A novel deep generative model for mRNA vaccine development: Designing 5' UTRs with N1-methyl-pseudouridine modification.

Efficient translation mediated by the 5' untranslated region (5' UTR) is essential for the robust efficacy of mRNA vaccines. However, the N1-methyl-pseudouridine (m1Ψ) modification of mRNA can impact the translation efficiency of the 5' UTR. We discovered that the optimal 5' UTR for m1Ψ-modified mRNA (m1Ψ-5' UTR) differs significantly from its unmodified counterpart, highlighting the need for a specialized tool for designing m1Ψ-5' UTRs rather than directly utilizing high-expression endogenous gene 5' UTRs. In response, we developed a novel machine learning-based tool, Smart5UTR, which employs a deep generative model to identify superior m1Ψ-5' UTRs in silico. The tailored loss function and network architecture enable Smart5UTR to overcome limitations inherent in existing models. As a result, Smart5UTR can successfully design superior 5' UTRs, greatly benefiting mRNA vaccine development. Notably, Smart5UTR-designed superior 5' UTRs significantly enhanced antibody titers induced by COVID-19 mRNA vaccines against the Delta and Omicron variants of SARS-CoV-2, surpassing the performance of vaccines using high-expression endogenous gene 5' UTRs.

Symptom management experiences of Chinese individuals with Crohn's disease: A longitudinal descriptive qualitative study.

Individuals diagnosed with Crohn's disease, a chronic lifelong condition, experience a dynamic or fluctuating process of developing symptom management behavior. However, less clear is how these individuals respond to and manage their symptoms over time. The aim of this study was to longitudinally explore the symptom management experiences of individuals with Crohn's disease in China. A longitudinal qualitative design was used. Eighteen individuals with newly diagnosed Crohn's disease were purposely selected. Semi-structured interviews were conducted on four occasions over a 12-month period. Interviews at each time point were transcribed and coded using conventional content analysis. Afterward, data analyses of each time point were compared longitudinally to form a holistic understanding. Three themes and eight subthemes emerged from the analysis: (1) disclosing symptoms strategically: voluntary disclosure, reluctance to disclose, no need to disclose; (2) decreasing vigilance in symptom prevention: preventing symptoms stringently, preventing symptoms discriminatively, preventing symptoms with decreased diligence; and (3) increasing autonomy in symptom treatment: actively seeking medical advice, self-treatment and self-observation. The participants were inclined to keep symptoms hidden from relatives and friends and showed a downward trend in actively disclosing physical discomfort to medical staff within the course of 1 year. The participants' attention to symptom prevention declined, but the enthusiasm and independence to eliminate symptoms on their own increased over time. Nurses could implement targeted interventions according to the characteristics of different periods to assist individuals with Crohn's disease in managing symptoms effectively, reducing symptom burden and improving their quality of life.

Lopinavir enhances anoikis by remodeling autophagy in a circRNA-dependent manner.

Macroautophagy/autophagy-mediated anoikis resistance is crucial for tumor metastasis. As a key autophagy-related protein, ATG4B has been demonstrated to be a prospective anti-tumor target. However, the existing ATG4B inhibitors are still far from clinical application, especially for tumor metastasis. In this study, we identified a novel circRNA, circSPECC1, that interacted with ATG4B. CircSPECC1 facilitated liquid-liquid phase separation of ATG4B, which boosted the ubiquitination and degradation of ATG4B in gastric cancer (GC) cells. Thus, pharmacological addition of circSPECC1 may serve as an innovative approach to suppress autophagy by targeting ATG4B. Specifically, the circSPECC1 underwent significant m6A modification in GC cells and was subsequently recognized and suppressed by the m6A reader protein ELAVL1/HuR. The activation of the ELAVL1-circSPECC1-ATG4B pathway was demonstrated to mediate anoikis resistance in GC cells. Moreover, we also verified that the above pathway was closely related to metastasis in tissues from GC patients. Furthermore, we determined that the FDA-approved compound lopinavir efficiently enhanced anoikis and prevented metastasis by eliminating repression of ELAVL1 on circSPECC1. In summary, this study provides novel insights into ATG4B-mediated autophagy and introduces a viable clinical inhibitor of autophagy, which may be beneficial for the treatment of GC with metastasis.

KIAA1429 facilitates metastasis via m6A-YTHDC1-dependent RND3 down-regulation in hepatocellular carcinoma cells.

N6-methyladenosine (m6A), a dynamically reversible modification in eukaryotic RNAs, modulates gene expression and pathological processes in various tumors. KIAA1429, the largest component of the m6A methyltransferase complex, plays an important role in m6A modification. However, the underlying mechanism of KIAA1429 in hepatocellular carcinoma (HCC) remains largely unknown. Immunohistochemical assay was performed to examine the expression of KIAA1429 in HCC tissues. Transwell, wound healing and animal experiments were used to investigate the influence of KIAA1429 on cell migration and invasion. The mRNA high-throughput sequencing (RNA-seq) and methylated RNA immunoprecipitation sequencing (MeRIP-seq) were performed to screen the downstream target of KIAA1429. RNA stability assays, RNA immunoprecipitation assay (RIP), MeRIP-qPCR and luciferase assay were used to evaluate the relationship between KIAA1429 and the m6A-modified genes. Results showed that the expression level of KIAA1429 was significantly higher in HCC tissues than in adjacent tissues, and the upregulation of KIAA1429 could promote HCC metastasis in vitro and in vivo. Mechanistically, we confirmed that KIAA1429 negatively regulated the tumor suppressor, Rho family GTPase 3 (RND3), by decreasing its mRNA stability in coordination with the m6A reader YTHDC1. Moreover, we demonstrated that KIAA1429 could regulate the m6A modification of RND3 mRNA via its RNA binding domain. Our data indicated that KIAA1429 exerted its oncogenic role by inhibiting RND3 expression in an m6A-dependent manner, suggesting that KIAA1429 might be a potential prognostic biomarker and therapeutic target in HCC.

CircPHKB decreases the sensitivity of liver cancer cells to sorafenib via miR-1234-3p/CYP2W1 axis.

Sorafenib is currently the first-line treatment for patients with advanced liver cancer, but its therapeutic efficacy declines significantly after a few months of treatment. Therefore, it is of great importance to investigate the regulatory mechanisms of sorafenib sensitivity in liver cancer cells. In this study, we provided initial evidence demonstrating that circPHKB, a novel circRNA markedly overexpressed in sorafenib-treated liver cancer cells, attenuated the sensitivity of liver cancer cells to sorafenib. Mechanically, circPHKB sequestered miR-1234-3p, resulting in the up-regulation of cytochrome P450 family 2 subfamily W member 1 (CYP2W1), thereby reducing the killing effect of sorafenib on liver cancer cells. Moreover, knockdown of circPHKB sensitized liver cancer cells to sorafenib in vivo. The findings reveal a novel circPHKB/miR-1234-3p/CYP2W1 pathway that decreases the sensitivity of liver cancer cells to sorafenib, suggesting that circPHKB and the axis may serve as promising targets to improve the therapeutic efficacy of sorafenib against liver cancer.

SpecHLA enables full-resolution HLA typing from sequencing data.

Reconstructing diploid sequences of human leukocyte antigen (HLA) genes, i.e., full-resolution HLA typing, from sequencing data is challenging. The high homogeneity across HLA genes and the high heterogeneity within HLA alleles complicate the identification of genomic source loci for sequencing reads. Here, we present SpecHLA, which utilizes fine-tuned reads binning and local assembly to achieve accurate full-resolution HLA typing. SpecHLA accepts sequencing data from paired-end, 10×-linked-reads, high-throughput chromosome conformation capture (Hi-C), Pacific Biosciences (PacBio), and Oxford Nanopore Technology (ONT). It can also incorporate pedigree data and genotype frequency to refine typing. In 32 Human Genome Structural Variation Consortium, Phase 2 (HGSVC2) samples, SpecHLA achieved 98.6% accuracy for G-group-resolution HLA typing, inferring entire HLA alleles with an average of three mismatches fewer, ten gaps fewer, and 590 bp less edit distance than HISAT-genotype per allele. Additionally, SpecHLA exhibited a 2-field typing accuracy of 98.6% in 875 real samples. Finally, SpecHLA detected HLA loss of heterozygosity with 99.7% specificity and 96.8% sensitivity in simulated samples of cancer cell lines.

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram.

Breakage-fusion-bridge (BFB) is a complex rearrangement that leads to tumor malignancy. Existing models for detecting BFBs rely on the ideal BFB hypothesis, ruling out the possibility of BFBs entangled with other structural variations, that is, complex BFBs. We propose an algorithm Ambigram to identify complex BFB and reconstruct the rearranged structure of the local genome during the cancer subclone evolution process. Ambigram handles data from short, linked, long, and single-cell sequences, and optical mapping technologies. Ambigram successfully deciphers the gold- or silver-standard complex BFBs against the state-of-the-art in multiple cancers. Ambigram dissects the intratumor heterogeneity of complex BFB events with single-cell reads from melanoma and gastric cancer. Furthermore, applying Ambigram to liver and cervical cancer data suggests that the BFB mechanism may mediate oncovirus integrations. BFB also exists in noncancer genomics. Investigating the complete human genome reference with Ambigram suggests that the BFB mechanism may be involved in two genome reorganizations of Homo Sapiens during evolution. Moreover, Ambigram discovers the signals of recurrent foldback inversions and complex BFBs in whole genome data from the 1000 genome project, and congenital heart diseases, respectively.

Quantitative annotations of T-Cell repertoire specificity.

The specificity of a T-cell receptor (TCR) repertoire determines personalized immune capacity. Existing methods have modeled the qualitative aspects of TCR specificity, while the quantitative aspects remained unaddressed. We developed a package, TCRanno, to quantify the specificity of TCR repertoires. We created deep-learning-based, epitope-aware vector embeddings to infer individual TCR specificity. Then we aggregated clonotype frequencies of TCRs to obtain a quantitative profile of repertoire specificity at epitope, antigen and organism levels. Applying TCRanno to 4195 TCR repertoires revealed quantitative changes in repertoire specificity upon infections, autoimmunity and cancers. Specifically, TCRanno found cytomegalovirus-specific TCRs in seronegative healthy individuals, supporting the possibility of abortive infections. TCRanno discovered age-accumulated fraction of severe acute respiratory syndrome coronavirus 2 specific TCRs in pre-pandemic samples, which may explain the aggressive symptoms and age-related severity of coronavirus disease 2019. TCRanno also identified the encounter of Hepatitis B antigens as a potential trigger of systemic lupus erythematosus. TCRanno annotations showed capability in distinguishing TCR repertoires of healthy and cancers including melanoma, lung and breast cancers. TCRanno also demonstrated usefulness to single-cell TCRseq+gene expression data analyses by isolating T-cells with the specificity of interest.

The symptom experience of newly diagnosed Chinese patients with Crohn's disease: A longitudinal qualitative study.

AIMS: To longitudinally explore the symptom experience of Chinese patients with Crohn's disease within the first year following their diagnosis. DESIGN: A longitudinal qualitative study. METHOD: Eighteen newly diagnosed Chinese patients with Crohn's disease were recruited through purposive sampling. Semi-structured interviews were conducted at four time points: soon after diagnosis, 3, 6 and 12 months post-diagnosis. Data were collected between January 2021 and February 2022. Conventional content analysis was used for data analysis of each time point. Afterwards, the data of each time point were compared longitudinally. COREQ checklist was followed. RESULTS: Three themes and eight sub-themes were formed through analysis: feelings towards symptoms (symptoms make me feel uneasy, symptoms make me feel inferior and symptoms make me feel helpless); acceptability of symptoms (difficult to accept, have to accept, be able to accept); functions of symptoms (assessing disease conditions and treatment effects, warning of disease management). CONCLUSIONS: Overall, the negative emotions related to symptoms gradually decreased over time, and the patient's acceptance of symptoms increased within the first year following diagnosis. In addition, when the disease was in remission after treatment, the warning function of symptoms gradually weakened. IMPACT: The process of how patients accept their symptoms found in this study provides a basis for nurses to improve patients' acceptance of symptoms and reduce their symptom-related negative emotions. This study also emphasizes the phenomenon that patients gradually ignore some symptoms with their increased acceptance level, which warrants additional health education to strengthen their awareness of self-management. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution was required to design or undertake this study. Patients contributed only to the data collection and member checking.

Alterations in nutrient digestion and utilization associated with different residual feed intake in Hu sheep.

Improving feed efficiency is crucial to the animal industry. Residual feed intake (RFI) is now regarded as an index of feed efficiency evaluation and is independent of growth characteristics. Our study aims to explore the alterations in growth performance and nutrient digestion in Hu sheep with different RFI phenotypes. Sixty-four male Hu sheep (body weight = 24.39 ± 1.12 kg; postnatal days = 90 ± 7.9) were selected for the study. After an evaluation period of 56 days and power analysis, samples were collected from 14 low RFI (L-RFI group, power = 0.95) and 14 high RFI sheep (H-RFI group, power = 0.95). The L-RFI sheep yielded a lower (P < 0.05) feed conversion ratio and dry matter intake; however, both groups exhibited similar average daily gain (P > 0.05). The acid detergent fiber, neutral detergent fiber, organic matter, and crude protein apparent digestibility were higher (P < 0.05) in L-RFI sheep. N intake and fecal N output (% of N intake) were lower (P < 0.05) and N retention (% of N intake) was higher (P < 0.05) in L-RFI sheep, whereas no difference (P > 0.05) was found in urine N output (% of N intake) between the 2 groups. Furthermore, L-RFI sheep gave lower (P < 0.05) serum glucose concentrations and higher (P < 0.05) non-esterified fatty acid concentrations. Meanwhile, a lower ruminal acetate molar proportion (P < 0.05) and higher propionate molar proportion (P < 0.05) were observed in L-RFI sheep. In summary, these results revealed that despite having lower dry matter intake, L-RFI sheep possess higher nutrient digestibility, N retention, ruminal propionate production and serum glucose utilization, in order to meet energy demands. Selection for low RFI sheep could reduce feed costs, which in turn provides economic benefits to the sheep industry.

Dihydroergotamine mesylate enhances the anti-tumor effect of sorafenib in liver cancer cells.

Liver cancer is the most common and frequentlyoccurring cancer. In addition to radiotherapy, chemotherapy and surgery are recommended as part of liver cancer treatment. The efficacy of sorafenib and sorafenib-based combination treatment against tumors has been verified. Although, clinical trials have revealed that some individuals are not sensitive to sorafenib therapy, and current therapeutic approaches are ineffective. Consequently, it is urgent to explore effective drug combinations and innovative techniques for increasing the effectiveness of sorafenib in the curing of liver tumor. Herein, we show that dihydroergotamine mesylate (DHE), an anti-migraine agent, could effectively suppress liver cancer cells proliferation by inhibiting STAT3 activation. However, DHE can enhance the protein stability of Mcl-1 by activating ERK, making DHE less effective in apoptosis induction. Specifically, DHE enhances the effects of sorafenib on liver cancer cells, such as decreased viability and increased apoptosis. Furthermore, the mixture of sorafenib and DHE could enhance DHE-triggered STAT3 suppression and inhibit DHE-mediated ERK-Mcl-1 pathway activation. In vivo, the combination of sorafenib with DHE produced a substantial synergy in suppressing tumour growth and causing apoptosis, ERK inhibition and Mcl-1 degradation. These findings suggest that DHE can effectively inhibit cell proliferation and enhance sorafenib anti-cancer activity in liver cancer cells. The current study provides some new insights that DHE asa novel anti-liver cancer therapeutic agent has been shown to improve treatment outcomes of sorafenib, which might be helpful in order to advance sorafenib in liver cancer therapeutics.

The Illness Experiences of Chinese Adolescent Patients Living with Crohn Disease: A Descriptive Qualitative Study.

The purpose of this qualitative study was to explore the illness experience of adolescent patients with Crohn disease and describe the impact of the disease on the everyday lives of these individuals within the Chinese social and cultural context to provide references for targeted interventions for the healthcare team. A descriptive qualitative design was adopted. Purposive sampling was used to select Chinese adolescent patients with Crohn disease to participate in face-to-face in-depth interviews. Data analysis was performed using the conventional content analysis method. Through the analysis of data from 14 adolescent patients with Crohn disease, four themes were formed: (1) I am different from others, (2) I am a burden to my parents, (3) I want to be the master of my own body, and (4) I grow up suffering from illness. Healthcare providers should offer more psychological support to adolescent Crohn disease patients and advise parents to shift more attention to the mental health of their children.

SMURF: embedding single-cell RNA-seq data with matrix factorization preserving self-consistency.

The advance in single-cell RNA-sequencing (scRNA-seq) sheds light on cell-specific transcriptomic studies of cell developments, complex diseases and cancers. Nevertheless, scRNA-seq techniques suffer from 'dropout' events, and imputation tools are proposed to address the sparsity. Here, rather than imputation, we propose a tool, SMURF, to extract the low-dimensional embeddings from cells and genes utilizing matrix factorization with a mixture of Poisson-Gamma divergent as objective while preserving self-consistency. SMURF exhibits feasible cell subpopulation discovery efficacy with obtained cell embeddings on replicated in silico and eight web lab scRNA datasets with ground truth cell types. Furthermore, SMURF can reduce the cell embedding to a 1D-oval space to recover the time course of cell cycle. SMURF can also serve as an imputation tool; the in silico data assessment shows that SMURF parades the most robust gene expression recovery power with low root mean square error and high Pearson correlation. Moreover, SMURF recovers the gene distribution for the WM989 Drop-seq data. SMURF is available at https://github.com/deepomicslab/SMURF.

TIMEDB: tumor immune micro-environment cell composition database with automatic analysis and interactive visualization.

Deciphering the cell-type composition in the tumor immune microenvironment (TIME) can significantly increase the efficacy of cancer treatment and improve the prognosis of cancer. Such a task has benefited from microarrays and RNA sequencing technologies, which have been widely adopted in cancer studies, resulting in extensive expression profiles with clinical phenotypes across multiple cancers. Current state-of-the-art tools can infer cell-type composition from bulk expression profiles, providing the possibility of investigating the inter-heterogeneity and intra-heterogeneity of TIME across cancer types. Much can be gained from these tools in conjunction with a well-curated database of TIME cell-type composition data, accompanied by the corresponding clinical information. However, currently available databases fall short in data volume, multi-platform dataset integration, and tool integration. In this work, we introduce TIMEDB (https://timedb.deepomics.org), an online database for human tumor immune microenvironment cell-type composition estimated from bulk expression profiles. TIMEDB stores manually curated expression profiles, cell-type composition profiles, and the corresponding clinical information of a total of 39,706 samples from 546 datasets across 43 cancer types. TIMEDB comes readily equipped with online tools for automatic analysis and interactive visualization, and aims to serve the community as a convenient tool for investigating the human tumor microenvironment.

Incorporating cell hierarchy to decipher the functional diversity of single cells.

Cells possess functional diversity hierarchically. However, most single-cell analyses neglect the nested structures while detecting and visualizing the functional diversity. Here, we incorporate cell hierarchy to study functional diversity at subpopulation, club (i.e., sub-subpopulation), and cell layers. Accordingly, we implement a package, SEAT, to construct cell hierarchies utilizing structure entropy by minimizing the global uncertainty in cell-cell graphs. With cell hierarchies, SEAT deciphers functional diversity in 36 datasets covering scRNA, scDNA, scATAC, and scRNA-scATAC multiome. First, SEAT finds optimal cell subpopulations with high clustering accuracy. It identifies cell types or fates from omics profiles and boosts accuracy from 0.34 to 1. Second, SEAT detects insightful functional diversity among cell clubs. The hierarchy of breast cancer cells reveals that the specific tumor cell club drives AREG-EGFT signaling. We identify a dense co-accessibility network of cis-regulatory elements specified by one cell club in GM12878. Third, the cell order from the hierarchy infers periodic pseudo-time of cells, improving accuracy from 0.79 to 0.89. Moreover, we incorporate cell hierarchy layers as prior knowledge to refine nonlinear dimension reduction, enabling us to visualize hierarchical cell layouts in low-dimensional space.

Transcriptomic analysis of mRNA expression in giant congenital melanocytic nevi.

BACKGROUND AND OBJECTIVE: GCMN is a sporadic disease with an incidence ranging from 1/20,000 to 1/500000. So far, several studies have found that GCMN is related to somatic mutations, but most of them have focused on known pathogenic genes, and transcriptome sequencing based on large datasets is relatively uncommon. At present, the use of next-generation sequencing technologies and bioinformatics platforms makes genomic information study more comprehensive and efficient. In this study, the transcriptome differences between GCMN lesions and surrounding normal skin tissues were investigated using high-throughput transcriptome sequencing, and hub genes and pathways related to pathogenesis were identified, providing a theoretical foundation for further research into the pathogenesis of GCMN. METHODS: Pathological skin tissue and surrounding normal skin tissue from GCMN patients, namely the pathological group (PG) and the control group (CG), were obtained. 1. All specimens were stained with HE to ensure that the samples met the experimental requirements. 2. Ten pairs of specimens were selected for high-throughput transcriptome sequencing, and the differentially expressed genes (DEGs) between the PG and the CG were obtained. The DEGs were analyzed by clusterProfiler R software for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The function of the subnetwork was analyzed and the hub genes were identified by the STRING database and Cytoscape software. 3. The expression differences of hub genes PTGS2, EGF, and SOX10 in pathological skin tissues and normal skin tissues were verified by qRT-PCR and immunofluorescence staining. RESULTS: 1. HE staining revealed a lot of melanocytes in the dermis and subcutaneous tissues. They were found around the hair follicles, sweat glands, sebaceous glands, and blood vessel walls, or in a specific pattern. 2. The screening threshold was set at p < 0.01 and |log2fc|<1, and a total of 1163 DEGs were discovered between the PG and CG, with 519 genes up-regulated and 644 genes down-regulated in the pathological tissues. According to the GO functional analysis, 29 biological processes, 18 cell compositions, and 17 molecular functions were significantly enriched, with the majority of them being related to keratinocytes and the extracellular matrix. There were 779 nodes and 2359 interactions in the protein interaction network. Using the MCODE plug-in, the network was divided into 25 functional clusters. According to ClueGO results, Cluster5 was involved in melanin biosynthesis and melanocyte proliferation. Using 11 operation methods in the Cytohubba plug-in, PTGS2, EGF, and SOX10 in Cluster5 were chosen as hub genes. 3. qRT-PCR and immunofluorescent staining revealed that compared to normal skin tissue, the expression of SOX10 was significantly up-regulated, and the expression of PTGS2 and EGF was significantly down-regulated in pathological skin tissue(P < 0.001). CONCLUSIONS: In GCMN, keratinocytes and extracellular matrix may directly and indirectly affect melanocyte activity. PTGS2, EGF, and SOX10 are important genes and significantly differentially expressed in pathological and normal skin tissues. These findings may serve as a springboard for future research.

eSMC: a statistical model to infer admixture events from individual genomics data.

BACKGROUND: Inferring historical population admixture events yield essential insights in understanding a species demographic history. Methods are available to infer admixture events in demographic history with extant genetic data from multiple sources. Due to the deficiency in ancient population genetic data, there lacks a method for admixture inference from a single source. Pairwise Sequentially Markovian Coalescent (PSMC) estimates the historical effective population size from lineage genomes of a single individual, based on the distribution of the most recent common ancestor between the diploid's alleles. However, PSMC does not infer the admixture event. RESULTS: Here, we proposed eSMC, an extended PSMC model for admixture inference from a single source. We evaluated our model's performance on both in silico data and real data. We simulated population admixture events at an admixture time range from 5 kya to 100 kya (5 years/generation) with population admix ratio at 1:1, 2:1, 3:1, and 4:1, respectively. The root means the square error is [Formula: see text] kya for all experiments. Then we implemented our method to infer the historical admixture events in human, donkey and goat populations. The estimated admixture time for both Han and Tibetan individuals range from 60 kya to 80 kya (25 years/generation), while the estimated admixture time for the domesticated donkeys and the goats ranged from 40 kya to 60 kya (8 years/generation) and 40 kya to 100 kya (6 years/generation), respectively. The estimated admixture times were concordance to the time that domestication occurred in human history. CONCLUSION: Our eSMC effectively infers the time of the most recent admixture event in history from a single individual's genomics data. The source code of eSMC is hosted at https://github.com/zachary-zzc/eSMC .

SPROUT: spectral sparsification helps restore the spatial structure at single-cell resolution.

Single-cell RNA sequencing thoroughly quantifies the individual cell transcriptomes but renounces the spatial structure. Conversely, recently emerged spatial transcriptomics technologies capture the cellular spatial structure but skimp cell or gene resolutions. Ligand-receptor interactions reveal the potential of cell proximity since they are spatially constrained. Cell-cell affinity values estimated by ligand-receptor interaction can partially represent the structure of cells but falsely include the pseudo affinities between distant or indirectly interacting cells. Here, we develop a software package, SPROUT, to reconstruct the single-cell resolution spatial structure from the transcriptomics data through diminished pseudo ligand-receptor affinities. For spatial data, SPROUT first curates the representative single-cell profiles for each spatial spot from a candidate library, then reduces the pseudo affinities in the intercellular affinity matrix by partial correlation, spectral graph sparsification, and spatial coordinates refinement. SPROUT embeds the estimated interactions into a low-dimensional space with the cross-entropy objective to restore the intercellular structures, which facilitates the discovery of dominant ligand-receptor pairs between neighboring cells at single-cell resolution. SPROUT reconstructed structures achieved shape Pearson correlations ranging from 0.91 to 0.97 on the mouse hippocampus and human organ tumor microenvironment datasets. Furthermore, SPROUT can solely de novo reconstruct the structures at single-cell resolution, i.e., reaching the cell-type proximity correlations of 0.68 and 0.89 between reconstructed and immunohistochemistry-informed spatial structures on a human developing heart dataset and a tumor microenvironment dataset, respectively.