Human cytomegalovirus (HCMV) is a ubiquitous pathogen that infects the majority of the world population and causes lifelong latent infection. HCMV has been shown to exacerbate cardiovascular diseases, including myocarditis, vascular sclerosis, and transplant vasculopathy. Recently, we have shown that murine CMV (MCMV) recapitulates the cardiovascular dysfunction observed in patients with HCMV-induced myocarditis. To understand the viral mechanisms involved in CMV-induced heart dysfunction, we further characterized cardiac function in response to MCMV and examined virally encoded G-protein-coupled receptor homologs (vGPCRs) US28 and M33 as potential factors that promote infection in the heart. We hypothesized that the CMV-encoded vGPCRs could exacerbate cardiovascular damage and dysfunction. Three viruses were used to evaluate the role of vGPCRs in cardiac dysfunction: wild-type MCMV, a M33-deficient virus (∆M33), and a virus with the M33 open reading frame (ORF) replaced with US28, an HCMV vGPCR . Our in vivo studies revealed that M33 plays a role in promoting cardiac dysfunction by increasing viral load and heart rate during acute infection. During latency, ΔM33-infected mice demonstrated reduced calcification, altered cellular gene expression, and less cardiac hypertrophy compared with wild-type MCMV-infected mice. Ex vivo viral reactivation from hearts was less efficient in ΔM33-infected animals. HCMV protein US28 expression restored the ability of the M33-deficient virus to reactivate from the heart. US28+ MCMV infection caused damage to the heart comparable with wild-type MCMV infection, suggesting that the US28 protein is sufficient to complement the function of M33 in the heart. Altogether, these data suggest a role for vGPCRs in viral pathogenesis in the heart and thus suggest that vGPCRs promote long-term cardiac damage and dysfunction. Human cytomegalovirus (HCMV), a betaherpesvirus, is a widespread pathogen that causes lifelong latent infection in much of the world population. While the most severe sequela result from systemic infections in immunocompromised patients and birth defects in infants, seropositivity also correlates with the exacerbation of many chronic diseases ,2. HCMV Similar to HCMV, MCMV infects many cell types and tissues, including the spleen, liver, and salivary glands ,17. In aOur recent studies have demonstrated similar cardiac dysfunction between MCMV-infected mice and HCMV-infected patients . Here, wAlthough M33 has not been shown to bind chemokines like US28, M33 is capable of similar signaling pathway activation and is proposed to be the functional homolog of US28 ,21,27,28To evaluate the role of vGPCRs in cardiac dysfunction, we focused on three viruses: wild-type parental strain K181-Perth (KP), a M33-deficient virus (ΔM33), and a M33-deficient virus that expressed the HCMV US28 (US28+) ,35. Our 2 at 37 °C. Wild-type viruses used for studies were the strains K181+ Stanford  and K181-Perth (referred to as KP). The M33-null mutant virus was ΔM33BT2 (referred to as ΔM33), which contains a LacZ insert disrupting the M33 gene locus [NIH 3T3 fibroblast cells  were grown in Dulbecco’s modified Eagle medium (DMEM) with 4.5 g/L glucose and L-glutamine without sodium pyruvate  supplemented with 10% FBS (Hyclone), 7.5% sodium bicarbonate, 4 mM HEPES, 2 mM L-glutamine, and 1% gentamycin . Cells wne locus ,35. A sene locus . Both mune locus . Virus t6 pfu of MCMV. At 3, 7, 14, 70, and 90 days post infection (dpi), animals were sacrificed and tissues removed for subsequent analysis [5-week-old female BALB/c mice were purchased from Jackson Laboratory . For MCMV infection, mice were intraperitoneally (i.p.) inoculated with 1 × 10analysis . For gananalysis . Mice wew/v) in DMEM media, and incubated on NIH 3T3 fibroblasts at 37 °C and 5% CO2 for 1 h. Following incubation, the supernatant was removed, and cells were overlayed with carboxymethyl cellulose, incubated for 5–6 days, and fixed and stained with Giemsa . MCMV plaques were visualized using a light microscope. Virus titers were represented as Log10 PFU/mL tissue homogenate.Viral replication in tissues of MCMV-infected mice was evaluated at 3, 7, and 14 dpi by plaque assay on NIH 3T3 fibroblasts, as previously described ,34. Brieearly gene 1 (E1) was amplified by using E1-specific primers (F-5′TCGCCCATCGTTTCGAGA-3′), (R-5′TCTCGTAGGTCCACTGACGGA-3′), and probe (6FAM-ACTCGAGTCGGACGCTGCATCAGAAT-TAMRA), as previously described [early gene 1. E1 was cloned into a pcDNA3.1 plasmid by using the fast cloning technique [Viral DNA load within the hearts was evaluated by quantitative PCR (qPCR) at 3, 7, and 14 dpi. From each heart, 0.1 g tissue was homogenized, and DNA was isolated using the QiaAmp DNA extraction kit . The escribed ,37,38. Vechnique ,40. The At 14, 70, and 90 dpi, the hearts of uninfected and MCMV-infected mice were evaluated by echocardiography . Briefly, mice were sedated with 2% isoflurane via nose cone inhalation and the heart rate, left ventricular internal diameter (diastolic/systolic), and left ventricular posterior wall thickness (diastolic/systolic) were measured ,41.At 70 and 90 dpi, mice were evaluated for viral reactivation from latency using the primary explant reactivation assay, as previously described . FollowiHearts were evaluated for phenotypic changes at all time points. Following analysis by echocardiography, hearts were fixed in 10% formalin, embedded in paraffin, and stained with either Alizarin red solution (4 per group) to evaluate calcification or hematoxylin and eosin (2 per group) to evaluate immune cell infiltration. Images were visualized with Nano Zoomer Digital Pathology 2 software. Hematoxylin and eosin (H and E) slides were blindly evaluated by a pathologist at the LSU School of Veterinary Medicine. In addition, all hearts were given an estimated pathology score to compare calcification between groups, as previously described . ScoringGAPDH, and fold change was determined. All hearts were individually analyzed, and then group averages were determined following the determination of fold change. All primers were synthesized by Integrated DNA Technologies ; they are listed in At 70 and 90 dpi, RNA was extracted from 0.1 g heart tissue, from 5 animals per group, using the RNeasy Mini Kit . Following RNA extraction, 100 ng of cDNA was synthesized per sample using the RT2 First Strand Kit per manufacturer’s instructions . Real-time PCR (RT-PCR) was conducted by using 25 primers sets specific to cellular genes of interest . The RT-g for 20 min. Lymphocytes were collected from the interface of the liquid layers and filtered again through a 40-micron strainer. Lymphocytes were pooled in each group and stained with CD3-FITC, CD4-PerCP-Cy5.5, and CD8-BV711 antibodies . All fluorophores were standardized with isotype controls  and compensation using fluorescence minus one (FMO) standards. Additionally, a PE-conjugated IE1-specific tetramer  synthesized by the National Institutes of Health Tetramer Core Facility at Emory was used to determine MCMV-specific CD8+ T cells. Flow cytometry was conducted on a Fortessa X-20 machine , and data were analyzed using FlowJo software .At 90 dpi, 5 hearts per group were collected for flow cytometry. Hearts were washed with PBS to remove peripheral blood, minced, and incubated in collagenase II solution  for 4 h at 37 °C. The tissue homogenate was then strained through a 40-micron cell strainer, layered on Lympholyte-M , and centrifuged at 500× t test to determine differences between individual groups. All statistics and figures were produced using Prism 8 software  Significance is shown as * p < 0.05; ** p < 0.001; *** p < 0.0001; and **** p < 0.00001.All results were analyzed by using group mean and standard deviation or standard error of the mean, depending on the number of replicates conducted. Significance was determined with ANOVA with multiple comparisons using Tukey’s post hoc test or Kruskal–Wallis with Dunn’s multiple comparisons test. Additional analysis was conducted by using Mann–Whitney U test or Student’s 6 PFU of wild-type MCMV by i.p. inoculation. Consistent with previous studies, GCV treatment significantly reduced viral replication in the spleen, liver, lungs, and salivary glands at 3, 7, and 14 dpi [Previously, we have shown that MCMV infection results in cardiac damage and dysfunction at 14 and 50 dpi. In order to further characterize the effects of MCMV infection within the heart, we questioned whether the damage and the dysfunction associated with MCMV infection of the heart were a result of viral modulation within the cell during the initial infection or whether they were consequences of viral replication. If viral replication is required, ganciclovir (GCV) treatment would significantly reduce MCMV replication within the heart and therefore limit cardiac dysfunction. For these studies, wild-type infected mice were either untreated or prophylactically treated with 50 mg/kg/day of GCV for 1 day and then as a therapeutic following infection for the duration of the study. At 1 day post-treatment, mice were infected with 1 × 10d 14 dpi . Due to d 14 dpi ,15,42. ABecause ganciclovir did not reduce acute cardiac dysfunction, a viral mechanism prior to DNA replication, due to the initial infection or immediate–early gene expression or the induction of a host factor that initiates heart damage could account for the dysfunction. Since US28 is present on the virion and exerts its signaling effects upon virus entry, US28 may play a role in exacerbating chronic diseases. Likewise, the M33 vGCPR counterpart in MCMV is also expressed prior to DNA replication, and both proteins have been implicated in modulating smooth muscle migration.6 PFU of KP, ΔM33, or US28+. At 3, 7, and 14 dpi, animals were sacrificed, and viral replication was evaluated using a plaque assay. As shown in Thus, we next explored whether vGPCRs contribute to cardiovascular dysfunction ,25,43,44To further discern differences between the wild-type virus and the mutant viruses, the viral DNA levels were evaluated. DNA was extracted, and qPCR was conducted to determine the viral copy number within the heart. Interestingly, both ΔM33 and US28+ infections in the heart resulted in significantly lower levels of viral DNA at 3 and 7 dpi when compared with the KP-infected hearts B.p = 0.13); however, when individually analyzed using a Mann–Whitney U test, increased calcification was observed in the US28+-infected animals (p = 0.02) compared with the uninfected controls (p = 0.07).We previously showed that MCMV infection results in significant calcification and collagen deposition during acute infection, and we questioned whether vGPCR function contributes to this phenotype ,39. To fcontrols . Though In addition to the calcification analysis, H and E staining was conducted to evaluate the damage and cellular infiltration within the heart during acute infection. This analysis revealed no differences between the groups at 3 and 14 dpi. However, at 7 dpi, MCMV infection caused mild myocarditis with lymphocyte infiltration, myofiber necrosis, and early stromal proliferation when compared with the uninfected controls . Owing tAs previously shown, MCMV-infected hearts demonstrated significant tachycardia compared with the uninfected control animals at 14 dpi; thus, we next explored whether vGPCRs contribute to MCMV-induced tachycardia . Echocar6 PFU of KP, ∆M33, or US28+ by i.p. inoculation and subsequently evaluated at 70 and 90 dpi. Similar to acute infection, at 70 dpi, there were no significant differences observed in calcification by Alizarin red staining or estimated pathology scoring (p = 0.07) when assessing the estimated pathology scores of the KP-infected hearts compared with the ∆M33-infected hearts that was not measured at 14 and 90 dpi between these groups  for reduced internal diameter during systole compared with the uninfected hearts  in the diastolic phase of the heartbeat. Furthermore, at 90 dpi  remodeling, as well as cytokines that have previously been shown to be altered from CMV infection ,47. MCMVThis preliminary snapshot of host genes also demonstrates that matrix metalloproteinases (MMPs) were highly upregulated in the MCMV-infected hearts when compared with the uninfected control animals. Although all three viruses were capable of inducing MMPs to some degree, the KP-infected animals demonstrated the highest induction, suggesting that in the absence of M33, MMPs and other ECM genes are subject to less modulation. However, this reduced modulation greatly varied between the genes; for example, MMP9 exhibited similar induction, whereas MMP12 was differentially expressed between the KP-infect hearts and the ∆M33-infected hearts. Because both MMP9 and MMP12 have been shown to be important in ECM remodeling, additional studies are needed to further understand this phenotype ,52,53.Conversely, SMAD signaling, growth factors, and most of the immune markers evaluated were not upregulated within the heart of the MCMV-infected animals. This may be due to the time point analyzed because the hearts are latently infected; however, given the exacerbated damage, we expected that there would have been an upregulation of these markers when compared with the uninfected hearts. Interestingly, there was an upregulation of IL6, TGFβ, and IL10 mRNA expression in the ∆M33-infected hearts that was not detected in the other groups. This suggests a role for M33 in the modulation of cytokine production in the heart. Recently, similar results have been found in aortic allografts at 30 dpi, where IL10 expression was significantly upregulated in the absence of M33 when compared with the wild-type MCMV-infected grafts . TogethePreviously, we demonstrated that MCMV readily reactivates from the heart using an explant reactivation assay and we hypothesized that repeated reactivations may induce changes in the microenvironment of the heart, which over time could exacerbate cardiovascular diseases . The ∆M3As shown in Long-term CMV infection drastically inflates the CMV-specific CD8 T-cell populations in HCMV-seropositive patients and MCMV-infected mice ,55,56. BHCMV seropositivity is associated with many cardiovascular diseases, including myocarditis, transplant vasculopathy, vascular sclerosis, and hypertension ,6,7,8,9.Similar to some of the other tissues, both ∆M33 and US28+ viruses disseminated to and replicated in the heart to comparable levels as wild-type KP during acute infection ,34. No sAs we have previously shown, latent MCMV infection exacerbates cardiac damage and dysfunction . To deteIn addition to calcification, the KP-infected animals had an increased expression of MMPs, which function in matrix degradation during ECM remodeling ,63. MMPsTo our surprise, the KP-infected mice did not exhibit an upregulation of signaling and immune markers compared with the uninfected animals , but ourFrom our studies, we propose that CMV replication causes phenotypic changes within the microenvironment of the heart following primary infection. CMV establishes latency within the heart and most likely further exacerbates damage and dysfunction through frequent reactivation events which produce progeny virus and the induction of inflammation. Because ∆M33 is deficient in reactivation from the spleen and lungs, it is possible that the reduced dysfunction observed at 70 dpi in the ∆M33-infected hearts may be associated with reduced in vivo reactivation . We showHCMV infection is associated with cardiovascular disease ,6,7,8,9.


CONSTANS-like (COL) gene family plays significant roles in the control of flowering, and its functions in Orchidaceae have been minimally explored. This research identified 68 potential COL genes within seven orchids’ complete genome, divided into three groups  via a phylogenetic tree. The modeled three-dimensional structure and the conserved domains exhibited a high degree of similarity among the orchid COL proteins. The selection pressure analysis showed that all orchid COLs suffered a strong purifying selection. Furthermore, the orchid COL genes exhibited functional and structural heterogeneity in terms of collinearity, gene structure, cis-acting elements within their promoters, and expression patterns. Moreover, we identified 50 genes in orchids with a homology to those involved in the COL transcriptional regulatory network in Arabidopsis. Additionally, the first overexpression of CsiCOL05 and CsiCOL09 in Cymbidium sinense protoplasts suggests that they may antagonize the regulation of flowering time and gynostemium development. Our study will undoubtedly provide new resources, ideas, and values for the modern breeding of orchids and other plants.The orchid is one of the most distinctive and highly valued flowering plants. Nevertheless, the  Vanilla genus, which belongs to the Vanilloideae family, has extensive usage in various industries, such as food, pharmaceuticals, cosmetics, beverages, and traditional crafts ..COL geneCOL genes: In the promoter regions of Orchidaceae COL genes  in A. shenzhenica, 2 (CsiCOL01 and CsiCOL03) in C. sinense, 2 (DcaCOL05 and DcaCOL09) in D. catenatum, 1 (DhuCOL07) in D. huoshanense, and 1 (VplCOL06) in V. planifolia, corresponding to the circadian expression pattern of COL genes [COL genes are related to the composition of cis-acting elements.Cis-acting elements in the promoters of orchid OL genes . the comg plants . Among tOL genes ,46. The COL genes during plant development. The COL genes showed different patterns of expression in the different tissues , which showed two β-sheets and three α-helices, 16 COLs  showed two β-sheets and two α-helices, DchCOL09 had two β-sheets and one α-helices, 2 COLs (VplCOL05 and VplCOL06) had two α-helices, and 3 COLs  exhibited only two β-sheets. Each strand in the asymmetric unit interacts with symmetrically related molecules on both sides to form an extended linear head-to-tail oligomeric configuration, resulting in an enhanced performance in transcriptional regulation [COL proteins are composed of an α-helix (Hh), extended strands (Ee), β-turns (Tt), and random coils (Cc), which, on average, account for 31.07%, 10.65%, 3.14%, and 55.15% of the protein structure, respectively  and PSEUDO-RESPONSE REGULATOR (PRR: Mol011035 and Mol029571) transcription factors, suggesting conserved functions of the genes within each cluster, such as, in plant growth, stress-related metabolic regulation [Mol011862) was significantly related to CsiCOLs in group I and group II. FLOWERING BHLH (FBH: Mol010847) was significantly correlated with CsiCOLs only in group I, while FK506-binding protein (FKBP12: Mol015806) was significantly correlated with CsiCOLs only in group III. Additionally, three genes were only significantly associated with CsiCOLs in group II, that is, GIGANTEA (GI: Mol017612), TARGET OF AT (TOE: Mol008285), and FLAVIN-BINDING KELCHREPEAT F-BOX1 (FKF1: Mol013985), respectively. This also indicates that the functions of CsiCOL genes diversified during evolution.To determine the potential transcriptional regulation mechanism of erformed . The resgulation , and thegulation . JUMANJICsiCOLs on the temporal association of flowering and floral morphogenesis , TERMINAL FLOWER 1 (TFL1), APETALA1 (AP1), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1), LEAFY (LFY), and AGAMOUS1 (AG1), based on gene ontology and the extant literature, which were then validated using quantitative real-time polymerase chain reaction (qRT-PCR) (FT/TFL1 genes form the phosphatidylethanolamine binding protein (PEBP) family, which has been implicated in activating flowering downstream of COL [AP1, SOC1, LFY, and AG1 in the regulation of flowering duration and floral patterning in orchids [CsiCOL05 had a significantly higher expression; meanwhile, for CsiCOL09, the expression level was much lower in gynostemium  was significantly upregulated compared to the control, and the expression level of two genes (CsiTFL1 and CsiAG1) was significantly downregulated in CsiCOL05-OE  . The FT/m of COL ,53,54. P orchids ,55,56,57ostemium A. The reCOL05-OE C. In conCOL09-OE D. In sumCOL gene family has been reported in many plants, it has rarely been reported in Orchidaceae. The orchid is a mainstay of the worldwide floriculture trade and a popular ornamental crop [COL gene family in Orchidaceae species. A comparison of COL gene families in seven orchids showed that they all have the typical conserved domains of the BBX and CCT domains [COLs, which respond to biotic [NFY) [COP1) [TPL) [Although the tal crop ,59, so t domains . The occo biotic  and abioo biotic  in angioic [NFY) , CONSTIT) [COP1) , and TOP1) [TPL) . Therefo1) [TPL) .COL gene family was systematically compared and analyzed. Seven orchids, Arabidopsis, and rice were used to construct a phylogenetic tree. However, not all of the COL proteins that are clustered in group I have two B-box domains. For example, CsiCOL04 and CsiCOL09 were classified in group I but contain only one B-box domain. In this study, the phylogenetic tree-based classification results are not exactly the same as in Arabidopsis [COL genes in accordance with that of the Orchidaceae genome indicates the conservation nature and necessity of the COL genes in orchids [D. huoshanense, which was much less than in V. planifolia (8). The significant proliferation of orchid COL duplicates in V. planifolia may be attributed to the protracted flowering duration through natural selection. The collinearity analysis revealed that segregation was key to COL gene family expansion. As the first study on COL gene families in orchids, our study serves as a useful data resource for future comparative and functional genome studies on COL gene families.In this study, the bidopsis ,32. The  orchids . During  orchids . There wCOL is a key regulator of photoperiod flowering [COL binds the conserved TGTG (N2-3) ATG motif in the FT promoter region, thereby activating FT/TFL to regulate the flowering time [FT and TFL1 have contrasting effects on both the flowering time and floral pattern [PaCOL1 in Arabidopsis exhibited earlier flowering under short-day (SD) conditions [CsiCOL05, CsCOL1, and CeCOL were overexpressed in Arabidopsis, resulting in early flowering and increased levels of AtFT expression under long-day (LD) conditions [FT/TFL from Oncidium Gower Ramsey and Dendrobium in Arabidopsis promoted or inhibited the flowering time and loss of inflorescence indeterminacy [bZIP) transcription factor FLOWERING LOCUS D (FD) plays a key role in the opposing interaction of FT and TFL1, which is dependent on competitive binding partners. This interaction triggers the transition from vegetative to reproductive growth by activating genes related to inflorescence and floral meristem identity, such as SOC1, AP1, and LFY [AG1 was found to be linked to the formation of the column in orchids [CsiCOL05 and CsiCOL09 in protoplasts, we speculated over the antagonistic effects of CsiCOL05 and CsiCOL09 on the regulation of the flowering time and gynostemium development in C. sinense  [CsiCOL5 exhibited heightened expression throughout all tissues, underscoring its crucial involvement in the overall growth and development of C. sinense.In addition, in grapevine, dormancy . MaCOL1 e banana . TaCol-Bin wheat . The parin wheat . In pak rs, ABF) . Upon ABCOLs, serving as key functional genes governing abiotic stress responses, flowering time regulation, and flower development within the Orchidaceae family, represent a valuable resource for enhancing orchid breeding. For instance, the Cymbidium gynostemium-like perianth variety will lose its floral scent [CsiCOLs. Moreover, a majority of orchids produce exceedingly minuscule seeds, often described as ‘dust-like’ [COL gene has the potential to govern seed size in plants [With the application of cell engineering and gene editing technologies in orchid molecular breeding ,86, we aal scent ,87, whilst-like’ ,89. Intrn plants ,91. ThisCOL proteins were identified as containing both B-box and CCT domains [COL genes in the genomes of C. sinense, P. equestris, D. catenatum, D. chrysotoxum, D. huoshanense, V. planifolia, and A. shenzhenica were identified using the Hidden Markov Model (HMM) program and related Pfam accessions (B-box and CCT domains corresponding to PF00643.19 and PF06203.9). All selected COL proteins were further identified using the Pfam database ) and Blastp in NCBI ). The conserved domains B-box and CCT were confirmed. In order to distinguish the COL genes, we named them on the basis of their physical location on the chromosomes in the orchid’s genome. Basic information on the number of amino acids, molecular weight, theoretical isoelectric point (pI), and instability index  was obtained using the ProtParam tool ). Then, the subcellular location information was obtained using the online tool BUSCA ). All the basic information of the COL genes can be found in All  domains . All COLCOL genes, the phylogenetic tree was constructed using COL proteins from seven orchids, Arabidopsis, and rice. The AthCOL and OsaCOL protein sequences come from the TAIR database ) and Rice Genome Annotation Project ). Sequence alignments were performed using the most accurate algorithm, JTT + I + G4, with 1000 cycles of iterative refinement, using MAFFT v.7.475 [To explore the phylogenetic relationships and taxonomy of  v.7.475 . The phy v.7.475 , with th v.7.475 .COL genes in C. sinense and the other five plant species  was identified using MCScanX [COL genes were mapped to chromosomes based on physical location from the orchid genome database, the TAIR database, and the rice genome annotation project. Gene colinear relationships were visualized using Tbtools v1.125 and Circos software v2.0 [Chromosomal location, comparative genome collinearity analysis, and selective pressure. The collinearity relationship of  MCScanX . The corare v2.0 . KaKs_Caare v2.0  was thenCOL genes was obtained from seven Orchidaceae genomes. Conserved motifs were identified using the MEME online site ) with the following parameters: maximum motifs number, 10; minimum and maximum widths, 6 and 50. The basic information about the sequence of the motifs is listed in Basic information, such as the physical location, amino acid sequence, and nucleotide sequence, of orchid COL genes were collected. This analysis was carried out with PlantCARE ) [For the analysis of cis-acting elements in their promoter region, the upstream sequences (2000 bp) of the orchid y 2023)) , and they 2023)) .C. sinense ‘Qi Hei’ is a famous traditional cultivar in China. For the ABA treatment, we used 2-year-old C. sinense ‘Qi Hei’ in flowerpots sprayed weekly with 100 μM ABA for one month, with deionized water treatment as control groups. Each biological replicate was a mixture of three plants. All the plants in this study were grown in the greenhouse of the Institute of Environmental Horticulture of the Guangdong Academy of Agricultural Sciences . The greenhouse was maintained at 25 ± 1 °C and 80% humidity. Roots, stems, leaves, flowers, and fruit tissues were collected from the cultivated plantlets. All the samples were collected and immediately frozen in liquid nitrogen and then stored at −80 °C until they were used for further analysis.https://swissmodel.expasy.org/interactive, (accessed on 25 February 2023)) [COLs. The tertiary structure is rainbow-colored to represent order from the N-terminus to C-terminus. The program SOPMA ) [SWISS-MODEL (y 2023))  was usedy 2023))  was usedCsiCOLs activity, transcription factors whose function has been verified in Arabidopsis [C. sinense, including TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATINGCELLFACTOR (TCP) , PHYTOCHROME AND FLOWERING TIME1 (PFT1), GI, JMJ28, FBH1, FBH2, FBH3, FBH4, CYCLING DOF FACTOR (CDF) , TOE1, TOE2, TOE3, CRYPTOCHROME (CRY) (CRY1 and CRY2), PHYTOCHROME-DEPENDENT LATE-FLOWERING (PHL), FKF1, PHYTOCHROME (PHY), PHYA, PHYB, HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENE 1 (HOS1), TIMING OF CAB EXPRESSION 1 (TOC1), PRR , CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), SUPPRESSOR OF PHYTOCHROME A (SPA) , SK12, FKBP12, and EARLY FLOWERING 3 (ELF3) (To predict the regulation of bidopsis  were use3 (ELF3) . In addiC. sinense were carried out based on previous protocols [CsiCOL05 and CsCOL09 into the PAN580-GFP vector. The aforementioned vectors containing pAN580-GFP, pAN580-CsiCOL05-GFP, and pAN580-CsCOL09-GFP were then introduced into Escherichia coli DH5α competent cells  according to the manufacturer’s guidelines. This step was followed by large-scale bacterial propagation and extraction of plasmid DNA, using the Endo-Free Plasmid Maxi Kit . The resulting plasmid DNA was then concentrated and adjusted to various concentrations, up to 2.0 μg/μL, before being introduced into orchid protoplasts. After incubation at 23 °C in a light-free environment for 16 h, the fluorescence emitted by the GFP or GFP-protein fusions could be observed using an LSM710 confocal laser scanning microscope. For nuclear visualization, the transfected protoplasts were stained with 50 μg/mL DAPI  at 37 °C for 10 min. Excitation of DAPI signals was performed with a blue diode laser, using a 405 nm excitation line with a 485 nm long-pass barrier filter.Protoplast isolation and transfection from the leaf bases of rotocols ,103. The5) were collected independently in three biological replicates and stored at −80 °C immediately after being frozen in liquid nitrogen. Total RNA was extracted from these samples, using TRIzol reagent . Then, using 1 μg RNA, a 20 μL cDNA system was synthesized according to the guidelines of the PrimeScript™ RT Reagent Kit with gDNA Eraser . qRT-PCR was performed on the Bio-Rad iCycler Real-Time PCR Detection System . This was performed with three biological replicates, using TaKaRa SYBR Premix Ex Taq™ . The total reaction system consisted of 20 μL containing 10 μL of SYBR Premix (2×), 1 μL cDNA, 1 μL each of sense and antisense primer (10 μM), and 7 μL of ddH2O. The qRT-PCR program was structured as follows: an initial predenaturation phase at 95 °C for 1 min, followed by 40 cycles of denaturation at 95 °C for 10 s, annealing at 56 °C for 30 s, and a final extension phase at 72 °C for 30 s. We used Primer Premier 5.0 for primer pair design, and the NCBI Blast program was used to determine the specificity of all primers (see C. sinense was used as an internal reference. Relative expression levels were calculated using the 2−ΔΔCT method [The transfectants (5 × 10mers see . The β-aT method .COL genes were successfully identified across seven distinct orchid species, and their phylogenetic tree, gene structure, chromosome localization, collinearity, gene replication, selective pressure, cis-acting elements, expression patterns, and protein structure were characterized. Furthermore, we delved into the regulation of co-activity-associated transcription factors within C. sinense. Remarkably, we conducted an exploration of subcellular localization and performed regulatory analyses through the transient overexpression of two CsiCOLs in Cymbidium protoplasts. We plotted potential regulatory patterns concerning their impact on flowering time and flower development. Our findings offer valuable insights and a conceptual foundation for exploring the unique functions of orchid growth and development, which carry significant implications for contemporary orchid breeding practices.Within the scope of this study, a total of 68


KRAS gene and overexpression of protein products of the MYC and ARF6 genes occur frequently in cancer. Here, the inseparable relationships and cooperation of the protein products of these three genes in cancer malignancy and immune evasion are discussed. mRNAs encoded by these genes share the common feature of a G-quadruplex structure, which directs them to be robustly expressed when cellular energy production is increased. These three proteins are also functionally inseparable from each other, as follows.　1) KRAS induces MYC gene expression, and may also promote eIF4A-dependent MYC and ARF6 mRNA translation, 2) MYC induces the expression of genes involved in mitochondrial biogenesis and oxidative phosphorylation, and 3) ARF6 protects mitochondria from oxidative injury. ARF6 may moreover promote cancer invasion and metastasis, and also acidosis and immune checkpoint. Therefore, the inseparable relationships and cooperation of KRAS, MYC, and ARF6 appear to result in the activation of mitochondria and the driving of ARF6-based malignancy and immune evasion. Such adverse associations are frequent in pancreatic cancer, and appear to be further enhanced by TP53 mutations.Mutations in the Video AbstractThe online version contains supplementary material available at 10.1186/s12964-023-01130-3. KRAS gene, and protein overexpression of c-MYC (referred to as MYC) and ARF6 are frequent in many types of cancers. KRAS mutations are well known to promote oncogenesis [TP53 is the most frequently mutated gene in human cancers [KRAS and TP53 genes, and the overexpression of MYC and ARF6 proteins are all prevalent [Mutations in the ogenesis , MYC oveogenesis , and ARFogenesis . Moreove cancers . Cancer revalent . The 5-yrevalent , and unfTP53 mutations may enhance the relationships and cooperation of these three musketeers by upregulating glucose uptake and the mevalonate pathway (MVP) activity, and by stopping the p53-mediated induction of certain miRNAs.Here discussed are that KRAS, MYC, and ARF6 are biochemically and functionally closely related with each other in promoting cancer malignancy and immune evasion. KRAS, MYC, and ARF6 mRNAs have the G-quadruplex (G4) structure in the 5'-untranslated region [ARF6 mRNA levels do not necessarily correlate with ARF6 protein levels in cancer cells [TP53 are known to promote cellular glucose uptake [TP53 mutations appear to be efficient in increasing KRAS, MYC, and ARF6 protein expression via promoting glycolysis and ATP production.d region . Althougd region . Thus, aer cells . Moreovee uptake . Thus, TMYC gene expression is downstream of RAS signaling [MYC will be constitutively expressed in the presence of oncogenic mutations of KRAS. Moreover, KRAS may also promote the eIF-4A-dependent translation of MYC and ARF6 mRNAs [PDCD4 gene, which is translated into the negative regulator of eIF-4A [KRAS mutations appear to cause the overexpression of MYC and ARF6 proteins in cancer cells. Moreover, growth factor receptor tyrosine kinases (RTKs) are frequently overexpressed in cancer. RAS is located downstream of RTK signaling. Thus, not only RAS mutations, but the overexpression of RTKs and their activation might also often cause ARF6 and MYC overexpression.ignaling . Hence, F6 mRNAs , 13. In f eIF-4A . Thus, KRAS isoforms are frequently mutated [KRAS mutations are predominant in cancer, particularly in PDAC, and 90% to 95% of PDACs have this mutation [KRAS mutations are also frequently found in colorectal cancer, in which approximately 35% have KRAS mutations [NRAS mutations are found in 15% to 20% of melanomas, and HRAS mutations are found in about 10% of bladder cancers and cervical cancers [i.e., which amino acid is frequently mutated) of KRAS and other RAS genes also varies substantially among tumors of different tissue origin, and among tumors of patients with different ages at diagnosis [There is a marked bias among cancer types as to which genes among the  mutated . KRAS mumutation , 5. KRASutations . On the  cancers . MoreoveRAS genes, the KRAS gene utilizes rare codons [KRAS, the G4 structure in the mRNA and the rare codons in the gene, will prevent the excessive expression of its protein product, and hence its mutations may be favored over mutations in other RAS genes in certain types of cancers. However, this notion still may not fully explain why KRAS mutations are so much more common in PDAC than in other types of cancer.Unlike other e codons . Thus, te codons . Thus, tEach isoform of the RAS protein undergoes different lipid modifications through different intracellular transport pathways, and hence localize to different microdomains of the plasma membrane –20. FurtThe ARF-GTPases appear to be the evolutionarily oldest type of small-GTPases, and play essential roles in the life of cells , 23. ThiKRAS mutations . AMAP1 contains several protein–protein interaction modules, including an SH3 domain and proline-rich regions [i.e., enhanced PD-L1 expression at the cell surface) and acidosis , which both favor cancer immune evasion [Like other small-GTPases, GTP-ARF6 uses effector proteins for its downstream signaling. AMAP1  is a major downstream effector of ARF6 . Like AR regions . Via the regions , 34. The regions . The occ regions –39. Ther evasion . In part evasion , see latThe overexpression of RTKs is a major risk factor of cancer, as mentioned earlier. Such RTKs include epidermal growth factor receptor, HER2 , platelet-derived growth factor receptor (PDGFR), and vascular endothelial cell growth factor receptor. ARF6 can be activated by these RTKs, in which a guanine nucleotide exchanger (GEF) for ARF6, GEP100, directly binds to the tyrosine phosphorylation sites of RTKs . Through12 activated under the GPCRs employs EFA6, which is a GEF for ARF6 [RTKs are not a major risk factor of clear cell renal cell carcinoma. This type of cancer often overexpresses autotaxin, which is also known as ectonucleotide pyrophosphatase/phosphodiesterase 2, and produces lysophosphatidic acid (LPA) from lysophosphatidylcholine extracellularly. LPA activates ARF6 via G-protein-coupled receptors (GPCRs), in which Gαfor ARF6 . Throughfor ARF6 .2+ [2+ [2+ to hydrolyze GTP-ARF6, and this should be tested in the future.AMAP1 has a domain homologous to GTPase-activating proteins (GAPs) of ARF-GTPases, and demonstrates GAP activity against the class I ARF-GTPases . On the 2+ . Intrigu2+ [2+ . Thus, iKRAS/TP53 double mutations. Gain-of function mutations of TP53 promote ARF6 activation by RTKs [TP53 [AMAP1 mRNA, and hence mutations in TP53 cause an increase in AMAP1 mRNA levels [The ARF6-AMAP1 pathway appears to be the major target of  by RTKs . In thisKs [TP53  promotesKs [TP53 . The gaiKs [TP53 ; and PDGKs [TP53 . In lineKs [TP53 . FurtherA levels .AMAP1 mRNA contains a 5'-terminal oligopyrimidine-like sequence, and requires eIF4E for translation [KRAS mutations appear to promote AMAP1 mRNA translation via enhancing mTORC1 and eIF4E [KRAS mutations, and also by normal RAS activated by RTKs. Indeed, the pattern of AMAP1 overexpression among cancers is similar to that of ARF6 overexpression [KRAS may also promote AMAP1 protein expression. nslation . KRAS sinslation , and mTOnslation . Thus, Knd eIF4E . As a repression , 32.MYC is a transcriptional cofactor binding directly to DNA. Chromatin immunoprecipitation studies have suggested more than thousands of genes as direct targets of MYC binding , 53. IntARF6 is also closely related to mitochondria. Because mitochondrial OXPHOS involves the production of reactive oxygen species (ROS), mitochondrial aggregation carries the risk of excessive ROS production by a ROS-induced ROS release (RIRR)-like mechanism . BindingThe ARF6-mitochondria link appears to be important for cancer cell invasion and metastasis. The ARF6-AMAP1 pathway promotes the invasion and metastasis of cancer cells, whereas cell invasion often involves cells entering physically narrow pathways, in which mitochondria tend to be densely accumulated. Cancer cells may moreover encounter an oxygen-rich environment during invasion and metastasis, which increases mitochondrial OXPHOS, which in turn increases the risk of RIRR. Intriguingly, moreover, the link between ARF6 and mitochondria only occurs in cell invasion, but not in two-dimensional cell migration . TherefoTP53 is mutated (Fig. Collectively, as KRAS and MYC activate mitochondria, KRAS activates ARF6, and ARF6 protects mitochondria, it is likely that KRAS, MYC, and ARF6 cooperatively control mitochondria in their biogenesis, metabolism, and integrity, which are all essential for cancer growth and survival; and, again, these events are likely to be further strengthened when ted Fig. .Fig. 1InTP53 is mutated, in which the TP53 mutation promotes G4 translation by promoting energy production, assists ARF6 activation, and increases AMAP1 mRNA levels. The end result of this cooperation appears to be the promotion of ARF6-based cancer invasion, metastasis, acidosis, radioresistance, and immune evasion, accompanied with increased mitochondrial activity (Fig. Here I discussed the mutually inseparable relationships and cooperation of KRAS, MYC, and ARF6 in cancer malignancy and immune evasion. The molecular bases of their interrelationships are the common usage of G4 in mRNAs, and the promotion of MYC and ARF6 expression by KRAS. Their relationships and cooperation may be strengthened when ity Fig. .Fig. 2KRARF6 and MYC mRNA translation, and the MVP inhibitor statins, which block ARF6 activation, can effectively mitigate ARF6-based malignancies and treatment resistance [KRAS mutations are now known to be druggable [Pharmacological inhibitors, such as the eIF4A inhibitor silvestrol, which blocks sistance , 41, 46.sistance . G4 struruggable , 61.Lastly, cancer patients often have circulatory disturbances –65, whic


Renal clear cell carcinoma (KIRC) is a malignancy of the renal epithelial cells with poor prognosis. Notably, the JAK-STAT pathway mediates cell proliferation and immune response. Accumulating evidence suggests that STATs act as immune checkpoint inhibitors in various cancers. Nonetheless, the role of STAT2 in KIRC remains elusive. Herein, analyses were performed using a series of interactive web databases including Oncomine, GEPIA and TIMER. In sub-group analyses, STAT2 was upregulated at both the mRNA and protein levels in KIRC patients. Besides, KIRC patients with high STAT2 expression exhibited a poor overall survival. Moreover, Cox regression analysis revealed that STAT2 expression, nodal metastasis and clinical stage were independent factors affecting the prognosis of KIRC patients. There was a significant positive correlation between STAT2 expression, and the abundance of immune cells as well as the expression of immune biomarker sets. In addition, STAT2 was found to be implicated in immune response, cytokine-cytokine receptor interaction, and Toll-like receptor signaling pathways. Also, several cancer-related kinases, miRNAs, and transcription factors associated with STAT2 were identified. Conclusively, we revealed that STAT2 is a potential prognosis biomarker and associated with immune infiltration in kidney renal clear cell carcinoma. This study offers additional data that will help in further research on the roles of STAT2 protein in carcinogenesis. Whist acknowledging the advances made in ultrasound and computed tomography for KIRC detection, 1/3 of patients are diagnosed at an advanced stage of the disease. This phenomenon ascribes to a lack of precise clinical symptoms of the disease. The prognosis of KIRC patients is poor particularly with patients in the advanced stage of the disease. Besides, less than 10% of KIRC patients in stage IV have a 5-year disease-specific survival. Despite checkpoint inhibitor-based immunotherapy becoming a superior therapeutic strategy for advanced malignancies, only a few immune checkpoint inhibitors have been identified for KIRC. Therefore, it is important to explore and authenticate precise and sensitive immune checkpoint inhibitors for KIRC immunotherapy.Renal clear cell carcinoma (KIRC) is a malignancy of the renal epithelial cells. It accounts for up to 80% to 90% of renal cell carcinomas. Annually, at least 209,000 people are diagnosed with KIRC across the globe. Moreover, more than 102,000 patients annually succumb to the disease.,4 The human genome codes for 7 STAT (STAT1/2/3/4/5A/5B/6) proteins. They function as transcriptional inducers, gene expression regulators via epigenetic modifications, and epithelial-mesenchymal transition mediators. Consequently, their functions generate a pro-tumorigenic microenvironment thereby promoting self-renewal and differentiation of cancer stem cells as well as establishing the formation of pre-metastatic niche.,6 Accumulating evidence has demonstrated that inhibition of the JAK-STAT pathway is a potential target for drug development and immunotherapy in various cancers. In oral cancer, STAT2 is associated with activated T-Cell signature and better outcome. Moreover, high expression of STAT2 predicted poor prognosis in non-small cell lung cancer. STAT2 acted as a prognostic biomarker in colorectal cancer.The Janus kinase-signal transducers and activators of transcription (JAK-STAT) pathway regulates cytokine associated signaling by mediating cell proliferation, survival, differentiation, and immune response, which could influence tumorigenesis.We sought to explore the role of STAT2 in genomic alterations, its prognostic value, its associated biological functions, and its potential role in immune response. This was executed using multi-dimensional analysis tools of various public databases. As a result, our findings provide additional data for STAT2 and JAK-STAT pathway as potential therapeutic targets and treatment options for KIRC.www.oncomine.org) is a versatile systematic platform comprising 715 datasets and 86,733 samples. It was established for drug development and clinical practice. STAT2 levels in KIRC patients were compared to those of renal tissues of healthy persons by Oncomine analytic tools. A P value of .05 and a fold change of 1.5 were used as the thresholds. Then, the Student t test was used to evaluate the difference. This analysis was performed on October 30, 2019.Oncomine (www.cistrome.shinyapps.io/timer/) is a comprehensive resource used for the clinical relevance of tumor-immune infiltrations. STAT2 levels in different types of tumors were explored using the “Diff Exp” module. Also, the levels of STAT2 in KIRC and its correlation with the abundance of immune cell infiltrates were explored using the “Gene” module. Additionally, the “correlation” module was used to analyze the correlation between STAT2 level and gene markers of immune cells. The gene markers and tumor-infiltrating immune cells, including CD8+ T cells, T cells , B cells, monocytes, TAMs, M1macrophages, M2 macrophages, neutrophils, natural killer cells, dendritic cells (DCs), T-helper 1 (Th1) cells, T-helper 2 (Th2) cells, follicular helper T (Tfh) cells, T-helper 17 (Th17) cells, Tregs, and exhausted T cells had been reported in previous studies.–14 In the “survival” module, a Cox proportional hazard model was constructed to further identify the independent factors among immune cells influencing the prognosis of KIRC patients. These analyses were performed on October 30, 2019, while the cox proportional hazard model was constructed on August 26, 2020. These analyses were performed using The Cancer Genome Atlas (TCGA) KIRC dataset (n = 538).TIMER  is a portal for promoting gene expression in cancer subgroups. The TCGA analysis module and the Clinical Proteome Tumor Analysis Consortium analysis module were used to determine the mRNA and protein levels of STAT2 respectively. This was repeated for the different KIRC sub-groups. The Student t test was also performed in this portal. P values less than .05 (P < .05) indicated that there were significant differences between the sub-groups. These analyses were performed using the TCGA KIRC dataset (n = 538) on October 30, 2019.UALCAN  with 95% confidence interval (CI).The prognosis value of immune checkpoints in KIRC was analyzed with the Kaplan–Meier survival analysis. The median of STAT2 expression was used to divide KIRC patients into high and low expression groups. A log-rank test was used to evaluated the www.cbioportal.org) is a portal used to explore, visualize and analyze multidimensional cancer genomics data. This tool was used to obtain the expression data of 538 TCGA KIRC samples (TCGA firehose legacy). mRNA expression z scores (RNA Seq V2 RSEM) were obtained using a z score threshold of ± 2.0. Protein expression z scores (RPPA) were obtained using a z score threshold of ± 2.0. Also, genetic alterations associated with STAT2 expression, the prognostic significance of STAT2, and the neighboring gene networks associated with STAT2 were analyzed.cBioPortal (www.david.ncifcrf.gov/home.jsp) is a functional annotation tool used to identify enriched biological themes. The extracted neighboring genes related to STAT2 expression were submitted to DAVID 6.8 tool for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the R program was used to visualize the results using the “clusterProfiler” package. This analysis was performed on October 30, 2019.DAVID 6.8 (www.linkedomics.org) is a systematic platform used to explore and analyze cancer-related multi-omics data. The Pearson’s Correlation test was performed based on the data of TCGA KIRC samples. STAT2 associated genes were explored using the “LinkFinder” module. Subsequently, the “LinkInterpreter” module was used to transform the STAT2 and associated genes data into biologically comprehensible data through pathway and network analyses. The pathways and network analyses included GO, KEGG pathways, kinase-target, miRNA-target enrichment, and transcription factor-target network. The minimum number of genes (size), the simulation value, and the P value cutoffs were set at 3, 500, and .05 respectively. These analyses were performed using the TCGA KIRC dataset (n = 538) on October 30, 2019.LinkedOmics  is a comprehensive portal for identifying diseases associated with a specific target or potential drug targets associated with a disease. Herein, this tool was used to identify diseases associated with STAT2. This analysis was performed on October 30, 2019.Open targets (www.genemania.org) is a protein-protein interaction (PPI) network constructing a portal that helps in understanding the underlying functions of target genes. Kinase_LYN network, MIR-337 network, and ETS transcription factor network genes were submitted to GeneMANIA geared towards visualizing them and understanding their functions. This analysis was performed on October 30, 2019.GeneMANIA (STAT2 mRNA expression in KIRC tissues was observed (P < .05)     Fig. A. Based STAT2 mRNA was observed in KIRC patients compared to the normal healthy persons in the sub-group analyses based on sample types, race, gender, age, KIRC subtypes, tumor grade, cancer stages, and nodal metastasis status , progression free Survival (PFS), and disease-specific survival (DFS) was shown in Figures STAT2 expression and immune biomarker sets of KIRC was evaluated using TIMER. A significant positive correlation was found between STAT2 expression and the abundance of B cells , CD8+ T cells , CD4+ T cells , macrophages , neutrophils , and dendritic cells  in KIRC patients . Immune biomarkers of T cells , B cells (CD19 and CD79A), monocytes (CD86 and CD11) M2 macrophages , and neutrophils  were positively correlated with STAT2 (Table P < .05). Moreover, immune biomarkers of the CD8+ T cells (CD8A and CD8B) and Natural killer cells  showed a positive weak correlation with STAT2 (Table P < .05). Immune biomarkers of the dendritic cells showed a strong positive correlation with STAT2 except CD1C. Similarly, there was a significant positive correlation of immune biomarkers of Th1, Th2 , Tfh (BCL6 and IL21), and Treg  (Table P < .05). Moreover, STAT2 expression positively correlated with immune biomarkers of T cell exhaustion  (Table P < .05). These results indicated that STAT2 was highly significant in immune escape in the KIRC microenvironment. This demonstrated that STAT2 is a potential immunotherapeutic target for KIRC therapy.Further, the correlation between P = 2.69e-7)   KIRC patients exhibited STAT2 associated genetic alteration , XAF1 , PLCB2 , and MYO9B  was ranked as the top 4 . GO enrichment function analyses revealed that the STAT2-associated genes encoded proteins were implicated in T cell activation, adaptive immune response, cytokine metabolic process, immunological synapse, cytokine receptor binding and activity, and apoptosis  showed a positive correlation with STAT2 whereas 4562 genes (dark green dots) showed a negative correlation with STAT2  Fig. A. A tota,22 In order to verify whether STAT2 in KIRC could affect the prognosis because of immune infiltration, we next performed prognostic analysis of STAT2 in KIRC based on immune cells. We found that high STAT2 expression in enriched/decreased Basophils cohort  while high STAT2 expression of KIRC in enriched CD8+ T cell cohort was associated with a poor prognosis . A total of 4 miRNA target networks were significantly involved including MIR-337(GAGCTGG), MIR-296 (GGGGCCC), MIR-518F, MIR-518E & MIR-518A (AGCGCTT), and MIR-191(AGCGCAG) . In the same line, the top 5 most significant transcription factor targets were involved in V$ETS_Q4, V$NERF_Q2, V$NFKAPPAB_01, V$IRF_Q6, and V$STAT3_01 .The kinase, miRNA, or transcription factor targets of STAT2 in KIRC were determined using GSEA. LYN, LCK, JAK3, SYK, and HCK were the top 5 most significant kinase targets Table . A PPI n Aberrant expression and pleiotropic effects of STATs such as those of STAT2 result in dysregulation of antiviral immunity and tumor pathogenesis.,24 Accumulating evidence has highlighted the role of STATs as therapy targets or immune checkpoint inhibitors in various cancers.,26 However, the role of STAT2 in KIRC remains controversial. This study therefore investigated various roles of STAT2 protein in KIRC patients.STAT proteins are transcription factors that mediate various cellular processes among them differentiation, proliferation, invasion, and apoptosis. Moreover, high transcription levels of STAT2 was associated with better relapse-free survival in breast cancer.STAT2 was detected in KIRC patients thereby revealing that it was up-regulated at both the mRNA and protein levels in tumor tissues. Nevertheless, this was not the case in normal healthy persons. Similar results were obtained in subgroup analyses based on sample types, race, gender, age, weight, tumor grade, cancer stage, and nodal metastatic status. Prognostic analysis revealed that patients in the low STAT2 expression group exhibited a better overall survival. These findings demonstrated that STAT2 is a potential prognostic biomarker for KIRC. Actually, previous studies have suggested STAT2 as biomarker for many cancers. In non-small cell lung cancer, STAT2 was a prognostic biomarker and high mRNA expression of STAT2 was significantly associated with shorter overall survival. Correlation between expression of STAT2, and immune cells, as well as biomarker sets in KIRC patients, revealed that there was a significant positive correlation between expression of STAT2 and immune cells such as B cells, CD8+ T cells, CD4+ T cells, macrophage, Neutrophils, and dendritic cells. Similarly, there was a significant positive correlation between STAT2 expression and immune biomarker sets such as PD-1, CTLA4, and STAT3. These results corroborated with those of Laurence, who reported that there were double-positive CD4+ and CD8+ T Cells as checkpoint inhibitors in renal cell carcinoma (RCC). Elsewhere, Kovaleva reported that RCC-specific macrophages were suitable for therapeutic targeting in RCC. Notably, PD-1 plays a significant role in antitumor activity and has been confirmed to be an immune checkpoint across multiple malignancies.,31 On the other hand, CTLA4 is an immune checkpoint for antitumor immunological reactions. It facilitates the Tyk2-STAT3-dependent B-cell oncogenicity. Herein, we found a significant correlation between STAT2, immune cell, and biomarker sets in KIRC. These findings demonstrated that STAT2 is a potential immune checkpoint inhibitor in KIRC.STATs and the JAK-STAT pathway regulate cytokine associated inflammation and immunity in the tumor microenvironment. Of note, the Toll-like receptor is mainly produced by the innate immune cells which significantly mediate and regulate adaptive immune responses. Also, the Toll-like receptor signaling pathway is involved in cancer progression and metastasis. Thus, STAT2 might play an important function in immune escape in the KIRC microenvironment suggesting that STAT2 is a potential immune checkpoint inhibitor for KIRC therapy.Furthermore, STAT2 associated genes and their functions in the gene regulation network of KIRC were explored to verify that STAT2 is a potential immune checkpoint inhibitor in KIRC. The functions of STAT2 and its associated genes were primarily implicated in T cell activation, adaptive immune response, cytokine-cytokine receptor interaction, NOD-like receptor signaling pathways, and Toll-like receptor signaling pathway. This was in agreement with the result from a study by Govender who reported that STAT2 could regulate type I Interferon-enhanced IL-10 expression in CD4 T Cells. Moreover, the tumor microenvironment is significantly associated with therapeutic response and survival of patients. STAT2 in KIRC was found to be associated with the LYN and LCK kinases network. These kinase networks are involved in the regulation of tumor microenvironment and immune response. Phuong-Hien reported that LYN kinase in the tumor microenvironment exerts an important function in tumor progression of various cancers types. Similarly, a previous study reported that the molecular role of LYN in the control of immunoreceptors can switch to direct homeostasis or inflammation. LCK is an important molecule regulating the functions of T-cells. It is critical in tumor cell signaling and T-cell function. As such, STAT2 might regulate the immune response in the KIRC tumor microenvironment via the LCK and LYN kinase network.Tumor immune escape and the initiation of metastasis promote oncogenesis and tumor progression. Similarly, miR-296 was found to suppress tumor metastasis in colorectal cancer via S100A4. At the same time, a previous study reported that miRNA-518 suppressed tumor cell growth and induced apoptosis in gastric cancer. As a consequence, STAT2 can regulate tumor cell proliferation, invasion, and apoptosis via these miRNAs in KIRC.Several miRNAs linked to STAT2 including MIR-337, MIR-296, MIR-518F, MIR-518E, MIR-518A, and MIR-191 were identified. These miRNAs are implicated in the regulation of tumor cell proliferation, invasion, and apoptosis. Moreover, they act as biomarkers in various cancers. Our results were consistent with those of Stefan, who reported that serum miR-191 and miR-337-3 were potential biomarkers in RCC.Nevertheless, this study was limited by several factors. First, the prognostic value, genetic alteration, and associated genes were unverified by a different database such as GEO. As such, future studies should incorporate a verification step to improve the credibility of our findings. Moreover, additional experimental are essential to explore the localization of STAT2 in immune cells.In conclusion, our findings reveal that STAT2 was upregulated in KIRC, significantly and positively correlated with immune cells and biomarker sets. Also, it was implicated in immune response, cytokine-cytokine receptor interaction, and Toll-like receptor signaling pathway, indicating that STAT2 is a potential immune checkpoint inhibitor for KIRC therapy.Data curation: Heng Wang.Formal analysis: Heng Wang.Investigation: Tao Zeng, Wen Tian.Project administration: Jianzhong Ye, Wen Tian.Software: Heng Wang.Validation: Jianzhong Ye.Writing – original draft: Tao Zeng, Wen Tian.Writing – review & editing: Jianzhong Ye, Wen Tian.


Innate lymphoid cells (ILCs) are heterogeneous innate immune cells which participate in host defense, mucosal repair and immunopathology by producing effector cytokines similarly to their adaptive immune cell counterparts. The development of ILC1, 2, and 3 subsets is controlled by core transcription factors: T-bet, GATA3, and RORγt, respectively. ILCs can undergo plasticity and transdifferentiate to other ILC subsets in response to invading pathogens and changes in local tissue environment. Accumulating evidence suggests that the plasticity and the maintenance of ILC identity is controlled by a balance between these and additional transcription factors such as STATs, Batf, Ikaros, Runx3, c-Maf, Bcl11b, and Zbtb46, activated in response to lineage-guiding cytokines. However, how interplay between these transcription factors leads to ILC plasticity and the maintenance of ILC identity remains hypothetical. In this review, we discuss recent advances in understanding transcriptional regulation of ILCs in homeostatic and inflammatory conditions. Upon ac2Tbx21 gene) and production of IFNγ/TNF upon activation  develop to terminally differentiated NK cells (CD27- CD11b+ KLRG1+) with high cytotoxic capacity and with the ability to produce IFNγ  whereas T-bet induced expression of the genes which regulate responsiveness to IL-12   . Both T-2, Ifnγ) , 30. The2, Ifnγ) , 30. MorIn contrast to NK cells, differentiation of ILC1s depends on T-bet, whereas Eomes is dispensable for ILC1 development , 33, 37.ILC2s participate in immune response against helminths by producing type two cytokines IL-4, IL-13, IL-5 and IL-9 –42. AddiRora binds to promoters of Il13 and Il5 genes in ILC2s, suggesting that RORα can promote effector function of ILC2s   cells and LTi-like cells  and depend on T-bet, which is required for their development (- ILC3s but not LTi cells (ILC3 development depends on RORγt (encoded by rc gene) . ILC3s crc gene) . Moreoverc gene) . ILC3s c6- cells . CCR6+ Ike cells . Althougke cells , 68. ILCke cells , 68. LTike cells , 69–72. n TF Ahr , 68. Somelopment , 73, 74.Ti cells . It was Ti cells . In addiTi cells . GATA3 cTi cells , 52, 75.3Extensive research over the past decade revealed plasticity within all ILC subsets that is largely controlled by tissue-derived factors. Thus, inflammation, infection or changing environmental conditions lead to activation of numerous intracellular signaling pathways that induce production of cytokines which in turn induce changes in ILC phenotypes and their function , 76. TheDuring pathogen invasion or ongoing inflammation cytokine production by immune and non-immune cells drives ILC plasticity by regulating the expression of lineage-determining transcription factors which, in turn induce production of effector cytokines by ILCs , 76, 79.Toxoplasma gondii infection   , 67. SinCR+ILC3s , it is pimmunity , 67. In immunity . Interesimmunity . These sDistinct cytokines regulate ILC2 plasticity , 45. ThuTaken together, recent studies identified the network of TFs which cooperate with core LDTFs to control ILC effector functions and their identity. Therefore, in the next sections of this review we will focus on recent advances in understanding the potential mechanisms maintaining the transcriptional identity of ILC subsets.4via IL-12R signaling promotes IFNγ production by NK cells and ILC1s, while   . Furtherentium) , 115.Rorc in T cells  and PTGS2  and by suppressing alternative cell lineage genes , 145. Gipression , 147. Mopression , 149  infection, where they initiate type 2 immune response by producing IL-13 (Candida albicans infections (via formation of complexes with transcription factors directly promotes RORγt expression in iILC2s without affecting GATA3 expression (Current studies in mouse models indicate the existence of ILC2 subsets that differently respond to IL-25 and IL-33 in the lungs , 153. Nang IL-13 . At the ng IL-13 . Additiofections , 153. Thpression . IL-33 apression , 42, 154pression , 154. Sipression . AccordiNb infection Batf regulates expression of IL-4 and IL-13 in iILC2s but not in nILC2s (Il23r, Il17a, Il6ra and Il1b (The role of Batf in the maintenance of ILC2 phenotype has also been described , 156. Abn nILC2s . Upon viRORα, Gfi-1 and ST2, and concomitant upregulation of Ahr and Il23r (Similar to Batf, Bcl11b and Gfi-1 are the transcription factors maintaining ILC2 identity by promoting type 2 effector program and repressing ILC3 associated genes  Figure, 159. Adnd Il23r . Ahr hasnd Il23r . Given tnd Il23r , 115, Bcnd Il23r , 162. Adnd Il23r , 159. Atnd Il23r .Ilrl1 gene to support IL-33R expression (IL-33 pathway serves as an additional regulator of the ILC2 identity , 163. Itpression , 159. Thpression , furtherpression , 165. Th10Recent studies have led to great progress in the characterization of ILC development and plasticity. An important feature of ILCs is their ability to quickly respond to the changing environment caused by tissue damage, pathogen invasion or cell stress. The prompt ILC response is mediated by rapid cytokine production to promote protection against harmful stimuli. Emerging studies report that most ILC subtypes exhibit plasticity and can acquire phenotype of another ILC subset in response to environmental changes. ILC plasticity could be one of the mechanisms enabling rapid response to pathogenic stimuli. Transcriptome analysis of ILCs revealed the existence of intermediate transcriptional profiles within every main ILC subset.ILC identity is controlled by transcription factors. Transcriptome studies revealed the similarities between mechanisms regulating effector programs in T cells and ILCs. Like T cells, ILCs depend on the same lineage-determining transcription factors T-bet, Eomes, GATA3, RORα, RORγt for their development and function. It is becoming increasingly clear that complex transcriptional networks that regulate ILC identity utilize similar gene-regulatory mechanisms compared to T cells. It is well established in the literature that core transcription factors are required to control ILC effector functions, but recent studies also highlighted that the ratio between different transcription factors determines ILC identity and phenotype maintenance. Moreover, the role of TFs also depends on the developmental stage of ILCs. Some transcription factors are critical to determine ILC fate, while other TFs define phenotype of mature ILCs. Emerging data suggests that tissue microenvironment can also impact the expression of genes which define ILC phenotypes. Epigenetic studies uncovered the differences in regulomes between ILCs and T cells during development. However, more work is required to fully understand how different transcription factors and epigenomic elements control gene expression and lineage specificity in response to different pathogenic stimuli. Mechanisms of epigenetic control of ILC plasticity are still poorly characterized. Revealing how chromatin landscape is changed in ILCs in response to different stimuli may uncover previously unrecognized mechanisms of transcriptional control of ILC functions as well as their phenotype.Although ILCs are present in human tissues and contribute to the host protection, it is still poorly understood how ILC identity is regulated in humans. The changes in ILC composition have been described in human diseases. However, it remains to be determined whether changes in ILC composition occur because of ILC plasticity or mediated by mature or immature precursors during inflammation. The regulatory mechanisms and the functional role of ILC plasticity during ontogenesis remains to be explored. Finally, understanding the regulation of transcription factor networks in ILCs could uncover new therapeutic targets to treat autoimmune diseases and chronic infections.Study concept and design: AK, AT. Wrote and edited manuscript: AK, SS, EK, AT. All authors contributed to the article and approved the submitted version.


Seventeen of 20 patients with Tier 2 variants had TP53 variants, and there was a statistically significant association between SUVmax and the presence of TP53 variants . Analysis of the correlation between the sum of the Tier 1 and Tier 2 numbers and SUVmax showed a statistically significant correlation . In conclusion, patients with advanced ovarian cancer with SNVs/indels on NGS, especially those with TP53 Tier 2 variants, showed a proportional association with tumor SUVmax on preoperative PET-CT.This study investigated the association between maximum standardized uptake values (SUVmax) on preoperative 18-FDG PET-CT and next-generation sequencing (NGS) results in post-surgical ovarian malignant tissue in patients with advanced ovarian cancer. Twenty-five patients with stage IIIC or IV ovarian cancer who underwent both preoperative 18-FDG PET-CT and postoperative NGS for ovarian malignancies were retrospectively enrolled. Two patients had no detected variants, 21 of the 23 patients with any somatic variant had at least one single nucleotide variant (SNV) or insertion/deletion (indel), 10 patients showed copy number variation (CNV), and two patients had a fusion variant. SUVmax differed according to the presence of SNVs/indels, with an SUVmax of 13.06 for patients with ≥ 1 SNV/indel and 6.28 for patients without ( Patients with advanced-stage epithelial ovarian cancer show a poor prognosis . The resIt is now possible to perform NGS rapidly and efficiently compared to direct sequencing. With NGS, both detailed diagnosis and customized treatment selection  have become possible . In gyne18F-fluoro-2-deoxy-d-glucose positron emission tomography-computed tomography (18-FDG PET/CT) imaging scans can display the distribution of the drug in a three-dimensional image /body weight [g]).All p-values were obtained using two-tailed tests; p < 0.05 was considered the threshold for statistical significance. As this study consisted of retrospective data collection, informed consent was not required. This retrospective study was approved by the Institutional Ethics Committee of Daegu Catholic University Hospital  and was conducted in accordance with the principles of the Declaration of Helsinki.Data were analyzed using IBM SPSS statistical software . Comparisons of variables between groups were based on independent samples t-tests and Pearson’s correlation tests. n = 17), mucinous cystadenocarcinoma (n = 1), endometrioid carcinoma (n = 1), clear cell carcinoma (n = 2), and carcinosarcoma (n = 4).A total of 25 patients with stage IIIC or IV ovarian cancer were enrolled in this study. All enrolled patients underwent both preoperative 18-FDG PET-CT and postoperative NGS for ovarian malignancy at Daegu Catholic University Hospital . The medical and demographic characteristics of the enrolled patients are summarized in NGS results, including for SNVs/indels, CNVs, and fusion variants, were reported in this research. Of the 25 enrolled patients, two patients had no variants and 23 patients had at least one SNV/indel, CNV, and/or fusion variant . Of the p = 0.003) between those with or without SNVs/indels, with an SUVmax of 13.06 for patients with at least one SNV/indel variant and 6.28 for patients without an SNV/indel variant (p = 0.008). In addition, 17 out of 20 patients with Tier 2 variants had TP53 variants, and there was a statistically significant association between SUVmax and the presence of TP53 variants .The average SUVmax values for each variant on 18-FDG PET-CT are compared in  variant . The SUVp = 0.002). The Pearson’s correlation coefficient was 0.588, indicating a moderate correlation. However, there was no statistically significant difference in SUVmax between single tiers of SNV/indel, CNV, or fusion variants.As shown in KRAS, BRCA1, and BRCA2. Among the Tier 1 and 2 variants, the most common variant was TP53. The detected Tier 1 variants were as follows: two KRAS variants (8%) and three BRCA1 or BRCA2 variants (12%). Tier 2 variants were as follows: 17 TP53 variants (68%), two PIK3CA variants (8%), and one (4%) variant each for PTEN, FBXW7, ESR1, FGFR2, SPOP, NOTCH3, MSH3, FGFR4, NF1, CREBBP, and ARID1A.TP53 variants, and the SUVmax of tumors on preoperative PET/CT. Given recent developments in molecular genetics, immunological examinations, and cancer treatments, both poly (ADP-ribose) polymerase (PARP) inhibitors and immune checkpoint inhibitors are being actively studied as treatment options that could be used alongside chemotherapy or radiation therapy in gynecological oncology [BRCA analysis (via blood tests) and NGS results  are tests used to indicate PARP inhibitor treatment. Both disease-free survival and overall survival are improved when a PARP inhibitor is applied to patients with germline or somatic BRCA mutations [In our study, we found a correlation between the presence of SNV/indel mutations in patients with advanced ovarian cancer, particularly those with Tier 2 oncology . Among tutations ,12. Simiutations ,14. HoweAlthough PET/CT has limitations in detecting small metastatic lesions or carcinomatosis, PET/CT is frequently used to both preoperatively predict clinical stage in patients with suspected ovarian cancer and determine the extent of surgery . Among tNGS detects alterations, deletions, duplications, insertions, inversions, rearrangements, translocations, or combinations of these genetic changes in genomic segments. NGS results include readings for SNV/indel, CNV, and fusion variants. We note that the most valuable findings are usually determined from SNV/indel results . SNVs anIn our study, patients with advanced ovarian cancer with Tier 1 and/or Tier 2 SNVs (according to NGS) were proportional to the SUVmax of the tumor on preoperative PET-CT. Therefore, it might be inferred that advanced ovarian cancer patients with Tier 1 and/or 2 SNVs are likely to be affected in the chemosensitivity, radiosensitivity, and tumor proliferation domains ,16. A stTP53 mutations showed higher SUVmax values than those from patients without TP53 mutations [BRCA variants detected via NGS and SUVmax values [In one study, malignant tumors derived from breast, lung, and colorectal cancer patients with utations . In addiutations . Howeverx values . HoweverSeveral previous studies have investigated the correlation between SUVmax and gene variants ,27. AccoSome limitations of this study are that it was a retrospective study conducted at one hospital center, and it included only a small number of patients. However, as the first study on the association between SUVmax of preoperative 18 FDG PET-CT and postoperative NGS in patients with advanced epithelial ovarian cancer, it has clinical value. In addition, few studies have investigated NGS finings, SUVmax detected via PET/CT, and response to immune checkpoint inhibitors. Based on the results of the present study, there is an association between preoperative PET/CT SUVmax and the presence of SNVs in postoperative NGS findings, and it is possible that these findings have implications with respect to a better response to immune checkpoint inhibitors. However, further research is needed.TP53 Tier 2 variants, showed a proportional association with tumor SUVmax on preoperative PET-CT.In conclusion, patients with advanced ovarian cancer with SNVs/indels on NGS, especially those with


Desulfovibrio, are responsible for the active generation of H2S in swine production waste. The model species for sulphate reduction studies, Desulfovibrio vulgaris strain L2, was previously isolated from swine manure characterized by high rates of dissimilatory sulphate reduction. The source of electron acceptors in low-sulphate swine waste for the high rate of H2S formation remains uncertain. Here, we demonstrate the ability of the L2 strain to use common animal farming supplements including L-lysine-sulphate, gypsum and gypsum plasterboards as electron acceptors for H2S production. Genome sequencing of strain L2 revealed the presence of two megaplasmids and predicted resistance to various antimicrobials and mercury, which was confirmed in physiological experiments. Most of antibiotic resistance genes (ARG) are carried by two class 1 integrons located on the chromosome and on the plasmid pDsulf-L2-2. These ARGs, predicted to confer resistance to beta-lactams, aminoglycosides, lincosamides, sulphonamides, chloramphenicol and tetracycline, were probably laterally acquired from various Gammaproteobacteria and Firmicutes. Resistance to mercury is likely enabled by two mer operons also located on the chromosome and on pDsulf-L2-2 and acquired via horizontal gene transfer. The second megaplasmid, pDsulf-L2-1, encoded nitrogenase, catalase and type III secretion system suggesting close contact of the strain with intestinal cells in the swine gut. The location of ARGs on mobile elements allows us to consider D. vulgaris strain L2 as a possible vector transferring antimicrobials resistance determinants between the gut microbiote and microbial communities in environmental biotopes.Sulphate-reducing bacteria, primarily  Desulfovibrio, also occur in the animal and human intestine [Desulfovibrio in the gut on fatty liver in diet-induces obese mice and children with obesity [D. desulfuricans isolated from an immunocompetent patient with bacteremia was susceptible to penicillin (MIC of 4 μg/mL) and other antimicrobial agents [Desulfovibrio evaluated at the Mayo Clinic from 1997 to 2013, which included D. legallii, D. desufuricans, D. fairfieldensis, D. intestinalis and D. piger, were susceptible to penicillin, metronidazole and carbapenems [Desulfovibrio spp. were highly susceptible to sulbactam-ampicillin, meropenem, clindamycin, metronidazole and chloramphenicol, but generally showed high MICs to piperacillin and piperacillin-tazobactam [Studies of antibiotic resistance genes (ARG) have mainly focused on pathogenic and commensal bacteria and paid less attention to environmentally relevant microorganisms. Sulphate-reducing bacteria (SRB) are a functional guild of prokaryotes of significant environmental importance due to the end product of their metabolism, hydrogen sulfide. Anaerobic SRB are common inhabitants of natural and technogenic ecosystems, such as marine and freshwater sediments, groundwater, soils and wastewater treatment facilities. SRB, primarily members of the genus ntestine ,5,6,7,8.ntestine ,9,10, inntestine , colorecntestine ,13, bactntestine ,15,16,17ntestine  and renantestine , are dis obesity . Little n MIC of  μg/mL anbapenems . Desulfozobactam .Desulfovibrio. The classical studies of J.R. Postgate reported the presence of megaplasmids in D. gigas, D. desulfuricans and D. vulgaris [D. vulgaris Hildenborough revealed plasmid-encoded nitrogen fixation, a type-III secretion system, and catalase [D. vulgaris plasmid encoding nif genes may be lost when the organism is cultivated in ammonium-containing media. The plasmid lacks homologs to previously characterized plasmid replication or partitioning genes. A small plasmid (8568 bp), pNC1, has been reported in D. africanus subsp. uniflagellum [D. africanus and Pseudomonas aeruginosa PA14. Plasmids often contribute to the spread of ARG via horizontal gene transfer between unrelated bacteria . The occvulgaris . Genome catalase . The D. lagellum . The clolagellum . Further2S formation [−3 day−1 and plays an important role in malodorous H2S production [4 use as a solid-phase electron acceptor by Desulfovibrio results in production of H2S concentrations that are compatible with those produced from soluble NaSO4 [4 reduction to H2S. SRB in wastewater treatment facilities can contribute to the undesirable continuous Hormation . Our preoduction . A microle NaSO4 . Lysine le NaSO4 . The sulDesulfovibrio spp. [Desulfovibrio in swine manure may originate from the pig gut. Recent reports have confirmed that Desulfovibrio is the dominant SRB in pig intestine [Desulfovibrio porci, has been isolated from pig feces [Desulfovibirio, D. desulfuricans L4 and D. vulgaris L2, were isolated from swine manure slurry [Desulfovibrio L4 genome revealed the presence of 10,876 bp long plasmid designated pDsulf-L4, containing a multidrug-resistance cassette consisting of the tetracycline resistance gene tetA (MFS family exporter), streptomycin resistance genes strA-strB (aminoglycoside phosphotransferases) and sulfonamide-resistance dihydropteroate synthase gene sul2. A horizontal acquisition of pDsulf-L4 from Shigella flexneri harboring the identical plasmid [D. desulfuricans L4 in the environment. Hydrogen sulphide production in swine manure slurry has been linked to rio spp. . The Desntestine ,33. A neig feces . Despiteig feces  and, cone slurry . Analysi plasmid  has beenD. vulgaris L2, as well as its ability to produce H2S from animal farming supplements such as L-lisyne suphate, gypsum and gypsum-containing plasterboard, remain unresolved. This study aims to characterize the physiology of the L2 strain with a focus on SO4-containing animal farming supplements and elucidate the antibiotic resistance mechanisms through genome sequencing.The presence of antibiotic resistance genes in The L2 strain was isolated from the settlement lagoon at a large swine finishing facility, as described previously . Briefly2SO4, 0.2 g KH2PO4, 0.25 g NH4Cl, 1 g NaCl, 0.4 g MgCl2·6H2O, 0.5 g KCl, 0.113 g CaCl2, 2 mL of vitamin solution, 1 mL of trace element solution, 1 mL each of Na2SeO3  and Na2WO4 (24.2 µM) solutions. Vitamin and trace element solutions were prepared as described by Widdel and Bak [Physiological tests were carried out in the modified WB medium that contained (per litre) 4.0 g Na and Bak . Each cu and Bak ,40. Lact−1 peptone and tryptone . Carbohydrate stock solutions were sterilized using polyethersulfone 0.22 µm Millex-GP filter units . If growth was observed, the culture was subcultured at least five times in the presence of each electron donor and acceptor to confirm their utilization. Growth was analyzed with the following electron donors: 7.5 mM formate, 9 mM acetate, 13.5 mM propionate, 7 mM butyrate, 7 mM pyruvate, 4.5 mM succinate, 9 mM fumarate, 7.5 mM malate, 5 mM citrate, 1 mM palmitate, 5 mM fructose, 5 mM glucose, 3 mM sucrose, 25 mM ethanol, 17 mM propanol, 13.5 mM butanol, 11 mM glycerol, and 1 g LThe tested soluble electron acceptors were the following: 28 mM sodium sulfate, 2 mM sodium sulfite, 20 mM sodium sulfite, 20 mM sodium thiosulfate, 10 mM fumarate and 5 mM calcium nitrate. Solid-phase electron acceptors, gypsum and gypsum plasterboard, were sterilized as powder by autoclaving. Each 12 mL culture vial received 100 mg of gypsum or gypsum plaster board. X-ray diffraction did not reveal impurities in the used gypsum specimen A. Plastehttps://github.com/najoshi/sickle; accessed on 28 January 2023).Genomic DNA was extracted from strain L2 cells using a Power Soil DNA Isolation Kit . The library for Illumina sequencing was prepared using the TruSeq Nano DNA Library Prep Kit . Sequencing on the Illumina MiSeq generated 4,590,696 paired-end reads . Overlapping paired-end reads were merged using FLASH v.1.2.11 , and lowDe novo assembly of MinION reads was performed using Flye v.2.7b [Genomic DNA of strain L2 was additionally sequenced on the MinION  using a Ligation Sequencing Kit 1D protocol and an R9.4 flow cell (FLO-MIN106). Sequencing resulted in 74,516 reads with a total length of ~552 Mbp. e v.2.7b , Illumine v.2.7b . Three ce v.2.7b .Desulfovibrio vulgaris Hildenorough . The sesediment . The phyf of 95% ,48. Stra−1  were as follows (in micrograms per milliliters): streptomycin, 800; tetracycline, 450; ampicillin, 750; kanamycin, 350; and gentamicin, 100. The strain could grow at HgDesulfobacterota, namely, sulfate permease, sulfate adenylyl transferase (sat), adenylsulfatereductase (aprAB) and dissimilatory sulfitereductase (dsrABD and dsrC). Also present are the genes for the adenylsulfatereductase-associated electron transport complex, QmoABC, heterodisulfidereductase, and the sulfite reductase-associated electron transport proteins, DsrMKJOP. The presence of several molybdopterin-dependent oxidoreductases of the Psr family is consistent with the ability of strain L2 to use alternative electron acceptors for anaerobic respiration. Moreover, the genome of strain L2 also contains cytochrome c oxidase, which can be involved not only in oxygen detoxification, but also in respiration under microaerophilic conditions.The genome of strain L2 consists of a chromosome of 3,611,640 bp and two circular plasmids 175,461 and 109,048 nucleotides long, designated pDsulf-L2-1 and pDsulf-L2-2, respectively. The chromosome contains all the genes required for dissimilatory sulfate reduction in D. vulgaris strains RCH1 (plasmid pDEVAL01), Hildenborough (plasmid pDV) and DP4 (plasmid pDVUL01). These strains are closely related to L2  to plasmids found in ed to L2 C and belDesulfovibrio species. Although sequences highly similar to some regions of pDsulf-L2-2  were found in various gamma-proteobacteria, a GeneBank search did not reveal sequences similar to the entire pDsulf-L2-2. The plasmid encodes several site-specific recombinases, transposases and toxin-antitoxin systems, as well as proteins involved in conjugative transfer and mobilization.Plasmids similar to pDsulf-L2-2 have not been found in any of the act) distantly related to SAT-2 streptothricinacetyltransferases and aminoglycoside acetyltransferase of the AAC(6′) family. Close homologues of these genes, including 100% identical integronintegrases, have been found in gamma-proteobacteria . The second closely located locus contains genes for the regulatory protein TetR and the tetracycline efflux pump Tet(C).A notable feature of the pDsulf-L2-2 plasmid is the presence of two gene clusters that can confer antibiotic resistance. The first is a class 1 integron  containiEnterobacteriaceae. The integron is then interrupted by an insert containing the oppositely oriented genes encoding the tetracycline-resistant ribosomal protective protein Tet(M), a conjugal transfer protein, two transposases, and the 23S rRNA methyltransferase CfrC conferring resistance to linezolid and phenicol antibiotics. Genes identical to tet(M) and cfrC were found in Firmicutes, Streptococcus pyogenes HKU419, and Clostridioides difficile 020696, respectively. The next is the second copy of the first gene of this integron, ANT(3″), it is followed by catB chloramphenicol acetyltransferase gene. This region is identical to the p035_A-VIM-1 plasmid of Klebsiella aerogenes 035. The next three genes are identical to the last three genes of the pDsulf-L2-2 plasmidintegron, qacE, sul1, and act.The chromosome of strain L2 also contains a class 1 integron with an integrase completely identical to that of the pDsulf-L2-2 integron . HoweverD. desulfuricans strain L4 isolated from the same manure storage lagoon.Another chromosomal locus contains genes for the regulatory protein TetR and the tetracycline efflux pump Tet(C). The sequences of these genes differed from the corresponding genes of the plasmid pDsulf-L2-2. However, a nearly identical region was found on the pDsulf-L4 plasmid of merRTPADE containing the genes for the regulatory protein MerR, the transport protein MerT, the periplasmic Hg2+—binding protein MerP, the mercuric ion reductase MerA, the transcription regulator MerD, the transport protein MerE and the protein containing the EAL domain. Such mer operons allow bacteria to detoxify Hg2+ by enzymatic reduction into volatile metallic mercury [mer operon is probably part of a transposon, since it is followed by genes for the resolvase and the Tn3 family transposase. Sequenced genomes of other Desulfovibrio species lacked similar mer operons, but gene clusters with identical nucleotide sequences are present in the chromosomes and plasmids of several species of Pseudomonas and Aeromonas.Plasmid pDsulf-L2-2 contains a mercuric resistance operon  mercury . In plasmerRTPCADE), with the exception of an additional merC gene for the mercury transport protein located between merP and merA. The nucleotide sequence identity between the plasmid and chromosomal mer operons is only 81–85%, indicating their independent acquisition by lateral transfer rather than transfer between pDsulf-L2-2 and the chromosome. Identical regions spanning both mer and tetR-tetC were found in plasmids and chromosomes of various Enterobacteriaceae , indicating a single acquisition event.Interestingly, the second mer operon is located on the chromosome of the L2 strain close to the tetR-tetC locus. This operon has a similar gene order and content  assembly showed that the genes encoding dissimilatory sulfite reductase were only identified in MAGs belonging to the Desulfovibrionaceae [Desulfovibrio, is an important constituent of microbial community in the animal intestine [The results of our study suggest that analysis . At the ionaceae . SRB havionaceae . There intestine ,5,6,7,8.Desulfovibrio in various pathologies has been documented, but the mechanisms remain largely unknown [D. fairfieldensis damages epithelial barriers and activate inflammation and pyroptosis in macrophages via outer membrane vesicles. The occurrence of type III secretion system (T3SS) on the pDsulf-L2-1 plasmid, revealed in our study, suggests its possible close contact with intestinal epithelial cells. T3SS is used by a number of pathogens, such as Escherichia coli, Salmonella, Yersinia and Pseudomonas [Rhizobium [Desulfovibrio species. Catalase, which plays a role in oxidative stress, has been identified as a putative T3SS effector shared between plant and animal pathogens [D. vulgaris contact with epithelial cells. The involvement of  unknown ,17. Nie  unknown  showed tudomonas , as wellhizobium , to deliathogens . The catDesulfovibrio susceptibility to clinically relevant antibiotics are based on physiological tests [Until now, the resistance determinants to tetracycline and other antimicrobials applied in animal husbandry have not been detected in SRB. Several reports of al tests ,21,22 anThe observed resistance of strain L2 to a number of antibiotics is most likely determined by laterally acquired resistance genes identified on the chromosome and plasmid pDsulf-L2-2. Aminoglycoside nucleotidyltransferase of the ANT(3″) family and aminoglycoside acetyltransferase of the AAC(6′) family are probably responsible for resistance to streptomycin, kanamycin and gentamicin. The observed resistance to ampicillin is probably due to beta-lactamases of the OXA-2 family. All of these resistance genes are located on a class 1 integron. Such integrons play a key role in the spread of antibiotic resistance because they can capture and express various resistance genes and are often located on plasmids and transposons facilitating their lateral transfer ,56. The Gamma-proteobacteria and Firmicutes, as evidenced by the presence of identical genes in these lineages and the absence of their close homologues in other Desulfovibrio species. The only exception is a region of about 2.4 kb containing tetR-tetC, which is common to the chromosome of strain L2 and the plasmid pDsulf-L4 of D. desulfuricans strain L4 isolated from the same site. This short (10876 bp) plasmid additionally contains strA-strB (aminoglycoside phosphotransferase) streptomycin resistance genes and the sul2 dihydropteroate synthase sulfonamide resistance gene [tetR-tetC locus in the L2 strain chromosome is linked to the mer operon, and the entire cluster was obtained from a member of the Enterobacteriaceae family, its independent acquisition by the L4 strain from the same donor is the most plausible scenario, although transfer from the L2 strain chromosome to the plasmid pDsulf-L4 of strain L4 cannot be ruled out. All of these resistance determinants were acquired by horizontal gene transfer from various nce gene , which aD. vulgaris, a model SRB. The D. vulgaris Hildenborough strain was isolated by J. R. Postgate in 1946 from clay near Hildenborough, Kent (UK) [Strain L2 belongs to ent (UK) . Two othent (UK) . All the2S is considered as one of the most important pollutants associated with livestock production [Desulfovibrio measured with a radioactive tracer in manure slurry at a large swine finishing facility [2S production. Our experiments with D. vulgaris L2 have shown that the gypsum and gypsum plasterboard used for animal bedding constitute a large reservoir of solid-phase sulphate that is used by Desulfovibrio and other SRB for their metabolism. The L2 strain grows at the same rate and produces the same amount of H2S from gypsum or gypsum plasterboard as it does from soluble sulphate. Hoduction . The higfacility  left ope4) has been used as a supplement to reduce the incidence of diarrhea and improve growth performance of piglets over the past decades [2S production in the animal gut.Currently, most of the supplemental lysine used in pig diets is in the form of hydrochloride, which contains 78.8% of lysine; more recently, lysine sulphate containing ≥54.6% of lysine has been introduced as an alternative source of supplemental lysine . Copper  decades . L-lysin