Developing Covalent Protein Drugs via Proximity-Enabled Reactive Therapeutics.

Small molecule covalent drugs provide desirable therapeutic properties over noncovalent ones for treating challenging diseases. The potential of covalent protein drugs, however, remains unexplored due to protein's inability to bind targets covalently. We report a proximity-enabled reactive therapeutics (PERx) approach to generate covalent protein drugs. Through genetic code expansion, a latent bioreactive amino acid fluorosulfate-L-tyrosine (FSY) was incorporated into human programmed cell death protein-1 (PD-1). Only when PD-1 interacts with PD-L1 did the FSY react with a proximal histidine of PD-L1 selectively, enabling irreversible binding of PD-1 to only PD-L1 in vitro and in vivo. When administrated in immune-humanized mice, the covalent PD-1(FSY) exhibited strikingly more potent antitumor effect over the noncovalent wild-type PD-1, attaining therapeutic efficacy equivalent or superior to anti-PD-L1 antibody. PERx should provide a general platform technology for converting various interacting proteins into covalent binders, achieving specific covalent protein targeting for biological studies and therapeutic capability unattainable with conventional noncovalent protein drugs.

Mapping the Mouse Cell Atlas by Microwell-Seq.

Single-cell RNA sequencing (scRNA-seq) technologies are poised to reshape the current cell-type classification system. However, a transcriptome-based single-cell atlas has not been achieved for complex mammalian systems. Here, we developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using simple, inexpensive devices. Using Microwell-seq, we analyzed more than 400,000 single cells covering all of the major mouse organs and constructed a basic scheme for a mouse cell atlas (MCA). We reveal a single-cell hierarchy for many tissues that have not been well characterized previously. We built a web-based "single-cell MCA analysis" pipeline that accurately defines cell types based on single-cell digital expression. Our study demonstrates the wide applicability of the Microwell-seq technology and MCA resource.

SnapShot: Chromosome organization.

Chromosomes in higher eukaryotes are folded at different length scales into loop extrusion domains, spatial compartments, and chromosome territories and exhibit interactions with nuclear structures such as the lamina. Microscopic methods can probe this structure by measuring positions of chromosomes in the nuclear space in individual cells, while sequencing-based contact capture approaches can report the frequency of contacts of different regions within these structural layers. To view this SnapShot, open or download the PDF.

Microbiota-derived 3-IAA influences chemotherapy efficacy in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second most deadly cancer by 2040, owing to the high incidence of metastatic disease and limited responses to treatment1,2. Less than half of all patients respond to the primary treatment for PDAC, chemotherapy3,4, and genetic alterations alone cannot explain this5. Diet is an environmental factor that can influence the response to therapies, but its role in PDAC is unclear. Here, using shotgun metagenomic sequencing and metabolomic screening, we show that the microbiota-derived tryptophan metabolite indole-3-acetic acid (3-IAA) is enriched in patients who respond to treatment. Faecal microbiota transplantation, short-term dietary manipulation of tryptophan and oral 3-IAA administration increase the efficacy of chemotherapy in humanized gnotobiotic mouse models of PDAC. Using a combination of loss- and gain-of-function experiments, we show that the efficacy of 3-IAA and chemotherapy is licensed by neutrophil-derived myeloperoxidase. Myeloperoxidase oxidizes 3-IAA, which in combination with chemotherapy induces a downregulation of the reactive oxygen species (ROS)-degrading enzymes glutathione peroxidase 3 and glutathione peroxidase 7. All of this results in the accumulation of ROS and the downregulation of autophagy in cancer cells, which compromises their metabolic fitness and, ultimately, their proliferation. In humans, we observed a significant correlation between the levels of 3-IAA and the efficacy of therapy in two independent PDAC cohorts. In summary, we identify a microbiota-derived metabolite that has clinical implications in the treatment of PDAC, and provide a motivation for considering nutritional interventions during the treatment of patients with cancer.

A backbone-centred energy function of neural networks for protein design.

A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it1,2. It has been suggested that the designability of backbones is governed mainly by side chain-independent or side chain type-insensitive molecular interactions3-5, indicating an approach for designing new backbones (ready for amino acid selection) based on continuous sampling and optimization of the backbone-centred energy surface. However, a sufficiently comprehensive and precise energy function has yet to be established for this purpose. Here we show that this goal is met by a statistical model named SCUBA (for Side Chain-Unknown Backbone Arrangement) that uses neural network-form energy terms. These terms are learned with a two-step approach that comprises kernel density estimation followed by neural network training and can analytically represent multidimensional, high-order correlations in known protein structures. We report the crystal structures of nine de novo proteins whose backbones were designed to high precision using SCUBA, four of which have novel, non-natural overall architectures. By eschewing use of fragments from existing protein structures, SCUBA-driven structure design facilitates far-reaching exploration of the designable backbone space, thus extending the novelty and diversity of the proteins amenable to de novo design.

Pathogenic fungi neutralize plant-derived ROS via Srpk1 deacetylation.

In response to infection, plants can induce the production of reactive oxygen species (ROS) to restrict pathogen invasion. In turn, adapted pathogens have evolved a counteracting mechanism of enzymatic ROS detoxification, but how it is activated remains elusive. Here, we show that in the tomato vascular wilt pathogen Fusarium oxysporum f. sp. lycopersici (Fol) this process is initiated by deacetylation of the FolSrpk1 kinase. Upon ROS exposure, Fol decreases FolSrpk1 acetylation on the K304 residue by altering the expression of the acetylation-controlling enzymes. Deacetylated FolSrpk1 disassociates from the cytoplasmic FolAha1 protein, thus enabling its nuclear translocation. Increased accumulation of FolSrpk1 in the nucleus allows for hyperphosphorylation of its phosphorylation target FolSr1 that subsequently enhances transcription of different types of antioxidant enzymes. Secretion of these enzymes removes plant-produced H2 O2 , and enables successful Fol invasion. Deacetylation of FolSrpk1 homologs has a similar function in Botrytis cinerea and likely other fungal pathogens. These findings reveal a conserved mechanism for initiation of ROS detoxification upon plant fungal infection.

Systematic comparison of sequencing-based spatial transcriptomic methods.

Recent developments of sequencing-based spatial transcriptomics (sST) have catalyzed important advancements by facilitating transcriptome-scale spatial gene expression measurement. Despite this progress, efforts to comprehensively benchmark different platforms are currently lacking. The extant variability across technologies and datasets poses challenges in formulating standardized evaluation metrics. In this study, we established a collection of reference tissues and regions characterized by well-defined histological architectures, and used them to generate data to compare 11 sST methods. We highlighted molecular diffusion as a variable parameter across different methods and tissues, significantly affecting the effective resolutions. Furthermore, we observed that spatial transcriptomic data demonstrate unique attributes beyond merely adding a spatial axis to single-cell data, including an enhanced ability to capture patterned rare cell states along with specific markers, albeit being influenced by multiple factors including sequencing depth and resolution. Our study assists biologists in sST platform selection, and helps foster a consensus on evaluation standards and establish a framework for future benchmarking efforts that can be used as a gold standard for the development and benchmarking of computational tools for spatial transcriptomic analysis.

Repeated stress to the skin amplifies neutrophil infiltration in a keratin 17- and PKCα-dependent manner.

Neutrophils are the first immune cells to reach inflamed sites and contribute to the pathogenesis of chronic inflammatory skin diseases. Yet, little is known about the pattern of neutrophil infiltration in inflamed skin in vivo and the mechanisms mediating their recruitment. Here, we provide insight into the dynamics of neutrophil infiltration in skin in response to acute or repeated inflammatory stress, highlighting a novel keratinocyte- and keratin 17 (K17)-dependent mechanism that regulates neutrophil recruitment to inflamed skin. We used the phorbol ester TPA and UVB, alone or in combination, to induce sterile inflammation in mouse skin. A single TPA treatment results in a neutrophil influx in the dermis that peaks at 12 h and resolves within 24 h. A subsequent TPA treatment or a UVB challenge, when applied 24 h but not 48 h later, accelerates, amplifies, and prolongs neutrophil infiltration. This transient amplification response (TAR) is mediated by local signals in inflamed skin, can be recapitulated in ex vivo culture, and involves the K17-dependent sustainment of protein kinase Cα (PKCα) activity and release of chemoattractants by stressed keratinocytes. K17 binds RACK1, a scaffold protein essential for PKCα activity. The N-terminal head domain of K17 is crucial for its association with RACK1 and regulation of PKCα activity. Analysis of RNAseq data reveals a signature consistent with TAR and PKCα activation in inflammatory skin diseases. These findings uncover a novel, keratin-dependent mechanism that amplifies neutrophil recruitment in skin under stress, with direct implications for inflammatory skin disorders.

Direct imaging of single-molecule electrochemical reactions in solution.

Chemical reactions tend to be conceptualized in terms of individual molecules transforming into products, but are usually observed in experiments that probe the average behaviour of the ensemble. Single-molecule methods move beyond ensemble averages and reveal the statistical distribution of reaction positions, pathways and dynamics1-3. This has been shown with optical traps and scanning probe microscopy manipulating and observing individual reactions at defined locations with high spatial resolution4,5, and with modern optical methods using ultrasensitive photodetectors3,6,7 that enable high-throughput single-molecule measurements. However, effective probing of single-molecule solution chemistry remains challenging. Here we demonstrate optical imaging of single-molecule electrochemical reactions7 in aqueous solution and its use for super-resolution microscopy. The method utilizes a chemiluminescent reaction involving a ruthenium complex electrochemically generated at an electrode8, which ensures minimal background signal. This allows us to directly capture single photons of the electrochemiluminescence of individual reactions, and to develop super-resolved electrochemiluminescence microscopy for imaging the adhesion dynamics of live cells with high spatiotemporal resolution. We anticipate that our method will advance the fundamental understanding of electrochemical reactions and prove useful for bioassays and cell-imaging applications.

The genomic origins of the Bronze Age Tarim Basin mummies.

The identity of the earliest inhabitants of Xinjiang, in the heart of Inner Asia, and the languages that they spoke have long been debated and remain contentious1. Here we present genomic data from 5 individuals dating to around 3000-2800 BC from the Dzungarian Basin and 13 individuals dating to around 2100-1700 BC from the Tarim Basin, representing the earliest yet discovered human remains from North and South Xinjiang, respectively. We find that the Early Bronze Age Dzungarian individuals exhibit a predominantly Afanasievo ancestry with an additional local contribution, and the Early-Middle Bronze Age Tarim individuals contain only a local ancestry. The Tarim individuals from the site of Xiaohe further exhibit strong evidence of milk proteins in their dental calculus, indicating a reliance on dairy pastoralism at the site since its founding. Our results do not support previous hypotheses for the origin of the Tarim mummies, who were argued to be Proto-Tocharian-speaking pastoralists descended from the Afanasievo1,2 or to have originated among the Bactria-Margiana Archaeological Complex3 or Inner Asian Mountain Corridor cultures4. Instead, although Tocharian may have been plausibly introduced to the Dzungarian Basin by Afanasievo migrants during the Early Bronze Age, we find that the earliest Tarim Basin cultures appear to have arisen from a genetically isolated local population that adopted neighbouring pastoralist and agriculturalist practices, which allowed them to settle and thrive along the shifting riverine oases of the Taklamakan Desert.

Endothelial to Mesenchymal Transition in Health and Disease.

The endothelium is one of the largest organ systems in the body, and data continue to emerge regarding the importance of endothelial cell (EC) dysfunction in vascular aging and a range of cardiovascular diseases (CVDs). Over the last two decades and as a process intimately related to EC dysfunction, an increasing number of studies have also implicated endothelial to mesenchymal transition (EndMT) as a potentially disease-causal pathobiologic process that is involved in a multitude of differing CVDs. However, EndMT is also involved in physiologic processes (e.g., cardiac development), and transient EndMT may contribute to vascular regeneration in certain contexts. Given that EndMT involves a major alteration in the EC-specific molecular program, and that it potentially contributes to CVD pathobiology, the clinical translation opportunities are significant, but further molecular and translational research is needed to see these opportunities realized.

Single-nucleus transcriptomic mapping uncovers targets for traumatic brain injury.

The subventricular zone (SVZ) is a neurogenic niche that contributes to homeostasis and repair after brain injury. However, the effects of mild traumatic brain injury (mTBI) on the divergence of the regulatory DNA landscape within the SVZ and its link to functional alterations remain unexplored. In this study, we mapped the transcriptome atlas of murine SVZ and its responses to mTBI at the single-cell level. We observed cell-specific gene expression changes following mTBI and unveiled diverse cell-to-cell interaction networks that influence a wide array of cellular processes. Moreover, we report novel neurogenesis lineage trajectories and related key transcription factors, which we validate through loss-of-function experiments. Specifically, we validate the role of Tcf7l1, a cell cycle gene regulator, in promoting neural stem cell differentiation toward the neuronal lineage after mTBI, providing a potential target for regenerative medicine. Overall, our study profiles an SVZ transcriptome reference map, which underlies the differential cellular behavior in response to mTBI. The identified key genes and pathways that may ameliorate brain damage or facilitate neural repair serve as a comprehensive resource for drug discovery in the context of mTBI.

GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection.

Genomic selection (GS) has emerged as an effective technology to accelerate crop hybrid breeding by enabling early selection prior to phenotype collection. Genomic best linear unbiased prediction (GBLUP) is a robust method that has been routinely used in GS breeding programs. However, GBLUP assumes that markers contribute equally to the total genetic variance, which may not be the case. In this study, we developed a novel GS method called GA-GBLUP that leverages the genetic algorithm (GA) to select markers related to the target trait. We defined four fitness functions for optimization, including AIC, BIC, R2, and HAT, to improve the predictability and bin adjacent markers based on the principle of linkage disequilibrium to reduce model dimension. The results demonstrate that the GA-GBLUP model, equipped with R2 and HAT fitness function, produces much higher predictability than GBLUP for most traits in rice and maize datasets, particularly for traits with low heritability. Moreover, we have developed a user-friendly R package, GAGBLUP, for GS, and the package is freely available on CRAN (https://CRAN.R-project.org/package=GAGBLUP).

YAP1 regulates thrombopoiesis by binding to MYH9 in immune thrombocytopenia.

Immune thrombocytopenia (ITP) is a complicated bleeding disease characterized by sharp platelet reduction. As a dominating element involved in ITP, megakaryocytes (MKs) are responsible for thrombopoiesis. However, the mechanism underlying the dysregulation of thrombopoiesis that occurs in ITP remains unidentified. In this study, we examined the role of yes-associated protein 1 (YAP1) in thrombopoiesis during ITP. We observed a reduced YAP1 expression with cytoskeletal actin misalignment in MKs from ITP patients. By using an experimental ITP mouse model, we showed that reduced YAP1 expression induced aberrant MK distribution, reduced the percentage of late MKs among total MKs, and caused submaximal platelet recovery. Mechanistically, YAP1 upregulation by binding of GATA binding protein 1 (GATA1) to its promoter promoted MK maturation. Phosphorylated YAP1 promoted cytoskeletal activation by binding of its WW2 domain to myosin heavy chain 9 (MYH9), facilitating thrombopoiesis. Targeting YAP1 by its activator XMU-MP-1 was sufficient to rescue cytoskeletal defects and thrombopoiesis dysregulation in YAP1+/- mice with ITP and patients. Taken together, these results demonstrate a crucial role for YAP1 in thrombopoiesis, providing a potential for the development of diagnostic markers and therapeutic options for ITP.

The TREM2-APOE Pathway Drives the Transcriptional Phenotype of Dysfunctional Microglia in Neurodegenerative Diseases.

Microglia play a pivotal role in the maintenance of brain homeostasis but lose homeostatic function during neurodegenerative disorders. We identified a specific apolipoprotein E (APOE)-dependent molecular signature in microglia from models of amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), and Alzheimer's disease (AD) and in microglia surrounding neuritic ß-amyloid (Aß)-plaques in the brains of people with AD. The APOE pathway mediated a switch from a homeostatic to a neurodegenerative microglia phenotype after phagocytosis of apoptotic neurons. TREM2 (triggering receptor expressed on myeloid cells 2) induced APOE signaling, and targeting the TREM2-APOE pathway restored the homeostatic signature of microglia in ALS and AD mouse models and prevented neuronal loss in an acute model of neurodegeneration. APOE-mediated neurodegenerative microglia had lost their tolerogenic function. Our work identifies the TREM2-APOE pathway as a major regulator of microglial functional phenotype in neurodegenerative diseases and serves as a novel target that could aid in the restoration of homeostatic microglia.

Simulation of Hubbard model physics in WSe2/WS2 moiré superlattices.

The Hubbard model, formulated by physicist John Hubbard in the 1960s1, is a simple theoretical model of interacting quantum particles in a lattice. The model is thought to capture the essential physics of high-temperature superconductors, magnetic insulators and other complex quantum many-body ground states2,3. Although the Hubbard model provides a greatly simplified representation of most real materials, it is nevertheless difficult to solve accurately except in the one-dimensional case2,3. Therefore, the physical realization of the Hubbard model in two or three dimensions, which can act as an analogue quantum simulator (that is, it can mimic the model and simulate its phase diagram and dynamics4,5), has a vital role in solving the strong-correlation puzzle, namely, revealing the physics of a large number of strongly interacting quantum particles. Here we obtain the phase diagram of the two-dimensional triangular-lattice Hubbard model by studying angle-aligned WSe2/WS2 bilayers, which form moiré superlattices6 because of the difference between the lattice constants of the two materials. We probe the charge and magnetic properties of the system by measuring the dependence of its optical response on an out-of-plane magnetic field and on the gate-tuned carrier density. At half-filling of the first hole moiré superlattice band, we observe a Mott insulating state with antiferromagnetic Curie-Weiss behaviour, as expected for a Hubbard model in the strong-interaction regime2,3,7-9. Above half-filling, our experiment suggests a possible quantum phase transition from an antiferromagnetic to a weak ferromagnetic state at filling factors near 0.6. Our results establish a new solid-state platform based on moiré superlattices that can be used to simulate problems in strong-correlation physics that are described by triangular-lattice Hubbard models.

Correlated insulating states at fractional fillings of moiré superlattices.

Quantum particles on a lattice with competing long-range interactions are ubiquitous in physics; transition metal oxides1,2, layered molecular crystals3 and trapped-ion arrays4 are a few examples. In the strongly interacting regime, these systems often show a rich variety of quantum many-body ground states that challenge theory2. The emergence of transition metal dichalcogenide moiré superlattices provides a highly controllable platform in which to study long-range electronic correlations5-12. Here we report an observation of nearly two dozen correlated insulating states at fractional fillings of tungsten diselenide/tungsten disulfide moiré superlattices. This finding is enabled by a new optical sensing technique that is based on the sensitivity to the dielectric environment of the exciton excited states in a single-layer semiconductor of tungsten diselenide. The cascade of insulating states shows an energy ordering that is nearly symmetric about a filling factor of half a particle per superlattice site. We propose a series of charge-ordered states at commensurate filling fractions that range from generalized Wigner crystals7 to charge density waves. Our study lays the groundwork for using moiré superlattices to simulate a wealth of quantum many-body problems that are described by the two-dimensional extended Hubbard model3,13,14 or spin models with long-range charge-charge and exchange interactions15,16.

CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops.

The explosive amount of multi-omics data has brought a paradigm shift both in academic research and further application in life science. However, managing and reusing the growing resources of genomic and phenotype data points presents considerable challenges for the research community. There is an urgent need for an integrated database that combines genome-wide association studies (GWAS) with genomic selection (GS). Here, we present CropGS-Hub, a comprehensive database comprising genotype, phenotype, and GWAS signals, as well as a one-stop platform with built-in algorithms for genomic prediction and crossing design. This database encompasses a comprehensive collection of over 224 billion genotype data and 434 thousand phenotype data generated from >30 000 individuals in 14 representative populations belonging to 7 major crop species. Moreover, the platform implemented three complete functional genomic selection related modules including phenotype prediction, user model training and crossing design, as well as a fast SNP genotyper plugin-in called SNPGT specifically built for CropGS-Hub, aiming to assist crop scientists and breeders without necessitating coding skills. CropGS-Hub can be accessed at https://iagr.genomics.cn/CropGS/.

Combined prediction and design reveals the target recognition mechanism of an intrinsically disordered protein interaction domain.

An increasing number of protein interaction domains and their targets are being found to be intrinsically disordered proteins (IDPs). The corresponding target recognition mechanisms are mostly elusive because of challenges in performing detailed structural analysis of highly dynamic IDP-IDP complexes. Here, we show that by combining recently developed computational approaches with experiments, the structure of the complex between the intrinsically disordered C-terminal domain (CTD) of protein 4.1G and its target IDP region in NuMA can be dissected at high resolution. First, we carry out systematic mutational scanning using dihydrofolate reductase-based protein complementarity analysis to identify essential interaction regions and key residues. The results are found to be highly consistent with an α/ß-type complex structure predicted by AlphaFold2 (AF2). We then design mutants based on the predicted structure using a deep learning protein sequence design method. The solved crystal structure of one mutant presents the same core structure as predicted by AF2. Further computational prediction and experimental assessment indicate that the well-defined core structure is conserved across complexes of 4.1G CTD with other potential targets. Thus, we reveal that an intrinsically disordered protein interaction domain uses an α/ß-type structure module formed through synergistic folding to recognize broad IDP targets. Moreover, we show that computational prediction and experiment can be jointly applied to segregate true IDP regions from the core structural domains of IDP-IDP complexes and to uncover the structure-dependent mechanisms of some otherwise elusive IDP-IDP interactions.