Escherichia coli sequence type 131 (ST131) is a pandemic, multidrug-resistant extraintestinal pathogen. The multiple distinctive ST131 subclones differ for rfb and fliC alleles (O and H antigens), fimH allele (type-1 fimbriae adhesin), resistance phenotype and genotype, clinical correlates, and host predilection. Current PCR assays for detecting ST131 and its main subclones offer limited sub-ST characterization. Here we combined 22 novel and 14 published primers for a multiplex PCR assay to detect and extensively characterize ST131 isolates. The primers target mdh36, gyrB47, trpA72, sbmA, plsB, nupC, rmuC, kefC, ybbW, the O16 and O25b rfb variants, five fimH alleles , two fliC alleles (H4 and H5), a (subclone-specific) fluoroquinolone resistance-associated parC allele, and a (subclone-specific) prophage marker. The resulting amplicons resolve 15 molecular subsets within ST131, including 3 within clade A (H41 subclone), 5 within clade B (H22 subclone), and 7 within clade C (H30 subclone), which includes subclones C0 (H30S: 2 subsets), C1 and C1-M27 (H30R1: 2 subsets), and C2 (H30Rx: 3 subsets). Validation in three laboratories showed that this assay provides a rapid, accurate, and portable method for rapidly detecting and characterizing E. coli ST131 and its key subsets. Additionally, for users with whole genome sequencing (WGS) capability, we developed a command-line executable called ST131Typer, an in silico version of the extended multiplex PCR assay. Its accuracy was 87.8%, with most issues due to incomplete or fragmented input genome assemblies. These two novel assays should facilitate detailed ST131 subtyping using either endpoint PCR or WGS.IMPORTANCE These novel assays provide greater subclonal resolution and characterization of E. coli ST131 isolates than do the available comparable PCR assays, plus offer a novel sequence-based alternative to PCR. They may prove useful for molecular epidemiological studies, surveillance, and, potentially, clinical management. Escherichia coli sequence type 131 (ST131), which arguably is the most epidemiologically successful multidrug-resistant E. coli lineage ever identified, emerged dramatically beginning in approximately 2000 to become a pandemic pathogen  typically exhibit the O25b somatic antigen and the H4 flagellar antigen.ST131 exhibits a complex clonal structure, as elucidated by phylogenetic analyses based on whole genome sequencing (WGS) data , 13 Fig. The mose fimH30 , 5. StraH30R in turn has important subcomponents, including subclones H30R1 (clade C1) and H30Rx (clade C2)  strains carry blaCTX-M-15, the distinctive characteristic that led to ST131's initial discovery   Fig. 1)H30R in t-M-14 14–. By contiscovery .H30R, H30 also has a basal, fluoroquinolone-susceptible H30S component (clade C0), which may be an evolutionary precursor to the pandemic H30R subclone  alleles (H41 subclone (clade A) is associated with trimethoprim-sulfamethoxazole resistance, younger patients, fimH41, and the O16 and H5 antigens (H22 subclone (clade B), which typically is less extensively antimicrobial-resistant than the other ST131 subclones, is associated with food animals, including poultry and swine, where it can acquire antimicrobial resistance that subsequently transmits to humans .In the J. Johnson Laboratory the PCR assay correctly identified as non-ST131 all 146 negative control isolates, i.e., for them it did not yield any of the three possible ST131-specific amplicons: When the new assay was applied to the Price collection in the J. Johnson Laboratory, in comparison with the published WGS phylogeny  it classified correctly by subclone all 105 ST131 strains . Similarly, when it was applied to the Gordon collection in the D. Gordon laboratory, in comparison with an unpublished WGS phylogeny  it classified correctly by subclone all 73 ST131 strains .fimH30 allele, the H30Rx clade, and the O25b and O16 rfb variants. It also yielded 100% accuracy  for detecting the parC E84V mutation, as identified by WGS , among 5 ST131 isolates with and 46 without this parC allele.In the J. Johnson Laboratory, the assay yielded 100% concordance with concurrently performed single or dual-target PCR assays for detecting the In the J. Johnson Laboratory, after optimization the assay's performance was consistent across three different thermal cyclers: Eppendorf Mastercycler x50, Bio-Rad MyCycler, and Bio-Rad T1000. Notably, however, with the Bio-Rad T1000 a 1°C higher annealing temperature was required with all pools to avoid nonspecific amplification.n = 179 isolates), the new assay identified 8 unique PCR profiles with just primer pool 1, whereas the addition of primer pools 2 and 3, and the 9-isolate Miscellaneous collection, increased this number to 15 (H30Rx:O-nontypeable (isolate JJ2449: Miscellaneous collection only), B0:fimH22 (isolate JJ1897: Price collection only), B1:fimH22-negative ; H35Rx/C2 (isolates JJ2643 and U004: Price collection only); A:O25b:H4 , A:O25b:H5 (isolate M670745: Gordon collection only), and C0:parC E84V (isolate BS448: Gordon collection only).Within the combined Price and Gordon collections , jointly identifying as ST131 the same 20 isolates, of which 5 were O16/A  and 15 were O25b . This collection's 20 ST131 isolates exhibited the 5 most common ST131-associated PCR patterns encountered in the Price and Gordon collections  the novel assay and (ii) established single or dual-target PCR assays. The assays were compared for their results regarding ST131 status, lections .rfb O16 and the trpA clade A-specific amplicon  and confirmed the 3 H30Rx/C2 isolates based on clade-specific SNPs in both sbmA and ybbW. It also uniquely assigned one of the 14 H30/C isolates to the (recently described) C1-M27 clade, assigned the single non-H30 O25b isolate to the B1 subclade, showed that this isolate had the fimH22 allele, identified all O16 isolates as having fliC H5 and fimH41, and identified all O25 isolates as having fliC H4.Additionally, in this testing of fresh clinical isolates the new multiplex assay augmented the conventional assays in several ways. Specifically, it confirmed the 5 O16/A ST131 isolates by both traditional fimH22 primer and one ybbW primer and (ii) more explicit instructions for gel interpretation. These modifications yielded 100% accurate assay results, without a need to adjust annealing temperatures.For a formal assessment of the new assay's portability across laboratories it underwent independent, blinded testing in the T. Johnson Laboratory, which is geographically removed from the originating (J. Johnson) laboratory. After an initial optimization phase involving known positive and negative controls, plus open between-laboratory communication regarding technical issues, blinded validation testing was done using a panel of 18 coded test isolates  . The blinded testing correctly identified the isolates' ST131 status, but initially yielded discrepancies regarding their extended PCR profiles. Assay modifications were implemented to address these discrepancies, including (i) length adjustments in one in vitro extended multiplex PCR assay for only 142  of the 173 ST131 strains.The overall accuracy of the (WGS-based) ST131Typer as a surrogate for the PCR assay, based on the 255 isolates tested, was 87.8% . However, performance varied greatly by endpoint. Specifically, ST131Typer correctly identified all 78 negative control isolates as non-ST131  and correctly classified 171 of the 173 ST131 strains by subclade . By contrast, ST131Typer yielded the same PCR profile as the rfb O25b variant (16 strains), fliC H4 (7 strains), kefC (4 strains), and fimH22, fimH30, fimH40, and prophage marker (1 strain each).Analysis of the 31 total instances where ST131Typer results did not match the PCR profile showed that 19% (6/31) were due to ST131Typer profile misclassifications and 81% (25/31) to unknown profile classifications. Supplemental material 5 lists the strains with a discrepancy, their placement in the phylogeny, their associated characteristics, and the specific discrepancies.  All 31 ST131Typer errors  were caused by inability to identify a single required target sequence, specifically the rfb O25b targets (15/16), and all four missing kefC targets, were highly fragmented and incomplete genome assemblies, with the forward and reverse primer sequences on different contigs, or one or both not detected. Indeed, N50 values  were considerably lower for assemblies with incorrect, versus correct, PCR profile classifications . When use as a supplemental typing method CGE’s SerotypeFinder identified the missing rfb O25b variant in 15 of the 16 strains where ST131Typer missed it. However, match identities were <100%, and high-scoring BLAST alignments typically shorter than the reference rfb O25b sequence.Potentially explaining nearly all missing fliC H4 and fimH target sequences, where the primer regions frequently included one or more SNPs. As for the rfb O25b target, SerotypeFinder identified the fliC H4 variant in all these samples, but with match identities <100% and high-scoring BLAST alignments shorter than the reference fliC H4 sequence. Likewise, for the three samples with a missing fimH allele per ST131Typer, CGE’s FimTyper identified fimH alleles that represented minor (1–2 nucleotide) variants of the alleles detected by PCR.Additional instances of mismatch between ST131Typer and the PCR assay were potentially from sequence variation in the forward or reverse primer regions. This was particularly evident with the missing in silico analog of it—for identifying and characterizing E. coli ST131 isolates. The PCR assay demonstrated an excellent ability to distinguish E. coli ST131 from other E. coli, to classify ST131 isolates by subclonal type , and to characterize the isolates for key accessory traits, including relevant fimH and fliC alleles, the O25b versus O16 rfb variants, and a fluoroquinolone resistance-associated parC SNP. The assay also was portable across laboratories and performed well with fresh clinical isolates. Thus, this novel PCR assay should prove useful for molecular epidemiological studies and, potentially, clinical diagnostics. The in silico version of the assay, ST131Typer, accurately distinguished E. coli ST131 from other E. coli, and classified ST131 isolates accurately into subclades. However, its ability to replicate the PCR assay's full profile patterns was impeded by incomplete genome assemblies and minor sequence variation.In this study, we developed and extensively validated a novel 3-pool, multiplex PCR assay—and a WGS-based, per se, key ST131 subsets, and various relevant accessory traits  showed that this variation in accessory traits within clade A was phylogenetically distributed, with the “atypical” variants occupying a basal position. This suggested that the O25b rfb allele and fliC H4 were possibly ancestral within clade A and, hence, perhaps within ST131 as a whole.The present multiplex assay, with its extensive range of targets, yielded several novel findings. Specifically, within clade A it identified uncharacteristic O25b-associated variants, in addition to the expected O16-associated variants, and separated these according to fimH35 from those with (characteristic) fimH30. Likewise, within subclades B0 and B1 it differentiated isolates with (uncharacteristic) fimH27 from those with (characteristic) fimH22, or neither of these. It also identified within clade C0 an isolate (BS448) that uniquely exhibited the distinctive fluoroquinolone resistance-associated parC SNP (a251t = E84V) that typifies clades C1 and C2, that is, H30R  and parC (g239t = S80I)  by conventional broad-range O serotyping. Whether this isolate's distinctive PCR profile represents a new O-negative H30Rx subtype or is unique to this particular isolate remains to be determined.Additionally, within clade C2 the new assay differentiated isolates with (uncharacteristic) E. coli isolates can be screened initially using pool 1, which in addition to detecting ST131 per se can resolve 8 different subclonal profiles. Isolates so identified as ST131 can then be further characterized using pools 2 and 3, which offer refined subclone/confirmatory discrimination and can identify additional accessory traits, including H30R's hallmark fluoroquinolone resistance-associated parC SNP , the individual pools can be used separately, including in a hierarchical manner. For example, generic When validated using an extensive panel of positive and negative control strains, the assay yielded 100% accuracy in comparison with external reference standards, including WGS analyses or individual PCR results. Additionally, it was portable across laboratories. Notably, however, in each new laboratory some optimization was needed. Thus, when the assay is established in additional laboratories further optimization may be needed to ensure the expected performance with relevant control strains.parC, it lacks resistance gene targets, including the various ST131-associated blaCTX-M variants and carbapenemase-encoding genes, for which supplemental assays would be needed. Second, its amplicon profiles are complex, potentially posing interpretive challenges. Adherence to detailed instructions and use of the provided interactive data entry spreadsheet can help. Third, the particular sublineages and associated traits included in the assay represent only a fraction of the ever-expanding number of possible targets and were selected somewhat arbitrarily. For example, the assay addresses minimally the recently appreciated clonal diversity within the H22/clade B lineage , H22 (clade B), and H30 (clade C), and components thereof. These components were, within the H22 subclone, subclade B0 ; within the H30 subclone, subclones H30S (C0), H30R1 (C1), and H30Rx (C2); and within subclone H30R1, the (blaCTX-M-27-associated) C1-M27 subclone. The accessory traits of interest included diverse ST131-associated variants of four key genes: fimH (type-1 fimbriae adhesin) (fliC (flagellar H antigen), rfb (O antigen), and parC (topoisomerase), specifically the (H30R1 and H30Rx)-associated E84V parC variant that is associated with higher fluoroquinolone MICs than those of other fluoroquinolone-resistant strains  and accessory traits . The seven phylogenetic subsets of interest  included the three major ST131 subdivisions, i.e., subclones  strains .in vitro performance against relevant positive and negative control strains, both as individual primer pairs and in multiplex pools. Amplicon specificity was assessed by comparing the observed product size with the expected product size for the particular target, not by sequencing. Primer sensitivity and specificity were assessed based on ability to amplify a product of the expected size with positive control strains but not negative control strains.Relevant published primers were used as-is or were modified as needed for optimized performance and compatibility with other primers. Novel primers were designed based on published target sequences and were optimized – for sensitivity, specificity, amplicon size, and compatibility with other primers – based on mdh36 and gyrB47 (ST131-specific), the O16 and O25b rfb variants, 5 fimH alleles, 2 fliC alleles, the fluoroquinolone resistance (FQR)-determining region of parC and selected other clade-specific genes or alleles thereof. The subclade markers (associated target clade/subclade) include trpA72 (clade A), plsB (clade B1), nupC , kefC , rmuC (subclade C1), ybbW and sbmA (subclade C2), and a prophage marker (C1-M27 subclade).The final assay comprised 36 total primers: 22 were novel and 14 were previously published . These pper se; its subclades H41-O16 (clade A), H30Rx (clade C2), and C1-M27; the fimH30 allele; and the O16 and O25b rfb variants. Pool 2 included primers specific for subclades H22 (clade B), B1, H30 (clade C), H30R1 (clade C1), and H30Rx (clade C2: using a different target than pool 1), plus the E84V parC mutation. Pool 3 included primers specific for the H4 and H5 fliC alleles and the fimH22, fimH35, and fimH41 allele complexes, with allele complex defined here as the type allele plus minor variants thereof.The primers were split into three multiplex reaction pools based on band size and annealing temperature . Pool 1 Taq polymerase was used  with the supplied buffer, adjusted to contain either 4 mM MgCl2 (pools 1 and 2) or 2 mM MgCl2 (pool 3.) The cycle routines were as follows: pool 1, 95°C 2 min; 30 cycles each , 72°C 2 min; pool 2, 95°C 2 min; 34 cycles each , 72°C 2 min; and pool 3, 95°C 2 min; 38 cycles each , 72°C 2 min. Reactions were then held at 12°C. Amplicon bands were resolved by 2% agarose gel electrophoresis and ethidium bromide staining.The three primer pools were used in separate PCRs and were tested on different thermal cyclers. A hot-start Seven strain sets  were used for assay derivation, validation, and portability assessment . The indE. coli isolates, including 138 from two published collections with available WGS data and eight supplemental isolates (assigned to the Miscellaneous collection) representing additional STs not found in these two collections (E. coli Reference (ECOR) collection (n = 72) (n = 66 isolates)    and a sesolates) , 35. The, and G) , 37, eacmH types , giving mH types .The positive controls were 178 diverse genome-sequenced ST131 isolates . These in = 105) was used in the first WGS-based phylogenetic analysis of ST131 , the other on a (trait-agnostic) alpha-numeric system. According to the latter taxonomy, the Price collection is distributed as follows (no. isolates per clade or subclade): 7 A, 3 B0, 32 B1, 4 C0, 32 C1, 1 C1-M27, and 26 C2 .The Price collection , which represents diverse sources, was distributed as follows in an unpublished core genome, SNP-based phylogeny : 15 A, 1 B0, 24 B1, 3 C0, 11 C1-non-M27, 7 C1-M27, and 12 C2 . For this phylogeny, the SNP data were derived using PARSNP (https://github.com/marbl/parsnp), with recombination detection/filtration, after which RAxML and PhyML trees were generated using TOPALi v.2 . Sequence-based results for this collection also were available for predicted O:H serotype, fimH allele, and fluoroquinolone resistance-associated gyrA/parC mutations. These isolates underwent PCR-based testing in the Gordon laboratory, using the present novel assay according to protocols provided by the (source) J. Johnson Laboratory.The Gordon collection (H22 and H30 subclones (clades B and C) or of the H30S and H30R subclones (C0 and C1/C2), subclone/clade assignment was resolved based on presence/absence of subclone/clade-specific genomic markers, as detected by WGS. Specifically, membership in the H30S subclone (clade C0) was defined by placement in the phylogeny within or immediately basal to the H30 subclone (clade C), but basal to the H30R1 and H30Rx subclones (clades C1 and C2), plus (according to WGS) containing the inclusive H30 subclone (clade C) marker kefC but lacking the markers for subclones H22 (clade B: nupC), H30R1 (C1: rmuC), and H30Rx (C2: ybbW and sbmA)  were based primarily on isolates' position within the corresponding core genome SNP-based phylogeny, for which subclone/clade identity was apparent from (i) comparisons with published ST131 phylograms and (ii) the consensus characteristics of a given subclone or clade's constituent isolates. For the several strains that were placed ambiguously in the phylograms, i.e., at the junction of the nd sbmA) .E. coli isolates were retrieved over a 3-month span from the Minneapolis VA Medical Center clinical microbiology laboratory and tested in parallel using both the novel assay and established single-plex PCR assays for the detection of ST131, the O25b and O16 rfb variants, the fimH30 allele, and the H30Rx/C2 subclone , along with the recommended assay protocol. In the T. Johnson Laboratory, the assay was done using a similar DNA extraction method (boiled lysates of overnight broth-grown bacteria) and similar reagents  as in the J. Johnson laboratory, but using a different type of thermal cycler . PCR products were separated in 2% agarose gels with ethidium bromide for visualization with UV light. Annealing temperatures and cycle numbers were adjusted as needed to achieve amplicon profiles for each pool similar to those shown in the provided protocol.For a formal validation of the novel PCR assay in a laboratory other than that in which it was developed, an unmasked set of ST131 and non-ST131 Once the assay was established in the T. Johnson Laboratory, a test set of 12 randomly assorted unique ST131 and 7 non-ST131 isolates  was analyzed in a blinded manner. Results from the 3 multiplex pools were assessed for presence/absence of amplicons of the expected size for the particular pool. Data were entered into an interactive Excel file containing integrated interpretive algorithms , which generated presumptive ST131 subclade assignments based on the binary amplicon data.in silico version of the extended multiplex PCR assay that utilizes WGS data, a command-line script was written to extract target sequences via the 20 primer pairs described in in silico the in vitro multiplex PCR assay, and because the multiplex PCR assay infers amplicon specificity based strictly on amplicon size, the in silico version does so as well. To run an analysis, the user calls the bash script ST131Typer.sh, which accepts two mandatory arguments: a single FASTA/multi-FASTA assembly file or a directory of multiple FASTA assembly files, and the user-defined output directory. Amplicons are then identified in each input assembly using the SeqKit software’s seqkit amplicon function  SerotypeFinder . This included 78 non-ST131 E. coli isolates (primarily from the ECOR collection) and 177 phylogenetically diverse ST131 isolates (primarily from the Price and Gordon collections). Assemblies were available in EnteroBase (https://github.com/tseemann/shovill). Assembly quality was assessed using QUAST (To assess the accuracy of ST131Typer, all isolates used for the extended multiplex PCR assay derivation and validation, and for which WGS data were publicly available, were used (teroBase  for mostng QUAST  and the PCR assay and ST131Typer performances were assessed as both specificity and overall accuracy, in comparison with relevant controls. Reported results included the point estimate and 95% confidence interval.https://github.com/JohnsonSingerLab/ST131Typer.ST131Typer is freely available and accessible at


Cis-regulatory elements are regions of noncoding DNA that regulate the transcription of neighboring genes. The study of cis-element architecture that functions in transcription regulation are essential. AAAG and ACGT are a class of cis-regulatory elements, known to interact with Dof and bZIP transcription factors respectively, and are known to regulate the expression of auxin response, gibberellin response, floral development, light response, seed storage proteins genes, biotic and abiotic stress genes in plants. Analysis of the frequency of occurrence of AAAG and ACGT motifs from varying spacer lengths (0–30 base pair) between these 2 motifs in both possible orientations—AAAG (N) ACGT and ACGT (N) AAAG, in the promoters and genome of Arabidopsis thaliana which indicated preferred orientation of AAAG (N) ACGT over ACGT (N) AAAG across the genome and in promoters. Further, microarray analysis revealed the involvement of these motifs in the genes downregulated under jasmonic acid response in an orientation-independent manner. These results were further confirmed by the transient expression studies with promoter-reporter cassettes carrying AAAG and ACGT motifs in both orientations. Furthermore, cluster analysis on genes with AAAG (N) ACGT and ACGT (N) AAAG motifs orientations revealed clusters of genes to be involved in ABA signaling, transcriptional regulation, DNA binding, and metal ion binding. These findings can be utilized in designing synthetic promoters for the development of stress-tolerant transgenic plants and also provides an insight into the roles of these motifs in transcriptional regulation. Cis-regulatory elements are regions of non-coding DNA that regulate the transcription of neighboring genes. AAAG and ACGT are classes of cis-regulatory motifs that interact with Dof and bZIP transcription factors, respectively. Here, Khan et al. use in silico approaches to perform a genome-wide promoter analysis, determining the frequency and patterns of occurrence of these motifs in Arabidopsis thaliana. Their findings will aid the design of synthetic promoters for the development of stress-tolerant transgenic plants. Cis-regulatory elements are short, functional noncoding DNA sequences, clustered within the promoter region of genes  which are binding sites for Dof (P-box binding factors) and bZIP (O2) TFs, respectively , in both possible orientations-AAAG (N) ACGT and ACGT (N) AAAG, in the genome of model plant A. thaliana. Optimum inter-motif distance has great importance as promoter activation by ACGT is differentially regulated by the spacing between the 2 motifs (bZIP and Dof interaction has been shown in the promoter of a seed storage protein gene (Zein) from maize. This promoter contains P-box  and promoters. For genome-wide analysis, the DNA sequence for all chromosomes was retrieved from TAIR  ACGT and ACGT (N) AAAG. Further, exact nucleotide sequences, for all spacer lengths from 0 to 30 bp of AAAG (N) ACGT and ACGT (N) AAAG, were also determined. Since flanking sites of the core sequence is essential for binding of TFs so we performed an analysis on flanking sites of the motifs: TAAAG and GACGTC, TGTAAAG and GACGTC in both the possible orientation. A comparison of core motifs to a longer motif was done in order to identify whether flanking sequences are predominating or not. There are many reports which show that any flanking sites can alter the binding site of TFs ((N) ACGT and ACGT (N) AAAG sequences, we used 12 random combinations of the 2 sequence sets: AAGA, AGAA, GAAA and CATG, GCAT, GTAC, TCAG as controls generated by shuffling AAAG and ACGT in all possible ways. Using the PLACE database, we ensured that each of these tetramer sequences is not conserved cis-element themselves ((N) ACGT motif with the corresponding frequency of control sequences for the same N = 0–30 bp.Further, another Python code was executed on the extracted sequences to determine the frequency of occurrence of AAAG and ACGT motifs in tandem, for varying spacer lengths from 0 to 30 bp, in both possible orientations, i.e. AAAG A. thaliana is about 36% ACGT and ACGT(N)AAAG were compared with various combinations of sequences AAGA, AGAA, GAAA, CATG, GCAT, GTAC, TCAG, and paired student t-test was applied to test the statistical significance of the sequences.A paired Student’s  results . For thicis-elements along with its spacer contributing to the high level of expression at the transcriptional level. For this, TF binding site analysis was performed using ConSite, a tool used to predict the TF binding site (TFBS) on regulatory elements  ACGT and ACGT(0–30 bp)AAAG motifs and MPS were compared and contrasted to check for binding suitability for TFs. The cut-off score for binding specificity was set to 80%.TCACTATATATAGGAAGTTCATTTCATTTGGAATGGACACGTGTTGTCATTTCTCAACAATTACCAACAACAACAAACAACAAACAACATTATACAATTACTATTTACAATTACATCTAGATAAACAATGGCTTCCTCC. TFBSs present on the highly occurring spacer sequences between AAAGcis-elements were upregulated or downregulated during these conditions. By comparing genes regulated by a condition with genes containing multiple AAAG (N) ACGT and ACGT (N) AAAG elements, we calculated the likelihood of occurrence by the following formula:P(A);Microarray data of genes upregulated and downregulated under various environmental conditions  or by hormones  were retrieved from EBI expression atlas . We set the threshold value as > 1.25 for the likelihood of occurrence for all conditions. This was followed by our previous work (A = event that a given gene is regulated (up/down) by a particular condition B = event that a given gene contains multiple AAAG-ACGT elements separated by (N)AAAG and AAAG(N)ACGT motifs within their promoters using DAVID  tool ((N) ACGT and ACGT (N) AAAG orientations. We further performed multidimensional clustering on 74 genes downregulating under JA in both orientations based on their spacer lengths. We found 34 and 33 such genes in AAAG (N) ACGT and ACGT (N) AAAG orientations respectively. We also discard the spacers that have 0 occurrences across all genes making them insignificant for the clustering. We found 10 and 4 such spacers in AAAG (N) ACGT and ACGT (N) AAAG orientations, respectively. We used the K-means clustering algorithm to fit or train our model , was cloned at the BamH1 site of the Pmec. Further, this promoter-reporter cassette was cloned in the pBluescript SK (±) Phagemid . Upstream of the 50 random nucleotide sequence, different combinations of the AAAG and ACGT motifs: AAAG(N)AAAG; N = 0, 5, 25 bp, ACGT(N)ACGT; N = 0, 5, 25 bp, AAAG(N) ACGT; N = 0, 5, 25 bp ACGT(N)AAAG; N = 0, 5, 25 bp were inserted at the XbaI site .A minimal promoter baI site . The AAAgusA using different minimal promoter cassettes (MPSs) under JA, the bombarded leaves were kept in the Petri dishes with Hoagland solution supplemented with 50 µM MeJA (methyl jasmonate). After treatment, the plates were kept in the plant growth chamber at a temperature of 25°C, 16 h light/8 h dark period for 48 h. The transient expression studies using a biolistic system were performed as described by 2HPO4 pH 7.0, 1 mM EDTA, 0.1% v/v Triton X-100, 1.0 mM DTT and 0.1% SLS). The glucuronidase activity was assayed in cell-free extracts using 4-methyl umbelliferyl glucuronide (t-test.To study the expression of the reporter gene We cloned the full-length promoter of PP2C-like gene (Gene id: AT5G59220)  using thA. thaliana to determine the frequency of occurrence of AAAG and ACGT motifs in tandem with varying spacer lengths from 0 to 30 bp between them. Results indicated preferred orientation of AAAG (N= 0–30 bp) ACGT over ACGT (N= 0–30 bp) AAAG orientation . At all spacer lengths, except N = 1, the frequency of occurrence of AAAG(N)ACGT orientation is more than ACGT(N)AAAG orientation. Moreover, it can be interpreted from t-test was also performed between 2 spacer sequences from 6 to 11 which also showed the difference was significant . Apart from spacer lengths 6–11, common peaks were observed at N = 15 and 24, and a common dip was observed at N = 25. For the orientation AAAG (N) ACGT, the highest frequency of occurrence was at spacer lengths of N = 6, 10, and lowest for N = 1. Similarly, for ACGT (N) AAAG orientation, the highest frequency of occurrence was observed at a spacer length of N = 10, and lowest at N = 0 (t-test indicated the difference between the 2 orientations AAAG (N) ACGT, ACGT (N) AAAG was highly significant. The t-value at 30 df for the test samples was 3.73 while the t critical is 2.04. We also did analysis using flanking sites of AAAG and ACGT motifs with the following sequences TAAAG(N)GACGTC and GACGTC(N)TAAAG which revealed significant peaks   and ACGT-AAAG orientation (range: 1.5–2.0) .A Studenat N = 0 . Student 24, 29) . The higcis-regulatory elements and are completely random 4-nucleotide long sequences. The following charts ((N) ACGT ((N) AAAG  GCAT, TCAG (N) AGAA, are not statistically significant.Spacer sequence analysis and frequency of occurrence analysis were also conducted for some control motifs in tandem. Control motifs selected were AAGA, AGAA, and GAAA for AAAG generated by shuffling AAAG sequence in all possible ways likewise ACGT was shuffled to generate: CATG, GCAT, GTAC, and TCAG. It was ensured that control motifs are themselves not g charts  show a c(N) ACGT  and ACGT(N) AAAG  both occ(N)ACGT, “A” nucleotide occurred at the first position in 14 spacer sequences (out of a possible 30), the third position in 4 spacer sequences, and at a few other positions in several other sequences. Whereas, the second most occurring nucleotide in consensus spacer sequences was “G” ((N)AAAG, nucleotide “G” occurred at the first position in a total of 5 spacer sequences: 1, 3, 6, 25, 27, while, nucleotide “A” occurred the most at 6 places, and nucleotide “T” at 1 instance  –2, A. thaliana homeobox-leucine zipper protein (Athb-1)–2, A. thaliana homeobox-leucine zipper protein (Athb)-5–2, and DOF3–1, Gibberellin- and abscisic acid-regulated MYB (GAMYB)–5, High mobility group box 1 protein (HMG-1)–6, HMG-I/Y–6, Avian myeloblastosis virus MYB TF from Petunia hybrida (MYB.ph3)–1, and SQUAMOSA (SQUA)–2.TF binding sites on highly occurring spacer sequences, along with MPS were determined using ConSite software as described in the TTGGGCTTTCAAAATTGTTAACTCACGT, was reported to have 43 TF binding sites, a total of 16 additional sites than MPS: Athb-1–1, DOF2–2, DOF3–4, HMG-1–1, and 2 each of Maize nuclear factor binding protein 1A (MNB1A), MYB.ph3, Prolamine-box binding factor (PBF), and SQUA. In the other orientation, a 14-nucleotide long spacer sequence, ACGTGGATGCTATTAT TAAAAG, was reported to have the maximum number of TF binding sites at 39 sites, a total of 12 more than MPS-1 sites of SQUA, and 1 site each for AGL3, Athb-1, Athb-5, bZIP 910, DOF2, DOF3, MNB1A, MYB.ph3, and PBF. Many other sequences between spacer 2, 3, 4, 5, 6, 7, 10, 21, 23, 24, 29, 30 in AAAG(N)ACGT orientation while 0, 1, 2, 10, 14, 16, 17, 19, 26, 27, 29 in ACGT(N)AAAG orientation had more number of TF binding sites than MPS ((N) ACGT orientation and spacer 0, 1, 10, 14, 16, 19, 26, 27, 29 had statistically significance than other sequences  ACGT and ACGT (N) AAAG elements. By comparing genes regulated by a condition with genes containing multiple ACGT (N) AAAG and AAAG (N) ACGT elements, we calculated the likelihood of occurrence for each condition ((N)ACGT and ACGT(N)AAAG motif in promoters downregulated in response to JA is 1.29 and 1.35, respectively ((N) ACGT and ACGT (N) AAAG being high in occurrence might play a crucial role in the promoters of genes downregulated during the JA response in both the orientation as their values are above the threshold by a significant margin. These observations suggest that AAAG and ACGT motifs are involved in the regulation of genes participating in abiotic and biotic stress conditions independent of their orientation. It was observed that the value of the likelihood of occurrence of none of the other conditions displayed any significant deviation.We identified the genes upregulated, downregulated by specific environmental conditions, or by hormones containing an upstream AAAG ondition  and S3. ectively . This po(N)ACGT orientation, 33 overlapping genes (97.1%) were of cellular components, 28 overlapping genes (82.4%) were found to be involved in biological processes and 24 overlapping genes (70.6%) were associated with molecular function in the cell. In the case of 33 genes with ACGT(N)AAAG orientation, all 33 genes (100%) were represented in cellular component, 24 overlapping genes (72.7%) were found to be associated with biological processes and 22 overlapping genes (66.7%) were found to be involved with molecular functions. We further refined the data by doing functional clustering on the data. (N) AAAG orientation. Terms attributed to ABA signaling, transcription regulation, extracellular region, and metal-ion binding were highly represented in the genes downregulated under JA with the ACGT-AAAG orientation with statistical significance. This reveals that all clusters are balanced since they have evenly distributed genes. The graph illustrates the respective gene in the clusters. Furthermore, each cluster was assessed using an Enrichment score  ACGT orientation. As the figure reveals, in AAAG (N) ACGT orientation, out of 35 genes, no genes were identified as outliers and all of them were clustered into 6 groups. While clusters C1, C2, C3, and C4 are well-balanced (relatively evenly distributed), clusters C5 and C6 are significantly imbalanced consisting of 3 and 4 genes, respectively. In both the orientations of AAAG and ACGT [AAAG(N)ACGT and ACGT(N)AAAG], only 1 cluster was found to be significant with an enrichment score >2 (score >2  and 4. Tscore >2 . However(N) ACGT and ACGT (N) AAAG orientations are shown in (N) ACGT orientation is 5  to fit the unsupervised model on the given data. (N) ACGT orientation. Among 34 genes: 18, 4, 3, 5, and 5 genes were grouped in clusters 0, 1, 2, 3, and 4 respectively with a mean Silhouette score of 0.242. A larger Silhouette value indicates that clusters are significant. Silhouette score elbow curve for AAAG ion is 5 . Even th(N) AAAG orientation (K = 7. (N) AAAG orientation. The graph reveals that the clusters C1 and C3 have only one gene  making them an outlier. AT3G11410 has occurrences on a total of 5 spacers, i.e. 14, 16, 18, 20, and 22 whereas; AT4G21440 has occurrences on 13 and 22 spacer values. The graph reveals that cluster 0 has a maximum number of genes (18) having similar behavior evident for higher values of spacers. Similar to AAAG(N)ACGT orientation, 3 clusters are well-shaped and equally distributed identifying one gene as an outlier and the remaining genes as highly similar forming a dense cluster.We found 7 optimal clusters in ACGT entation . The Sil(N=0–30) ACGT ((N=0–30) AAAG (In order to gain insight into the regulatory functions of spacer sequences (0–30 bp) between the motifs, we identified the location of AAAG and ACGT motifs in both the orientation: AAAG 30) ACGT  and ACGT30) AAAG  respectiFor ACGT-AAAG orientation, we also got the highest frequency of occurrences i.e. 4 at the spacer length 20, 22, 23. GO term analysis reveals that these 4 genes at spacer length 20 are cellular components, enriched with the term metal-ion binding. Genes at spacer 22 are involved in biological processes, enriched with the term responses to osmotic stress. All 4 genes at spacer 23 are cellular components, enriched with the term nucleus.gusA gene in tobacco leaves bombarded with promoter-reporter cassette carrying a single AAAG and ACGT motif, in tandem and separated by a spacer of 5 and 25 nucleotides under JA was analyzed. The expression of the reporter gene driven by AAAG with ACGT motif separated by 5 and 25 nucleotides in both orientations was also studied. The leaves bombarded with a 50 + Pmec reporter cassette without any AAAG or ACGT motif were regarded as a control.The expression of the The data (as shown in Fluorometric assay was performed for the measurement of GUS activity. The expression of GUS in the full-length PP2C-like promoter (AT5G59220) was found to be high in uninduced conditions while in response to MeJA, approximately ∼6.5-fold decrease in GUS expression was observed (4048 ± 286) . HoweverCis-regulatory elements, AAAG and ACGT are known to play a vital role in regulating several processes including floral development  ACGT as the preferred orientation of these motifs for TF binding. An interesting observation was that the spacer lengths 6 and 10 occur at a maximum frequency in AAAG(N)ACGT orientation, while spacer length 10 also occurs maximally in ACGT(N)AAAG orientation. These sequences occur more than the other spacer sequences suggests that these lengths might serve as optimal lengths for TF binding  ACGT. Also, “A” was found at the last position in the spacer sequence in 4 spacer lengths. These observations are in synchronization with the other inferences as AAAGA and AAAAG act as binding sites for several Dof family of TFs ((N) AAAG.elopment , light relopment , tissue-in genes . Analyse binding  also obs binding . This in binding . We founol cases . From spMicroarray analysis was carried out to determine the function of these motifs in upregulated or downregulated genes under environmental conditions and in response to phytohormones. Since AAAG and ACGT motifs are enriched in the genes getting downregulated in response to JA it could be deduced that these motifs are involved in the downregulation of genes taking part in JA responses in an orientation independent manner. The data suggest that the binding of the repressor seems to be distance-dependent rather than sequence-dependent so as to bring downregulation under JA response in an orientation-independent manner . GO anal(N) ACGT and ACGT(N) AAAG motifs were conducted for all spacer lengths. In ACGT(N) AAAG orientation, cluster 0 has the maximum number of genes. These genes are mostly present on one spacer only. For example, AT5G22460, AT3G45530, AT5G01270, AT2G38390, AT4G19230, AT1G18100, AT4G14010, AT1G18900, AT4G13190, AT1G16500, AT5G59845, AT5G06760, AT2G30550, and AT4G32020 are present only on 7, 30, 2, 25, 27, 24, 12, 18, 4, 10, 26, 22, 21, and 11 respectively. Cluster 0 also has 4 genes  which are present in more than 1 spacer but have similar spacers as other genes in their cluster. Surprisingly, there is no cluster that has genes all present on only 1 spacer length. We found an interesting insight that all the IDs present in cluster 2  are present on spacer lengths 9 and 29 with 1 overlapping gene. AT3G11410 and AT4G21440 are identified as outliers in clusters 1 and 3 since these are the only genes with unique behavior. AT3G11410 appears on 5 spacer lengths while AT4G21440 appears twice on 1 spacer itself. In AAAG (N) ACGT orientation, cluster 1 has the maximum number of genes grouped together i.e. 18. All the genes are present on at least 1 spacer while only 2 IDs are present on 2 spacers i.e. AT3G60080 (spacer 3 and 19), AT3G55120 (spacer 3 and 18). In cluster 2, all genes  are present on exactly 1 spacer length, i.e. 15 and do not appear anywhere else. In cluster 4, all the genes except AT1G20640 are present on 2 spacers and share a common spacer too. For example, while AT1G67340, AT3G03170, AT1G20640 are present on spacer length 2, AT3G03170 if further present with AT5G52300 and AT2G38530 at spacer 28. Except for AT5G57050 AT4G34860, all IDs in cluster 3: AT3G11410, AT1G10370, AT3G45530, AT1G18900 are present on spacer 7 while AT5G57050 is present on spacer 29 and 30. Similarly, except AT4G34860, all gene ids in cluster 1: AT2G38390, AT5G06760, AT2G30550 are present at 10 spacers while AT4G34860 is also present at spacer 20. This analysis reveals that most of the genes in the clusters belong to a particular spacer length suggesting the importance of spacer length between AAAG and ACGT in the promoters of the genes involved in the biological processes in plants or function as cellular components.Cluster analysis on genes downregulated under JA with AAAG N5(ACGT), (AAAG)N25(ACGT), (ACGT)N5(AAAG), (ACGT)N5(AAAG) constructs. Our transient expression studies on full-length PP2C- like promoter and its mutated version indicate that the region between AAAG (TGATG) ACGT of this promoter is responsible for downregulation under JA treatment. As the expression of any gene, largely relies upon the cis-regulatory elements arranged within the promoter regions, so in order to modulate the expression of the transgene, the role of AAAG and ACGT motifs as the negative regulator in JA responses could be taken into consideration in the designing of synthetic promoters. The results of this study can assist in the promoter designing, as spacer lengths and specific sequences between AAAG and ACGT motifs for binding are required for triggering a stress response (The transient expression studies strengthened our in silico findings that the AAAG and ACGT motifs downregulate the gene expression under JA responses irrespective of their orientation. The data further suggests that the AAAG and ACGT motifs might be acting as a negative regulator leading to reduced reporter gene expression in response to JA in (AAAG)cis-regulatory elements in the A. thaliana genome. We established preferences for specific orientation, specific spacer lengths, and specific conserved nucleotides in the promoter region for the above-mentioned 2 motifs in tandem. Further, the interplay of these 2 motifs was observed to have an effect on downregulation of genes under JA responses in an orientation-independent manner. This information would be crucial for designing stress-inducible synthetic promoters for the development of highly productive and stress-resistant transgenic crops.This study was aimed at analyzing patterns of ACGT and AAAG The data generated/analyzed during the study are available in the supplementary data sheets, supplementary figures, and supplementary tables.G3 online.ZHK performed the experiments and drafted the article. SD and MBM helped in in-silico and statistical analysis. SLB helped in editing the manuscript. SA performed clustering on gene data and generated inferences. DG helped in gene expression studies. RM conceived the original idea and SM investigated and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.RM and SM are thankful to the Department of Science and Technology (DST) Government of India under the Science and Engineering Research Board (SERB) scheme for financial support. This work was supported by the DST-SERB project bearing file number EMR/2016/002470 sanctioned by the government of India to SM and RM.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.jkac057_Supplementary_Data_sheet_S1Click here for additional data file.jkac057_Supplementary_Data_sheet_S2Click here for additional data file.jkac057_Supplementary_Data_sheet_S3Click here for additional data file.jkac057_Supplementary_Figure_S1Click here for additional data file.jkac057_Supplementary_Figure_S2Click here for additional data file.jkac057_Supplementary_Figure_S3Click here for additional data file.jkac057_Supplementary_Figure_S4Click here for additional data file.jkac057_Supplementary_Figure_S5Click here for additional data file.jkac057_Supplementary_Figure_S6Click here for additional data file.jkac057_Supplementary_Figure_S7Click here for additional data file.jkac057_Supplementary_Table_S1Click here for additional data file.jkac057_Supplementary_Table_S2Click here for additional data file.jkac057_Supplementary_Table_S3Click here for additional data file.jkac057_Supplementary_Table_S4Click here for additional data file.jkac057_Supplementary_Table_S5Click here for additional data file.jkac057_Supplementary_Table_S6Click here for additional data file.jkac057_Supplementary_Figure_LegendClick here for additional data file.


Rationale: Traditional treatments for leukemia fail to address stem cell drug resistance characterized by epigenetic mediators such as histone lysine-specific demethylase 4 (KDM4). The KDM4 family, which acts as epigenetic regulators inducing histone demethylation during the development and progression of leukemia, lacks specific molecular inhibitors.Methods: The KDM4 inhibitor, SD49-7, was synthesized and purified based on acyl hydrazone Schiff base. The interaction between SD49-7 and KDM4s was monitored in vitro by surface plasma resonance (SPR). In vitro and in vivo biological function experiments were performed to analyze apoptosis, colony-formation, proliferation, differentiation, and cell cycle in cell sub-lines and mice. Molecular mechanisms were demonstrated by RNA-seq, ChIP-seq, RT-qPCR and Western blotting.Results: We found significantly high KDM4A expression levels in several human leukemia subtypes. The knockdown of KDM4s inhibited leukemogenesis in the MLL-AF9 leukemia mouse model but did not affect the survival of normal human hematopoietic cells. We identified SD49-7 as a selective KDM4 inhibitor that impaired the progression of leukemia stem cells (LSCs) in vitro. SD49-7 suppressed leukemia development in the mouse model and patient-derived xenograft model of leukemia. Depletion of KDM4s activated the apoptosis signaling pathway by suppressing MDM2 expression via modulating H3K9me3 levels on the MDM2 promoter region.Conclusion: Our study demonstrates a unique KDM4 inhibitor for LSCs to overcome the resistance to traditional treatment and offers KDM4 inhibition as a promising strategy for resistant leukemia therapy. Acute myeloid leukemia (AML) is a malignant disorder characterized by abnormal growth and differentiation of hematopoietic stem/progenitor cells (HSPCs)  KDM4A, KDM4B, KDM4C, and KDM4D. These proteins are highly homologous except for KDM4D, which lacks the C-terminal part of the protein  Kdm4c or using a KDM4C inhibitor, SD70, can successfully suppress the transcription and transformation ability of MLL fusions in leukemia cells via a KDM4C-ALKBH5-AXL signaling axis Kdm4a, b, and c could block leukemia progression Methylation of histone lysine residues, which can selectively activate or silence gene expression, is important for epigenetic information and is closely related to AML development Traditional clinical chemotherapy drugs that target cell proliferation have little potency in eliminating LSCs because of their quiescent status KDM4A expression levels were significantly higher in several human leukemia subtypes, and silencing of Kdm4a could sufficiently inhibit the leukemogenic ability in an in vivo MLL-AF9 leukemia model KDM4C knockdown, the survival of human CD34+ umbilical cord blood cells was rarely affected by knocking down KDM4A. Furthermore, we acquired a series of known and/or potential KDM4 inhibitors for screening, and one of these candidates, SD49-7, impaired LSCs by targeting KDM4A but did not affect normal HSCs both in mice and patient-derived tumor xenograft (PDX) AML models. Mechanistically, we found that depletion of KDM4A by either shRNA or SD49-7 activated the apoptosis signaling pathway by inhibiting MDM2 expression via modulating H3K9me3 levels on the MDM2 promoter region. Our study elucidated the regulatory role of KDM4 in LSCs, implicating the KDM4A/MDM2 pathway in LSC regulation. We also evaluated a novel KDM4 inhibitor that could selectively eradicate LSCs and serve as a promising candidate for leukemia therapy. Our work provided new insights into the mechanism of KDM4 in leukemia regulation and novel ideas for epigenetic drug design to target LSCs.In this study, we found that http://servers.binf.ku.dk/hemaexplorer/). Our analysis indicated that KDM4A was expressed at significantly higher levels in four AML subtypes than normal mononuclear cell controls, while KDM4C was expressed at only slightly higher levels in AML with MLL-amplification than in controls. The expression of KDM4B was higher in normal mononuclear cells than in different AML subtypes   of the recipients of KDM4A KD cells  to validate the interactions between SD49-7 or SD70 and KDM4A or KDM4C s Figure E. To fur+ cells  were dramatically influenced  were provided by the Institute of Hematology and Blood Diseases Hospital . Umbilical cord blood samples (n = 15) of healthy donors were acquired by Shandong Qilu stem cell engineering Co., Ltd. This study was carried out in accordance with the Declaration of Helsinki and approved by the Ethics Review Board of the Institute of Hematology and Blood Diseases Hospital and the Chinese Academy of Medical Sciences .Mice were bred in a specific-pathogen-free animal core facility with free access to food and water. All animal protocols were approved by the Animal Care and Use Committee of the State Key Laboratory of Experimental Hematology.+ leukemia cells, provided by the Tao Cheng laboratory +mCherry+ cells were sorted with a flow cytometer and were used for the following experiments.Primary MLL-AF9 GFP+ hUCB cells were isolated by immunomagnetic methods using the MACS CD34 progenitor cell isolation kit (Miltenyi Biotec). Isolated human UCB CD34+ cells were resuspended in IMDM (Gibco) supplemented with 10% FBS (Gibco), 100 ng/mL human SCF (PeproTech), 100 ng/mL human TPO (PeproTech), and 100 ng/mL human Flt3L (PeproTech) at a concentration of 1 × 105 cells/mL. Next, cells were plated into RetroNectin precoated 24-well plates. Polybrene  and lentivirus  were added to each well. After the plates were centrifuged at 1,800 rpm at 33 °C for 90 min, the cells were cultured at 37 °C in a humidified incubator. After 48 h, the GFP+ cells were sorted with a flow cytometer and were used for the following experiments.CD34-ΔΔCt method. Primers used in this study are shown in Total RNAs of MLL-AF9 or hUCB cells were extracted using TRIzol reagent (Invitrogen) according to manufacturer's instructions. After RNA quality control by Nanodrop 2000 (Nanodrop Technologies), 5 μg of total RNA was reverse transcribed into cDNA using One-Step gDNA Removal and cDNA Synthesis SuperMix (TransGen Biotech) according to the manufacturer's instruction. Anchored oligo(dT)20 primer was used to obtain cDNA. Quantitative RT‐PCR was performed in 10 μL quantitative PCR reactions in triplicate using TB Green Premix Ex Taq (Takara) following the manufacturer's protocol. The PCR was run in an ABI QuantStudio 6 (Thermo Fisher Scientific) real-time fluorescence quantitative PCR instrument with a cycling condition of 95 °C for 2 min, followed by 40 cycles of 95 °C for 5 sec and 60 °C for 34s. The expression of target transcripts was standardized to GAPDH, and the relative expression of target transcripts was calculated according to the 2Total cellular proteins from murine primary MLL-AF9 leukemia cells or hUCB cells were lysed with RIPA buffer (Thermo Fisher Scientific), resolved on 12% SurePAGE Gels (GenScript) and transferred to PVDF membranes (Merck Millipore). The antibodies used are listed in The indicated number of cells were seeded in 24-well plates, cultured, and treated with various compounds for 24h. An apoptosis analysis kit  was applied to detect the apoptosis status of cells by flow cytometry . Cell differentiation was measured by the fluorescence intensity of CD11b. Cells were resuspended in PI/RNase staining buffer for further cell cycle analysis. For proliferation analysis, cells were cocultured  for 72h and were counted every 24h by the trypan blue exclusion cell counting method.+ cells were plated in methylcellulose medium  according to the manufacturer's instructions. Murine primary MLL-AF9 derived leukemia cells were cultured in MethoCult M3434 (StemCell Technologies) methylcellulose medium. Colonies were counted and recorded under a microscope  after 7-12 days of incubation. For the serial colony-forming unit assay, colonies were collected and readjusted for cell density as before, and the colony-forming unit assay procedure was repeated. The number and morphological features of colonies were recorded 7 days later.THP-1 cells or umbilical cord blood-derived CD342 incubator at 37 °C. A stock solution of SD49-7 and SD70 at a concentration of 20mM was prepared by dissolving the compound in sterile DMSO and stored at -20 °C until use.HL-60, K562, HL-60/ADR, K562/ADR, and THP-1 cell lines were grown in suspension in RPMI 1640 medium (Gibco) supplemented with 2mM L-glutamine, 10% heat-inactivated FBS (Gibco), 1% penicillin/streptomycin (Thermo Fisher Scientific) in a humidified 5% CO3 cells/well and treated with different compounds at a concentration gradient for 72 h. After treatment, MTT was added at a final concentration of 0.5 mg/mL and allowed to react with cells for 4 h. The formazan precipitate was dissolved in DMSO, and absorbance was read at 570 nm using a microplate reader . The 50% inhibitory concentration (IC50) value was determined by GraphPad Prism 8 project.MTT assays were used to detect the cytotoxicity of compounds. Leukemia cells were seeded in 96-well plates at a density of 5×10The SPR system  was used to measure the binding of SD49-7 or SD70 to KDM4A and KDM4C, respectively. Briefly, KDM4A or KDM4C proteins were dissolved in 10 mM sodium acetate buffer (pH 4.0) to a final concentration of 100 µg/mL and then were immobilized on CM5 chips  using a standard amine coupling procedure. The running buffer was PBS (pH 7.4) with 0.005% P20 surfactant. Various dilutions of compounds were used and the binding of SD49-7 or SD70 to KDM4A or KDM4C was analyzed with Biacore T200 Evaluation Software 3.1 to get the KD value.7 cells. Nuclear extracts were used as the enzyme source to measure demethylase activity.Nuclear extraction kit (Epigentek) was applied to isolate nuclear proteins from THP-1 cells according to the manufacturer's instructions. The total yield was up to 100 μg per 10Demethylase kinetics of SD79-7 and SD70 was evaluated by the JMJD2 demethylase activity assay kit (Epigentek). Enzymatic reactions were set up for blank and samples with nuclear extracts in the presence or absence of inhibitors (1 μM SD79-7 and 1.75 μM SD70) and incubated with the substrate and assay buffer at 37 °C for 120 min. Subsequently, the wells were washed and incubated with the capture antibody at room temperature for 60 min followed by incubation with a detection antibody at room temperature for 10 min. The amount of demethylated products was colorimetrically detected by a microplate reader (Bio-Tek) at 450 nm with an optional reference wavelength of 655 nm. The KDM4s demethylase activity was calculated using the following formula: Inhibition % = (1-(Inhibitor Sample OD - Blank OD)/(No Inhibitor Sample OD - Blank OD)) × 100%.ex vivo assay, viable cells (2×105 cells/0.2 mL PBS) were injected into the tail vein of syngeneic 18-19g female C57BL/6J mice. The mice were sacrificed 21 days later to detect the leukemia burden in major hematopoietic tissues. For the limiting dilution assay, 50,000, 5,000, 500 or 50 cells were injected into the tail vein of C57BL/6J mice. The number of recipients that developed leukemia and died was recorded to calculate the LSC frequencies according to Poisson statistics with ELDA software Murine primary MLL-AF9 leukemia cells expressing GFP were treated with compounds at the indicated concentration for 24 h, and then collected and resuspended in cold PBS. For the via tail vein 3 days before injection with SD49-7 (5 mg/kg), SD70 (7.5 mg/kg), or vehicle (PEG300: dextrose 5% in water (D5W) = 3:1) intraperitoneally (i.p.) for 5 consecutive days and then every 2 days for 3 weeks. About 8 weeks after transplantation, mice were sacrificed to analyze the engraftment efficiency in bone marrow by flow cytometry .Primary mononuclear cells (MNCs) isolated from a relapsed AML patient were injected into sub-lethally irradiated (250 cGy) NOD/SCID mice https://david.ncifcrf.gov/) http://www.gsea-msigdb.org/gsea/index.jsp). The geneset of HALLMARK P53 PATHWAY (http://www.gsea-msigdb.org/gsea/msigdb/cards/HALLMA RK _P53_ PATHWAY.html) was used to assess the effect of SD49-7 on p53 signaling.THP-1 cells were treated with SD49-7 for 24 hours. The cells were lysed to isolate RNA, and gene expression was detected using a whole-genome gene expression chip (Genergy). Data analysis was performed to identify critical pathways. Differentially expressed genes were cut off with fold-change > 2 or < 0.5, p ≤ 0.05. KEGG analysis  assays were performed using the Enzymatic Chromatin IP Kit  according to the manufacturer's instructions. THP-1 cells were lysed after culturing for 24 hours with or without SD49-7 treatment. Protein/DNA complexes were immunoprecipitated by H3K9me3 antibodies, using normal rabbit IgG as a negative control. The primers used for PCR amplification are shown in t test, and the Kaplan-Meier method and Log-rank test were used for survival analysis. Quantitative results are presented as the mean ± standard deviation (SD), and a p-value < 0.05 was considered to be statistically significant.Analyses were carried out by GraphPad Prism v8.0 with Student's-Reagents or Resources can be found in Other details of KDM4A depletion inhibits leukemogenesis and avoids the impairment of normal hematopoietic cells.A specific KDM4 inhibitor, SD49-7, selectively eradicates LSCs without impairing normal hematopoietic cells.CIP1.KDM4 inhibition deregulates MDM2 and elevates p21Supplementary figures and tables.Click here for additional data file.


Increasing the expression level of the SARS-CoV-2 spike (S) protein has been critical for COVID-19 vaccine development. While previous efforts largely focused on engineering the receptor-binding domain (RBD) and the S2 subunit, the amino-terminal domain (NTD) has been long overlooked because of the limited understanding of its biophysical constraints. In this study, the effects of thousands of NTD single mutations on S protein expression were quantified by deep mutational scanning. Our results revealed that in terms of S protein expression, the mutational tolerability of NTD residues was inversely correlated with their proximity to the RBD and S2. We also identified NTD mutations at the interdomain interface that increased S protein expression without altering its antigenicity. Overall, this study not only advances the understanding of the biophysical constraints of the NTD but also provides invaluable insights into S-based immunogen design. A survey on thousands of SARS-CoV-2 S protein NTD mutations reveals a complementary strategy for immunogen optimization. The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to the coronavirus disease 2019 (COVID-19) pandemic . Instead, the mutational tolerability of NTD residues strongly correlated with their distance to RBD and S2. Residues S50 and G232 were two exceptions, in which they were proximal to S2 and RBD, respectively, and yet had a high mutational tolerability. Subsequently, we functionally characterized two mutations that increased S protein expression, namely, S50Q and G232E. These results have important implications toward understanding NTD evolution and S-based immunogen design.To study how SARS-CoV-2 S protein expression is influenced by NTD mutations, we created a mutant library that contained all possible single amino acid mutations across residues 14 to 301 of the S protein. Each of these 288 residues was mutated with the choice of all 19 other amino acids and the stop codon, leading to a mutant library with 5760 single amino acid mutations. We used a cassette-based polymerase chain reaction (PCR) strategy that was designed to avoid potential off-target errors and generation of double mutants during the library construction process (fig. S1). As a quality control, Sanger sequencing was performed on 10 selected colonies following the construction of the mutant library. All of them contained a single mutation as expected. The mutant library was expressed using the human embryonic kidney (HEK) 293T landing pad cell system such that each transfected cell stably expressed only one mutant (P = 6 × 10−166), which validated the selectivity of the deep mutational scanning experiment. Silent mutation and missense mutations had similar expression scores, although the difference is statistically significant (P = 2 × 10−5), indicating that most amino acid mutations in the NTD did not affect S protein expression. While dead cells could potentially increase the noise of the deep mutational scanning results, this effect seemed to be relatively minor in our experiment (fig. S5). In addition, a Pearson correlation of 0.53 was obtained between the expression scores of each mutant from two independent biological replicates (fig. S4B), demonstrating the reproducibility of the deep mutational scanning experiment.To evaluate the quality of the deep mutational scanning results, we assessed the expression score distributions of missense, nonsense, and silent mutations (fig. S4A). The difference between the expression scores of silent mutations and nonsense mutations was apparent and significant , others were enriched in low-expression mutations  and had lower mutational tolerability (P ≤ 0.03) when compared to the rapidly evolving NTD antigenic supersite  and 1.5-fold (P = 9 × 10−4), respectively, whereas that of S50Q/G232E increased by 2.5-fold (P = 2 × 10−6). Although fold change in MFI is unlikely to linearly correlate with the fold change in protein synthesis, such increase in MFI shows that S50Q, G232E, and S50Q/G232E double mutant have increased surface expression compared to WT.While NTD residues adjacent to RBD/S2 typically had a low mutational tolerability, S50 and G232 were two exceptions . For exaTm of 46°C to 46.5°C. These observations indicate that despite both S50Q and G232E improve the interaction between NTD and the rest of the S protein, they have minimal impact on the global folding stability of the S protein. Notably, all mutants increased the yield of the soluble recombinantly expressed S protein compared to WT (fig. S6), although the rank order was different from that of the membrane-bound form   (45–47).1–10 were mixed with HEK293T landing pad cells that expressed S proteins and mNG211. Green fluorescence due to mNG2 complementation was generated when fusion between the two cell lines occurred. Fluorescence microscopy analysis showed that all mutants facilitated hACE2-mediated fusion (P = 0.03) and G232E  showed mild, yet significant, increases in fusion activity compared to WT. Similarly, at 24-hour postmixing, S50Q , G232E , and S50Q/G232E double mutant  all showed an increase in fusion activity compared to WT. Such a mild increase in fusion activity may simply be attributed to the higher expression level of the mutants. However, because the relationship between protein expression level and fusion activity remained elusive, we are unable to assess the fusion activity per S protein molecule based on the current data. Negative control cells expressing the K986P/V987P double mutant, which is known to stabilize the prefusion form of the S protein    for NTD cell lines or hygromycin (100 μg/ml) for hACE2 cell lines] was supplemented to the medium to carry out positive enrichment of cells with successful recombination. Constructed cell lines would remain in the complete growth medium supplemented with doxycycline and the positive selection antibiotics.HEK293T landing pad cells (g for 5 min at room temperature. Cells were then resuspended in FACS buffer . Subsequently, cells were incubated with CC40.8 (5 μg/ml) at 4°C with gentle shaking for 1 hour. Cells were washed once with ice-cold FACS buffer and incubated with PE anti-human IgG Fc  at 4°C with gentle shaking in the dark for 1 hour. Cells were washed once and resuspended in ice-cold FACS buffer. Cells were then filtered using a 40-μm cell strainer (VWR) before cell sorting. FACS was performed using a BD FACSAria II cell sorter (BD Biosciences) with a 561-nm laser and a 582/15 band-pass filter. Cells were collected into ice-cold D10 medium  and binned into no (bin 0), low (bin 1), medium (bin 2), and high (bin 3) expression according to PE signal, where each bin contains 25% of the singlet population (fig. S2). A biological replicate of the deep mutational scanning experiment was performed, starting from the transfection step.Four T-75 flasks (Corning) that were 90% confluent with cells that carried the NTD mutant library were washed with 1× phosphate-buffered saline (PBS), harvested with warm versene, and pelleted via centrifugation at 300g, 4°C for 15 min and then resuspended in 200 μl of PBS (Corning). Genomic DNA extraction was then performed using the DNA Blood and Tissue Kit  according to the manufacturer’s instructions with a modification: Cells were incubated at 56°C for 30 min instead of 10 min. The NTD mutant library was amplified from the genomic DNA in two nonoverlapping fragments using KOD Hot Start DNA polymerase  per the manufacturer’s instruction with the following two primer sets, respectively : set 1: 5′-CACTCTTTCCCTACACGACGCTCTTCCGATCTCTGCTGCCTCTGGTGTCCAGC-3′ (NTD-DMS-recover-1F) and 5′-GACTGGAGTTCAGACGTGTGCTCTTCCGATCTGTTGGCGCTGCTGTACACCCG-3′ (NTD-DMS-recover-1R); set 2: 5′-CACTCTTTCCCTACACGACGCTCTTCCGATCTAGCTGGATGGAAAGCGAGTTC-3′ (NTD-DMS-recover-2F) and 5′-GACTGGAGTTCAGACGTGTGCTCTTCCGATCTCACGGTGAAGGACTTCAGGGT-3′ (NTD-DMS-recover-2R).Sorted cells from each bin were pelleted at 300A second round of PCR was carried out to add the adapter sequence and index to the amplicons as described previously (F) of a mutant i at position s within bin n of replicate k was computed for each replicate as followsNext-generation sequencing data were obtained in FASTQ format. Forward and reverse reads of each paired-end read were merged by PEAR  of mutant i at position s as followsA pseudocount of 1 was added to the read counts of each mutant to avoid division by zero in subsequent steps. We then calculated the total frequency  of each mutant among 4 bins (bin 0 to bin 3) in each replicate was computed as described previously . The mean value of weighted average for nonsense and silent mutations was calculated. Expression score (ES) of a mutant i at position s was calculated by taking the average of the expression scores between replicates. Mutational tolerability of position s was then calculated by taking the average of the expression scores of all mutants at that positionThe final expression score of a mutant DSSP   was used  (N-acetyl-d-glucosamine were removed using PyMOL (Schrödinger). Then, the amino acids were renumbered using pdb-tools (https://github.com/nicwulab/SARS-CoV-2_NTD_DMS/tree/main/rosetta.The structure of the S protein was obtained from PDB (PDB 6ZGE)  a GCN4 leucine zipper, a GS linker, mNG211, and a 2A self-cleaving peptide was inserted into the S plasmid between the IRES and the puromycin resistance marker. Each plasmid construct was transfected and recombined into HEK293T landing pad cells per step described above.hACE2 construct was constructed in a previous study (5 landing pad cells expressing hACE2 with mNG21–10 were seeded in six-well plates (Fisher Scientific). The cells were then incubated at 37°C with 5% CO2 for 15 min to allow seeding. Subsequently, 5 × 105 landing pad cells expressing S with mNG211 were then added dropwise to the seeded hACE2 cells. Both cells were filtered through 40-μm cell strainer (VWR) before seeding. At 3- and 24-hour postmixing, fusion events in each well were qualitatively assessed with an ECHO Revolve epifluorescence microscope (ECHO) in inverted format. Overlaid images were captured on white light and fluorescein isothiocyanate filter channels using an UPlanFL N 10×/0.30 numerical aperture objective (Olympus) with identical light intensity and exposure settings for all conditions. Cells in each well were then collected using 0.5 mM EDTA, pelleted via centrifugation at 300g for 5 min at room temperature, and resuspended in the FACS buffer. LSRII flow cytometry (BD Biosciences) was used to quantify the fusion events of each sample. Negative controls were measured first to set up proper gating strategies (fig. S9). Then, the flow cytometry analysis was performed on 105 live cells for each sample. Data were analyzed using FCS Express 6 software (De Novo Software). The percentage of mNG2-positive population of each sample was used for normalization (table S4).Once the stable cell lines were created, 5 × 106 cells that carried the selected SARS-CoV-2 S NTD mutant were washed with 1× PBS, harvested with warm versene, and pelleted via centrifugation at 300g for 5 min at room temperature. The cells were resuspended in the FACS buffer. Subsequently, cells were incubated with 5 μg/ml of the selected antibodies at 4°C with gentle shaking for 1 hour. Cells were then washed once with ice-cold FACS buffer and incubated with PE anti-human IgG Fc  at 4°C with gentle shaking in the dark for 1 hour. Cells were washed once, pelleted via centrifugation at 300g for 5 min at room temperature, and resuspended in ice-cold FACS buffer. LSRII flow cytometry (BD Biosciences) was used to measure the PE signal of each sample. Negative controls were measured first to set up proper gating strategies (figs. S8 and S10). Then, the flow cytometry analysis was performed on 105 singlets for each sample. Data were analyzed using FCS Express 6 software (De Novo Software).Approximately 1 × 10i, the following equation was used to compute the normalized expression (NE)The MFI of the entire population was recorded for each sample, followed by the normalization as previously described .6 cells ml−1 using the ExpiFectamine 293 Transfection Kit (Thermo Fisher Scientific) following the manufacturer’s instructions. Transfected cells were then incubated at 37°C, 8% CO2 and shaking at 125 rpm for 6 days. Cell cultures were then harvested and centrifuged at 4000g at 4°C for 15 min. The supernatant was clarified using a 0.22-μm polyethersulfone filter (Millipore). S protein in the clarified supernatant was then purified using Nickel Sepharose Excel resin (Cytiva), with 20 mM imidazole in PBS as wash buffer, and 300 mM imidazole in PBS as elution buffer. Three rounds of 2-ml elutions were performed. The eluted protein was then concentrated and analyzed by SDS–polyacrylamide gel electrophoresis reducing gels . Concentrated protein solution was further purified using Superdex 200 XK 16/100 size exclusion column (Cytiva) in 20 mM tris-HCl (pH 8.0) and 150 mM NaCl (fig. S6B). Selected elution fractions were combined and concentrated. Final protein concentration was measured using NanoDrop One (Thermo Fisher Scientific).SARS-CoV-2 S ectodomain with the PRRA motif in the furin cleavage site deleted and mutations K986P/V987P, which are known to stabilize the prefusion conformation and increase expression (d(RFU)/dT, was defined as the melting temperature (Tm). Data were analyzed using OriginPro 2020b (Origin Lab). Raw data are shown in table S5.Five micrograms of purified protein was mixed with 5× SYPRO orange (Thermo Fisher Scientific) in 20 mM tris-HCl (pH 8.0), 150 mM NaCl at a final volume of 25 μl. The sample mixture was then transferred into an optically clear PCR tube (VWR). SYPRO orange fluorescence data in relative fluorescence unit (RFU) was collected from 10° to 95°C using CFX Connect Real-Time PCR Detection System (Bio-Rad). The temperature corresponding to the lowest point of the first derivative, −


Background: Gastric cancer (GC) has a high mortality rate and is particularly prevalent in China. The extracellular matrix protein, prolyl 4-hydroxylase subunit alpha 3 (P4HA3), has been implicated in various cancers. We aimed to assess the diagnostic and prognostic value of P4HA3 in GC and investigate its correlation with immune cell infiltration.Methods: The present study used microarray data from the Cancer Genome Atlas (TCGA) to analyze the association of P4HA3 expression with clinicopathological features. Data from the Gene Expression Omnibus (GEO) were used for validation. Receiver operating characteristic (ROC) and Kaplan–Meier curves were constructed to determine the diagnostic and prognostic value of P4HA3 in GC. Univariate and multivariate regression analyses were performed to assess the impact of P4HA3 on overall survival (OS) rates. A protein–protein interaction (PPI) network was generated and functional enrichment evaluated. Single-sample gene set enrichment analysis (ssGSEA) was conducted to correlate P4HA3 expression with immune cell infiltration. The correlation between P4HA3 and immune check point genes was studied.Results: P4HA3 was over-expressed in GC, along with 15 other types of cancer, including breast invasive carcinoma and cholangiocarcinoma. P4HA3 showed high diagnostic and prognostic value in GC and was an independent prognostic factor. P4HA3, TNM  stage, pathological stage and age all correlated with OS rates. Genes related to P4HA3 were enriched in the lumen of the endoplasmic reticulum and included procollagen-proline 3-dioxygenase activity. P4HA3 expression correlated with numbers of macrophages, natural killer (NK) cells, immature dendritic cells (iDC), mast cells, eosinophils, effective memory T cells (Tem), T-helper 1 (Th1) cells and dendritic cells (DC). P4HA3 was positively correlated with hepatitis A virus cellular receptor 2 (HAVCR2) and programmed cell death 1 ligand 2 (PDCD1LG2).Conclusion: P4HA3 is a potential independent biomarker for prognosis of GC and may be an immunotherapy target in the treatment of GC. Global age-standardized incidence and mortality rates are 11.1 per 100,000 and 7.7 per 100,000. Rates are considerably higher in China, where incidence and mortality occur at 20.6 per 100,000 and 15.9 per 100,000, respectively  is a catalytic subunit involved in collagen synthesis. Its overexpression has been associated with tumors and with non-cancerous diseases, including idiopathic pituitary adenoma, melanoma, stomach carcinoma, breast cancer and pulmonary fibrosis .A recent study has suggested that upregulation of P4HA3 is associated with enhanced metastasis and poor survival of GC patients . Howeverhttps://www.cancer.gov/tcga) is an open database which aims to make molecular data characterizing the cancer-related genome freely available and to link genomic data to patients’ clinicopathological information. RNA-sequencing data (level 3) with corresponding clinicopathological information were downloaded from the TCGA database. Data was converted from fragments per kilobase per million (FPKM) to transcripts per million reads (TPM). Survival data were published in Cell (https://xenabrowser.net/datapages/) (https://www.ncbi.nlm.nih.gov/geo/) to validate the P4HA3 expression level. The Cancer Genome Atlas (TCGA) project ( in Cell . For anaapages/) . GSE5412Receiver operating characteristic (ROC) and Kaplan-Meier survival curves were constructed and used to analyze the diagnostic and prognostic value of P4HA3, respectively. The association between P4HA3 expression and overall survival (OS) rates of GC patients was assessed by univariate and multivariate regression analyses.https://metascape.org/gp/index.html)  of more than 1.5 were acquired and grouped into clusters based on their connections. p-values were calculated from the cumulative hypergeometric distribution and q-values using the Banjamini-Hochberg procedure to account for multiple testing. Kappa scores were used as the similarity metric when performing hierachical clustering of the enriched terms and sub-trees with a similarity of >0.3 were considered a cluster. The most statistically significant term within a cluster was used to represent that cluster.Protein–protein interaction (PPI) network analysis of P4HA3 was performed by using the search tool of a single named protein with default parameters within the STRING database  . Pathwayex.html) . The comp < 0.05 were considered to indicate significant positive or negative correlation. The expression of the following immune-checkpoint–relevant transcripts was assessed: sialic acid binding Ig like lectin 15 (SIGLEC15), T cell immunoreceptor with Ig and ITIM domains (TIGIT), CD274 Molecule (CD274), hepatitis A virus cellular receptor 2 (HAVCR2), programmed cell death 1 (PDCD1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), lymphocyte activating 3 (LAG3) and programmed cell death 1 ligand 2 (PDCD1LG2)  .https://www.xiantao.love/products) embedded with R software and R packages, including org.Hs.eg.db, GEOquery, limma, ggplot2, clusterProfiler, survminer, survival and pROC  were performed using Xiantao Academic , cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), acute myeloid leukemia (LAML), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), rectum adenocarcinoma (READ), thymoma (THYM) and stomach adenocarcinoma STAD; . All-samHelicobacter pylori infection status 1, COL1A2, COL3A1, COL6A3, COL12A1, COL20A1, prolyl 3-hydroxylase (P3H)1, P3H2 and P3H3 ; Table 4The association between P4HA3 and the degree of immune cell infiltration in GC was explored using ssGSEA analysis . MacrophPatients were divided into two groups according to P4HA3 expression and those with high expression had higher levels of the immune-checkpoint–relevant transcripts, HAVCR2 and PDCD1LG2, than those with low expression . P4HA3 eProlyl 4-hydroxylase (P4H) activity is essential for maintenance of the collagen triple helix and P4HAs  plus P4HB are highly expressed in numerous tumors where they may contribute to cancer progression. A number of inhibitors of P4HAS and P4HB have been shown to exert anti-tumor effects, suggesting that P4H is an achievable target for cancer therapy . ExpressmRNA expression levels across many different cancer types were analyzed using data from the TCGA database. P4HA3 mRNA was up-regulated in GC, along with BRCA, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KIRC, LAML, LUAD, LUSC, PAAD, PCPG, READ and THYM, in agreement with the previous study of A key component of the current study was to address the diagnostic and prognostic value of P4HA3. GC patients tended to have higher P4HA3 mRNA expression when they were infected by HP, resulting in diagnosis with higher T stages and lower histological grades, or when they were diagnosed at late pathological stages. ROC analysis indicated differences in P4HA3 expression between tumor tissues and non-cancerous tissues. Kaplan–Meier survival analysis indicated that those GC patients with higher levels of P4HA3 tended to have shorter OS. Multivariate Cox analysis demonstrated that high levels of P4HA3 mRNA constituted an independent risk factor for OS and were associated with poor GC prognosis. Thus, we believe that P4HA3 could serve as a novel diagnostic and independent prognostic biomarker for GC patients.P4HA3 has been shown to have an association with many different cancers. It promoted cell proliferation, invasion and migration in head and neck squamous cell carcinoma and melanoma cells  and reduMacrophages and NK cells influence the tumor microenvironment and tumor immunity . InfiltrImmune checkpoint molecules regulate self-tolerance to prevent autoimmune reactions and minimize tissue damage by controlling the length and intensity of the immune response. Expression of checkpoint molecules acts to limit the immune and anti-tumor immune response, enabling escape of tumor cells . PatientIn conclusion, the purpose of the current study was to determine the diagnostic and prognostic value of P4HA3 and its correlation with immune cell infiltration in GC. P4HA3 emerges as a feasible diagnostic and prognostic biomarker and immunotherapy target. However, the current results are all derived from bioinformatics analysis and limited by the absence of experimental confirmation. Further clinical experiments are underway to verify the function of P4HA3 in GC.


The binding energies calculated at B3LYP-D3/def2TZVP level showed that the contribution order of amino acid side chains to the binding affinity was carboxyl > benzene ring > hydroxyl > sulfhydryl > amino group. The affinity order was inversely proportional to the radius and charge transfer of heavy metal cations, approximately following the order of: Ni2+ > Fe3+ > Cu2+ > Hg2+ > Zn2+ > Cd2+ > Mn2+. Compared to the gas-phase in other researches, the water environment has a significant influence on structures and binding energies of the heavy metal and amino acid binary complexes. Collectively, the present results will provide a basis for the design of a chelating agent  to effectively remove heavy metals from the environment.Heavy metals are non-biodegradable and carcinogenic pollutants with great bio-accumulation potential. Their ubiquitous occurrence in water and soils has caused serious environmental concerns. Effective strategies that can eliminate the heavy metal pollution are urgently needed. Here the adsorption potential of seven heavy metal cations (Cd With the rapid development of the global metal and mining industries, heavy metals are large accumulated in the upper crust and aquatic environment. Due to its particularities, non-biodegradability, bio-accumulation potential, and carcinogenicity, heavy metal pollution is a serious threat to human health and environmental sustainability . Efficie2+, Hg2+, Mn2+, Ni2+, Zn2+, and so on  and [Mn+-AA-03] in n = 2,3). In the later mode, the metal cation interacted with two carbonyls (C=O), liking the structure [Mn+-AA-02]. In the acidic AA-metal cations complexes, it was observed that the structure [Mn+-AA-02] was the most stable by comparing the ∆G of three configurations (2), a tridentate binding , was the lowest energy structure in the gas-phase in previous studies [n+-AA-02].The calculated results indicated that the complexes of [acidic AAs-metal cation] had two geometric models: salt bridge (SB) mode and charge solvation (CS) mode ,29. In turations . Two neg studies ,31,32. T3+).In the water solution, the zwitterion of alkaline AAs, Arginine (Arg) Histidine (His) and Lysine (Lys), was equipped with an electronegative amino group on the side chain, which took a hydrogen ion from aqueous solution to form a positive amino group  was about 44 kJ/mol higher than [Cd2+-Asp-02] (CS structure). Similar results were found in other studies. The relative energy of the SB structure was 40 kJ/mol higher than the CS structure in normal Aspartic acid interacting with copper cation  and [Mn+-AA-03] were SB modes. The difference was that [Mn+-AA-03] had one more hydrogen bond, NH⋯S/O than [Mn+-AA-01]. [Mn+-AA-02] was CS mode, whose metal cations bound with an O atom on the carbonyl and an O/S atom of hydroxyl/sulfhydryl whose metal cations bound with an O atom on the carbonyl and an O/S atom of hydroxyl/sulfhydryl group. In addition, Ser-metal cation complexes had the [Mn+-AA-04] structure, in which the metal cations bound to an O atom on the carbonyl. The ∆G of optimized structures , Tryptophan (Try), and Tyrosine (Tyr) were paid attention to herein. The stable conformers containing both the SB and CS modes were obtained in n+-AA-02] structure. In the HOMO calculated results [n+-AA-01] and [Mn+-AA-02], M=Hg, Cd; AA=Phe, Trp, Tyr. Similarly, the  structures (SB mode) became isoenergetic, especially for K+ and Rb+ in the Group 1 alkali metals . The results indicated that the metal cations preferred to simultaneously combine with [C=O] from the amide and carboxyl groups. In addition, an interesting conformer was found. In the structures [Mn+-Asn-04], a CS mode, the metal cations interacted with O and N of the amide group on the amino acid side chains, which made structure stabilities close to SB conformers, [Mn+-Asn-01]. However, the complexes of the Gln-metal cations were different to those of the Glu-metal cations. In n+-Gln-01) and a new CS structure, [Mn+-Gln-03], became more stable (−] structures (SB mode) were favored for larger cations  and that the  structures contributed more to smaller cations  in the gas-phase.Asn and Gln were the amino acids carrying an acyl group, derived from acidic amino acids. Similar to Asp-metal cation complexes, the Asn-metal cation complexes generated four conformers  and the e stable . InfrareTwo types of conformations, SB structures and CS structures, were found by optimizing the conformers of metal cations with Thr, Met and Pro. However, the [S] CS structure was obtained in the conformer instead of the predicted [SO] CS structure. As described above for hydroxyl and sulfhydryl AAs complexing with metal cations, the stable structures of Thr/Met-metal cation complexes were the CS and SB structures, respectively . The sta2+ conformers had similar energy values with differences of 6–15 kJ/mol. The reason was most likely that the smallest radius of nickel cation leads to a preference for SB structures over CS structures. The previous studies  conformers lengthened in the order Hg2+ > Cd2+> Mn2+> Zn2+> Cu2+> Fe3+>Ni2+. The order of Mn+--O from Hg2+ to Ni2+ was approximately similar to the ionic radii for Hg2+ (1.19 Å), Cd2+ (0.95 Å), Zn2+ (0.74 Å), Cu2+ (0.73 Å), Mn2+ (0.67 Å), Fe3+ (0.64 Å), Ni2+ (0.56 Å), respectively , [Mn+-Ala-01] and [Mn+-Tyr-02] structures were not only the most stable structure, but also had the highest bindE and ∆QM  > Ni2+ (0.87) > Cu2+ (0.77) > Zn2+ (0.65) > Hg2+ (0.54) > Cd2+ (0.47) > Mn2+ (0.39), which approximately correlated with the bindE order: Ni2+ (357.6) > Fe3+ (306.9) > Cu2+ (238.7) > Hg2+ (173.8) > Zn2+ (168.5) > Cd2+ (147.3) > Mn2+ (108.7). Small metal cations had better spatial structure and more charge transfer, which was consistent with Lewis-acids nature and led to higher affinity for AAs. Among the bindE comparisons of 20 amino acids  > Mn2+ 8.7. Smalali ions  have beelexation . The preAs shown in 2+, Cu2+, Fe3+, Hg2+, Mn2+, Ni2+ and Zn2+) was systematically investigated with the DFT method. At the B3LYP-D3/def2TZVP level, the optimized geometry results indicated that the zwitterionic amino acids (ZW-AAs) were abundant in aqueous solutions due to the effects of hydrogen bonds and amino protonation. For AAs with different side chains, the contribution trend of the side chains to heavy metal cation (HMC) affinity was: carboxyl group > benzene ring > hydroxyl group > sulfhydryl group > amino group. AAs were more attractive to metal cations with a smaller radius following the order: Ni2+ >Fe3+ > Cu2+ > Hg2+ > Zn2+ > Cd2+ > Mn2+. The AAs-affinity of Mn2+ was lower than that of other metals due to weak Lewis acid properties. In addition, the order of affinity of all AAs for HMC followed Asp > Glu >Trp > Asn > Thr > Tyr > Ser > Phe > Ile > Cys > Val > Ala > Pro > Leu > Gln > Met > Gly > His > Lys > Arg. Collectively, the present results will provide the basis of guidance for the removal methods of heavy metal cations and reduce the heavy metal pollution in water and soil environments.To explain the mechanism of complexation between amino acids and heavy metals, and help effectively remove heavy metals from the environment, the adsorption potential of 20 amino acids with seven heavy metal cations (Cd