Biosynthesis of Epipyrone A Reveals a Highly Specific Membrane-Bound Fungal C-Glycosyltransferase for Pyrone Galactosylation.

Epipyrone A is a unique C-galactosylated 4-hydroxy-2-pyrone derivative with an antifungal potential from the fungus Epicoccum nigrum. We elucidated its biosynthesis via heterologous expression and characterized an unprecedented membrane-bound pyrone C-glycosyltransferase biochemically. Molecular docking and mutagenesis experiments suggested a possible mechanism for the heterocyclic C-glycosylation and the importance of a transmembrane helix for its catalysis. These results expand the repertoire of C-glycosyltransferases and provide new insights into the formation of C-glycosides in fungi.

KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity.

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box "TTGAC(C/T)" but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.

Plant-on-chip: Core morphogenesis processes in the tiny plant Wolffia australiana.

A plant can be thought of as a colony comprising numerous growth buds, each developing to its own rhythm. Such lack of synchrony impedes efforts to describe core principles of plant morphogenesis, dissect the underlying mechanisms, and identify regulators. Here, we use the minimalist known angiosperm to overcome this challenge and provide a model system for plant morphogenesis. We present a detailed morphological description of the monocot Wolffia australiana, as well as high-quality genome information. Further, we developed the plant-on-chip culture system and demonstrate the application of advanced technologies such as single-nucleus RNA-sequencing, protein structure prediction, and gene editing. We provide proof-of-concept examples that illustrate how W. australiana can decipher the core regulatory mechanisms of plant morphogenesis.

Aptamer-based nanointerferometer enables amplification-free ultrasensitive detection and differentiation of SARS-CoV-2 variants.

The state-of-the-art SARS-CoV-2 detection methods include qRT-PCR and antibody-based lateral flow assay (LFA) point-of-care tests. Despite the high sensitivity and selectivity, qRT-PCR is slow, expensive and needs well-trained operators. On the other extreme, LFA suffers from low sensitivity albeit its fast detection speed, low detection cost and ease of use. Therefore, the continuing COVID-19 pandemic calls for a SARS-CoV-2 detection method that is rapid, convenient and cost-effective without compromise in sensitivity. Here we provide a proof-of-principle demonstration of an optimized aptamer-based nanointerferometer that enables rapid and amplification-free detection of SARS-CoV-2 spike protein-coated pseudovirus directly from human saliva with the limit of detection (LOD) of about 400 copies per mL. This LOD is on par with that of qRT-PCR, making it 1000 to 100,000-fold more sensitive than commercial LFA tests. Using various combinations of negative selections during the screens for the aptamer targeting the receptor binding domain of the spike protein of SARS-CoV-2, we isolated two aptamers that can distinguish the Omicron and Delta variants. Integrating these two aptamers with LFA strips or the nanointerferometer sensors allows both detection and differentiation of the Omicron and Delta variants which has the potential to realize rapid triage of patients infected different SARS-CoV-2 variants.

A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data.

Single-cell RNA sequencing is the reference technology to characterize the composition of the tumor microenvironment and to study tumor heterogeneity at high resolution. Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single-cell RNA-seq data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to datasets encompassing 106 samples and 93,322 cells from different tumor types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

Co-evolution-based prediction of metal-binding sites in proteomes by machine learning.

Metal ions have various important biological roles in proteins, including structural maintenance, molecular recognition and catalysis. Previous methods of predicting metal-binding sites in proteomes were based on either sequence or structural motifs. Here we developed a co-evolution-based pipeline named 'MetalNet' to systematically predict metal-binding sites in proteomes. We applied MetalNet to proteomes of four representative prokaryotic species and predicted 4,849 potential metalloproteins, which substantially expands the currently annotated metalloproteomes. We biochemically and structurally validated previously unannotated metal-binding sites in several proteins, including apo-citrate lyase phosphoribosyl-dephospho-CoA transferase citX, an Escherichia coli enzyme lacking structural or sequence homology to any known metalloprotein (Protein Data Bank (PDB) codes: 7DCM and 7DCN ). MetalNet also successfully recapitulated all known zinc-binding sites from the human spliceosome complex. The pipeline of MetalNet provides a unique and enabling tool for interrogating the hidden metalloproteome and studying metal biology.

Human antibody BD-218 has broad neutralizing activity against concerning variants of SARS-CoV-2.

As SARS-CoV-2 variants of concern (VOC) reduce the effectiveness of existing anti-COVID therapeutics, it is increasingly critical to identify highly potent neutralizing antibodies (nAbs) that bind to conserved regions across multiple variants, especially beta, delta, and omicron variants. Using single-cell sequencing with biochemical methods and pseudo-typed virus neutralization experiments, here we report the characterization of a potent nAb BD-218, identified from an early screen of patients recovering from the original virus. We have determined the cryo-EM structure of the BD-218/spike protein complex to define its epitope in detail, which revealed that BD-218 interacts with a novel epitope on the receptor-binding domain (RBD) of the spike protein. We concluded that BD-218 is a highly effective and broadly active nAb against SARS-CoV-2 variants with promising potential for therapeutic development.

DNA-TCP complex structures reveal a unique recognition mechanism for TCP transcription factor families.

Plant-specific TCP transcription factors are key regulators of diverse plant functions. TCP transcription factors have long been annotated as basic helix-loop-helix (bHLH) transcription factors according to remote sequence homology without experimental validation, and their consensus DNA-binding sequences and protein-DNA recognition mechanisms have remained elusive. Here, we report the crystal structures of the class I TCP domain from AtTCP15 and the class II TCP domain from AtTCP10 in complex with different double-stranded DNA (dsDNA). The complex structures reveal that the TCP domain is a distinct DNA-binding motif and the homodimeric TCP domains adopt a unique three-site recognition mode, binding to dsDNA mainly through a central pair of ß-strands formed by the dimer interface and two basic flexible loops from each monomer. The consensus DNA-binding sequence for class I TCPs is a perfectly palindromic 11 bp (GTGGGNCCCAC), whereas that for class II TCPs is a near-palindromic 11 bp (GTGGTCCCCAC). The unique DNA binding mode allows the TCP domains to display broad specificity for a range of DNA sequences even shorter than 11 bp, adding further complexity to the regulatory network of plant TCP transcription factors.

Illuminating the dark protein-protein interactome.

In living systems, a complex network of protein-protein interactions (PPIs) underlies most biochemical events. The human protein-protein interactome has been surveyed using yeast two-hybrid (Y2H)- and mass spectrometry (MS)-based approaches such as affinity purification coupled to MS (AP-MS). Despite decades of systematic investigations and collaborative multi-disciplinary efforts, there is no "gold standard" for documenting PPIs. A surprisingly large fraction of the human interactome remains uncharted, which we refer to as the "dark interactome." In this review, we highlight the complexity of the human interactome and discuss the current status of the human reference interactome maps. We discuss why a large proportion of the human interactome has remained refractory to traditional approaches. We propose an experimental model that can enable the identification of the dark interactome in a cell-type-specific manner. We also propose a framework to implement when embarking on studies designed to rigorously identify and characterize protein interactions.

Arabidopsis transcription factor TCP4 represses chlorophyll biosynthesis to prevent petal greening.

Green petals pose a challenge for pollinators to distinguish flowers from leaves, but they are valuable as a specialty flower trait. However, little is understood about the molecular mechanisms that underlie the development of green petals. Here, we report that CINCINNATA (CIN)-like TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) proteins play key roles in the control of petal color. The septuple tcp2/3/4/5/10/13/17 mutant produced flowers with green petals due to chlorophyll accumulation. Expression of TCP4 complemented the petal phenotype of tcp2/3/4/5/10/13/17. We found that chloroplasts were converted into leucoplasts in the distal parts of wild-type petals but not in the proximal parts during flower development, whereas plastid conversion was compromised in the distal parts of tcp2/3/4/5/10/13/17 petals. TCP4 and most CIN-like TCPs were predominantly expressed in distal petal regions, consistent with the green-white pattern in wild-type petals and the petal greening observed in the distal parts of tcp2/3/4/5/10/13/17 petals. RNA-sequencing data revealed that most chlorophyll biosynthesis genes were downregulated in the white distal parts of wild-type petals, but these genes had elevated expression in the distal green parts of tcp2/3/4/5/10/13/17 petals and the green proximal parts of wild-type petals. We revealed that TCP4 repressed chlorophyll biosynthesis by directly binding to the promoters of PROTOCHLOROPHYLLIDE REDUCTASE (PORB), DIVINYL REDUCTASE (DVR), and SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1), which are known to promote petal greening. We found that the conversion of chloroplasts to leucoplasts and the green coloration in the proximal parts of petals appeared to be conserved among plant species. Our findings uncover a major molecular mechanism that underpins the formation of petal color patterns and provide a foundation for the breeding of plants with green flowers.

Computational insights into differential interaction of mammalian angiotensin-converting enzyme 2 with the SARS-CoV-2 spike receptor binding domain.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Angiotensin-converting enzyme 2 (ACE2) has been identified as the host cell receptor that binds to the receptor-binding domain (RBD) of the SARS-COV-2 spike protein and mediates cell entry. Because the ACE2 proteins are widely available in mammals, it is important to investigate the interactions between the RBD and the ACE2 of other mammals. Here we analyzed the sequences of ACE2 proteins from 16 mammals, predicted the structures of ACE2-RBD complexes by homology modeling, and refined the complexes using molecular dynamics simulation. Analyses on sequence, structure, and dynamics synergistically provide valuable insights into the interactions between ACE2 and RBD. The analysis outcomes suggest that the ACE2 of bovine, cat, and panda form strong binding interactions with RBD, while in the cases of rat, least horseshoe bat, horse, pig, mouse, and civet, the ACE2 proteins interact weakly with RBD.

Mutations on RBD of SARS-CoV-2 Omicron variant result in stronger binding to human ACE2 receptor.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to more than 270 million infections and 5.3 million of deaths worldwide. Several major variants of SARS-CoV-2 have emerged and posed challenges in controlling the pandemic. The recently occurred Omicron variant raised serious concerns about reducing the efficacy of vaccines and neutralization antibodies due to its vast mutations. We have modelled the complex structure of the human ACE2 protein and the receptor binding domain (RBD) of Omicron Spike protein (S-protein), and conducted atomistic molecular dynamics simulations to study the binding interactions. The analysis shows that the Omicron RBD binds more strongly to the human ACE2 protein than the original strain. The mutations at the ACE2-RBD interface enhance the tight binding by increasing hydrogen bonding interaction and enlarging buried solvent accessible surface area.

Revealing atomic-scale molecular diffusion of a plant-transcription factor WRKY domain protein along DNA.

Transcription factor (TF) target search on genome is highly essential for gene expression and regulation. High-resolution determination of TF diffusion along DNA remains technically challenging. Here, we constructed a TF model system using the plant WRKY domain protein in complex with DNA from crystallography and demonstrated microsecond diffusion dynamics of WRKY on DNA by employing all-atom molecular-dynamics (MD) simulations. Notably, we found that WRKY preferentially binds to one strand of DNA with significant energetic bias compared with the other, or nonpreferred strand. The preferential DNA-strand binding becomes most prominent in the static process, from nonspecific to specific DNA binding, but less distinct during diffusive movements of the domain protein on the DNA. Remarkably, without employing acceleration forces or bias, we captured a complete one-base-pair stepping cycle of the protein tracking along major groove of DNA with a homogeneous poly-adenosine sequence, as individual hydrogen bonds break and reform at the protein-DNA binding interface. Further DNA-groove tracking motions of the protein forward or backward, with occasional sliding as well as strand crossing to minor groove of DNA, were also captured. The processive diffusion of WRKY along DNA has been further sampled via coarse-grained MD simulations. The study thus provides structural dynamics details on diffusion of a small TF domain protein, suggests how the protein approaches a specific recognition site on DNA, and supports further high-precision experimental detection. The stochastic movements revealed in the TF diffusion also provide general clues about how other protein walkers step and slide along DNA.

Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.

A map of tumor-host interactions in glioma at single-cell resolution.

BACKGROUND: Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. RESULTS: We present a novel method, single-cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. CONCLUSIONS: Our results provide a complete map of the active tumor-host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.

Structurally Resolved SARS-CoV-2 Antibody Shows High Efficacy in Severely Infected Hamsters and Provides a Potent Cocktail Pairing Strategy.

Understanding how potent neutralizing antibodies (NAbs) inhibit SARS-CoV-2 is critical for effective therapeutic development. We previously described BD-368-2, a SARS-CoV-2 NAb with high potency; however, its neutralization mechanism is largely unknown. Here, we report the 3.5-Å cryo-EM structure of BD-368-2/trimeric-spike complex, revealing that BD-368-2 fully blocks ACE2 recognition by occupying all three receptor-binding domains (RBDs) simultaneously, regardless of their "up" or "down" conformations. Also, BD-368-2 treats infected adult hamsters at low dosages and at various administering windows, in contrast to placebo hamsters that manifested severe interstitial pneumonia. Moreover, BD-368-2's epitope completely avoids the common binding site of VH3-53/VH3-66 recurrent NAbs, evidenced by tripartite co-crystal structures with RBDs. Pairing BD-368-2 with a potent recurrent NAb neutralizes SARS-CoV-2 pseudovirus at pM level and rescues mutation-induced neutralization escapes. Together, our results rationalized a new RBD epitope that leads to high neutralization potency and demonstrated BD-368-2's therapeutic potential in treating COVID-19.

Mn2+ Directly Activates cGAS and Structural Analysis Suggests Mn2+ Induces a Noncanonical Catalytic Synthesis of 2'3'-cGAMP.

DNA binding allosterically activates the cytosolic DNA sensor cGAS (cyclic GMP-AMP [cGAMP] synthase) to synthesize 2'3'-cGAMP, using Mg2+ as the metal cofactor that catalyzes two nucleotidyl-transferring reactions. We previously found that Mn2+ potentiates cGAS activation, but the underlying mechanism remains unclear. Here, we report that Mn2+ directly activates cGAS. Structural analysis reveals that Mn2+-activated cGAS undergoes globally similar conformational changes to DNA-activated cGAS but forms a unique η1 helix to widen the catalytic pocket, allowing substrate entry and cGAMP synthesis. Strikingly, in Mn2+-activated cGAS, the linear intermediates pppGpG and pGpA take an inverted orientation in the active pocket, suggesting a noncanonical but accelerated cGAMP cyclization without substrate flip-over. Moreover, unlike the octahedral coordination around Mg2+, the two catalytic Mn2+ are coordinated by triphosphate moiety of the inverted substrate, independent of the catalytic triad residues. Our findings thus uncover Mn2+ as a cGAS activator that initiates noncanonical 2'3'-cGAMP synthesis.

Potent Neutralizing Antibodies against SARS-CoV-2 Identified by High-Throughput Single-Cell Sequencing of Convalescent Patients' B Cells.

The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here, we report the rapid identification of SARS-CoV-2-neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients. From 8,558 antigen-binding IgG1+ clonotypes, 14 potent neutralizing antibodies were identified, with the most potent one, BD-368-2, exhibiting an IC50 of 1.2 and 15 ng/mL against pseudotyped and authentic SARS-CoV-2, respectively. BD-368-2 also displayed strong therapeutic and prophylactic efficacy in SARS-CoV-2-infected hACE2-transgenic mice. Additionally, the 3.8 Å cryo-EM structure of a neutralizing antibody in complex with the spike-ectodomain trimer revealed the antibody's epitope overlaps with the ACE2 binding site. Moreover, we demonstrated that SARS-CoV-2-neutralizing antibodies could be directly selected based on similarities of their predicted CDR3H structures to those of SARS-CoV-neutralizing antibodies. Altogether, we showed that human neutralizing antibodies could be efficiently discovered by high-throughput single B cell sequencing in response to pandemic infectious diseases.