction of binding affinity and antibody escape. As the first work on SARS-CoV-2 RBD mutation simulation, we successfully identify mutations in the RBD regions of 5 VOCs and can screen millions of potential variants in seconds. Our workflow scales to 4096 NPUs with 96.5% scalability and 493.9x speedup in mixed precision computing, while achieving a peak performance of 366.8 PFLOPS (reaching 34.9% theoretical peak) on Pengcheng Cloudbrain-II. Our method paves the way for simulating coronavirus evolution in order to prepare for a future pandemic that will inevitably take place. Our models are released at https://github.com/ZhiweiNiepku/SARS-CoV-2_mutation_simulation to facilitate future related work. JustificationWe develop a novel multi-constraint variation prediction framework to simulate SARS-CoV-2 RBD mutations, reaching a peak performance of 366.8 PFLOPS with 96.5% scalability and achieving 493.9x speedup. Our method facilitates the prediction and prioritization of future high-risk variants for the early deployment of drugs and vaccines. Performance attributes O_TBL View this table: org.highwire.dtl.DTLVardef@1b1873aorg.highwire.dtl.DTLVardef@25314eorg.highwire.dtl.DTLVardef@1c80130org.highwire.dtl.DTLVardef@1c61b21org.highwire.dtl.DTLVardef@11f21c5_HPS_FORMAT_FIGEXP M_TBL C_TBL Overview of the problemCoronavirus Disease 2019 (COVID-19) has spread rapidly to more than 200 countries or regions since December 2019. Due to its high infectivity, there have been over 645 million confirmed cases, including approximately 6.6 million deaths, reported by the World Health Organization (WHO) as of December 20221. In addition to being a serious threat to human health, COVID-19 has had a catastrophic impact on the global economy.

bioinformatics↗

bioRxiv2022

Imaging the Neural Substrate of Trigeminal Neuralgia Pain Using Deep Learning

Trigeminal neuralgia (TN) is a severe and disabling facial pain condition and is characterized by intermittent, severe, electric shock-like pain in one (or more) trigeminal subdivisions. This pain can be triggered by an innocuous stimulus or can be spontaneous. Presently available therapies for TN include both surgical and pharmacological management; however, the lack of a known etiology for TN contributes to the unpredictable response to treatment and the variability in long-term clinical outcomes. Given this, a range of peripheral and central mechanisms underlying TN pain remain to be understood. We acquired functional magnetic resonance imaging (fMRI) data from TN patients who (1) rested comfortably in the scanner during a resting state session and (2) rated their pain levels in real time using a calibrated tracking ball-controlled scale in a pain tracking session. Following data acquisition, the data was analyzed using the conventional correlation analysis and two artificial intelligence (AI)-inspired deep learning methods: convolutional neural network (CNN) and graph convolutional neural network (GCNN). Each of the three methods yielded a set of brain regions related to the generation and perception of pain in TN. There were six regions that were identified by all three methods, including the superior temporal cortex, the insula, the fusiform, the precentral gyrus, the superior frontal gyrus, and the supramarginal gyrus. Additionally, 17 regions, including dorsal anterior cingulate cortex(dACC) and the thalamus, were identified by at least two of the three methods. Collectively, these 23 regions represent signature centers of TN pain and provide target areas for future studies relating to central mechanisms of TN.

neuroscience↗

bioRxiv2022

TRPV1-mediated sonogenetic neuromodulation of motor cortex in freely moving mice

BackgroundNoninvasive and cell-type-specific neuromodulation tools are critically needed for probing intact brain function. Sonogenetics for noninvasive activation of neurons engineered to express thermosensitive transient receptor potential vanilloid 1 (TRPV1) by transcranial focused ultrasound (FUS) was recently developed to address this need. However, using TRPV1-mediated sonogenetics to evoke behavior by targeting the cortex is challenged by its proximity to the skull due to high skull absorption of ultrasound and increased risks of thermal-induced tissue damage. ObjectiveThis study evaluated the feasibility and safety of TRPV1-mediated sonogenetics in targeting the motor cortex to modulate the locomotor behavior of freely moving mice. MethodsAdeno-associated virus was delivered to the mouse motor cortex via intracranial injection to express TRPV1 in excitatory neurons. A wearable FUS device was installed on the mouse head after a month to control neuronal activity by activating virally expressed TRPV1 through FUS sonication at different acoustic pressures. Immunohistochemistry staining of ex vivo brain slices was performed to verify neuron activation and evaluate safety. ResultsTRPV1-mediated sonogenetic stimulation at 0.7 MPa successfully evoked rotational behavior in the direction contralateral to the stimulation site, activated cortical neurons as indicated by the upregulation of c-Fos, and did not induce significant changes in inflammatory or apoptotic markers (GFAP, lba1, and Caspase-3). Sonogenetic stimulation of TRPV1 mice at a higher acoustic pressure, 1.1 MPa, induced significant changes in motor behavior and upregulation of c-Fos compared with FUS sonication of naive mice at 1.1 MPa. However, signs of damage at the meninges were observed at 1.1 MPa. ConclusionsTRPV1-mediated sonogenetics can achieve effective and safe neuromodulation at the cortex with carefully selected FUS parameters. These findings expand the application of this technique to include superficial brain targets.

bioengineering↗

bioRxiv2022

Mechanically manipulate glymphatic transportation by ultrasound combined with microbubbles

The glymphatic system is a perivascular fluid transport system for waste clearance. Glymphatic transportation is believed to be driven by the perivascular pumping effect generated by arterial wall pulsation induced by the cardiac cycle. Ultrasound sonication of circulating microbubbles in the cerebral vasculature induces volumetric expansion and contraction of microbubbles that push and pull on the vessel wall to generate a microbubble pumping effect. The objective of this study was to evaluate whether glymphatic transportation can be mechanically manipulated by focused ultrasound (FUS) sonication of microbubbles. The glymphatic pathway in intact mouse brains was studied using intranasal administration of fluorescently labeled albumin as a fluid tracer followed by FUS sonication at a deep brain target (thalamus) in the presence of intravenously injected microbubbles. Three-dimensional confocal microscopy imaging of optically cleared brain tissue revealed that FUS sonication enhanced the transport of fluorescently labeled albumin tracer in the perivascular space along microvessels, primarily the arterioles. We also obtained evidence of FUS-enhanced penetration of the albumin tracer from the perivascular space into the interstitial space. This study revealed that ultrasound combined with circulating microbubbles could noninvasively enhance glymphatic transportation in the brain. Significance StatementThe glymphatic system is a waste clearance system in the brain analogous to the lymphatic system in peripheral organs. Glymphatic system impairment might contribute to brain disease pathologies, including those in neurodegenerative diseases, traumatic brain injury, and stroke. This study revealed that ultrasound could mechanically enhance glymphatic transportation. This result opens opportunities for using ultrasound to probe the role of the glymphatic system in brain function and brain diseases. Findings from this study suggest that ultrasound can be utilized as a noninvasive/nonpharmacological approach to mitigate brain diseases caused by impaired glymphatic function.

bioengineering↗

bioRxiv2022

Snf1/AMPK fine-tunes TORC1 signaling in response to glucose starvation

The AMP-activated protein kinase (AMPK) and the target of rapamycin complex 1 (TORC1) are central kinase modules of two opposing signaling pathways that control eukaryotic cell growth and metabolism in response to the availability of energy and nutrients. Accordingly, energy depletion activates AMPK to inhibit growth, while nutrients and high energy levels activate TORC1 to promote growth. Both in mammals and lower eukaryotes such as yeast, the AMPK and TORC1 pathways are wired to each other at different levels, which ensures homeostatic control of growth and metabolism. In this context, a previous study (Hughes Hallet et. al, 2015) reported that AMPK in yeast, i.e. Snf1, plays a role in short-term downregulation of TORC1 activity upon acute glucose starvation, but the underlying mechanism has remained elusive. Using a combination of unbiased mass spectrometry (MS)-based phosphoproteomics, genetic, biochemical, and physiological experiments, we show here that Snf1 contributes to glucose starvation-induced short-term TORC1 inactivation primarily through the TORC1-regulatory protein Pib2. Our data, therefore, extend the function of Pib2 to a hub that integrates both glucose and, as reported earlier, glutamine signals to control TORC1. We further demonstrate that Snf1 phosphorylates the TORC1 effector kinase Sch9 within its N-terminal region and thereby antagonizes the phosphorylation of a C-terminal TORC1-target residue within Sch9 itself that is critical for its activity. The consequences of Snf1-mediated phosphorylation of Pib2 and Sch9 are physiologically additive and sufficient to explain the role of Snf1 in short-term inhibition of TORC1 in acutely glucose-starved cells.

biochemistry↗

bioRxiv2022

Pangenome-based dynamic trajectories of intracellular gene transfers in Poaceae unveil a high rate of unceasing integration and selective retention in Triticeae

Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshapes the nuclear genome during evolution. Despite the substantial contribution of IGTs to genome variation, the dynamic trajectories of IGTs at the pangenomic level remain elusive. Here, we propose a novel approach, IGTminer, to map the evolutionary trajectories of IGTs by collinearity and gene reannotation across multiple genome assemblies. IGTminer was applied to create a nuclear organelle gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops, revealing the polymorphisms and trajectory dynamics of NOGs. The NOGs produced were verified by experimental evidence and resequencing datasets. We found that most of the NOGs were recently transferred and lineage specific, and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat had a higher retention rate of NOGs than maize and rice, and the retained NOGs were likely involved in the photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during two rounds of polyploidization and contributed to the genetic diversities among modern wheat varieties. Finally, we proposed a radiocarbon-like model illustrating the transfer and elimination dynamics of NOGs, highlighting the unceasing integration and selective retention of NOGs over evolutionary time. In addition, we implemented an interactive webserver for NOG exploration in Poaceae. In summary, this study provides new resources and clues for the roles of IGTs in shaping inter- and intraspecies genome variation and driving plant genome evolution.

evolutionary biology↗

bioRxiv2022

Cell division history encodes directional information of fate transitions

Single-cell RNA-sequencing (scRNA-seq) enables systematic mapping of cellular differentiation trajectories. However, inferring the cell-fate transitions under diseases or perturbations is still challenging due to the high cellular plasticity. Here, we demonstrate that monotonically expressed genes (MEGs) along cell divisions record the directions of state transitions regardless of the cellular processes. We developed a computational framework (PhyloVelo) to identify MEGs and reconstruct a novel transcriptomic velocity field by leveraging both scRNA-seq and phylogenetic information. PhyloVelo accurately recovered linear, bifurcated and convergent differentiations in simulations and C. elegans. It outperformed current approaches for delineating cellular trajectories in embryo development and tumor evolution through analysis of five CRISPR/Cas9-based lineage tracing datasets. Together, our study unveils an internal cellular clock and provides a powerful method for cellfate analysis in diverse biological contexts.

genomics↗

bioRxiv2022

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FMs effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field.

bioinformatics↗

bioRxiv2022

A resource for the comparison and integration of heterogeneous microbiome networks

Naturally occurring microbial communities often comprise thousands of taxa involved in complex networks of interactions. These interactions can be mediated by several mechanisms, including the competition for resources, the exchange of signals and nutrients, cell-cell contact and antibiotic warfare. In addition to direct measurements and computational predictions of interactions, abundant data on microbial co-occurrence associations can be inferred from correlations of taxa across samples, which can be estimated from metagenomic, and amplicon datasets. The analysis and interpretation of interaction and correlation networks are limited by the challenge of comparing across different datasets, due to heterogeneity of the data itself and to the lack of a platform to facilitate such comparisons. Here, we introduce the Microbial Interaction Network Database (MIND) - a web-based platform for the integrative analysis of different types of microbial networks, freely available at http://microbialnet.org/. In addition to containing a growing body of curated data, including amplicon-based co-occurrence networks, genome-scale model-derived networks, metabolic influence networks and horizontal gene transfer networks, MIND allows users to upload and analyze newly generated networks using a JSON format and standard NCBI taxonomy. The platform provides convenient functions to compare and query multiple networks simultaneously, and to visualize and export networks and datasets. Through some illustrative examples, we demonstrate how the platform might facilitate discoveries and help generate new hypotheses on host-associated and environmentally important microbial ecosystems through the power of knowledge integration.

systems biology↗

bioRxiv2022

Neutralization of Omicron BA.4/BA.5 and BA.2.75 by Booster Vaccination or BA.2 Breakthrough Infection Sera

Many new Omicron sub-lineages have been reported to evade neutralizing antibody response, including BA.2, BA.2.12.1, BA.4 and BA.5. Most recently, another emerging sub-lineage BA.2.75 has been reported in multiple countries. In this study, we constructed a comprehensive panel of pseudoviruses (PsVs), including wild-type, Delta, BA.1, BA.1.1, BA.2, BA.3, BA.2.3.1, BA.2.10.1, BA.2.12.1, BA.2.13, BA.2.75 and BA.4/BA.5, with accumulate coverage reached 91% according to the proportion of sequences deposited in GISAID database since Jan 1st, 2022. We collected serum samples from healthy adults at day14 post homologous booster with BBIBP-CorV, or heterologous booster with ZF2001, primed with two doses of BBIBP-CorV, or from convalescents immunized with three-dose inactivated vaccines prior to infection with Omicron BA.2, and tested their neutralization activity on this panel of PsVs. Our results demonstrated that all Omicron sub-lineages showed substantial evasion of neutralizing antibodies induced by vaccination and infection, although BA.2.75 accumulated the largest number of mutations in its spike, BA.4 and BA.5 showed the strongest serum escape. However, BA.2 breakthrough infection could remarkably elevated neutralization titers against all different variants, especially titers against BA.2 and its derivative sub-lineages.

immunology↗

bioRxiv2022

Single Cell Transcriptomics identifies a WNT7A-FZD5 Signaling Axis that maintains Fallopian Tube Stem Cells in Patient-derived Organoids

Despite its significance to reproduction, fertility, sexually transmitted infections and various pathologies, the fallopian tube (FT) is relatively understudied. Strong evidence points to the FT as the tissue-of-origin of high grade serous ovarian cancer (HGSOC), the most fatal gynaecological malignancy. HGSOC precursor lesions arise specifically in the distal FT (fimbria) which is reported to be enriched in stem-like cells. Investigation of the role of FT stem cells in health and disease has been hampered by a lack of characterization of FT stem cells and lack of models that recapitulate stem cell renewal and differentiation in vitro. Using optimized organoid culture conditions to address these limitations, we found that FT stem cell renewal is highly dependent on WNT/{beta}-catenin signaling and engineered endogenous WNT/{beta}-catenin signaling reporter organoids to biomark, isolate and characterize putative FT stem cells. Using functional approaches as well as bulk and single cell transcriptomic analyses, we show that an endogenous hormonally-regulated WNT7A-FZD5 signaling axis is critical for self-renewal of human FT stem cells, and that WNT/{beta}-catenin pathway-activated FT cells form a distinct transcriptomic cluster of cells enriched in ECM remodelling and integrin signaling pathways. In addition, we find that the WNT7A-FZD5 signaling axis is dispensable for mouse oviduct regeneration. Overall, we provide a deep characterization of FT stem cells and their molecular requirements for self-renewal, paving the way for mechanistic work investigating the role of stem cells in FT health and disease. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/502319v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@124d8a0org.highwire.dtl.DTLVardef@9f92borg.highwire.dtl.DTLVardef@c57b33org.highwire.dtl.DTLVardef@11b5bec_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Multi-environmental population phenotyping suggest the higher risks of wheat Rht-B1b and Rht-D1b cultivars in global warming scenarios

After six decades practice, the semi-dwarf alleles Rht-B1b and Rht-D1b (also called Rht-1 and Rht-2) had been applied into around 70% current wheat cultivars, laid the foundation for the worldwide wheat production supply, then the agronomic traits controlled by the two alleles still keep unclear except dwarfing wheat. Here 13 agronomic traits were investigated in 400 wheat accessions with seven environments, uncovered the genetic effects of Rht-B1b and Rht-D1b on wheat structure and yield traits in different genetic backgrounds and environments, and the distinct genetic effects between Rht-B1b and Rht-D1b, suggesting that the introduction of green revolution alleles profoundly shaped the agronomy traits of modern wheat cultivars. The late-sowing assays and regression analysis based on the phenotypic and their meteorological data showed the accessions containing Rht-B1b and Rht-D1b are more sensitive to the temperature increase, and the Rht-D1b may lost additional 8% yield compared the cultivars without the green revolution alleles if the average temperature increases 1 {degrees}C. These results suggest the application of green revolution are facing more challenges to maintain the futural wheat production supply in global warming scenarios.

molecular biology↗

bioRxiv2022

Discovering and targeting dynamic drugging pocketsof the oncogene KRAS-G12D

Activated KRAS-G12D mutations are the one of most frequent oncogenic drivers in human cancers. Unfortunately, no therapeutic agent directly targeting KRAS-G12D has been clinically approved yet, with such mutated species remaining undrugged. Notably, cofactor Mg2+ is closely related to the function of small GTPases, but no investigation has been done yet on Mg2+ when associated with KRAS. Herein, through microsecond scale molecular dynamics simulations we have found that Mg2+ plays a crucial role in the conformational changes of the KRAS-GDP complex. We have located two brand new druggable dynamic pockets exclusive to KRAS-G12D. Using the structural characteristics of these two dynamic pockets, we designed in silico the inhibitor DBD15-21-22, which can specifically and tightly target KRAS-G12D-GDP-Mg2+ ternary complex and we have verified that DBD15-21-22 is harmless for wild-type KRAS. Overall, we provide two brand new druggable pockets located on KRAS-G12D, as well as suitable strategies for KRAS-G12D inhibition.

cancer biology↗