Predicting potential microbe-disease associations based on multi-source features and deep learning.

Studies have confirmed that the occurrence of many complex diseases in the human body is closely related to the microbial community, and microbes can affect tumorigenesis and metastasis by regulating the tumor microenvironment. However, there are still large gaps in the clinical observation of the microbiota in disease. Although biological experiments are accurate in identifying disease-associated microbes, they are also time-consuming and expensive. The computational models for effective identification of diseases related microbes can shorten this process, and reduce capital and time costs. Based on this, in the paper, a model named DSAE_RF is presented to predict latent microbe-disease associations by combining multi-source features and deep learning. DSAE_RF calculates four similarities between microbes and diseases, which are then used as feature vectors for the disease-microbe pairs. Later, reliable negative samples are screened by k-means clustering, and a deep sparse autoencoder neural network is further used to extract effective features of the disease-microbe pairs. In this foundation, a random forest classifier is presented to predict the associations between microbes and diseases. To assess the performance of the model in this paper, 10-fold cross-validation is implemented on the same dataset. As a result, the AUC and AUPR of the model are 0.9448 and 0.9431, respectively. Furthermore, we also conduct a variety of experiments, including comparison of negative sample selection methods, comparison with different models and classifiers, Kolmogorov-Smirnov test and t-test, ablation experiments, robustness analysis, and case studies on Covid-19 and colorectal cancer. The results fully demonstrate the reliability and availability of our model.

P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network.

Although many single-cell computational methods proposed use gene expression as input, recent studies show that replacing 'unstable' gene expression with 'stable' gene-gene associations can greatly improve the performance of downstream analysis. To obtain accurate gene-gene associations, conditional cell-specific network method (c-CSN) filters out the indirect associations of cell-specific network method (CSN) based on the conditional independence of statistics. However, when there are strong connections in networks, the c-CSN suffers from false negative problem in network construction. To overcome this problem, a new partial cell-specific network method (p-CSN) based on the partial independence of statistics is proposed in this paper, which eliminates the singularity of the c-CSN by implicitly including direct associations among estimated variables. Based on the p-CSN, single-cell network entropy (scNEntropy) is further proposed to quantify cell state. The superiorities of our method are verified on several datasets. (i) Compared with traditional gene regulatory network construction methods, the p-CSN constructs partial cell-specific networks, namely, one cell to one network. (ii) When there are strong connections in networks, the p-CSN reduces the false negative probability of the c-CSN. (iii) The input of more accurate gene-gene associations further optimizes the performance of downstream analyses. (iv) The scNEntropy effectively quantifies cell state and reconstructs cell pseudo-time.

Characterization of natural co-infection with goose astrovirus genotypes I and II in gout affected goslings.

RESEARCH HIGHLIGHTS: Urate tophi were found in the kidneys, liver, spleen and lungs.IFA confirmed the co-expression of GoAstV-I and II antigens in the same kidney.

[Identifying spatial domains from spatial transcriptome by graph attention network].

Due to the high dimensionality and complexity of the data, the analysis of spatial transcriptome data has been a challenging problem. Meanwhile, cluster analysis is the core issue of the analysis of spatial transcriptome data. In this article, a deep learning approach is proposed based on graph attention networks for clustering analysis of spatial transcriptome data. Our method first enhances the spatial transcriptome data, then uses graph attention networks to extract features from nodes, and finally uses the Leiden algorithm for clustering analysis. Compared with the traditional non-spatial and spatial clustering methods, our method has better performance in data analysis through the clustering evaluation index. The experimental results show that the proposed method can effectively cluster spatial transcriptome data and identify different spatial domains, which provides a new tool for studying spatial transcriptome data.

Iris lactea var. chinensis plant drought tolerance depends on the response of proline metabolism, transcription factors, transporters and the ROS-scavenging system.

BACKGROUND: Iris lactea var. chinensis, a perennial herbaceous species, is widely distributed and has good drought tolerance traits. However, there is little information in public databases concerning this herb, so it is difficult to understand the mechanism underlying its drought tolerance. RESULTS: In this study, we used Illumina sequencing technology to conduct an RNA sequencing (RNA-seq) analysis of I. lactea var. chinensis plants under water-stressed conditions and rehydration to explore the potential mechanisms involved in plant drought tolerance. The resulting de novo assembled transcriptome revealed 126,979 unigenes, of which 44,247 were successfully annotated. Among these, 1187 differentially expressed genes (DEGs) were identified from a comparison of the water-stressed treatment and the control (CK) treatment (T/CK); there were 481 upregulated genes and 706 downregulated genes. Additionally, 275 DEGs were identified in the comparison of the rehydration treatment and the water-stressed treatment (R/T). Based on Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) analysis, the expression levels of eight randomly selected unigenes were consistent with the transcriptomic data under water-stressed and rehydration treatment, as well as in the CK. According to Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, proline metabolism-related DEGs, including those involved in the 'proline catabolic process', the 'proline metabolic process', and 'arginine and proline metabolism', may play important roles in plant drought tolerance. Additionally, these DEGs encoded 43 transcription factors (TFs), 46 transporters, and 22 reactive oxygen species (ROS)-scavenging system-related proteins. Biochemical analysis and histochemical detection showed that proline and ROS were accumulated under water-stressed conditions, which is consistent with the result of the transcriptomic analysis. CONCLUSIONS: In summary, our transcriptomic data revealed that the drought tolerance of I. lactea var. chinensis depends on proline metabolism, the action of TFs and transporters, and a strong ROS-scavenging system. The related genes found in this study could help us understand the mechanisms underlying the drought tolerance of I. lactea var. chinensis.

Sandbur Drought Tolerance Reflects Phenotypic Plasticity Based on the Accumulation of Sugars, Lipids, and Flavonoid Intermediates and the Scavenging of Reactive Oxygen Species in the Root.

The perennial grass Cenchrus spinifex (common sandbur) is an invasive species that grows in arid and semi-arid regions due to its remarkable phenotypic plasticity, which confers the ability to withstand drought and other forms of abiotic stress. Exploring the molecular mechanisms of drought tolerance in common sandbur could lead to the development of new strategies for the protection of natural and agricultural environments from this weed. To determine the molecular basis of drought tolerance in C. spinifex, we used isobaric tags for relative and absolute quantitation (iTRAQ) to identify proteins differing in abundance between roots growing in normal soil and roots subjected to moderate or severe drought stress. The analysis of these proteins revealed that drought tolerance in C. spinifex primarily reflects the modulation of core physiological activities such as protein synthesis, transport and energy utilization as well as the accumulation of flavonoid intermediates and the scavenging of reactive oxygen species. Accordingly, plants subjected to drought stress accumulated sucrose, fatty acids, and ascorbate, shifted their redox potential (as determined by the NADH/NAD ratio), accumulated flavonoid intermediates at the expense of anthocyanins and lignin, and produced less actin, indicating fundamental reorganization of the cytoskeleton. Our results show that C. spinifex responds to drought stress by coordinating multiple metabolic pathways along with other adaptations. It is likely that the underlying metabolic plasticity of this species plays a key role in its invasive success, particularly in semi-arid and arid environments.

H+ -Insertion Boosted α-MnO2 for an Aqueous Zn-Ion Battery.

Rechargeable Zn/MnO2 batteries using mild aqueous electrolytes are attracting extensive attention due to their low cost, high safety, and environmental friendliness. However, the charge-storage mechanism involved remains a topic of controversy so far. Also, the practical energy density and cycling stability are still major issues for their applications. Herein, a free-standing α-MnO2 cathode for aqueous zinc-ion batteries (ZIBs) is directly constructed with ultralong nanowires, leading to a rather high energy density of 384 mWh g-1 for the entire electrode. Greatly, the H+ /Zn2+ coinsertion mechanism of α-MnO2 cathode for aqueous ZIBs is confirmed by a combined analysis of in situ X-ray diffractometry, ex situ transmission electron microscopy, and electrochemical methods. More interestingly, the Zn2+ -insertion is found to be less reversible than H+ -insertion in view of the dramatic capacity fading occurring in the Zn2+ -insertion step, which is further evidenced by the discovery of an irreversible ZnMn2 O4 layer at the surface of α-MnO2 . Hence, the H+ -insertion process actually plays a crucial role in maintaining the cycling performance of the aqueous Zn/α-MnO2 battery. This work is believed to provide an insight into the charge-storage mechanism of α-MnO2 in aqueous systems and paves the way for designing aqueous ZIBs with high energy density and long-term cycling ability.

Phase-Controllable Cobalt Phosphides Induced through Hydrogel for Higher Lithium Storages.

Transition metal phosphides (TMPs) have gained increased attention in energy storage due to their potential applications for optimizing electrochemical performances. However, their preparation routes usually require highly toxic and flammable phosphorus sources with strict reaction conditions. The existence of multiple energetically favorable stoichiometries also makes it a challenge to achieve phase control of metal phosphides. In this work, we have successfully realized the phase-controllable framework of cobalt phosphide from Co2P to CoP by employing a semi-interpenetrating network (semi-IPN) hydrogel as a precursor. Interestingly, the semi-IPN hydrogel could serve as a self-assembly/sacrificing template to accomplish 3D space confinement, where poly(vinylphosphonic acid) (PVPA) was identified as a prominent phosphorus source due to its strong metal complexation ability and high thermal stability. Furthermore, this route is successfully extended to the synthesis of other TMPs, including Fe2P, Ni2P, and Cu3P. The specific structure of cobalt phosphides gives rise to superior lithium storage performance, showing superior cycling stability (495.2 mAh g-1 after 1000 cycles at 2.0 A g-1). This approach envisions a new outlook on exploitation of essential functional hydrogels for the creation of inorganic materials toward sustainable energy development.

Photoelectrochemical determination of the activity of histone acetyltransferase and inhibitor screening by using MoS2 nanosheets.

The enzyme histone acetyltransferase (HAT) catalyzes the acetylation of a substrate peptide, and acetyl coenzyme A is converted to coenzyme A (CoA). A photoelectrochemical method is described for the determination of the HAT activity by using exfoliated MoS2 nanosheets, phos-tag-biotin, and ß-galactosidase (ß-Gal) based signal amplification. The MoS2 nanosheets are employed as the photoactive material, graphene nanosheets as electron transfer promoter, gold nanoparticles as recognition and capture reagent for CoA, and phos-tag-biotin as the reagent to link CoA and ß-Gal. The enzyme ß-Gal catalyzes the hydrolysis of substrate O-galactosyl-4-aminophenol to generate free 4-aminophenol which is a photoelectrochemical electron donor. The photocurrent increases with the activity of HAT. Under optimal conditions, the response is linear in the 0.3 to 100 nM activity range, and the detection limit is 0.14 nM (at S/N = 3). The assay was applied to HAT inhibitor screening, specifically for the inhibitors C646 and anacardic acid. The IC50 values are 0.28 and 39 µM, respectively. The method is deemed to be a promising tool for epigenetic research and HAT-targeted cancer drug discovery. Graphical abstract Histone acetyltransferase was detected using a sensitive photoelectrochemical method using MoS2 nanosheets as photoactive material.

Amplified electrochemical immunoassay for 5-methylcytosine using a nanocomposite prepared from graphene oxide, magnetite nanoparticles and ß-cyclodextrin.

A nanocomposite was prepared from ß-cyclodextrin (ß-CD) functionalized graphene oxide and magnetic nanoparticles (GO/Fe3O4/ß-CD). In parallel, a polyamidoamine dendrimer conjugated to avidinylated alkaline phosphatase (PAMAM-avidin-ALP) was prepared and exploited as a signal amplification unit in a voltammetric immunoassay for 5-methylcytosine (5mC) in genomic DNA. The GO/Fe3O4/ß-CD as a substrate material exhibited good solubility, electrical conductivity and large surface. This is beneficial for the further modification of antibodies (Ab) by host-guest interaction and amide bonds. By taking advantage of three-dimensional structure to capture avidin-ALP by amide linkages, PAMAM was used as a catalytic signal amplification element in this assay. Under the optimized condition and at a typical working potential of 0.94 V, the response to 5mC is linear in the 0.01-50 nM concentration range with a detection limit of 3.2 pM (at S/N = 3). The method is stable, selective and reproducible. It was applied to the determination of 5mC in genomic DNA of human tissue. Graphical abstract An electrochemical immunoassay was constructed for 5-methylcytosine detection based on nanocomposite of graphene oxide, magnetite nanoparticles and ß-cyclodextrin, and enzymatic signal amplification.

c-Met and ERß expression differences in basal-like and non-basal-like triple-negative breast cancer.

Basal-like breast cancer (BLBC) and triple-negative breast cancer (TNBC) are two entities of breast cancer that share similar poor prognosis. Even though both cancers have overlaps, there are still some differences between those two types. It has been reported that the c-Met high expression was associated with poor prognosis not only in breast cancer but also in many other cancers. The role of ERß in pathogenesis and treatment of breast cancer has remained controversial. In this study, we firstly distinguished basal-like from nonbasal-like cancer patients in TNBC patients using CK5/6 and EGFR as markers and next determined the relationship of basal-like breast cancer with c-Met or ERß expression levels and prognosis in TNBC patients. One hundred twenty-seven patients who had been diagnosed with TNBC were enrolled. The clinical and pathological characteristics of the patients were recorded. The expression of EGFR, CK5/6, ERß, and c-Met were evaluated with immunohistochemical methods using paraffin blocks. The median age of patients was 50.7 years. CK5/6 immunopositivity was 31.5 % (40/127), and EGFR was 40.2 % (51/127). Of the TNBC cases, 55.1 % (71/127) were positive for either CK5/6 or EGFR and were thus classified as basal-like breast cancer. C-Met (P < 0.001) and ERß (P = 0.002) overexpression, small tumor sizes, a ductal subtype, and high-grade tumor were significantly correlated with BLBC. High c-Met expression was detected in 43.3 % patients. Metastatic lymph nodes and tumor size (>5 cm), which were both important prognostic predictors, were significantly associated with recurrence and mortality. BLBC typically demonstrates a unique profile. CK5/6 and EGFR expression combination indicates a higher basal-like phenotype possibility. The expression of c-Met and ERß were significantly related to the basal-like phenotype. The classical markers, lymph node metastasis, and tumor size were found to have important prognostic value. However, high c-Met expression and basal-like phenotypes did not show a direct correlation with poor prognosis.

NFMCLDA: Predicting miRNA-based lncRNA-disease associations by network fusion and matrix completion.

In recent years, emerging evidence has revealed a strong association between dysregulations of long non-coding RNAs (lncRNAs) and sophisticated human diseases. Biological experiments are adequate to identify such associations, but they are costly and time-consuming. Therefore, developing high-quality computational methods is a challenging and urgent task in the field of bioinformatics. This paper proposes a new lncRNA-disease association inference approach NFMCLDA (Network Fusion and Matrix Completion lncRNA-Disease Association), which can effectively integrate multi-source association data. In this approach, miRNA information is used as the transition path, and an unbalanced random walk method on three-layer heterogeneous network is adopted in the preprocessing. Therefore, more effective information between networks can be mined and the sparsity problem of the association matrix can be solved. Finally, the matrix completion method accurately predicts associations. The results show that NFMCLDA can provide more accurate lncRNA-disease associations than state-of-the-art methods. The areas under the receiver operating characteristic curves are 0.9648 and 0.9713, respectively, through the cross-validation of 5-fold and 10-fold. Data from published case studies on four diseases - lung cancer, osteosarcoma, cervical cancer, and colon cancer - have confirmed the reliable predictive potential of NFMCLDA model.

Efficacy of Dupilumab in Children 6 Months to 11 Years Old With Atopic Dermatitis: A Retrospective Real-World Study in China.

Background: Atopic dermatitis (AD) is a common skin disease that affects patients' quality of life, especially in the pediatric population. Dupilumab has shown good efficacy and safety in the treatment of AD in adolescents and adults, but the real data on younger children using dupilumab are scarce. Objectives: We investigated the doses, efficacy, and safety of dupilumab in children with moderate-to-severe AD aged ≥6 months to 11 years. Methods: This single-center retrospective cohort analysis included dupilumab-treated patients with severe AD under 12 years of age. Primary endpoints included the proportion of Validated Investigator Global Assessment (vIGA) 0/1 achieved and the percentage change from baseline in eczema area and severity index (EASI) and SCORing Atopic Dermatitis (SCORAD) at week 24 (W24). Secondary endpoints were mean change in pruritus numerical rating score (P-NRS) and body surface area (BSA) after W24 of treatment, description of adverse events, and Children's Dermatology Life Quality Index (CDLQI) improvement from baseline in endpoints. Results: Fifty-seven patients were included (mean age 7.2 ± 3.0 years). The primary endpoint (vIGA = 0/1) was achieved by 51 of 57 (89.5%) patients at W24. Significant improvements in EASI, SCORAD, P-NRS, and CDLQI scores were observed from baseline to W24 with dupilumab treatment and remained until W40. In different age groups, the endpoint vIGA achieved 0/1: 95.2% (20/21) of younger children and 88.9% (32/36) of older children. No serious adverse drug reactions were reported. Conclusions: This study aimed to describe the safety and efficacy of dupilumab in pediatric patients and examined differences of efficacy with various doses. The outcomes are comparable with those of existing clinical trials. Phase III Clinical Trial: NCT03346434.

Intrusive trichome bases in the leaves of silverleaf nightshade (Solanum elaeagnifolium; Solanaceae) do not facilitate fluorescent tracer uptake.

PREMISE OF THE STUDY: Solanum elaeagnifolium (silverleaf nightshade), having originated in the Americas, is now a serious summer-growing, perennial weed in many countries, including Australia. Most surfaces of the plants have a dense covering of trichomes, giving them a silvery-white appearance, hence the common name. We aimed to identify structural and functional properties of its leaves, especially the trichomes, that may affect the uptake of foliar-applied tracer dyes. METHODS: The structure of leaves of Solanum elaeagnifolium was examined by light and scanning electron microscopy. The potential for transport of materials between trichomes and veins was studied with symplastic (carboxyfluorescein diacetate) and apoplastic (lucifer yellow) tracer dyes. KEY RESULTS: Mature leaves had a dense covering of complex, stellate trichomes on both surfaces, particularly the abaxial. The basal cells of Solanum elaeagnifolium trichomes penetrated into the underlying palisade mesophyll layers. The innermost lobes of these basal cells sometimes contacted the bundle sheath of the veins, but were not observed to directly contact the xylem or phloem. We found that neither symplastic nor apoplastic dyes were transferred between the basal cells of the trichomes and the vascular tissues. The trichome layer repelled water-based tracer dyes, while one of four adjuvants tested facilitated entry of both symplastic and apoplastic dyes. CONCLUSIONS: Our results did not support a transport function for the trichomes. The trichomes may protect the mesophytic leaves from invertebrate herbivory, while also probably decreasing radiation absorbed resulting in cooler leaves in this summer-growing species.

scGAMNN: Graph Antoencoder-Based Single-Cell RNA Sequencing Data Integration Algorithm Using Mutual Nearest Neighbors.

It is critical to correctly assemble high-dimensional single-cell RNA sequencing (scRNA-seq) datasets and downscale them for downstream analysis. However, given the complex relationships between cells, it remains a challenge to simultaneously eliminate batch effects between datasets and maintain the topology between cells within each dataset. Here, we propose scGAMNN, a deep learning model based on graph autoencoder, to simultaneously achieve batch correction and topology-preserving dimensionality reduction. The low-dimensional integrated data obtained by scGAMNN can be used for visualization, clustering and trajectory inference.By comparing it with the other five methods, multiple tasks show that scGAMNN consistently has comparable data integration performance in clustering and trajectory conservation.

Goose surfactant protein A inhibits the growth of avian pathogenic Escherichia coli via an aggregation-dependent mechanism that decreases motility and increases membrane permeability.

Pulmonary collectins have been reported to bind carbohydrates on pathogens and inhibit infection by agglutination, neutralization, and opsonization. In this study, surfactant protein A (SP-A) was identified from goose lung and characterized at expression- and agglutination-functional levels. The deduced amino acid sequence of goose surfactant protein A (gSP-A) has two characteristic structures: a shorter, collagen-like region and a carbohydrate recognition domain. The latter contains two conserved motifs in its Ca2+-binding site: EPN (Glu-Pro-Asn) and WND (Trp-Asn-Asp). Expression analysis using qRT-PCR and fluorescence IHC revealed that gSP-A was highly expressed in the air sac and present in several other tissues, including the lung and trachea. We went on to produce recombinant gSP-A (RgSP-A) using a baculovirus/insect cell system and purified using a Ni2+ affinity column. A biological activity assay showed that all bacterial strains tested in this study were aggregated by RgSP-A, but only Escherichia coli AE17 (E. coli AE17, O2) and E. coli AE158 (O78) were susceptible to RgSP-A-mediated growth inhibition at 2-6 h. Moreover, the swarming motility of the two bacterial strains were weakened with increasing RgSP-A concentration, and their membrane permeability was compromised at 3 h, as determined by flow cytometry and laser confocal microscopy. Therefore, RgSP-A is capable of reducing bacterial viability of E. coli O2 and O78 via an aggregation-dependent mechanism which involves decreasing motility and increasing the bacterial membrane permeability. These data will facilitate detailed studies into the role of gSP-A in innate immune defense as well as for development of antibacterial agents.

Three-dimensional spheroid formation of adipose-derived stem cells improves the survival of fat transplantation by enhance their therapeutic effect.

Adipose-derived stem cells (ADSCs) have important applications in basic research, especially in fat transplantation. Some studies have found that three-dimensional (3D) spheroids formed by mesenchymal stem cells have enhanced therapeutic potential. However, the fundamental basics of this effect are still being discussed. ADSCs were harvested from subcutaneous adipose tissues and 3D spheroids were formed by the automatic aggregation of ADSCs in a non-adhesive 6-well plate. Oxygen glucose deprivation (OGD) was used to simulate the transplantation microenvironment. We found that 3D culture of ADSCs triggered cell autophagy. After inhibiting autophagy by Chloroquine, the rates of apoptosis were increased. When the 3D ADSC-spheroids were re-planked, the number of senescent ADSCs decreased, and the proliferation ability was promoted. In addition, there were more cytokines secreted by 3D ADSC-spheroids including VEGF, IGF-1, and TGF-ß. After adding the conditioned medium with human umbilical vein endothelial cells (HUVECs), 3D ADSC-spheroids were more likely to promote migration, and tube formation, stimulating the formation of new blood vessels. Fat grafting experiments in nude mice also showed that 3D ADSC-spheroids enhanced survival and neovascularization of fat grafts. These results suggested that 3D spheroids culturing of ADSCs can increase the therapeutic potential in fat transplantation.

Complete chloroplast genome of Serrated Tussock, Nassella trichotoma (Poaceae: Stipeae).

Nassella trichotoma is one of the most serious weed species in Australia. It is often confused with other Nassella and stipoid species, especially at the young seedling stage, adding another layer of complexity in effective weed management. We report here the complete chloroplast genome of N. trichotoma (137,568 bp, GenBank accession number KX792500.2) sequenced using Next Generation Sequencing technology (Illumina). The N. trichotoma was grouped closely with other Nassella species and separated from other Stipeae species in the phylogenetic tree constructed based on the complete chloroplast genome sequences. The sequence information could be used for further identification of novel DNA barcodes for correct weed identification and subsequently improve management of this invasive grass.

scBPGRN: Integrating single-cell multi-omics data to construct gene regulatory networks based on BP neural network.

The deterioration and metastasis of cancer involve various aspects of genomic changes, including genomic DNA changes, epigenetic modifications, gene expression, and other complex interactions. Therefore, integrating single-cell multi-omics data to construct gene regulatory networks containing more omics information is of great significance for understanding the pathogenesis of cancer. In this article, an algorithm integrating single-cell RNA sequencing data and DNA methylation data to construct a gene regulatory network based on the back-propagation (BP) neural network (scBPGRN) is proposed. This algorithm uses biweight extreme correlation coefficients to measure the correlation between factors and uses neural networks to calculate generalized weights to construct gene regulation networks. Finally, the node strength is calculated to identify the genes associated with cancer. We apply the scBPGRN algorithm to hepatocellular carcinoma (HCC) data. We construct a regulatory network and identify top-ranked genes, such as MYCBP, KLHL35, PRKCZ, and SERPINA6, as the key HCC-related genes. We analyze the top 100 genes, and the HCC-related genes are concentrated in the top 20. In addition, the single cell data is found to consist of two subpopulations. We also apply scBPGRN to two subpopulations. We analyze the top 50 genes in them, and the HCC-related genes are concentrated in the top 20. The consequences of functional enrichment analysis indicate that the gene regulatory network we have constructed is valid. Our results have been verified in several pieces of literature. This study provides a reference for the integration of single-cell multi-omics data to construct gene regulatory networks.

Lung infection of avian pathogenic Escherichia coli co-upregulates the expression of cSP-A and cLL in chickens.

The host innate defense-pathogen interaction in the lung has always been a topic of concern. The respiratory tract is a common entry route for Avian pathogenic Escherichia coli (APEC). Chicken surfactant protein A (cSP-A) and chicken lung lectin (cLL) can bind to the carbohydrate moieties of various microorganisms. Despite their detection in chickens, their role in the innate immune response is largely unknown. This study aimed to examine whether the expression levels of cSP-A and cLL in the chicken respiratory system were affected by APEC infection. A lung colonization model was established in vivo using 5-day-old specific-pathogen-free chickens infected intratracheally with APEC. The chickens were euthanized 12 h post-infection (hpi) and 1-3 days post-infection (dpi) to detect various indicators. The results of quantitative reverse transcription-polymerase chain reaction and fluorescence multiplex immunohistochemical staining showed that the mRNA and protein expression levels of cSP-A and cLL in the lung and trachea were significantly co-upregulated at 2dpi.Transcriptome RNA-sequencing analysis indicated that the inoculation with APEC AE17 at 2 dpi resulted in differential gene expression of approximately 810 genes compared with control birds, but only a few genes were expressed with astatistically significant ≧2-fold difference. cLL and cSP-A were among the significantly upregulated genes involved in innate immunity. These findings indicated that cSP-A and cLL might play an important role in lung innate host defense against APEC infection at the early stage.