Although multiple actionable genes have been identified in melanoma, 38–42% of patients are still not druggable based on current research. In our study, DNA-NGS and RNA-NGS were utilized to construct molecular profiles of a Chinese cohort of 469 melanoma patients. Up to 11.7% (7/60) of patients in the undruggable group could be recognized as actionable by DNA and RNA sequential sequencing. Additionally, the use of RNA-NGS enhanced the proportion of druggable fusions from 2.56% to 17.27%. In total, the use of RNA-NGS increased the druggable proportion from 75% to 78%. Our study systemically analyzed the genetic landscape of Asian melanoma and demonstrated how DNA and RNA sequential sequencing is essential in bringing clinical benefits to more melanoma patients.n = 469) were sequentially sequenced by DNA-NGS and RNA-NGS. The genomic alterations were determined, and potentially actionable targets were investigated. Results: Patients with potential druggable targets were identified in 75% of Chinese melanoma patients by DNA-NGS based on OncoKB, which was much higher than in a previous Asian study. NRG1 fusions were first identified in melanoma. In addition, up to 11.7% (7/60) of patients in the undruggable group could be recognized as actionable by including RNA-NGS analysis. By comparing the fusion detection rate between DNA-NGS and RNA-NGS, all available samples after DNA-NGS detection were further verified by RNA-NGS. The use of RNA-NGS enhanced the proportion of druggable fusions from 2.56% to 17.27%. In total, the use of RNA-NGS increased the druggable proportion from 75% to 78%. Conclusions: In this study, we systemically analyzed the actionable landscape of melanoma in the largest Asian cohort. In addition, we first demonstrated how DNA and RNA sequential sequencing is essential in bringing clinical benefits to more patients with melanoma.Background: In contrast to Caucasian melanoma, which has been extensively studied, there are few studies on melanoma in Asian populations. Sporadic studies reported that only 40% of Asian melanoma patients could be druggable, which was much lower than that in Caucasians. More studies are required to refine this conclusion. Methods: Chinese melanoma patients ( BRAF V600E could be targeted with dabrafenib and trametinib, which have been approved by the FDA for pan-cancer treatment [NRTK fusions could be inhibited by TRK inhibitors [The morbidity rate of melanoma has rapidly increased in recent years, causing more than 57,000 deaths worldwide in 2020 . DNA-basreatment ,9. For ehibitors ,11,12,13Although multiple actionable genes have been identified in melanoma, 38–42% of patients are still not druggable based on current research ,15. In nTo identify underlying genomic targets with clinical significance, DNA-NGS and RNA-NGS were utilized to construct molecular profiles of a Chinese cohort of 469 melanoma patients. We systematically delineated the molecular genetic landscape of Chinese melanoma patients and stratified patients into druggable or undruggable groups based on actionable genes, TMB status, and MSI status. Furthermore, potential actionable genes were investigated in the undruggable group, and we demonstrated how RNA sequencing is essential in bringing benefits to more melanoma patients.Tumor histological specimens  obtained from multi-centers ) between March 2018 and May 2020 were used for NGS detection. This study has been approved by the Ethics Committee of the Zhejiang Cancer Hospital (IRB-2021-3). All patients were diagnosed via pathology, imaging, and clinical findings.Genomic DNA was extracted from tumor samples using a QIAamp DNA FFPE Tissue Kit  and fragmented to construct a library using KAPA Hyper Prep kits . DNA fragments of 200~400 bp were purified by an Agencourt AMPure XP Kit . Fragmented genomic DNA libraries were constructed with the KAPA HTP Library Preparation Kit  according to the instruction manual. After determining the concentration by a Qubit dsDNA HS Assay kit, DNA libraries were analyzed using Onco PanScan™ , which is an 825-gene panel that includes major tumor-related genes.Total RNA was isolated from FFPE samples using the AllPrep DNA/RNA Mini Kit . The RNA quality and quantity were determined by the Qubit RNA HS Assay  and the 4200 TapeStation System , respectively. Qualified RNA was used to synthesize double-stranded cDNA using a SuperScript VILO cDNA Synthesis kit  and an Abclonal Second Strand Synthesis Module  according to the recommended protocol. To prepare genomic libraries, the double-stranded cDNA was fragmented and constructed by a KAPA HTP Library Preparation Kit . The prepared libraries were captured with FusionCapture™ , which contains 395 cancer-related genes, and then subjected to Illumina NovaSeq6000  for paired-end sequencing. The sequencing reads were mapped to UCSC hg19 through HISAT2-2.0.5, and FusionMap was used to identify gene fusions.All statistical analyses were conducted using GraphPad Prism (version 8.02) software. The results are expressed as the mean ± SEM. The data were analyzed using a t test or one-way ANOVA, followed by the appropriate post-hoc tests .BRAF mutation, RAS mutation , and NF1 mutation, which are included in the KRAS/RAF pathway, were found in 120 (26%), 115 (25%), and 46 (10%) samples, respectively. Mutations in PTEN and PIK3CA from the PIK3CA pathway were identified in 28 (6%) and 14 (3%) patients, respectively. The genes from the CDKN2A pathway were also analyzed, and TP53 , CDK4 , MDM2 , and CDKN2A  were the most frequently mutated genes. Furthermore, two receptor tyrosine kinase fusion genes not related to the above pathways, ALK and NRG1, were found in our cohort, accounting for 1.5% (n = 7) and 0.6% (n = 3), respectively. In addition, other top six mutated genes in the cohort were KIT , CCND1 , FAT3 , LRP1B , MYC (5%), and TERT (4%) (Melanoma samples were obtained from 256 men (55%) and 213 women (45%) with ages ranging from 5 to 89 years (average age = 57 years). Collectively, 469 resected melanoma samples were screened by DNA sequencing. Numerous pathways were involved in the landscape. The ERT (4%) A. Apart http://oncokb.org/, accessed on 1 January 2022). Seventy-five percent (352/469) of patients had actionable genes after matching those genes with actionable mutations in OncoKB. The druggable patients were then grouped based on the highest level of drug response evidence in OncoKB. Approximately 47% (164/352) of patients could be classified as OncoKB level 1. This was followed by level 2 , level 3 , and level 4   B.BRAF, NRAS, and NF1 mutations were the top three in the SNV/Indel group, accounting for more than half of the total. In the CNV group, the proportions of CDK4 and MDM2 amplification were obviously predominant. Only three druggable tyrosine kinase fusion genes  were identified at the DNA level, and the BRAF fusions were dominant  in the fusion group. Furthermore, the top genes in the three groups were analyzed, and the number of gene mutations was counted based on the highest actionable level from OncoKB. The top actionable mutation genes in the study were BRAF, NRAS, NF1, and CDK4. Most of the genes only had one highest level due to a single variation. However, BRAF, FGFR1, and KIT presented two highest levels because of various mutations /Indel, CNV (copy number variant), and fusion, which were found in 85% (299/352), 17% (59/352), and 3% (10/352) of patients, respectively C. The pautations D.BRAF , RAF1 , ALK , FGFR1 , ETV6 , AKT3 , TCF12 , ATF , ZCCHC7 , ARHGEF2 , KDM6A , and WHSC1L1  . All fusions with druggable potential could be targeted by drugs from clinical trials  A. These , n = 1) B. Based l trials C. In totALK (n = 4), BRAF (n = 10), NRG1 (n = 2), RAF1 (n = 2), BCR (n = 1), NAB2 (n = 2), RELA (n = 2), and TERT (n = 2) (n = 110), regardless of whether they were druggable. At the RNA level, positive fusions were validated in 38 patients: ALK (n = 3), BRAF (n = 10), FGFR1 (n = 1), NTRK2 (n = 1), NTRK3 (n = 1), RAF1 (n = 3), AKT3 (n = 1), ATF1 (n = 1), CBFB (n = 1), ETS1 (n = 2), ETV6 (n = 2), JAZF1 (n = 2), KDM6A (n = 1), MAG (n = 1), METFA (n = 1), NF1 (n = 1), PAX5 (n = 1), RB1 (n = 1), SMARCB1 (n = 1), TCF12 (n = 1), WHSC1L1 (n = 1), and ZCCHC7 (n = 1) :  (n = 2) A. We exp (n = 1) A. RNA-NG (n = 1) A. If onl (n = 1) A. Overal (n = 1) B.The significant enhancement of fusion detection by RNA-NGS was attributed to the different designs of the DNA-NGS and RNA-NGS panels, which could be categorized into four groups: breakpoints that were covered by only the RNA-NGS panel (RNA cover only), breakpoints that were covered by DNA-NGS but failed to identify fusions (DNA cover but negative), the fusions that were verified by both DNA-NGS and RNA-NGS (Consistency), and the different partners that were validated by DNA-NGS and RNA-NGS (RNA correction) A. In theBRAF-WDFY1 to CUX1-BRAF and LMCD1-RAF1 to ERC1-RAF1 (BRAF-WDFY1 fusion detected by DNA NGS with “antisense rearrangements” juxtaposing the 5′ portion of the kinase genes and the 3′ portion of intergenic partners (BRAF lacked the tyrosine kinase domain (TKD), and the patient could not be referred to RAF tyrosine kinase domain (TKIs). However, the RNA-NGS results revealed that CUX1 exon 11 was fused to BRAF exon 9 with an intact TKD. The inconsistency between the DNA and RNA results was perhaps due to the reciprocal rearrangement in which DNA-NGS detected only the opposite breakpoint downstream of BRAF rather than the primary junction constituting CUX1 and BRAF. In Patient 2, DNA-NGS revealed that the partner LMCD1 was fused to the 3′ portion of RAF1 and that the breakpoint was in intron 9 of RAF1. At the RNA level, CUX1-BRAF was found, in which exon 8 of RAF1 was involved  from the Park et al. study [BRAF fusion and one ALK fusion were identified in the largest Chinese cohort (n = 81) from the Huang et al. study [n = 469). The leading number of fusions with clinical significance in our cohort was that of BRAF , which was slightly higher than that in the Caucasian population (1.1%) [KIAA1549-BRAF is the most common BRAF fusion [BRAF fusions in our present study were discrete. This result demonstrated that there was no enriched BRAF fusion type in melanoma. Furthermore, the RAF1 fusions  in the same pathway as BRAF were first reported in the Asian cohort. Among these fusions, four (three BRAF fusions and one RAF1 fusion) were novel. Additionally, our study identified NRG1 fusions in melanoma, which have never been found before. Surprisingly, we found high numbers of ALK rearrangements in melanoma (n = 4) for the first time. However, compared to the results in lung cancer [ALK fusions in our study were totally different, and none of them were the canonical type (EML4-ALK). Couts et al. demonstrated that melanoma expressing EML4-ALK was sensitive to ALK inhibitors in vitro and in vivo [ALK fusions from our study.Melanoma has been studied extensively in the Caucasian population ,18,19,20l. study . Only onl. study . In contn (1.1%) . It is iF fusion . The parg cancer , the par in vivo . This reBRAF fusions. In our study, RNA-NGS sequencing was systemically performed on patients without potential clinical utility at the DNA level for the first time, and comprehensive fusion types were investigated. In addition to the BRAF fusions, ALK, RAF1, and FGFR1 fusions were detected in the cohort. Briefly, up to 11.7% (7/60) of patients in the undruggable group could benefit from RNA-NGS based on the results. Overall, the use of RNA-NGS increased the proportion of treatable patients from 75% to 78%.Although more than half of the population could be targetable based on DNA-NGS results from our findings and the abovementioned studies ,15, apprNTRK3 is close to 100 kb in length (UCSC Genome Browser), which is close to 10% of the total size of the panel. Tiling such introns is not only technically challenging but also not practical in terms of the overall sequencing throughput. Additionally, introns with low frequency will not be tiled due to the cost factor. For example, ALK fusions have been frequently found in introns 18, 19, and 20 [ALK breakpoint in intron 17 was first identified in our study, so it is unrealistic to be covered as a frequent intron in gene rearrangement.The increased proportion of fusion detection by RNA-seq could be attributed to several causes. Large introns could not be covered by the panel assay due to their length. For example, intron 13 of , and 20 . To our CD74, the most frequent partner in the ROS1 fusion, is usually covered by the DNA-seq panel. However, the partners in the BRAF fusions were too diverse to be covered.On the other hand, eight fusions only detected by RNA-NGS were expected to be identified by DNA-NGS. Due to the complexity of the introns, the rearrangement that takes place in an intron may not be successfully detected by DNA-NGS. Five of those fusions involved BRAF on introns 7, 8, and 9. Similar to ROS1, the repeat sequence in those introns can be present at many other sites in the genome, and the inclusion of baits for these regions would simply result in unmappable reads ,30. TherSeveral limitations should be discussed. The clinicopathological parameters, such as clinical subtypes and disease stages were missed in the study. Those parameters could bring more a comprehensive understanding of Asian melanoma. Due to limitations in the amount of specimens, only samples with enough specimens were further sequenced by RNA-NGS. The resulting increased proportion of potential druggable patients in the undruggable group may be biased. However, more than half of the samples in the undruggable group had been analyzed by RNA-NGS, so the results did not induce significant bias. In addition, this study was a retrospective study, and patients with positive fusion detected by RNA-NGS were not able to receive targeted therapy, especially those with novel fusions with potential clinical significance. Therefore, further prospective trials of applying DNA and RNA sequential sequencing in targeted therapy for melanoma patients are needed in the future.This study systemically analyzed the genetic landscape of Asian melanoma and demonstrated how DNA and RNA sequential sequencing is essential in bringing clinical benefits to more melanoma patients.


Hundreds of bacterial small RNAs (sRNAs) require the Hfq chaperone to regulate mRNA expression. Hfq is limiting, thus competition among sRNAs for binding to Hfq shapes the proteomes of individual cells. To understand how sRNAs compete for a common partner, we present a single-molecule fluorescence platform to simultaneously visualize binding and release of multiple sRNAs with Hfq. We show that RNA residents rarely dissociate on their own. Instead, clashes between residents and challengers on the same face of Hfq cause rapid exchange, whereas RNAs that recognize different surfaces may cohabit Hfq for several minutes before one RNA departs. The prevalence of these pathways depends on the structure of each RNA and how it interacts with Hfq. We propose that sRNA diversity creates many pairwise interactions with Hfq that allow for distinct biological outcomes: active exchange favors fast regulation whereas co-residence of dissimilar RNAs favors target co-recognition or target exclusion. Bacterial sRNAs compete for limited copies of an RNA chaperone. Here, real-time single-molecule imaging shows that pairwise interactions of sRNAs with Hfq determine if the sRNAs are actively exchanged or stably coexist on the shared protein. When RBPs are limiting in number, their RNA ligands compete for binding12. This competition is often thought to depend on the order of recruitment, or the binding energetics. However, RBPs usually contain several RNA-binding domains, which not only confer stability to the complexes, but also allow a single RBP to interact with multiple RNAs15. Moreover, these multiple interaction sites can facilitate RNA exchange, enabling the continual remodeling of RBP complexes.The functions of cellular RNAs are influenced by their interactions with RNA-binding proteins (RBPs), which may exchange or remodel the RNAs over their life cycle16 by base pairing to a complementary region of an mRNA and altering its translation or stability17. sRNA regulation is facilitated by Hfq, a hexameric ring-shaped protein capable of simultaneously binding sRNAs and mRNAs18. This simultaneous binding is accomplished by distinct surfaces that recognize U-rich and A-rich motifs in the RNA substrates of Hfq19. Class I sRNAs interact with the proximal face and outer rim of the Hfq ring, whereas their mRNA targets bind the distal face of the ring. Class II sRNAs bind to the proximal and distal faces and base pair with targets that interact with the rim20.Bacterial small RNAs (sRNAs) regulate metabolism and stress response23. Additionally, one sRNA can regulate multiple targets, and multiple sRNAs can regulate a single target, resulting in a highly interconnected regulatory network dependent on Hfq availability24. Indeed, a recent report proposed that competition among targets for Hfq determines the subset of mRNAs that are regulated by sRNAs11.The copy number of sRNA and mRNA targets of Hfq generally exceeds the pool of free protein. As a result, sRNAs must compete for binding to Hfq, which stabilizes them against turnover. This adds to the sum of interactions that contribute to sRNA regulation within a cell. Pioneering studies established that sRNA overexpression decreases regulation by endogenous sRNAs, because of competition for binding to Hfq25. Thus, it has been argued that sRNAs cannot passively wait for other RNAs to dissociate from Hfq before binding themselves27. Indeed, Fender and co-workers26 showed that sRNA off-rates increase with competitor RNA concentration, suggesting that RNAs actively “cycle” on Hfq. Fast regulation could also be achieved if competitors do not need to displace a resident from Hfq to engage with their targets, that is, both sRNAs reside on the protein. However, active exchange and coexistence between two RNAs bound to a chaperone have not been directly observed, to our knowledge. Consequently, our understanding of how sRNAs gain access to Hfq is still limited.Although sRNAs bind Hfq tightly, potentially delaying their exchange, yet regulation occurs in just a few minutes upon sRNA expression30. Thus far, competition performance is not predicted by the binding affinities, association, or dissociation rates of individual RNAs31. However, these properties are rarely measured in the presence of other RNAs. Thus, we still do not know which RNA features affect competition for Hfq or for other RNA chaperones.The mechanism of competition is important for understanding how individual RNAs perform within a network of similar RNA ligands. Previous work has shown that competition performance is affected by sRNA structure, with the class II sRNAs being more proficient at displacing other sRNAs from Hfq34 and stimulate research on active RNA exchange on other RBPs.In this work, we directly observe sRNA competition for Hfq in real-time, using a new method of immobilizing single Hfq hexamers for single-molecule total internal fluorescence (smTIRF) microscopy. Our results show that resident sRNAs rarely dissociate from Hfq before a competitor sRNA binds (passive competition). Instead, resident sRNAs are rapidly displaced after they clash with an incoming challenger (active competition). Unexpectedly, the results also show that two sRNAs may reside on an Hfq hexamer for more than 20 s (stable coexistence). We propose that stable coexistence may support new forms of sRNA regulation and may alter the engagement with mRNA targets. Importantly, we show that the mechanism of competition depends on the identity of the sRNA pair, not the resident or competitor alone, explaining the diversity of outcomes. Our findings on competition suggest nuances in regulation that could guide the design of novel synthetic circuitsTo study how sRNAs compete for Hfq, we devised a smTIRF microscopy assay, in which the Hfq hexamer is biotinylated on one of its CTDs . The biotinylation tag had only a minor effect on Hfq’s function in sRNA regulation . The least replacement occurred when DsrA searched for a place on Hfq pre-bound to ChiX . These results agreed with previous reports that ChiX sRNA is a powerful competitor for HfqThird, we found that when a class I or class II sRNA competed against itself (H-DA vs DA or H-CX vs CX), an intermediate number of residents were displaced (42% resident remaining at 5 nM competitor). Interestingly, the degree of competition was similar for both homotypic sRNA pairs. This suggested that the extent of exchange is limited when sRNAs compete for the same binding surfaces on Hfq.To study the competition process, we observed the binding and dissociation of single sRNA molecules in real-time for 5 min after adding competitor sRNAs. Figure To characterize the aggregate kinetics of resident displacement, we calculated the percentage of residents remaining on Hfq from 0 to 5 min following the addition of 5 nM competitor sRNA Fig. . The resOur single molecule assay can distinguish passive competition, in which a resident sRNA spontaneously dissociates from Hfq before a competitor binds, from active competition, in which the resident dissociates after a competitor sRNA binds to the same Hfq hexamer. Strikingly, the resident sRNAs rarely dissociated from Hfq spontaneously during a 5 min movie; this passive mode accounted for ≤ 17% of sRNA exchange  typically have several binding domains or surfacesAlthough these exchange pathways coexist in real time, their frequencies depend on how the RNAs engage the protein: RNAs capable of forming many contacts with Hfq favor active competition (rapid exchange), while RNAs that interact with opposite faces of Hfq favor stable coexistence (with either RNA disengaging from Hfq) Fig. . As a re35 as opposed to empty Hfq37. Given that Hfq is likely always engaged with RNA in the cell26, impeded binding to an occupied Hfq should be the most common scenario.Although sRNA exchange likely requires Hfq’s multiple RNA binding surfaces, the displacement mechanism remains unknown. Our measurements of the binding kinetics suggest that active exchange occurs through a clash between a resident on Hfq and an incoming competitor. Although the resident impedes access by an RNA competing for the same surface of Hfq, subsequent displacement of the resident is fast. Thus, sRNA association is rate-limiting Fig. . Only tw26, resident sRNAs are displaced when a competitor progressively invades the binding pockets of adjacent subunits, ultimately disengaging the resident from Hfq. Using this model, the authors estimated a resident dissociation rate of 0.06 s−1 or a lifetime of 16.7 s, which is similar to our Although resident sRNAs often dissociate within the same movie frame as competitor binding  mRNA displaces β-actin mRNA from the Zipcode binding protein 1 (ZBP1) in neurons42. It was also noted before31 that the dissociation rate of RNAs bound to the bacterial Rho factor increase with increasing concentrations of chase RNA44. Thus, active exchange may be an understudied mechanism explaining how RBPs capture their prospective ligands.Hfq, an RBP that actively exchanges its ligands, possesses features common to other RBPs, such as multiple RNA recognition surfaces, clusters of basic and acidic residues, and intrinsically disordered regions. These similarities raise the possibility that other RBPs also facilitate the exchange of their RNA substrates. For example, microRNAs compete for the RNA-induced silencing complex (RISC)34 with novel features, like target blocking. It still remains to characterize competition in the presence of cognate and non-cognate targets to better understand the interplay between RNAs during regulation. We hope that our work motivates the study of active displacement in other RNA-protein systems.Our work has elucidated sRNA strategies to compete for the bacterial chaperone Hfq that highlight nuances in regulation when many RNAs are present, as occurs in the cell. These competition principles should aid in the design of Hfq-based synthetic circuits45, except for the addition of 20 mM GMP. Transcription products were purified by PAGE and dissolved in water for immediate chemical modification and fluorescent labeling.DNA templates for sRNAs transcription were constructed by extension of overlapping DNA oligonucleotides (Thermo Fisher Scientific) using Q5 DNA polymerase . One, two or three guanosines were added at the 5’end to improve transcription by T7 polymerase  and ethylenediamine  were removed after the generation of a primary amine using centrifugal filters  followed by ethanol precipitation of the RNA. For labeling, one package of Cy3 or Cy5 NHS mono reactive dye  was dissolved in 60 µL DMSO , and 30 µL of the dissolved dye was added to the RNA solution and incubated overnight at room temperature. Excess dye was removed using a Chroma TE-30 spin column  followed by ethanol precipitation of the RNA. Excess free dye was not observed in purified labeled RNAs checked by denaturing PAGE. The labeling efficiency calculated from the ratio of dye to RNA concentration obtained from the absorption at 554 or 650 nm relative to 260 nm was 80–100% for all the labeled RNAs.Fluorophores were attached to the sRNA 5’ end in two stepsE. coli Hfq (EcHfq). The AviTag is recognized by E. coli’s biotin ligase (BirA) which catalyzes the conjugation of a biotin to the tagged protein48. For over-expression, the tag sequence was added using around-the-horn site-directed mutagenesis of pET21b-EcHfq, with primer set 1  was fused to the C-terminus of chiP expression by ChiX sRNA, fresh colonies of DJS2689 (PM1205 lacI’::PBAD-chiP-lacZ Δhfq::cat-sacB)30, alone, or transformed with plasmids expressing untagged Hfq (pD871-EcHfq) or tagged Hfq-CAvi (pD871-EcHfq-CAvi) were used to inoculate 20 mL LB-Miller media supplemented with 0.001% rhamnose (plus 25 μg/mL kanamycin for transformed cells), and grown overnight (~16 h) at 37 °C, 200 rpm. The next day, 0.2 mL of each overnight starter culture was used to inoculate 20 mL of fresh LB-Miller media. All cultures were supplemented with 0.001% rhamnose and 0.004% arabinose, and cultures containing pD871 transformants were further supplemented with 25 μg/mL kanamycin. Cells were grown to an OD600 between 0.7 and 0.8, and a β-galactosidase assay was performed  cells were co-transformed with plasmids expressing wild type Hfq (pET21b-EcHfq)49 and Hfq-CAvi (pD871-EcHfq-CAvi). Transformed cells were grown in LB-Miller media supplemented with 100 µg/mL ampicillin and 25 µg/mL kanamycin at 37 °C until OD600 = 0.5. Hfq and Hfq-CAvi expression was induced with 1 mM IPTG and 0.2 mM rhamnose , respectively. Biotin  was added with the inducers to promote the biotinylation of Hfq-CAvi monomers by endogenous BirA. Cells were grown for another 4 h at 37 °C and then collected by centrifugation and lysed, with the lysate treated and purified with a Ni2+ affinity column30. The eluate from the Ni2+ column was dialyzed into cation exchange buffer  and loaded onto a cation-exchange column  equilibrated in the same buffer. A buffer with pH 6.5 was chosen to discourage the binding of Hfq:Hfq-CAvi mixed hexamers with more than 3 tagged monomers (pI ≤ 6.4 estimated by ExPASy’s compute pI tool50). The column was washed with cation exchange buffer and eluted with a linear gradient of 0.2-1 M NaCl. Desired fractions were pooled, dialyzed into HB buffer , concentrated with centrifugal filters  and stored at −80 °C. The obtained protein is referred to as BioHfq throughout the text.To decrease the impact of tagging and biotinylation on Hfq’s function, Hfq hexamers containing around one modified CTD were prepared by co-expression of wild type Hfq and Hfq-CAvi. 51, with the following modifications: 5′-32P-labeled DsrA was 2 nM , tRNA and tracking dyes were omitted, and reactions were incubated at room temperature for 30 min. A partition function for two independent sites was fitted to the measured fractions of protein-bound RNA51. Dissociation constants for Hfq and BioHfq were found to be similar  was pre-bound to Hfq or BioHfq  in TNK buffer . After 30 min, 1 µL 10x TNK buffer or 0.01–1,000 nM unlabeled competitor DsrA were added to the reaction, and the incubation continued for another 30 min before samples were loaded in native 6% (w/v) polyacrylamide (29:1 mono:bis) gels. Gels were dried and quantified using ImageJ (1.53c). The bound protein-RNA fractions were fit with an empirical competitive model, as reported previously30. Competitor concentrations at which 50% of DsrA was displaced were in the same order of magnitude for Hfq and BioHfq , and 50 ng Hfq-CAvi (fully tagged) in 150 mM Tris·HCl pH 6.8, 1.5% SDS, 30% (v/v) glycerol were resolved on a 4-20% gradient Tris-Glycine gel (30 min at 200 V). Proteins were transferred to a nitrocellulose membrane using a semidry blotter and Towbin buffer  methanol, pH 8.3) for 1 h at 65 mA. The membrane was blocked with 5% BSA in 1 × TBST  for 1 h at room temperature, then incubated with primary antibody (0.5 µg/mL (1:1000 dilution) Avi Tag antibody, mAb, mouse; GenScript USA Inc., A01738-40) in 1× TBST, overnight at 4 °C. After three washes with 1× TBST, the membrane was incubated with the secondary antibody (2 µL antibody in 10 mL 1× TBST (1:5000 dilution); goat anti-mouse Alexa 594, Invitrogen, R37121) for 1 h at room temperature. The membrane was washed thrice with 1× TBST and allowed to fully dry, and then imaged in a Typhoon 9500 with excitation at 532 nm and emission collected with a long pass filter (>575 nm).53. Cy3 and Cy5 fluorophores were excited with green (532 nm) and red (640 nm) lasers, respectively; emission intensities were collected with a 60X water immersion objective coupled to an EMCCD camera. Data recording was controlled using custom software (https://github.com/Ha-SingleMoleculeLab/Data-Aquisition). Short movies  were recorded with both green and red lasers on. For long movies , the first and last second were recorded while exciting Cy3 and Cy5, while an alternating excitation scheme was used for the remainder of the movie to limit photobleaching.Single-molecule data were obtained using a home-built prism-type total internal reflection fluorescence (TIRF) microscope54 and incubated for 1-5 min. The slide was then washed with imaging buffer , 0.01% octaethylene glycol monododecyl ether (Nikkol), 0.8% glucose) supplemented with 165 U/mL glucose oxidase  and 2 U RNasin Plus . Cy3 spots were only observed when both BioHfq and NeutrAvidin were present on the slide . Cy3-sRNA·BioHfq complexes were added to a DDS-passivated quartz slide pretreated with biotinylated BSA , Tween-20 (0.2%) and NeutrAvidin For competition experiments, short movies (~50 frames) were first recorded in different fields of view to determine the average number of Cy3-sRNA·BioHfq complexes before the competition. Immediately afterward, competitor sRNAs in the imaging buffer were flowed into the slide chamber during acquisition. The increase in the background in the Cy5 channel corresponded to the time of competitor addition. After the real-time competition experiment , short movies (~50 frames) were collected in different fields of view (FOV) to determine the average number of Cy3- and Cy5-labeled molecules after the competition. To minimize having two or more Hfq closely located, we aimed to balance a low spot density but with a significant number of molecules per experiment (~500 molecules).55. Cy3-sRNA molecules were first selected as areas of interest (AOIs). AOIs were manually inspected to ensure single molecules were present; AOIs with two or more Hfq were not considered for further analysis. The intensity of the selected Cy3 AOIs was integrated over the entire length of the movie and then the AOI positions were mapped to the Cy5 channel to obtain the Cy3 and Cy5 intensity time trajectories56. Cy3 and Cy5 intensities for the same AOI were overlaid to visualize resident and competitors interacting with a single Hfq , Cy3-sRNA (resident) or Cy5-sRNA (competitor) . If these numbers were similar (<15% different), photobleaching was considered not significant, and such movies were analyzed further. Binding intervals for Cy3-labeled residents and Cy5-labeled competitors were obtained independently from Cy3 and Cy5 fluorescent traces of the same Hfq moleculeThe competitor association times with immobilized Hfq  nM, resulting in ~(25–150) s for the RNA to access Hfq. Thus, 20 s is a reasonable value for the minimum time an sRNA needs to remain on Hfq to regulate its targets.A 20 s threshold for defining stable coexisting resident/competitor pairs was established by examining probability density plots of coexistence times  at KS-test Data Entry (csbsju.edu)Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Crowd counting is considered a challenging issue in computer vision. One of the most critical challenges in crowd counting is considering the impact of scale variations. Compared with other methods, better performance is achieved with CNN-based methods. However, given the limit of fixed geometric structures, the head-scale features are not completely obtained. Deformable convolution with additional offsets is widely used in the fields of image classification and pattern recognition, as it can successfully exploit the potential of spatial information. However, owing to the randomly generated parameters of offsets in network initialization, the sampling points of the deformable convolution are disorderly stacked, weakening the effectiveness of feature extraction. To handle the invalid learning of offsets and the inefficient utilization of deformable convolution, an offset-decoupled deformable convolution (ODConv) is proposed in this paper. It can completely obtain information within the effective region of sampling points, leading to better performance. In extensive experiments, average MAE of 62.3, 8.3, 91.9, and 159.3 are achieved using our method on the ShanghaiTech A, ShanghaiTech B, UCF-QNRF, and UCF_CC_50 datasets, respectively, outperforming the state-of-the-art methods and validating the effectiveness of the proposed ODConv. Furthermore, benefiting from the advancement of digital monitoring6, the foundation of hardware is provided for research based on crowd counting. Therefore, crowd counting has attracted great attention in the field of computer vision due to the obvious requirement for public security and a stable hardware foundation.Public safety has attracted significant attention in recent years due to the increased worldwide population and accelerated urbanization. According to the needs of public safety and transport management, crowd counting8, feature-based regression methods10, and CNN-based methods13. Although superiority in terms of accuracy, efficiency, and robustness is shown in CNN-based approaches, CNNs’ inability to adapt to head-scale changes is still an obstacle, limiting the increase in accuracy. Many CNN-based methods15 attempt to address the aforementioned problem. However, there are also some barriers to handle. One is that, along with the improved accuracy, the number of arguments in the network has significantly increased, which means the training efficiency is consequently reduced. On the other hand, these methods are deficient in mechanisms to obtain the head-scale features completely by handling geometric transformations.The present crowd counting algorithms can be divided into three types: tracking-based methods17 is proposed to improve the CNNs’ capability of modeling geometric transformations by adding additional offsets, enhancing the adjustable receptive field of convolution. However, as shown in Fig. To address the abovementioned problems, a module called deformable convolution 18 is adopted as the backbone. The last dilated convolution layer is replaced with deformable convolution as the baseline, which is denoted as CSRNet⊕ . Without bells and whistles, by replacing the DConv in CSRNet⊕ with the proposed ODConv, we achieve better performance .In this paper, a novel deformable convolution called offset-decoupled deformable convolution  is proposed. To implement this ODConv, the traditional offset map is decoupled into the product of an initial offset map (pre_offset map) and a scale map. The potential performance of deformable convolution is better exploited by controlling the pre_offset map and the scale map. In our implementation, CSRNet18. On the other hand, based on the proposed ODConv, better performance is gained over the state-of-the-art on several crowd counting networks.In summary, the main contributions of this paper are twofold. First, an offset-decoupled deformable convolution (ODConv) is proposed, which constrains the offsets to a certain extent. It can obtain more complete information within the effective region of the sampling point while performing the same computation as CSRNetSince a method is proposed to improve the crowd counting performance by integrating offset-decoupled deformable convolution into the end-to-end network, the following two aspects related to our work are discussed.8 and works well for low-density crowds. By learning a mapping between captured features and counts, regression-based methods10 have significant advantages over detection-based methods in dealing with occlusion in dense crowds. Furthermore, with the great success of CNNs in other fields, they are widely utilized in crowd counting. In CNN-based methods, input images are mapped to density maps by using a nonlinear function to obtain estimated counts21. Wang et al.22 were pioneers in using CNNs to estimate crowd counts, proposing an end-to-end CNN model for counting from images of dense crowds. In contrast to the abovementioned model, Zhang et al.23 extended the network to a multicolumn architecture for variation of the receptive field and better robustness. On the basis of a multicolumn architecture, Onoro et al.24 proposed a model called HydraCNN, which is able to adapt to varied crowd counts and scenarios. The similarity between the abovementioned methods is that they all aim to increase the accuracy of crowd counting by altering the structure of the network. Another approach that is used to obtain better performance is to remove the limitation caused by the fixed geometric structures of convolution. For example, CSRNet18 was proposed to expand the receptive field while maintaining resolution, and a dilated convolution neural network was used as the back-end network. Nevertheless, CSRNet still has a fixed receptive field for extracting different head-scale sizes of features, resulting in low counting accuracy on various scales.Crowd counting methods can be classified into three categories: detection-based methods, feature-based regression methods, and CNN-based methods. A sliding window detector is utilized to identify targets in detection-based methods.25 proposed a perspective-guided convolution network (PGCNet) with an effective perspective estimation branch that guides variation smoothing of feature maps, enhancing the capability of feature alignment. Xia et al.26 proposed a coordinated feature fusion network (CFFNet) to solve the problem that spatial misalignment is ignored in feature extraction in traditional networks. A module called the spatial alignment module (SAM) was embedded to learn the offset of pixels to generate a high-quality density map for estimation and more detailed spatial distribution descriptions.Considering that spatial information is ignored in the abovementioned methods, there are several approaches to address this issue. One approach is to strengthen the architecture of convolutional neural networks. Yan et al17, which can be used to model nonrigid objects by adding extra learnable offsets to the original model. When 2D offsets, which are dependent on the input features, are added to the regular grid sampling locations in the standard convolution, the sampling grid is enabled to deform freely. Due to the effective improvement in CNNs’ capability of modeling geometric transformations, deformable convolution is widely used in image classification and pattern recognition. For example, Wu et al.27 proposed an offset-adjustable deformable convolution for virtual tracking. Offset adaptive technology is integrated to capture the spatial information of tracking objects and better performance is achieved. Guo et al.28 proposed a model called the dilated-attention-deformable convolution network (DADNet), in which deformable convolutional density map estimation (DME) enhances the flexibility of the sampling location of objects by adaptive offsets. Although deformable convolution can be used to model the features of a continuous scale, the offsets of sampling points are difficult to effectively learn, which leads to clustering in the features of sample points. As a result, the potential performance of deformable convolution is unable to be exerted.In addition to integrating modules and branches in the network to handle scale variations, there is another way to increase the flexibility of feature aggregation, that is, improving the fixed geometric structures of CNNs using deformable convolutionAs mentioned above, multiscale feature fusion is utilized in most algorithms, which leads to a significant increase in network parameters and computation. However, offsets are relatively large and generally exceed 1 pixel. If only the tanh function is added as an activation function, the offset loss is changed from -1 to 1, indicating that not all offsets are trained effectively. The current methods do not discuss which kind of activation function should be used after offset loss. Therefore, a step-by-step decreasing scaled deformable loss is proposed in this paper to decouple the offset of the deformable convolution into the product of the initial offset and the scale, which constrains the learning of the initial offset and the scale through additional loss. As a result, the deformable convolution’s potential is better utilized.In this section, we first introduce the principles of offset-decoupled deformable convolution , and then the architecture of the training network is presented.As illustrated in Fig. As shown in Fig. For example, given an input feature of size Thus, the constrained loss of the scale map can be presented as scale loss:Then, the loss of the pre_offset map called the pre_offset loss is:The loss of density estimation is:In conventional deformable convolution, the learned effect of offsets is completely determined by the input feature and random initialized offset convolution. In this situation, the variance of offsets is so large at some positions on the offset map that the sampling points are disordered. As a result, it is difficult for the network to train.The abovementioned problem can be addressed by offset-decoupled deformable convolution. Figure The offsets of the deformable convolution are decoupled into the product of the initial offset and the scale to constrain the learning of the initial offsets. As shown in Fig. T, the weighting coefficient is k and m, respectively.For epoch The architecture of the network is represented in Fig. 18 is used as the backbone network. In particular, the batch normalization layer is integrated after each convolution layer to boost the robustness of training with cropped images. To validate the effectiveness of ODConv, the last layer of dilated convolution is replaced with DConv and ODConv, denoted as CSRNet⊕ and CSRNet (ODConv), respectively. In the following section, the effectiveness of our ODConv is validated.CSRNetThe authors declare that the images that could lead to human identification in Figs. a,d,f areIn this section, the evaluation metric and datasets are introduced, and then the implementation details are described.30 are used in the evaluation metrics, which adopt mean absolute error  and mean square error  to verify accuracy. MAE and MSE are shown in Eqs. (N is the number of samples and The same methods as in the prior work in Eqs.  and 7),,30 are uOn four popular datasets, ShanghaiTech Part A, ShanghaiTech Part B, UCF-QNRF, and UCF_CC_50, the ODConv and other state-of-the-art approaches are evaluated. Furthermore, ablation experiments are carried out on UCF-QNRF and UCF_CC_50.UCF_CC_50 15. The UCF_CC_50 dataset contains 50 images with varied crowd densities. The range of counts in each image varies from 94 to 4543, with an average number of 1280. To increase the amount of data and test accuracy, we divided the dataset into 5 groups according to fivefold cross-validation.UCF-QNRF 31. UCF-QNRF is characterized by high resolution and high crowd density. It contains 1535 images, with an average of 814 head annotations per image, and there are 12,865 people in the most crowded image. Compared with ShanghaiTech B, UCF-QNRF has more images for testing, 334 in total, and the rest are training images.ShanghaiTech A and B 23. Most of the pictures in this dataset, which is 185 divided into Part A and Part B, come from the internet and the streets of Shanghai. Part A contains 482 images, and Part B contains 716 images. The difference between the two parts is that the resolution of Part B is higher and the number of images is larger.18 is replaced with VGG16-BN. In particular, since the batch normalization layer is popularly utilized in crowd counting, similar to most crowd counting approaches36, it is integrated after each convolution layer in our backbone to boost the robustness of training with cropped images. After replacement, the overall network is regarded as the baseline of the experiment, which is called CSRNet⊕ . Finally, the last layer of dilated convolution in the baseline is replaced by offset-decoupled deformable convolution, and the network is defined as our ODConv.First, the backbone of CSRNet37 is adopted with a fixed learning rate of 1e − 3. All images are resized to 400 × 400. The parameters , and step are set to 4, 0.2, 50, and 50, respectively. With different parameter combinations, 400 epochs are trained in 2 days for each experiment.In the experiments, a fixed 7 × 7 Gaussian kernel is utilized to generate density maps. The Adam optimizerIn this section, the proposed ODconv is compared with state-of-the-art methods on the four abovementioned datasets. In addition, an ablation study is conducted to demonstrate the superiority of the parameters utilized in the experiments.UCF-QNRF and UCF_CC_50. Significant gains of 91.9 and 159.3 MAE, respectively, are obtained in the test results with our proposed method on the datasets UCF-QRNF and UCF_CC_50, as shown in Table ShanghaiTech A and B. As shown in Table In this section, the influence of the number of deformable layers in our network is first demonstrated. In addition, the validity of offset-decoupled deformable convolution is confirmed by the visualization of offsets in Fig. Dilated convolution, which is integrated into the architecture of CSRNet, is gradually changed into deformable convolution. Then, each layer of deformable convolution is replaced with ODConv. As the performance shows in Table The sampling points of DConv and our proposed ODConv are shown in Fig. To illustrate the effectiveness of ODConv compared with DConv, we adopt a metric called the mean absolute error . The curves of the comparison with or without To reduce the impact caused by the variance of the sampling points, additional loss is added to the predicted scale map to make it as close as possible to 1.With the progress of training, 43 is adopted in which a p-value is calculated to determine whether the model’s performance is statistically significant. If the p-value is less than 0.05, we could consider that a significant difference exists between the two sets of data analysis. In this section, a new baseline consisting of ResNet-5044 is built to verify the extensibility of ODConv. The last layer of dilated convolution of ResNet-50 (backbone) is replaced with Deformable Convolution and Offset-decoupled Deformable Convolution called ResNet-50 (DConv) and ResNet-50 (ODConv), respectively. Then, the UCF_CC_50 dataset is divided into ten subsets, and tenfold cross-validation is performed. A graphical representation of the results is shown in Fig. t = 3.513, p = 0.0066 < 0.05). Then, the p-value  on CSRNet (DConv) and Ours (ODConv) in Fig. t = 2.840, p = 0.0194 < 0.05), indicating that ODConv can make significant differences on different backbones.To illustrate the robustness of ODConv on other backbones and the effectiveness compared with DConv, the T-testIn this paper, an offset-decoupled deformable convolution (ODConv) is proposed. Compared with the original method, the superiority of ODConv shown on constrained offsets. The offsets of sampling points in ODConv are decomposed, and the constraints are added to the offsets, decreasing the confusion or stacking of sampling points. As an example, the crowd counting results show that our ODConv can effectively improve the performance with little extra computational burden.


Fusarium moniliforme and Fusarium rotundus, which can contaminate a variety of foods and their products and severely affect agricultural and animal husbandry production  and Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) techniques are particularly powerful in genome-wide transcriptomic and regulatory profiling . RNA-seqTo understand the transcriptional and regulatory mechanisms underlying the cytotoxic effect of FB1, we applied RNA-seq for transcriptomic profiling of mRNA, lncRNA, circRNA and miRNA in porcine alveolar macrophages during FB1 exposure , which g5 cells/mL and cultured in a 5% CO2 incubator at 37°C for 24 h. FB1 at a final concentration of 50 μg/ml was added to the culture medium of the experimental wells, and the same amount of enzyme-free water was added to the culture medium of the control wells. After 24 h of FB1 treatment of cells and control cell culture, cells were collected for RNA-seq and ATAC-seq, respectively. Three FB1 treated samples and three control samples were collected for strand-specific library construction  of ribosomes depleted for RNA-seq   treated with different concentrations  of FB1 at different culture time points  was measured on a Tecan Infinit 200 microplate reader (Tecan) platform using the Cell CountingKit-8 (CCK-8) kit , and finally 50 μg/ml FB1 was induced for 24 h as the optimal treatment concentration and action time to investigate the cytotoxicity of FB1 on 3D4/21 cells. Porcine alveolar macrophages were seeded in 6-well plates at a density of 5 × 10 RNA-seq . Two FB1 RNA-seq . At the  RNA-seq .Total RNA was extracted from the experimental samples using the Trizol  kit according to the instructions, RNA purity and concentration were preliminarily detected using a NanoDrop2000 spectrophotometer , and RNA integrity was accurately quantified using an Agilent 2100  bioanalyzer. Then, we remove the rRNAs from the total RNA of the sample, retain mRNAs and ncRNAs, reverse transcribe the obtained RNA, purify the cDNA fragment using QiaQuick PCR kit , repair the end, add PolyA, add sequencing linker, degrade the product by UNG (Uracil-N-Glycosylase) enzyme and amplify the product by PCR, and sequence the library by Illumina HiSeqTM4000.Total RNA was extracted from the experimental samples using the Trizol  kit according to the instructions. The RNA of the size of 18–30 nt was enriched by polyacrylamide gel electrophoresis (PAGE). The 3′ adapter and 5′ adapter were connected respectively, and the small RNA connected with the two adapters was reverse transcribed. The bands of 140–160 bp in size were amplified by PCR and recovered and purified to complete the library construction. The constructed library was quality controlled using an Agilent 2100  and sequenced by Illumina HiSeqTM2500.https://CRAN.R-project.org/package=gmodels). Differentially expressed genes were identified by DESeq2  and sequenced by Gene Denovo Biotechnology Co., Ltd. .Data quality control was performed on ATAC-seq raw reads obtained from the sequencer before information analysis, and low-quality reads containing adapter reads, reads containing more than 10% unknown nucleotides (N), and low-quality reads containing more than 50% low quality  bases were removed to obtain high quality clean reads. The processed reads were aligned to the pig reference genome (release Sscrofa11.1) using Bowtie2 v2.2.8 , with reFor rRNA-depleted RNA-seq data, we confirmed that all samples are of similar sequencing depth, and the raw data are of good quality with >95% of bases pass the Q20 threshold. All these samples achieved alignment efficiency of higher than 91% . PCA andFor miRNA-seq data, after quality control and pre-processing, more than 99% of the raw reads are retained as clean reads, and the proportions of clean tags of the small RNAs exceeded 98% . As expeAfter quality control of ATAC-seq data, clean reads were mapped to the pig reference genome . The genIn summary, using the porcine alveolar macrophage cell line (3D4/21) as model, we applied both rRNA-depleted RNA sequencing (RNA-seq) and small RNA-seq to analyze the genome-wide transcriptional alterations of mRNA, lncRNA, circRNA and miRNA before and after exposure to FB1. To further reveal the underlying regulatory mechanism, we applied Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) to determine the genome-wide chromatin accessibility alterations in response to FB1-induced cytotoxicity. We anticipate that this dataset will serve as valuable resource for clarifying the transcriptional and regulatory mechanism underlying the immunotoxicity of FB1, and facilitate the identification of the key genes and signaling pathways contributing to mammalian cells response to FB1 exposure.


S. cerevisiae borate transporter Bor1p and examine whether key biochemical features of SLC4 transporters extend to borate transporters. We show that borate transporters and SLC4 transporters share multiple properties, including lipid-promoted dimerization, sensitivity to stilbene disulfonate-derived inhibitors, and a requirement for an acidic residue at the solute binding site. We also identify several amino acids critical for Bor1p function and show that disease-causing mutations in human SLC4A1 will eliminate in vivo function when their homologous mutations are introduced in Bor1p. Our data help elucidate mechanistic features of Bor1p and reveal significant functional properties shared between borate transporters and SLC4 transporters.Borate transporters are membrane transport proteins that regulate intracellular borate levels. In plants, borate is a micronutrient essential for growth but is toxic in excess, while in yeast, borate is unnecessary for growth and borate export confers tolerance. Borate transporters share structural homology with human bicarbonate transporters in the SLC4 family despite low sequence identity and differences in transported solutes. Here, we characterize the  A. thaliana under limiting borate conditions, but is degraded under high borate concentrations to avoid the accumulation of toxic borate levels in plant shoots [S. cerevisiae, borate is not required for growth, and the function of its borate transporter Bor1p (ScBor1p) is important for mediating resistance to toxic levels of borate [A. thaliana [S. mikatae [O. sativa [Bicarbonate transporters in the solute carrier (SLC) 4 family include electroneutral anion exchangers and sodium-coupled cotransporters. The archetypal SLC4 anion exchanger is SLC4A1, also known as Band 3 or Anion Exchanger 1 (AE1). SLC4A1 is the most abundant membrane protein in human red blood cells . Despitet shoots . In S. cf borate . Structu. sativa , along w. sativa ,13,14,15. sativa , and SLC. sativa , all sha. sativa . The sam. sativa ,20 and U. sativa , as well. sativa  and orth. sativa  and SLC2. sativa , showingS. cerevisiae Bor1p can be overexpressed and purified and has a readily observable phenotype [Despite the structural similarities between borate transporters and SLC4 transporters, one striking difference is that they differ in solute; all but one of the ten human SLC4 transporters transport bicarbonate, while borate transporters instead transport borate. Thus, it remains an open question as to what other biophysical characteristics and functional similarities might extend from SLC4 transporters to borate transporters and vice versa. In particular, the role lipids play in mediating multimeric assembly, whether borate transporters display sensitivity to stilbene disulfonate-derived inhibitors, and structural and mechanistic similarities between amino acids at or near the solute binding site all remain outstanding questions. Because henotype , we charS. cerevisiae strain BTSY1 (MATα his3::GAL1-GAL4 pep4 prb1-1122) [w/v) n-Dodecyl-beta-d-Maltopyranoside (DDM), protein was purified by performing nickel affinity chromatography followed by size exclusion chromatography. Protein was injected onto a Superdex 200 Increase 10/300 GL column (Cytiva) equilibrated in 20 mM Mes pH 6.5, 100 mM NaCl, 2% glycerol, and 0.03% DDM. To compare size exclusion chromatograms between wild-type and mutant ScBor1p, preparations of 1 L of cell culture were grown and harvested under identical conditions.ScBor1p was overexpressed and purified as described previously . Brieflyb1-1122) . Cells wv/v) Triton X-100 and were incubated at 4 °C overnight under gentle nutation. Purified ScBor1p was added to the destabilized liposomes at a 1:20 protein:lipid (w:w) ratio and incubated for 1 h at 4 °C. To extract detergent, SM2 Bio-beads  were added sequentially in 2 steps. First, 50 mg SM2 Bio-beads were added and incubated for 1 h at 4 °C, followed by the addition of another 50 mg of SM2 Bio-beads and another incubation for 1 h at 4 °C. The glutaraldehyde cross-linking assay was performed as described previously [w/v) sodium dodecyl sulfate (SDS) detergent .Purified ScBor1p was reconstituted into lipids by adapting a protocol using preformed vesicles permeabilized with Triton X-100  . 1-palmieviously , with cr2DIDS experiments, the protocol was identical. However, per L of media we used 1 g monosodium glutamate instead of 5 g ammonium sulfate for a nitrogen source. Additionally, inhibitors were prepared at 50 mM in dimethyl sulfoxide (DMSO), which permitted adding up to 300 μM inhibitors with only 0.6% DMSO present. Therefore, 0.6% DMSO was used in all other lesser inhibitor concentrations and control conditions.The genetic plating assay was performed as described previously . A yeastg, 300 μL of supernatant was prepared for curcumin addition per the previously reported protocol, with the data collected using a quartz cuvette that was washed twice with 91% isopropyl alcohol in between measurements. Standard curves were generated from standards containing 0, 0.625, 1.25, 2.5, and 5.0 mg/L of borate. To avoid the risk of borate entering the experiment via borosilicate glassware, no solutions in these experiments touched glass. 95% confidence intervals were generated for n = 7 biologically independent experiments.The spectrophotometric assay to quantify borate from cell lysates was adapted from a previously published protocol . Yeast c6, rabbit polyclonal primary antibody  was incubated at 4 °C overnight, and the HRP-conjugated goat anti-rabbit secondary antibody  was incubated at room temperature for one hour before exposure using chemiluminescent horseradish peroxidase substrate to image. Total protein loading controls were imaged using Bio-Rad stain-free gels.Protein overexpression protocols were adapted from those described above, but with the following distinctions: 50 mL yeast cultures were grown using strain BTSY1, and after 16 h induction by 2% galactose the cells were lysed by passing once through an Emulsiflex-B15 homogenizer  at 22,500 psi. Membranes were collected by differential centrifugation and resuspended in 20 mM Tris pH 7.4, 1 mM EDTA, 1 mM PMSF, 10% glycerol, and 300 mM NaCl. For Western blot analysis, 10 μg total protein was loaded per lane, and proteins were transferred to a PVDF membrane in a wet tank. The anti-HisAll ten transporters in the human SLC4 family are composed of an N-terminal cytoplasmic domain linked to a C-terminal membrane transport domain. A sequence alignment of ScBor1p with human SLC4A1 shows just over 24% sequence identity between their transporter domains . Fungal A. thaliana Bor1 and the yeast S. mikatae Bor1p (SmBor1p) in dimeric assemblies [S. cerevisiae [ScBor1p could be readily purified as described previously . When sosemblies ,4, and Ssemblies . We testrevisiae , and we revisiae . The PC A previous study on ScBor1p showed that PS and PE each shift ScBor1p to just under 50% dimer, while PC did not support dimerization . There aA. thaliana Bor4 transporter (AtBOR4) to SITS through genetic plating assays. We chose AtBOR4 both because the sensitivity of plant borate transporters to SITS is unknown and because a prior study showed that among all seven A. thaliana borate transporters, BOR4 shows the strongest growth phenotype against boric acid in bor1 deletion cells [2DIDS) shows borate transporter sensitivity, though H2DIDS also shows some toxicity in non-borate testing conditions. Therefore, the effect of H2DIDS on ScBor1p is less clear (One hallmark feature of human SLC4 transporters is the inhibition of their anion transport by stilbene disulfonate-derived inhibitors ,37. If Son cells . Our resss clear . A previPrevious studies in SLC4A1 show that the solute binding site contains a glutamate, E681 in human numbering, that is essential for function ,40,41. AHaving examined D347, the amino acid most established to be critical for transport, we next wanted to identify other proximal amino acids that might be important for the solute binding and transport mechanism of ScBor1p. We performed alanine scanning mutagenesis on amino acids that are conserved in borate transporters  and adjaMutations in human SLC4A1 are known to lead to several genetic disorders, including hereditary spherocytosis and hereditary stomatocytosis . Prior wWhen borate transporters were first discovered, the sequence similarity between them and human SLC4 transporters was noted immediately . More th+/OH− [Studies of the one SLC4 transporter that does not transport bicarbonate, SLC4A11, reveal additional connections between the SLC4 family and borate transport. When SLC4A11 was first characterized it was initially proposed to transport borate , but thi+/OH− ,50,51,52+/OH− . Further


With the advent of the Internet era, Chinese users tend to choose to express their opinions on social media platforms represented by Sina Weibo. The changes in people’s emotions toward cities from the microblogging texts can reflect the image of cities presented on mainstream social media, and thus target a good image of cities. In this paper, we collected microblog data containing “Shanghai” from 1 January 2019 to 1 September 2022 by Python technology, and we used three methods: Term Frequency-Inverse Document Frequency keyword statistics, Latent Dirichlet Allocation theme model construction, and sentiment analysis by Zhiwang Sentiment Dictionary. We also explore the impact of the COVID-19 epidemic on Shanghai’s urban image in the context of the “Shanghai Territorial Static Management”, an important public opinion topic during the COVID-19 epidemic. The results of the study show that the “Shanghai-wide static management” of COVID-19 epidemic has significantly reduced the public’s perception of Shanghai and negatively affected the city’s image. By analyzing the data results, we summarize the basic characteristics of Shanghai’s city image and provide strategies for communicating Shanghai’s city image in the post-epidemic era. City image is the public’s overall impression and evaluation of the city’s material elements such as economic resources, infrastructure, and other non-material elements such as history and culture. It not only reflects the city’s historical accumulation and development status, but also contains the prospect of the city’s future development potential. The perception, feeling, and opinion of the public on the city image are of great significance to the city management, city planning, city culture perception, and the development of tourism resources. At the same time, the city image also reacts to the residents’ living happiness. A good urban image of the city where people live can enhance residents’ sense of self-identity and reduce their psychological pressure in daily life, as well as play a positive role in maintaining residents’ mental health ,2,3.As the Internet enters the era of Web2.0, social media platforms represented by Facebook, Weibo, Zhihu, and Twitter have significantly broken through the limitations of traditional media in information production and dissemination with their distinctive characteristics of openness, timeliness, interactivity, and connectivity . AccordiCurrently, group discourse in social media is increasing, and Sina Weibo has come to be one of the necessary channels for the public to attain real-time data and discuss trending current affairs. As one of the social media systems, Sina Weibo can collect a large number of users’ most real thoughts. Especially, during the epidemic, the attributes of Weibo as a public dialogue platform grew to be significant, turning into the most essential platform for the public to acquire records about the epidemic and to exchange and discuss information. According to Weibo Data Center statistics, 37,000 government micro-blogs and 3000+ media micro-blogs launched 6,076,000 portions of authoritative records about the epidemic in 2020, with a total of 364.7 billion reads and initiated 30,000 stay-at-home announcements of the epidemic, with over three billion viewers [In the age of the digital network, people have changed from passive to professional consultation to active access to information through various Internet channels . As peopThe research object of this paper is the urban image of Shanghai and makes use of internet crawler technological knowledge to attain micro-blogs containing “Shanghai” from 1 January 2019 to 1 September 2022. Duplicate comments and noisy data were removed to prevent users from repeatedly posting a large number of the same comments and advertising messages that are not related to the topic. Term Frequency-Inverse Document Frequency keyword statistics and Latent Dirichlet Allocation topic modeling were performed on the processed tweets to interpret the keywords and topics displayed for Shanghai each year. This paper similarly quantifies the sentiment value of Shanghai as a town at each time point: the usage of sentiment evaluation is based entirely on the Zhiwang Sentiment Dictionary and analyzes its sentiment value trends from 1 January 2019 to 1 September 2022. Finally, the city image of Shanghai is derived, and the communication strategy of Shanghai city image after the unexpected event is proposed based on the analysis results. By improving the urban image of Shanghai, Shanghai residents can enhance their sense of self-identity.“Image” refers to an abstract feeling and perception, a perception of an area, or a combination of people’s opinions, judgments, and emotions ,9. LynchWith the development of modern network, some scholars have suggested that the construction of city image is a process of external communication, that is, the city image is composed of mass media, individual experiences and environmental factors . In addiCity image is not only a kind of social existence, but also a kind of social evaluation, which is subjective. The shaping of urban image is also a process of public perception and re-evaluation of the city ,24. StudPublic emergencies refer to natural disasters, accidents, public health incidents and social security incidents that occur suddenly and cause or may cause serious social harm and need to be dealt with by emergency measures. In recent years, scholars at home and abroad have launched research on information dissemination in public emergencies. Theja Bhavaraju et al. studied the changes of indicators such as the duration of attention and emotion of disaster events on Twitter ; Kumar eCOVID-19 spread primarily through respiratory droplets and contact, is a new infectious disease that is generally contagious to humans . On JanuThe spread of social and communication technologies online has led to the use of social media by many people and the timely participation of the public in emergency response ,31. MoreSentiment analysis uses text mining techniques to identify and extract information for project evaluation and monitoring to aid decision-making . LexiconThe main method currently used for sentiment mining is to use sentiment dictionaries, which match sentiment words to texts, aggregate sentiment words for scoring, and finally interpret the sentiment tendency of texts. The sentiment evaluation approach used in this paper is the Zhiwang sentiment dictionary, which affords a complete set of 12 files, divided into English and Chinese. Among them, the Chinese sentiment dictionary consists of evaluation, sentiment, assertion, and degree (positive and negative) of sentiment texts. In this paper, the evaluation and emotion words are integrated and used as emotion dictionaries. The degree words contained in the degree word list are divided into six emotion degree dictionaries according to the rank distinction: highest–very–more–slightly–insufficiently–too much.The TF-IDF method is divided into two parts: word frequency (TF) and inverse document frequency (IDF). TF identifies the frequency of words. The calculation method is shown as Formula (1):In the formula, the place i is a one-of-a-kind word, j denotes a diverse tweet, and IDF is used to identify the importance of phrases. It can increase the importance of rare phrases and reduce the importance of common phrases, as shown in Formula (2):Finally, multiply the result value of Formula (1) with that of Formula (2) to get the value of TF-IDF, as shown in Formula (3). This means that the larger the TF-IDF value, the more important the phrase:Hot words in the network can be extracted directly by word frequency statistics but cannot identify the semantic correlation behind the phrases. Different phrases may have the same thematic context, such as “the thunder is loud” and “I do not have an umbrella”, each of which reflects the subject matter of “rainy weather”. However, if solely the phrase frequency is counted, it is difficult to get the real theme of the text, because each phrase is not necessarily identified as a high-frequency phrase.LDA is a model that considers semantic associations between texts. LDA is a three-level Bayesian probabilistic graphical mannequin with three granularities: document, topic, and phrase . The LDAIn order to deal with public sentiment in the context of the epidemic and to grasp the problems brought on by the image of the city, the LDA model can assist in the procedure of text-based evaluation through practicable theme identification and person-clustering. The key to using the LDA is to determine the most appropriate broad topic category. The effectiveness of subject matter origin in the LDA is immediately associated with the variety of attainable themes. Coherence or perplexity ,52,53,54In general, the feature lgorithm , FormulaTo sum up, this paper selects the evaluation methods of big coherence and small coherence to obtain the number of themes and complete the construction of the LDA.Emotion analysis extracts the attitude tendency of text, which belongs to the sub-field of natural language processing. We used the informed dictionary for sentiment analysis and achieved a wide range of accurate sounding phrases and complex language rules to generate sentiment values. After identifying sentiment words, the sentiment intensity of phrases is measured, assigning lower scores to degree words that are further away from the sentiment word primarily based on adverbs, negation, punctuation, and conjunctions.The number of sentiment phrases in the passage is decided by means of including 1 with the variety of positive phrases and 1 with the variety of negative phrases, and in the process of counting the variety of sentiment phrases, it is additionally vital to decide whether or not there is a degree adverb earlier than the sentiment word, and if so, it is imperative to provide extraordinary weights in accordance to the kind of degree adverb and multiply it by means of the range of sentiment words. If a sentence ends with an exclamation point (!) or a question mark (?), such punctuation marks often indicate the strengthening of emotional reactions, so a certain number of emotional words needs to be increased. Then, the sentiment value (positive words–negative words) of the whole paragraph is calculated, and the sentiment tendency of the paragraph is obtained. Finally, the sentiment value of every paragraph is counted and summed to obtain the complete sentiment value of the textual content. The overall flow block diagram is as follows :We used micro-blogging data sources for our research: blog posts containing “Shanghai” from 1 January 2019 to 1 September 2022 were collected pro-grammatically in Python. To obtain a clearer picture of the adjustments in the data, we divided the data into four quarters each year (three months make up a quarter) and collected blog posts with the words “Shanghai” from 1 January 2019 to 1 September 2022. The whole quantity of weblog posts with the phrase “Shanghai” in 11 groups is 100,438; for the purpose of analysis, we will be in the first quarter of 2020 to 2022 in the third quarter respectively. Following are the numbers for A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, and C3 :(1)This study uses web crawler technology to collect all micro-blogs containing “Shanghai” on micro-blogging platforms from 1 January 2019 to 1 September 2022. First, we cleaned the data: the original micro-blog data contained a lot of confusing codes, characters, links and other useless contents. This data needs to be cleaned to obtain a more standardized dataset. The meaningless symbols such as “@, #, , ”, URL links, and all numbers and foreign languages  were filtered out to reduce the data noise. Finally, “Shanghai” was excluded because all blog posts contain the word “Shanghai”, which is not practical for the follow-up study.(2)Splitting and deactivating words was then completed. Micro-blog text is composed of individual words. In this paper, the corpus is divided and deactivated with the help of a pkuseg Chinese word separation toolkit, a new phrase separation kit which greatly improves the accuracy of phrase separation for exclusive domain information. According to the results, pkuseg reduced the word separation error rate by 79.33% and 63.67% on the example datasets (MSRA and CTB8), respectively . After gWe first use the TF-IDF method to calculate the TF-IDF value, and then we sort the keywords. The occurrence times of keywords were obtained by word frequency statistics.The novel coronavirus outbreak of 2020 swept everywhere, generating topics of discussion around the world. “Police stations” and “police” were in the fourth and eleventh places respectively, indicating that in addition to medical personnel, police were also involved in handling the epidemic in the face of the outbreak. Positive words such as “support”, “cheer”, “hope”, and “peace” also appear, expressing people’s support for overcoming the epidemic. This indicates that the public sentiment in COVID-19 period was generally positive. In addition, the word “program” appears in the 18th position. In January and March, during the Chinese Spring Festival, the CCTV Spring Festival Gala 2020 added a special program on the fight against the epidemic, focusing on the medical workers and people who were fighting on the front line of the epidemic, conveying the strong confidence and determination of the people. The program was widely praised, and the ratings of the Spring Festival Gala increased significantly compared with previous years.From the keyword ranking in the second quarter of 2020 , “testinIn the third quarter of 2020 , the epiIn the fourth quarter, “happy” rose to the first place, and the adjectives are still mainly positive, indicating that the image of Shanghai has been improved. The fourth quarter coincided with the handover of the old and new years, and the keywords “New Year”, “New Year’s Eve”, and “fireworks” were added, while “expectation” and “cheer” were added as well. The words “expectation”, “cheer”, “hope” and “hard work”, which express good expectations for the New Year, remained at the top of the keyword rankings. In addition, “Disney” also became a new word in the top 20 keywords in the fourth quarter, and Shanghai, as the only city in China with Disneyland, will also become a topic of interest. Words like “epidemic”, “hospital”, “mask” and other words related to COVID-19 epidemic no longer appear in the top 20 keywords.Among the top 20 keywords in the first quarter of 2021 , “Legal”In the third quarter of 2021 , “house”In the first quarter of 2022 , althougIn the third quarter , the epiIn this article, we counted the top 20 keywords in Weibo posts about Shanghai from January 2020 to September 2022. Positive words such as “happy”, “good”, and “good-looking” appear more often in these three years. The number of positive words in the top 20 declined significantly during the period when the epidemic first broke out in January–June 2021 and during the sudden and serious epidemic in Shanghai in January–June 2022, with “epidemic,” and “virus” appearing as keywords. The number of epidemic-related words such as “nucleic acid” and “hospital” has increased, indicating that Shanghai’s image will be negatively affected in 2022 due to the large-scale epidemic closure event.The number of topics is determined by two metrics, perplexity and consistency. In practical applications, adjusting the number of topics only according to perplexity may result in topic extraction results that cannot be interpreted by humans. Therefore, in this paper, we typically refer to the consistency rating to decide the wide variety of topics. In the results of the first quarter of 2020 , Topic1 In the results for the second quarter of 2020 , Topic1 In the results for the third quarter of 2020 , Topic1 In the results of the fourth quarter of 2020 , Topic1 In the results of the first quarter of 2021 , Topic1 In the results of the second quarter of 2021 , Topic1 In the Q3 2021 results , Topic1 In the results for the fourth quarter of 2021 , Topic1 In the results for the first quarter of 2022 , Topic1 Since April 4, Shanghai has entered into a situation of “territory-wide static management”. In the results for the second quarter of 2022 , Topic1 By the third quarter of 2022, the epidemic situation in Shanghai gradually improved, people started to resume work and production, and their lives returned to normal. In the results of the third quarter of 2022 , Topic1 Keywords in statistics, such as “cute”, “happy”, “good”, “happy”, “good-looking”, “healthy”, etc., assist us in recognizing people’s emotional perception of Shanghai, because these adjectives express mostly positive emotional tendencies. In this paper, we also quantified the emotional values of the town of Shanghai at a range of time points by using the Knowing Sentiment Analysis method . Figure Compared to an average of 11 quarters, the sentiment values of A1, A2, B1, C1, C2, and C3 are below the mean value, and the sentiment values of C2 and C3 are under 0, displaying a negative sentiment tendency. The sentiment values of A4, B2, and B4 are slightly higher than the average sentiment values and are relatively stable.Based on the data of keywords, it can be seen that there are many factors affecting public sentiment. For example, major festivals will also affect the public’s attitude toward speech on Sina Weibo. Therefore, we did a cross-sectional analysis of public sentiment in the same quarter over three years of the epidemic. First of all, A2’s emotional value was 0.006, and A3’s emotional value was 0.068, which were the two quarters with the lowest and highest emotional value in 2020, respectively. From the perspective of the epidemic development at that time, A2 was the peak of the epidemic in China. A3 was significantly improved, and life returned to normal, so the emotional value increased. The emotional value of B2 and B3 was 0.024 and 0.059, respectively, showing an upward trend with the improvement of the epidemic. However, the emotional values of C2 and C3 were −0.006 and −0.014, respectively, which showed a downward trend, corresponding to the epidemic situation in Shanghai at that time from local containment to large-scale containment. It was concluded that this was not a normal epidemic situation. Secondly, A3 and B3 are the peak emotional values in 2020 and 2021, respectively, while in the same quarter of 2022 (C3), they are the lowest emotional values in the past three years, indicating that this is not a normal epidemic situation, but the result of the outbreak in Shanghai. Thirdly, in 2020 and 2021, the public’s emotional value was always positive until the severe outbreak in Shanghai , when the public’s emotional value fell to negative value, which also means there was an impact of the outbreak on the public, so that the public’s perception of the image of Shanghai will be affected.First of all, Shanghai is a city with active economic development. It is located at the junction of Jiangsu and Zhejiang provinces, the mouth of the Yangtze River, one of the water and land transportation hubs in China, the starting and ending points of the Beijing-Shanghai and Shanghai-Hangzhou railroads, and an important aviation center and one of the three major international airports in China. Shanghai’s unique geographical advantages have created prosperity in shipping and trade, and its economic development has also received widespread attention, especially during the epidemic. The massive closure and shutdown of production caused serious losses to the offline real economy, with rising house prices and decreasing income, which brought great economic pressure to the public, and the keywords and LDA models repeatedly showed “house prices “, “economy”, “deposit”, “wage”, “price”, “consumption”, and so on. This shows that micro-blog users cannot discuss Shanghai without mentioning economic issues.Second, Shanghai is closely connected with other cities at home and abroad. Based on Shanghai’s superior geographical location, its access to other cities is very convenient, and Shanghai is an important port for China’s foreign exchanges. “Nanjing”, “Chengdu”, “Guangzhou”, “Beijing”, and other city terms appear in high frequency words many times. Words such as “America”, “global”, and “world” appear in the keywords and LDA theme models, indicating that people travel between these cities and Shanghai with high frequency.Thirdly, Shanghai is an important source of fashion culture and fashion industry in China. Shanghai not only has a complete fashion industry chain, but also is an important market for Chinese fashion consumers. “Shanghai International Fashion & Apparel Expo”, “Shanghai International Fashion Culture Festival”, and other large-scale expositions, as well as Shanghai fashion landmarks such as Tianzifang, 1933 Old Square, M50 and SVA Crossing complement each other, forming a closed loop of design, production, dissemination, and consumption. The words “fashion”, “design”, “exhibition”, “clothes”, “embroidery”, and other words became key words.Fourth, Shanghai presents an image of openness, innovation, and tolerance. Shanghai is home to a young and energetic community, which allows new and interesting behavioral activities to flourish here. On the one hand, online activities such as “live streaming”, “likes”, and “videos” became key words as people were isolated at home due to the epidemic control. On the other hand, during the stable period of the epidemic, offline activities such as “hitting”, “wearing”, “photo”, “movie “, “movie”, “screening”, and other activities appeared in Weibo many times. This shows that Shanghai’s attitude toward innovative activities is more accepting and inclusive.Finally, the analysis revealed that the image of the city is vulnerable to the impact of unexpected events. Starting from the sudden outbreak of the COVID-19 epidemic in 2020, people’s sentiment values have significantly decreased whenever the epidemic is serious. The sudden and serious epidemic in Shanghai in the first half of the year caused people’s sentiment perception of Shanghai to reach negative values. The words “epidemic”, “nucleic acid”, “supplies”, “quarantine”, “sealing”, and “city closure” indicate the difficult living conditions of Shanghai people at the moment of the epidemic, while the words “hard-earned money”, “wages”, and “prices”, and “blood money” reflect the influence of the epidemic on Shanghai’s economy, and the words “rumor”, “rumors”, and “court” reflect the impact of on-line public opinion and legal issues on Shanghai’s urban image. First of all, among the adjectives in the keywords, words such as “beautiful” and “happy”, which are always associated with urban tourism, are often associated with positive content, making people have a positive feeling about Shanghai. Therefore, in the post-epidemic era, Shanghai can make use of existing resources (such as Disney) combined with Shanghai’s local culture (such as red culture) to promote the city image and improve the public’s attitude toward Shanghai through tourism resources. It is worth noting that holding major national events in Shanghai is conducive to shaping the image of Shanghai. Themed activities such as internationally renowned exhibitions, fashion events and international fashion forums can be relied on to combine Shanghai’s unique cultural temperament with multiple fashion elements. These endeavors can cultivate a city’s intellectual property with lasting charm and influence.Second, we should focus on improving the image of Shanghai in terms of culture, entertainment, and appearance. In order to improve the public’s negative impression of Shanghai caused by the outbreak of the epidemic, it is necessary to re-explore the value of Shanghai culture, symbolize the representative elements, and strengthen the effect of Shanghai city brand-building from the perspective of visual aesthetics and visual perception. For example, the concepts and symbols of Shanghai time-honored fashion brands, fashion landmarks, and Shanghai style cheongsam culture can be story-shaped and visualized in the communication process to enhance their folk and brand attributes, so as to identify with Shanghai cultural values. From the results of keywords, statistics and LDA thematic model, it can be seen that these rich and colorful cultural resources are far from being fully explored and displayed, and there are few relevant discussions. Chinese media can create sub-accounts with different themes according to audience interests, make full use of pictures and videos to display more intuitive content, tap the photographable resources of Shanghai culture, and spread the image of Shanghai through digital media, so as to improve the public’s emotional perception of Shanghai.Thirdly, keyword statistics show that the public’s attention to Shanghai occurs mostly at the abstract level , whilst ignoring its special sense as a physical space. We should not only pay attention to the virtual image presented on the network, but also improve the city’s physical image construction. Continuing to enhance and create humanistic landmarks in the town, enriching residents’ cultural and recreational life, improving transportation, roads, and ecological environment, and gaining immersive experiences through visible and auditory sensory perceptions can assist humans in structuring a deep and complex image of the metropolis .Finally, attention should be paid to the identification of network opinion leaders and public opinion guidance. In the case of an emergency epidemic, the role of network opinion leaders should be paid attention to. The LDA model proposed in this paper can not only show the objective factual information of Internet users about the development of the epidemic, but also the subjective comments and feelings of Internet users. Especially in the period of epidemic control, the demand of network users for information related to the COVID-19 epidemic has increased rapidly with the passage of time. Since some topics can reflect topics, events, sub-topics, or even derivative topics, the determination of community opinion leaders for each part plays an important role in guiding public opinion toward and conducting more effective public opinion supervision during the epidemic. Therefore, the media, the government, and other institutions can try their best to meet the information topic needs of these opinion fields, so that opinion leaders can maximize their positive energy guidance and public opinion channeling in the network topic community.Meanwhile, during the period of public opinion outbreak and predominant discussion, media, government, and relevant public opinion supervision departments can recommend diversified thematic information to opinion leaders through appropriate topic selection, and introduce other topics as important as the topic information of the COVID-19 epidemic. Official media and relevant institutions should actively cooperate with non-official media by highlighting a variety of topics to influence the focus of public attention and awareness of the environment and engaging in continuous data tracking analysis. We must avoid network users too concentrated on a class of epidemic information, resulting in information overload, information burnout and negative impact, triggering secondary public opinion events .This paper collects micro-blogs about “Shanghai” on Weibo from January 2020 to September 2022 through net crawler technology, and analyzes the introduced town image of Shanghai via TF-IDF key-word statistics, LDA subject mining, and sentiment evaluation of Zhiwang. Based on the analysis results, this paper proposes communication strategies to improve the public’s negative perception of the city and promote the city image after public emergencies. According to the research and analysis, the image of Shanghai in micro-blogs shows the following characteristics: first, Shanghai is a city with active economic development. Second, Shanghai has more connections with other cities at home and abroad. Third, Shanghai’s fashion culture and fashion industry are relatively developed. Fourth, Shanghai presents an open, innovative, and inclusive image. Fifth, the public’s perception of Shanghai is susceptible to emergencies.Based on the analysis of the city image and characteristics of Shanghai, corresponding strategies are further proposed. First, after the epidemic situation is alleviated, the city tourism should be promoted by combining the existing tourism resources with the local culture of Shanghai. Second, we should deeply explore the value of Shanghai culture, strengthen the effect of Shanghai brand-building, and improve the public’s negative impression of Shanghai due to the outbreak of COVID-19. Thirdly, attached importance to the identification of online opinion leaders and the guidance of public opinion is needed. In the post-epidemic era, the city image of Shanghai will be guided to the direction of positive energy while channeling public opinion.Our research expands on the research of urban image-related fields, with major contributions in the following three aspects. First, in the aspect of methodology, this paper further mined the data about Shanghai city image in Weibo and used TF-IDF method to extract keywords. Thematic analysis is conducted by LDA model and user sentiment is analyzed by Zhiwang sentiment dictionary. The aggregate of the three strategies provides a complete evaluation of micro-blog users’ perceptions of Shanghai city image and forms a text mining framework for social media platforms used in city image investigation. Second, on the theoretical side, the study of unexpected public events and city image is extended, emphasizing that unexpected public events can have a negative impact on the city image; therefore, a communication strategy for Shanghai’s city image is proposed. Third, from the perspective of practical application, Shanghai is in the period of urban construction and recovery after the epidemic. This study provides powerful data support and communication strategies for Shanghai to rebuild a good city image, and thus it helps to improve the self-identity of Shanghai citizens ,2,3.However, it is also important to note that the current research has certain limitations. First of all, the groups covered in this article are limited. Weibo users do not represent the total population in Shanghai. Future studies need to improve data integrity. Nearly 80% of Sina Weibo’s user base is made up of people under 30, and more than half of its users have a bachelor’s degree or above. As a result, our data may miss some populations. In the future, we will analyze more social media data and improve user data. Second, the findings in this paper, broadly speaking, make use of textual content data, and the unique record kinds can be similarly improved in the future to consist of images, videos, and audios. In addition, more than one fact can be studied from a couple of perspectives. Third, the scope of this paper is restricted to digital participation. This paper excludes citizens’ offline discussions about Shanghai from its research. Future research has to focus on how offline participation can better help policymakers’ decisions. Moreover, mining data from social media and e-participation structures can facilitate offline engagement activities. This ecosystem view of offline and on-line engagement to enhance the image of cities deserves similar exploration. Fourth, further analysis of the available negative comments has not been conducted. Subsequent research work can analyze negative remark content material identification, negative remark content material clustering, and negative remark conduct formation, and the effects can supply assistance to authorities’ departments and related organizations to develop city image communication strategies.