IRF4 is a key thermogenic transcriptional partner of PGC-1α.

Brown fat can reduce obesity through the dissipation of calories as heat. Control of thermogenic gene expression occurs via the induction of various coactivators, most notably PGC-1α. In contrast, the transcription factor partner(s) of these cofactors are poorly described. Here, we identify interferon regulatory factor 4 (IRF4) as a dominant transcriptional effector of thermogenesis. IRF4 is induced by cold and cAMP in adipocytes and is sufficient to promote increased thermogenic gene expression, energy expenditure, and cold tolerance. Conversely, knockout of IRF4 in UCP1(+) cells causes reduced thermogenic gene expression and energy expenditure, obesity, and cold intolerance. IRF4 also induces the expression of PGC-1α and PRDM16 and interacts with PGC-1α, driving Ucp1 expression. Finally, cold, ß-agonists, or forced expression of PGC-1α are unable to cause thermogenic gene expression in the absence of IRF4. These studies establish IRF4 as a transcriptional driver of a program of thermogenic gene expression and energy expenditure.

Haplotype-resolved 3D chromatin architecture of the hybrid pig.

In diploid mammals, allele-specific three-dimensional (3D) genome architecture may lead to imbalanced gene expression. Through ultradeep in situ Hi-C sequencing of three representative somatic tissues (liver, skeletal muscle, and brain) from hybrid pigs generated by reciprocal crosses of phenotypically and physiologically divergent Berkshire and Tibetan pigs, we uncover extensive chromatin reorganization between homologous chromosomes across multiple scales. Haplotype-based interrogation of multi-omic data revealed the tissue dependence of 3D chromatin conformation, suggesting that parent-of-origin-specific conformation may drive gene imprinting. We quantify the effects of genetic variations and histone modifications on allelic differences of long-range promoter-enhancer contacts, which likely contribute to the phenotypic differences between the parental pig breeds. We also observe the fine structure of somatically paired homologous chromosomes in the pig genome, which has a functional implication genome-wide. This work illustrates how allele-specific chromatin architecture facilitates concomitant shifts in allele-biased gene expression, as well as the possible consequential phenotypic changes in mammals.

Transcription Factor PU.1 Represses and Activates Gene Expression in Early T Cells by Redirecting Partner Transcription Factor Binding.

Transcription factors normally regulate gene expression through their action at sites where they bind to DNA. However, the balance of activating and repressive functions that a transcription factor can mediate is not completely understood. Here, we showed that the transcription factor PU.1 regulated gene expression in early T cell development both by recruiting partner transcription factors to its own binding sites and by depleting them from the binding sites that they preferred when PU.1 was absent. The removal of partner factors Satb1 and Runx1 occurred primarily from sites where PU.1 itself did not bind. Genes linked to sites of partner factor "theft" were enriched for genes that PU.1 represses despite lack of binding, both in a model cell line system and in normal T cell development. Thus, system-level competitive recruitment dynamics permit PU.1 to affect gene expression both through its own target sites and through action at a distance.

Transformation of Accessible Chromatin and 3D Nucleome Underlies Lineage Commitment of Early T Cells.

How chromatin reorganization coordinates differentiation and lineage commitment from hematopoietic stem and progenitor cells (HSPCs) to mature immune cells has not been well understood. Here, we carried out an integrative analysis of chromatin accessibility, topologically associating domains, AB compartments, and gene expression from HSPCs to CD4+CD8+ T cells. We found that abrupt genome-wide changes at all three levels of chromatin organization occur during the transition from double-negative stage 2 (DN2) to DN3, accompanying the T lineage commitment. The transcription factor BCL11B, a critical regulator of T cell commitment, is associated with increased chromatin interaction, and Bcl11b deletion compromised chromatin interaction at its target genes. We propose that these large-scale and concerted changes in chromatin organization present an energy barrier to prevent the cell from reversing its fate to earlier stages or redirecting to alternatives and thus lock the cell fate into the T lineages.

TLR9 and beclin 1 crosstalk regulates muscle AMPK activation in exercise.

The activation of adenosine monophosphate-activated protein kinase (AMPK) in skeletal muscle coordinates systemic metabolic responses to exercise1. Autophagy-a lysosomal degradation pathway that maintains cellular homeostasis2-is upregulated during exercise, and a core autophagy protein, beclin 1, is required for AMPK activation in skeletal muscle3. Here we describe a role for the innate immune-sensing molecule Toll-like receptor 9 (TLR9)4, and its interaction with beclin 1, in exercise-induced activation of AMPK in skeletal muscle. Mice that lack TLR9 are deficient in both exercise-induced activation of AMPK and plasma membrane localization of the GLUT4 glucose transporter in skeletal muscle, but are not deficient in autophagy. TLR9 binds beclin 1, and this interaction is increased by energy stress (glucose starvation and endurance exercise) and decreased by a BCL2 mutation3,5 that blocks the disruption of BCL2-beclin 1 binding. TLR9 regulates the assembly of the endolysosomal phosphatidylinositol 3-kinase complex (PI3KC3-C2)-which contains beclin 1 and UVRAG-in skeletal muscle during exercise, and knockout of beclin 1 or UVRAG inhibits the cellular AMPK activation induced by glucose starvation. Moreover, TLR9 functions in a muscle-autonomous fashion in ex vivo contraction-induced AMPK activation, glucose uptake and beclin 1-UVRAG complex assembly. These findings reveal a heretofore undescribed role for a Toll-like receptor in skeletal-muscle AMPK activation and glucose metabolism during exercise, as well as unexpected crosstalk between this innate immune sensor and autophagy proteins.

Spatio-temporal transcriptome dynamics coordinate rapid transition of core crop functions in 'lactating' pigeon.

Pigeons (Columba livia) are among a select few avian species that have developed a specialized reproductive mode wherein the parents produce a 'milk' in their crop to feed newborn squabs. Nonetheless, the transcriptomic dynamics and role in the rapid transition of core crop functions during 'lactation' remain largely unexplored. Here, we generated a de novo pigeon genome assembly to construct a high resolution spatio-temporal transcriptomic landscape of the crop epithelium across the entire breeding stage. This multi-omics analysis identified a set of 'lactation'-related genes involved in lipid and protein metabolism, which contribute to the rapid functional transitions in the crop. Analysis of in situ high-throughput chromatin conformation capture (Hi-C) sequencing revealed extensive reorganization of promoter-enhancer interactions linked to the dynamic expression of these 'lactation'-related genes between stages. Moreover, their expression is spatially localized in specific epithelial layers, and can be correlated with phenotypic changes in the crop. These results illustrate the preferential de novo synthesis of 'milk' lipids and proteins in the crop, and provides candidate enhancer loci for further investigation of the regulatory elements controlling pigeon 'lactation'.

Intracellular Magnetic Hyperthermia Enables Concurrent Down-Regulation of CD47 and SIRPα To Potentiate Antitumor Immunity.

Harnessing the potential of tumor-associated macrophages (TAMs) to engulf tumor cells offers promising avenues for cancer therapy. Targeting phagocytosis checkpoints, particularly the CD47-signal regulatory protein α (SIRPα) axis, is crucial for modulating TAM activity. However, single checkpoint inhibition has shown a limited efficacy. In this study, we demonstrate that ferrimagnetic vortex-domain iron oxide (FVIO) nanoring-mediated magnetic hyperthermia effectively suppresses the expression of CD47 protein on Hepa1-6 tumor cells and SIRPα receptor on macrophages, which disrupts CD47-SIRPα interaction. FVIO-mediated magnetic hyperthermia also induces immunogenic cell death and polarizes TAMs toward M1 phenotype. These changes collectively bolster the phagocytic ability of macrophages to eliminate tumor cells. Furthermore, FVIO-mediated magnetic hyperthermia concurrently escalates cytotoxic T lymphocyte levels and diminishes regulatory T cell levels. Our findings reveal that magnetic hyperthermia offers a novel approach for dual down-regulation of CD47 and SIRPα, reshaping the tumor microenvironment to stimulate immune responses, culminating in significant antitumor activity.

Vaccination Shapes Within-Host SARS-CoV-2 Diversity of Omicron BA.2.2 Breakthrough Infection.

BACKGROUND: Low-frequency intrahost single-nucleotide variants of SARS-CoV-2 have been recognized as predictive indicators of selection. However, the impact of vaccination on the intrahost evolution of SARS-CoV-2 remains uncertain at present. METHODS: We investigated the genetic variation of SARS-CoV-2 in individuals who were unvaccinated, partially vaccinated, or fully vaccinated during Shanghai's Omicron BA.2.2 wave. We substantiated the connection between particular amino acid substitutions and immune-mediated selection through a pseudovirus neutralization assay or by cross-verification with the human leukocyte antigen-associated T-cell epitopes. RESULTS: In contrast to those with immunologic naivety or partial vaccination, participants who were fully vaccinated had intrahost variant spectra characterized by reduced diversity. Nevertheless, the distribution of mutations in the fully vaccinated group was enriched in the spike protein. The distribution of intrahost single-nucleotide variants in individuals who were immunocompetent did not demonstrate notable signs of positive selection, in contrast to the observed adaptation in 2 participants who were immunocompromised who had an extended period of viral shedding. CONCLUSIONS: In SARS-CoV-2 infections, vaccine-induced immunity was associated with decreased diversity of within-host variant spectra, with milder inflammatory pathophysiology. The enrichment of mutations in the spike protein gene indicates selection pressure exerted by vaccination on the evolution of SARS-CoV-2.

Sub-1 nm Materials Chemistry: Challenges and Prospects.

Subnanometer materials (SNMs) refer to nanomaterials with a feature size close to 1 nm, similar to the diameter of a single polymer, DNA strand, and a single cluster/unit cell. The growth and assembly of subnanometer building blocks can be controlled by interactions at atomic levels, representing the limit for the precise manipulation of materials. The size, geometry, and flexibility of 1D SNMs inorganic backbones are similar to the polymer chains, bringing excellent gelability, adhesiveness, and processability different from inorganic nanocrystals. The ultrahigh surface atom ratio of SNMs results in significantly increased surface energy, leading to significant rearrangement of surface atoms. Unconventional phases, immiscible metal alloys, and high entropy materials with few atomic layers can be stabilized, and the spontaneous twisting of SNMs may induce the intrinsic structural chirality. Electron delocalization may also emerge at the subnanoscale, giving rise to the significantly enhanced catalytic activity. In this perspective, we summarized recent progress on SNMs, including their synthesis, polymer-like properties, metastable phases, structural chirality, and catalytic properties, toward energy conversion. As a critical size region in nanoscience, the development of functional SNMs may fuse the boundary of inorganic materials and polymers and conduce to the precise manufacturing of materials at atomic levels.

Polyoxometallate Cluster Induced High-Entropy Oxide Sub-1 nm Nanosheets as Photoelectrocatalysts for Zn-Air Batteries.

The lack of highly efficient and inexpensive catalysts severely hinders the large-scale application of Zn-air batteries (ZABs). High-entropy oxides (HEOs) exhibit unique structures and attractive properties; thus, they are promising to be used in ZABs. However, conventional high-temperature synthesis methods tend to obtain microscale HEOs with a lower exposure rate of active sites. Here, we report a facile solvothermal strategy for preparing two-dimensional (2D) HEO sub-1 nm nanosheets (SNSs) induced by polyoxometalate (POM) clusters. Taking advantage of the special 2D sub-1 nm structure and precise element regulation, these 2D HEOs-POM SNSs exhibit enhanced bifunctional oxygen evolution and oxygen reduction reaction activity under light irradiation. Further applying these 2D HEOs-POM SNSs to ZABs as cathode catalysts, the CoFeNiMnCuZnOx-phosphomolybdic acid SNSs-based ZABs deliver a low charge/discharge voltage gap of 0.25 V at 2 mA cm-2 under light irradiation. Meanwhile, it could maintain an ultralong-term stability for 1600 h at 2 mA cm-2 and 930 h at 10 mA cm-2. The 2D sub-1 nm structure and fine element control in HEOs provide opportunities to solve the problems of low intrinsic activity, limited active sites, and instability of air cathodes in ZABs.

Tuning the Chirality Evolution in Achiral Subnanometer Systems by Judicious Control of Molecule Interactions.

Chirality evolution from molecule levels to the nanoscale in an achiral system is a fundamental issue that remains undiscovered. Here, we report the assembly of polyoxometalate (POM) clusters into chiral subnanostructures in achiral systems by programmable single-molecule interactions. Driven by the competing binding of Ca2+ and surface ligands, POM assemblies would twist into helical nanobelts, nanorings, and nanotubes with tunable helicity. Chiral molecules can be used to differentiate the formation energies of chiral isomers and immobilize the homochiral isomer, where strong circular dichroism (CD) signals are obtained in both solutions and films. Chiral helical nanobelts can be used as circularly polarized light (CPL) photodetectors due to their distinct chiroptic responsivity for right and left CPL. By the fine-tuning of interactions at single-molecule levels, the morphology and CD spectra of helical assemblies can be precisely controlled, providing an atomic precision model for investigation of the structure-chirality relationship and chirality manipulation at the nanoscale.

Single-Walled Cluster Nanotubes for Single-Atom Catalysts with Precise Structures.

Spatially confining isolated atomic sites in low-dimensional nanostructures is a promising strategy for preparing high-performance single-atom catalysts (SACs). Herein, fascinating polyoxometalate cluster-based single-walled nanotubes (POM-SWNTs) with atomically precise structures, uniform diameter, and single-cluster wall thickness are constructed by lacunary POM clusters (PW11 and P2W17 clusters). Isolated metal centers are accurately incorporated into the PW11-SWNTs and P2W17-SWNTs supports. The structures of the resulting MPW11-SWNTs and MP2W17-SWNTs are well established (M = Cu, Pt). Molecular dynamics simulations demonstrate the stability of POM-SWNTs. Furthermore, the turnover frequency of PtP2W17-SWNTs is 20 times higher than that of PtP2W17 cluster units and 140 times higher than that of Pt nanoparticles in the alcoholysis of dimethylphenylsilane. Theoretical studies indicate that incorporating a Pt atom into the P2W17 support induces straightforward electron transfer between them, combining the nanoconfined environment to enhance the catalytic activity of PtP2W17-SWNTs. This work shows the feasibility of using subnanometric POM clusters to assemble single-walled cluster nanotubes, highlighting their potential to prepare superior SACs with precise structures.

Flexibility On-Demand: Multivariate 3D Covalent Organic Frameworks.

Dynamic 3D covalent organic frameworks (dynaCOFs) have shown concerted structural transformation and responses upon adaptive guest adsorption. The multivariate (MTV) strategy incorporating multiple functionalities within a backbone is attractive for tuning the framework flexibility and dynamic responses. However, a major synthetic challenge arises from the different chemical reactivities of linkers usually resulting in phase separation. Here, we report a general synthetic protocol for making 3D MTV-COFs by balancing the linker reactivity and solvent polarity. Specifically, 15 crystalline and phase pure MTV-COF-300 isostructures are constructed by linking a tetrahedral unit with eight ditopic struts carrying various functional groups. We find that the electron-donating groups make the linker reactivity too low to allow the reaction to proceed fully, while the electron-withdrawing groups afford increased reactivity and hardly yield crystalline materials. To overcome the crystallization dilemma, the combination of polar aprotic with nonpolar solvents was used to improve the solubility of oligomers and slow the reaction kinetics in MTV-COF synthesis. We demonstrate the abilities of these MTV-COFs to tune gas dynamic behaviors and the separation of benzene and cyclohexane. These findings reveal the integration of multivariate functionalities into dynaCOFs with on-demand flexibility to achieve dynamic synergism in particular applications, outperforming their pure, monofunctional counterparts.

Complete chloroplast genome of the Malus baccata var. gracilis provides insights into the evolution and phylogeny of Malus species.

Malus baccata (L.) var. gracilis (Rehd.) has high ornamental value and breeding significance, and comparative chloroplast genome analysis was applied to facilitate genetic breeding for desired traits and resistance and provide insight into the phylogeny of this genus. Using data from whole-genome sequencing, a tetrameric chloroplast genome with a length of 159,992 bp and a total GC content of 36.56% was constructed. The M. baccata var. gracilis chloroplast genome consists of a large single-copy sequence (88,100 bp), a short single-copy region (19,186 bp), and two inverted repeat regions, IRa (26,353 bp) and IRb (26,353 bp). This chloroplast genome contains 112 annotated genes, including 79 protein-coding genes (nine multicopy), 29 tRNA genes (eight multicopy), and four rRNA genes (all multicopy). Calculating the relative synonymous codon usage revealed a total of 32 high-frequency codons, and the codons exhibited a biased usage pattern towards A/U as the ending nucleotide. Interspecific sequence comparison and boundary analysis revealed significant sequence variation in the vast single-copy region, as well as generally similar expansion and contraction of the SSC and IR regions for 10 analyzed Malus species. M. baccata var. gracilis and Malus hupehensis were grouped together into one branch based on phylogenetic analysis of chloroplast genome sequences. The chloroplast genome of Malus species provides an important foundation for species identification, genetic diversity analysis, and Malus chloroplast genetic engineering. Additionally, the results can facilitate the use of pendant traits to improve apple tree shape.

σ-Hole Effect-Induced Electroluminescence of Halogen Cocrystals for Determination of Iodide in Seawater.

Developing new electrochemiluminescence (ECL) luminators with high stability, wide applicability, and strong designability is of great strategic significance to promote the ECL field to the frontier. Here, driven by the I···N bond, 1,3,5-trifluoro-2,4,6-triiodobenzene (TFTI) and 2,4,6-trimethyl-1,3,5-triazine (TMT) self-assembled into a novel halogen cocrystal (TFTI-TMT) through slow solution volatilization. Significant difference of charge density existed between the N atoms on TMT and the σ-hole of the I atoms on TFTI. Upon the induction of σ-hole effect, high-speed and spontaneous charge transferring from TMT to the σ-hole of TFTI occurred, stimulating exciting ECL signals. Besides, the σ-hole of the I atoms could capture iodine ions specifically, which blocked the original charge transfer from the N atoms to the σ-hole, causing the ECL signal of TFTI-TMT to undergo a quenching rate as high as 92.9%. Excitingly, the ECL sensing of TFTI-TMT toward I- possessed a wide linear range (10-5000 nM) and ultralow detection limit (3 nM) in a real water sample. The halogen cocrystal strategy makes σ-hole a remarkable new viewpoint of ECL luminator design and enables ECL analysis technology to contribute to addressing the environmental and health threats posed by iodide pollution.

Effects of tea infusion on selenium uptake in grapevine.

Increased selenium (Se) content in fruits can supply Se in human body, but the effects of teas on the Se uptake in fruit trees are unknown. The effects of infusions of four teas (green, black, dark, and white) on the Se uptake of grapevine were studied to promote the Se uptake in fruit trees in this study. However, only black tea infusion increased the biomass, photosynthetic pigment content, superoxide dismutase (SOD) activity, peroxidase (POD) activity, and soluble protein content of grapevine. Except for white tea infusion, other tea infusions also increased the catalase (CAT) activity of grapevine. Furthermore, the tea infusions increased the activities of adenosine triphosphate sulfurase (ATPS) and adenosine 5'-phosphosulfate reductase (APR), and decreased the activities of serine acetyltransferase (SAT) and selenocysteine methyltransferase (SMT). Only the dark and white tea infusions increased the shoot total Se content by 86.53% and 23.32%, respectively (compared with the control), and also increased the shoot inorganic Se content and shoot organic Se content. Notably, four tea infusions decreased the organic Se proportion and increased the inorganic Se proportion in grapevine. Correlation and grey relational analyses showed that the root total Se content, ATPS activity, and ARP activity were closely associated with the shoot total Se content. The principal component and cluster analyses also showed that the ATPS activity, APR activity, root total Se content, and shoot total Se content were classified into one category. These findings show that black tea infusion can promote grapevine growth, while dark and white tea infusions can promote the Se uptake in grapevine.

Electron-Delocalization Across High Surface Entropy Sub-1 nm Nanobelts Toward Enhanced Electrocatalytic Urea Oxidation.

Integration of inherently incompatible elements into a single sublattice, resulting in the formation of monophasic metal oxide, holds great scientific promise; it unveils that the overlooked surface entropy in subnanometer materials can thermodynamically facilitate the formation of homogeneous single-phase structures. Here a facile approach is proposed for synthesizing multimetallic oxide subnanometer nanobelts (MMO-PMA SNBs) by harnessing the potential of phosphomolybdic acid (PMA) clusters to capture inorganic nuclei and inhibiting their subsequent growth in solvothermal reactions. Experimental and theoretical analyses show that PMA in MMO-PMA SNBs not only aids subnanometer structure formation but also induces in situ modifications to catalytic sites. The electron transfer from PMA, coupled with the loss of elemental identity of transition metals, leads to electron delocalization, jointly activating the reaction sites. The unique structure makes pentametallic oxide (PMO-PMA SNBs) achieve a current density of 10 mA cm-2 at a low potential of 1.34 V and remain stable for 24 h at 10 mA cm-2 on urea oxidation reaction (UOR). The exceptional UOR catalytic activity suggests a potential for utilizing multimetallic subnanometer nanostructures in energy conversion and environmental remediation.

AMDE: a novel attention-mechanism-based multidimensional feature encoder for drug-drug interaction prediction.

The properties of the drug may be altered by the combination, which may cause unexpected drug-drug interactions (DDIs). Prediction of DDIs provides combination strategies of drugs for systematic and effective treatment. In most of deep learning-based methods for predicting DDI, encoded information about the drugs is insufficient in some extent, which limits the performances of DDIs prediction. In this work, we propose a novel attention-mechanism-based multidimensional feature encoder for DDIs prediction, namely attention-based multidimensional feature encoder (AMDE). Specifically, in AMDE, we encode drug features from multiple dimensions, including information from both Simplified Molecular-Input Line-Entry System sequence and atomic graph of the drug. Data experiments are conducted on DDI data set selected from Drugbank, involving a total of 34 282 DDI relationships with 17 141 positive DDI samples and 17 141 negative samples. Experimental results show that our AMDE performs better than some state-of-the-art baseline methods, including Random Forest, One-Dimension Convolutional Neural Networks, DeepDrug, Long Short-Term Memory, Seq2seq, Deepconv, DeepDDI, Graph Attention Networks and Knowledge Graph Neural Networks. In practice, we select a set of 150 drugs with 3723 DDIs, which are never appeared in training, validation and test sets. AMDE performs well in DDIs prediction task, with AUROC and AUPRC 0.981 and 0.975. As well, we use Torasemide (DB00214) as an example and predict the most likely drug to interact with it. The top 15 scores all have been reported with clear interactions in literatures.

Molormer: a lightweight self-attention-based method focused on spatial structure of molecular graph for drug-drug interactions prediction.

Multi-drug combinations for the treatment of complex diseases are gradually becoming an important treatment, and this type of treatment can take advantage of the synergistic effects among drugs. However, drug-drug interactions (DDIs) are not just all beneficial. Accurate and rapid identifications of the DDIs are essential to enhance the effectiveness of combination therapy and avoid unintended side effects. Traditional DDIs prediction methods use only drug sequence information or drug graph information, which ignores information about the position of atoms and edges in the spatial structure. In this paper, we propose Molormer, a method based on a lightweight attention mechanism for DDIs prediction. Molormer takes the two-dimension (2D) structures of drugs as input and encodes the molecular graph with spatial information. Besides, Molormer uses lightweight-based attention mechanism and self-attention distilling to process spatially the encoded molecular graph, which not only retains the multi-headed attention mechanism but also reduces the computational and storage costs. Finally, we use the Siamese network architecture to serve as the architecture of Molormer, which can make full use of the limited data to train the model for better performance and also limit the differences to some extent between networks dealing with drug features. Experiments show that our proposed method outperforms state-of-the-art methods in Accuracy, Precision, Recall and F1 on multi-label DDIs dataset. In the case study section, we used Molormer to make predictions of new interactions for the drugs Aliskiren, Selexipag and Vorapaxar and validated parts of the predictions. Code and models are available at https://github.com/IsXudongZhang/Molormer.

Multi-omics landscapes reveal heterogeneity in long COVID patients characterized with enhanced neutrophil activity.

BACKGROUND: Omicron variant impacts populations with its rapid contagiousness, and part of patients suffered from persistent symptoms termed as long COVID. The molecular and immune mechanisms of this currently dominant global variant leading to long COVID remain unclear, due to long COVID heterogeneity across populations. METHODS: We recruited 66 participants in total, 22 out of 66 were healthy control without COVID-19 infection history, and 22 complaining about long COVID symptoms 6 months after first infection of Omicron, referred as long COVID (LC) Group. The left ones were defined as non-long COVID (NLC) Group. We profiled them via plasma neutralizing antibody titer, SARS-CoV-2 viral load, transcriptomic and proteomics screening, and machine learning. RESULTS: No serum residual SARS-CoV-2 was observed in the participants 6 months post COVID-19 infection. No significant difference in neutralizing antibody titers was found between the long COVID (LC) Group and the non-long COVID (NLC) Group. Transcriptomic and proteomic profiling allow the stratification of long COVID into neutrophil function upregulated (NU-LC) and downregulated types (ND-LC). The NU-LC, identifiable through a refined set of 5 blood gene markers (ABCA13, CEACAM6, CRISP3, CTSG and BPI), displays evidence of relatively higher neutrophil counts and function of degranulation than the ND-LC at 6 months after infection, while recovered at 12 months post COVID-19. CONCLUSION: The transcriptomic and proteomic profiling revealed heterogeneity among long COVID patients. We discovered a subgroup of long COVID population characterized by neutrophil activation, which might associate with the development of psychiatric symptoms and indicate a higher inflammatory state. Meanwhile, a cluster of 5 genes was manually curated as the most potent discriminators of NU-LC from long COVID population. This study can serve as a foundational exploration of the heterogeneity in the pathogenesis of long COVID and assist in therapeutic targeting and detailed epidemiological investigation of long COVID.