Type 2 vomeronasal receptor expression in the olfactory organ of African lungfish, Protopterus annectens.

The olfactory organ of tetrapods, with few exceptions, comprises the main and accessory organs: olfactory epithelium (OE) and vomeronasal organ (VNO). Unlike tetrapods, teleost fish lack a VNO. However, lungfish, a type of sarcopterygian fish closely related to tetrapods, possesses a lamellar OE similar to the OE of teleosts and a recess epithelium (RecE) resembling the amphibian VNO. The RecE has been hypothesized as a primordial VNO. Olfactory receptors in tetrapods are distinctively expressed in the OE and VNO. For instance, type 2 vomeronasal receptors (V2Rs) in Xenopus are categorized into those exclusively expressed in the OE and those solely expressed in the VNO. It remains unclear whether V2Rs are differentially expressed between the lamellar OE and RecE in lungfish. This study investigated V2R expression in the lamellar OE and RecE of the African lungfish, Protopterus annectens. P. annectens V2Rs were categorized into three groups: those exclusively expressed in the lamellar OE, those exclusively expressed in the RecE, and those expressed in both the lamellar OE and RecE. V2Rs exclusively expressed in the RecE and those expressed in both the lamellar OE and RecE formed a distinct clade in the phylogenetic tree, whereas others were solely expressed in the lamellar OE. These findings suggest that lungfish V2R expression represents an intermediate stage toward complete segregation between V2Rs expressed in the OE and those expressed in the VNO.

Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance.

Studying the genetic regulation of protein expression (through protein quantitative trait loci (pQTLs)) offers a deeper understanding of regulatory variants uncharacterized by mRNA expression regulation (expression QTLs (eQTLs)) studies. Here we report cis-eQTL and cis-pQTL statistical fine-mapping from 1,405 genotyped samples with blood mRNA and 2,932 plasma samples of protein expression, as part of the Japan COVID-19 Task Force (JCTF). Fine-mapped eQTLs (n = 3,464) were enriched for 932 variants validated with a massively parallel reporter assay. Fine-mapped pQTLs (n = 582) were enriched for missense variations on structured and extracellular domains, although the possibility of epitope-binding artifacts remains. Trans-eQTL and trans-pQTL analysis highlighted associations of class I HLA allele variation with KIR genes. We contrast the multi-tissue origin of plasma protein with blood mRNA, contributing to the limited colocalization level, distinct regulatory mechanisms and trait relevance of eQTLs and pQTLs. We report a negative correlation between ABO mRNA and protein expression because of linkage disequilibrium between distinct nearby eQTLs and pQTLs.

Anisotropic Hydrogel Microelectrodes for Intraspinal Neural Recordings in vivo.

Creating durable, motion-compliant neural interfaces is crucial for accessing dynamic tissues under in vivo conditions and linking neural activity with behaviors. Utilizing the self-alignment of nano-fillers in a polymeric matrix under repetitive tension, here, we introduce conductive carbon nanotubes with high aspect ratios into semi-crystalline polyvinyl alcohol hydrogels and create electrically anisotropic percolation pathways through cyclic stretching. The resulting anisotropic hydrogel fibers (diameter of 187 ± 13 µm) exhibit fatigue resistance (20,000 cycles at 20% strain) with a stretchability of 64.5 ± 7.9%, and low electrochemical impedance (900 ± 149 kΩ @ 1kHz). We observe the re-constructed nanofillers' axial alignment and a corresponding anisotropic impedance decrease along the direction of cyclic stretching. We fabricate fiber-shaped hydrogels into bioelectronic devices and implant them into wild-type and transgenic Thy1-ChR2-EYFP mice to record electromyographic signals from muscles in anesthetized and freely moving conditions. These hydrogel fibers effectively enable the simultaneous recording of electrical signals from ventral spinal cord neurons and the tibialis anterior muscles during optogenetic stimulation. Importantly, the devices maintain functionality with repeatable recording results over eight months after implantation, demonstrating their durability and potential for long-term monitoring in neurophysiological studies.

Assessment of Protein-Protein Docking Models Using Deep Learning.

Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes have been determined by biophysical experimental methods, such as X-ray crystallography and cryogenic electron microscopy. However, as experimental methods are costly in resources, many computational methods have been developed that model protein complex structures. One of the difficulties in computational protein complex modeling (protein docking) is to select the most accurate models among many models that are usually generated by a docking method. This article reviews advances in protein docking model assessment methods, focusing on recent developments that apply deep learning to several network architectures.

Spinal projecting neurons in rostral ventromedial medulla co-regulate motor and sympathetic tone.

Many behaviors require the coordinated actions of somatic and autonomic functions. However, the underlying mechanisms remain elusive. By opto-stimulating different populations of descending spinal projecting neurons (SPNs) in anesthetized mice, we show that stimulation of excitatory SPNs in the rostral ventromedial medulla (rVMM) resulted in a simultaneous increase in somatomotor and sympathetic activities. Conversely, opto-stimulation of rVMM inhibitory SPNs decreased both activities. Anatomically, these SPNs innervate both sympathetic preganglionic neurons and motor-related regions in the spinal cord. Fiber-photometry recording indicated that the activities of rVMM SPNs correlate with different levels of muscle and sympathetic tone during distinct arousal states. Inhibiting rVMM excitatory SPNs reduced basal muscle and sympathetic tone, impairing locomotion initiation and high-speed performance. In contrast, silencing the inhibitory population abolished muscle atonia and sympathetic hypoactivity during rapid eye movement (REM) sleep. Together, these results identify rVMM SPNs as descending spinal projecting pathways controlling the tone of both the somatomotor and sympathetic systems.

A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons.

The brain controls nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from the brain to the spinal cord. However, a comprehensive molecular characterization of brain-wide SPNs is still lacking. Here we transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain1. This taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) heterogeneous populations in the reticular formation with broad spinal termination patterns, suitable for relaying commands related to the activities of the entire spinal cord; and (3) modulatory neurons expressing slow-acting neurotransmitters and/or neuropeptides in the hypothalamus, midbrain and reticular formation for 'gain setting' of brain-spinal signals. In addition, this atlas revealed a LIM homeobox transcription factor code that parcellates the reticulospinal neurons into five molecularly distinct and spatially segregated populations. Finally, we found transcriptional signatures of a subset of SPNs with large soma size and correlated these with fast-firing electrophysiological properties. Together, this study establishes a comprehensive taxonomy of brain-wide SPNs and provides insight into the functional organization of SPNs in mediating brain control of bodily functions.

Aqueous Circularly Polarized Luminescence Induced by Homopolypeptide Self-Assembly.

Remarkable advances have been achieved in solution self-assembly of polypeptides from the perspective of nanostructures, mechanisms, and applications. Despite the intrinsic chirality of polypeptides, the promising generation of aqueous circularly polarized luminescence (CPL) based on their self-assembly has been rarely reported due to the weak fluorescence of most polypeptides and the indeterminate self-assembly mechanism. Here, we propose a facile strategy for achieving aqueous CPL based on the self-assembly of simple homopolypeptides modified with a terminal group featuring both twisted intramolecular charge transfer and aggregation-induced emission properties. A morphology-dependent CPL can be observed under different self-assembly conditions by altering the solvents. A nanotoroid-dispersed aqueous solution with detectable CPL can be obtained by using tetrahydrofuran as a good solvent for the self-assembly, which is attributed to the involvement of the terminal group in the chiral environment formed by the homopolypeptide chains. However, such a chiral packing mode cannot be realized in nanorods self-assembled from dioxane, resulting in an inactive CPL phenomenon. Furthermore, CPL signals can be greatly amplified by co-assembly of homopolypeptides with the achiral small molecule derived from the terminal group. This work not only provides a pathway to construct aqueous CPL-active homopolypeptide nanomaterials but also reveals a potential mechanism in the self-assembly for chiral production, transfer, and amplification in polypeptide-based nanostructures.

Improved Peptide Docking with Privileged Knowledge Distillation using Deep Learning.

Protein-peptide interactions play a key role in biological processes. Understanding the interactions that occur within a receptor-peptide complex can help in discovering and altering their biological functions. Various computational methods for modeling the structures of receptor-peptide complexes have been developed. Recently, accurate structure prediction enabled by deep learning methods has significantly advanced the field of structural biology. AlphaFold (AF) is among the top-performing structure prediction methods and has highly accurate structure modeling performance on single-chain targets. Shortly after the release of AlphaFold, AlphaFold-Multimer (AFM) was developed in a similar fashion as AF for prediction of protein complex structures. AFM has achieved competitive performance in modeling protein-peptide interactions compared to previous computational methods; however, still further improvement is needed. Here, we present DistPepFold, which improves protein-peptide complex docking using an AFM-based architecture through a privileged knowledge distillation approach. DistPepFold leverages a teacher model that uses native interaction information during training and transfers its knowledge to a student model through a teacher-student distillation process. We evaluated DistPepFold's docking performance on two protein-peptide complex datasets and showed that DistPepFold outperforms AFM. Furthermore, we demonstrate that the student model was able to learn from the teacher model to make structural improvements based on AFM predictions.

Distance-AF: Modifying Predicted Protein Structure Models by Alphafold2 with User-Specified Distance Constraints.

The three-dimensional structure of a protein plays a fundamental role in determining its function and has an essential impact on understanding biological processes. Despite significant progress in protein structure prediction, such as AlphaFold2, challenges remain on those hard targets that Alphafold2 does not often perform well due to the complex folding of protein and a large number of possible conformations. Here we present a modified version of the AlphaFold2, called Distance-AF, which aims to improve the performance of AlphaFold2 by including distance constraints as input information. Distance-AF uses AlphaFold2's predicted structure as a starting point and incorporates distance constraints between amino acids to adjust folding of the protein structure until it meets the constraints. Distance-AF can correct the domain orientation on challenging targets, leading to more accurate structures with a lower root mean square deviation (RMSD). The ability of Distance-AF is also useful in fitting protein structures into cryo-electron microscopy maps.

In situ hybridization analysis of odorant receptor expression in the olfactory organ of the pig-nosed turtle Carettochelys insculpta.

The turtle olfactory organ consists of upper (UCE) and lower (LCE) chamber epithelium, which send axons to the ventral and dorsal portions of the olfactory bulbs, respectively. Generally, the UCE is associated with glands and contains ciliated olfactory receptor neurons (ORNs), while the LCE is devoid of glands and contains microvillous ORNs. However, the olfactory organ of the pig-nosed turtle Carettochelys insculpta appears to be a single olfactory system morphologically: there are no associated glands; ciliated ORNs are distributed throughout the olfactory organ; and the olfactory bulb is not divided into ventral and dorsal portions. In this study, we analyzed the expression of odorant receptors (ORs), the major olfactory receptors in turtles, in the pig-nosed turtle olfactory organ, via in situ hybridization. Of 690 ORs, 375 were classified as class I and 315 as class II. Some class II ORs were expressed predominantly in the posterior dorsomedial walls of the nasal cavity, while other class II ORs and all class I ORs examined were expressed in the remaining region. These results suggest that the pig-nosed turtle olfactory organ can be divided into two regions according to the expression of ORs.

NuFold: A Novel Tertiary RNA Structure Prediction Method Using Deep Learning with Flexible Nucleobase Center Representation.

RNA is not only playing a core role in the central dogma as mRNA between DNA and protein, but also many non-coding RNAs have been discovered to have unique and diverse biological functions. As genome sequences become increasingly available and our knowledge of RNA sequences grows, the study of RNA's structure and function has become more demanding. However, experimental determination of three-dimensional RNA structures is both costly and time-consuming, resulting in a substantial disparity between RNA sequence data and structural insights. In response to this challenge, we propose a novel computational approach that harnesses state-of-the-art deep learning architecture NuFold to accurately predict RNA tertiary structures. This approach aims to offer a cost-effective and efficient means of bridging the gap between RNA sequence information and structural comprehension. NuFold implements a nucleobase center representation, which allows it to reproduce all possible nucleotide conformations accurately.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Photoactivatable Sequential Destruction of Multiorganelles for Cancer Therapy.

Organelle-targeted therapy guided by fluorescence imaging is promising for precise cancer treatment. However, most current organelle-targeted therapeutics can only destruct single organelles, which suffer from limited therapeutic efficacy. To address this challenge, a photoactivatable probe was developed for sequential photodynamic destruction of multiorganelles in cancer cells, including lysosomes, lipid droplets, and mitochondria. This photoactivatable probe not only exhibits efficient cancer cell eradication in vitro but also can suppress tumor growth in vivo. Simultaneously, the photoactivatable probe enables sequential destruction of multiple organelles in cancer cells, which can be observed in situ through the conversion of green-to-red fluorescence facilitated by a photooxidative dehydrogenation reaction. We believe this photoactivatable probe for sequential destruction of multiple organelles associated with fluorescence color conversion provides a new strategy for cancer treatment with greatly improved efficacy.

Aggregation-induced emission biomaterials for anti-pathogen medical applications: detecting, imaging and killing.

Microbial pathogens, including bacteria, fungi and viruses, greatly threaten the global public health. For pathogen infections, early diagnosis and precise treatment are essential to cut the mortality rate. The emergence of aggregation-induced emission (AIE) biomaterials provides an effective and promising tool for the theranostics of pathogen infections. In this review, the recent advances about AIE biomaterials for anti-pathogen theranostics are summarized. With the excellent sensitivity and photostability, AIE biomaterials have been widely applied for precise diagnosis of pathogens. Besides, different types of anti-pathogen methods based on AIE biomaterials will be presented in detail, including chemotherapy and phototherapy. Finally, the existing deficiencies and future development of AIE biomaterials for anti-pathogen applications will be discussed.

Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types.

The human genome contains millions of candidate cis-regulatory elements (CREs) with cell-type-specific activities that shape both health and myriad disease states. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these CREs. Here, we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of over 680,000 sequences, representing a nearly comprehensive set of all annotated CREs among three cell types (HepG2, K562, and WTC11), finding 41.7% to be functional. By testing sequences in both orientations, we find promoters to have significant strand orientation effects. We also observe that their 200 nucleotide cores function as non-cell-type-specific 'on switches' providing similar expression levels to their associated gene. In contrast, enhancers have weaker orientation effects, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict CRE function with high accuracy and delineate regulatory motifs. Testing an additional lentiMPRA library encompassing 60,000 CREs in all three cell types, we further identified factors that determine cell-type specificity. Collectively, our work provides an exhaustive catalog of functional CREs in three widely used cell lines, and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

Essential amino acids in the Plant-Conserved and Class-Specific Regions of cellulose synthases.

The Plant-Conserved Region (P-CR) and the Class-Specific Region (CSR) are two plant-unique sequences in the catalytic core of cellulose synthases (CESAs) for which specific functions have not been established. Here, we used site-directed mutagenesis to replace amino acids and motifs within these sequences predicted to be essential for assembly and function of CESAs. We developed an in vivo method to determine the ability of mutated CesA1 transgenes to complement an Arabidopsis (Arabidopsis thaliana) temperature-sensitive root-swelling1 (rsw1) mutant. Replacement of a Cys residue in the CSR, which blocks dimerization in vitro, rendered the AtCesA1 transgene unable to complement the rsw1 mutation. Examination of the CSR sequences from 33 diverse angiosperm species showed domains of high-sequence conservation in a class-specific manner but with variation in the degrees of disorder, indicating a nonredundant role of the CSR structures in different CESA isoform classes. The Cys residue essential for dimerization was not always located in domains of intrinsic disorder. Expression of AtCesA1 transgene constructs, in which Pro417 and Arg453 were substituted for Ala or Lys in the coiled-coil of the P-CR, were also unable to complement the rsw1 mutation. Despite an expected role for Arg457 in trimerization of CESA proteins, AtCesA1 transgenes with Arg457Ala mutations were able to fully restore the wild-type phenotype in rsw1. Our data support that Cys662 within the CSR and Pro417 and Arg453 within the P-CR of Arabidopsis CESA1 are essential residues for functional synthase complex formation, but our data do not support a specific role for Arg457 in trimerization in native CESA complexes.

A clickable AIEgen for visualization of macrophage-microbe interaction.

Visualization of immunocyte-microbe interaction is of great importance to reveal the physiological role and working mechanism of innate and adaptive immune system. The lack of rapid and stable microbial labeling platform and insufficient understanding of macrophage-microbe interaction may delay precautions that could be made. In this contribution, a clickable AIEgen, CDPP-NCS, containing a cationic pyridinium moiety for targeting bacteria and an isothiocyanate moiety for covalently bonding with amine groups, is successfully developed. With the advantages of excellent photostability and rapid bioconjugation with amine groups on the bacterial envelope, the processes of macrophage-bacterium interactions with subcellular resolution has been successfully captured using this clickable AIE probe. Therefore, the new clickable AIEgen is a powerful tool to study the interaction between cell and bacterium.

Recent advances of aggregation-induced emission materials for fluorescence image-guided surgery.

Real-time intraoperative guidance is essential during various surgical treatment of many diseases. Aggregation-induced emission (AIE) materials have shown great potential for guiding surgeons during complex interventions, with the merits of deep tissue penetration, high quantum yield, high molar absorptivity, low background, good targeting ability and excellent photostability. Herein, we provided insights to design efficient AIE materials regarding three key parameters, i.e., deep-tissue penetration ability, high brightness of AIE luminogens (AIEgens), and precise tumor/other pathology nidus targeting strategies, for realizing better application of fluorescence image-guided surgery. Representative interdisciplinary achievements were outlined for the demonstration of this emerging field. Challenges and future opportunities of AIE materials were briefly discussed. The aim of this review is to provide a comprehensive view of AIE materials for intraoperative guidance for researchers and surgeons, and to inspire more further correlational studies in the new frontiers of image-guided surgery.

A photoactivatable theranostic probe for simultaneous oxidative stress-triggered multi-color cellular imaging and photodynamic therapy.

Simultaneous in situ monitoring critical organelles upon oxidative stress and implementing therapeutics utilizing oxidative stress are of vital importance and remain challenging task. Herein, we rationally design and facilely synthesized a photoactivatable fluorescent probe bearing 1,4-dihydropyridine moiety with aggregation-induced emission (AIE) tendency, namely TPA-DHPy, which can rapidly transform into its pyridine counterpart TPA-Py via photo-oxidative dehydrogenation showing strong polarity sensitivity and largely red-shifted emission. TPA-DHPy- and TPA-Py-based type I/type II photosensitization is able to effectively generate reactive oxygen species to induce in situ oxidative stress under white light irradiation. TPA-DHPy can be taken up by cancer cells, and gradually light up lipid droplets (LDs) and endoplasmic reticulum (ER) during photoactivatable process, as well as in situ monitoring difference and alteration of their microenvironment upon oxidative stress by means of multi-color fluorescence imaging in lambda mode. Furthermore, the in situ generated TPA-Py is capable of further destroying the functions of LDs and ER with prolonging the irradiation time, and remarkably inhibiting tumor growth under white light irradiation by the way of photodynamic therapy. This study thus offers useful insights into designing a new generation of theranostic agents towards imaging-guided precise cancer therapy.