Vimentin, hyaluronan synthase-3, S100 calcium binding protein A6, TGFB1, CD44, CD55, and CD109 in European American and African American aggressive variant prostate cancer (AVPC) subtypes—mCRPC, neuroendocrine variant (NEPC), and taxane-resistant. The taxane-resistant gene FSCN1 was also expressed highly in single-cell subclonal populations in mCRPC. Furthermore, metronomic-topotecan single agent and combinations with DTX downregulated these EMT markers as well as CD44+ and CD44+/CD133+ “stem-like” cell populations. A microfluidic chip-based cell invasion assay revealed that METRO-TOPO treatment as a single agent or in combination with DTX was potentially effective against invasive prostate cancer spread. Our RNA-seq and scRNA-seq analysis were supported by in silico and in vitro studies, suggesting METRO-TOPO combined with DTX may inhibit oncogenic progression by reducing cancer stemness in AVPC through the inhibition of EMT markers and multiple oncogenic factors/pathways.Prostate cancer is the second leading cause of noncutaneous cancer-related deaths in American men. Androgen deprivation therapy (ADT), radical prostatectomy, and radiotherapy remain the primary treatment for patients with early-stage prostate cancer (castration-sensitive prostate cancer). Following ADT, many patients ultimately develop metastatic castration-resistant prostate cancer (mCRPC). Standard chemotherapy options for CRPC are docetaxel (DTX) and cabazitaxel, which increase median survival, although the development of resistance is common. Cancer stem-like cells possess mesenchymal phenotypes [epithelial-to-mesenchymal transition (EMT)] and play crucial roles in tumor initiation and progression of mCRPC. We have shown that low-dose continuous administration of topotecan (METRO-TOPO) inhibits prostate cancer growth by interfering with key cancer pathway genes. This study utilized bulk and single-cell or whole-transcriptome analysis [(RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq)], and we observed greater expression of several EMT markers, including The utilization of metronomic-like dosing regimens of topotecan alone and in combination with DTX resulted in the suppression of makers associated with EMT and stem-like cell populations in AVPC models. The identification of molecular signatures and their potential to serve as novel biomarkers for monitoring treatment efficacy and disease progression response to treatment efficacy and disease progression were achieved using bulk RNA-seq and single-cell-omics methodologies. The androgen receptor (AR) signaling pathway plays a pivotal role in prostate development and homeostasis, as well as in the progression of prostate cancer  disease  in tumors displaying mesenchymal phenotypes  and CD44of mCRPC . Furtherof mCRPC . TherefoP < 0.05) compared with conventional topotecan (CONV-TOPO) treatment in prostate cancer cell lines (P ≤ 0.05) smaller tumor volume (65.4% ± 11.2%) compared with control (136% ± 14%) and CONV-TOPO–treated animals (138% ± 10%) in an aggressive xenograft tumor model of human prostate cancer implanted in male NCr athymic mice (P ≤ 0.05) smaller tumor volumes (54.8% ± 16.5%) than animals receiving CONV-TOPO dosing (144% ± 11%) or the control group  smaller tumor volumes compared with ALZET control animals with no observable toxicities (Low-dose continuous drug exposure using metronomic-like (METRO) chemotherapy involves frequent administration of chemotherapeutic agents at low or fractionated doses at close intervals over prolonged periods of time . METRO ill lines . We thenmic mice . This ov; ref. 3 . ALZET pxicities . Moleculxicities . Severalxicities . Howeverin vitro model systems of treatment-refractory and treatment-emergent AVPC, we demonstrated that the METRO-TOPO showed efficacy as a single agent, as shown previously. We showed synergistic activity in combination with conventional taxanes (CONV-DTX) and METRO-TOPO. A microfluidic chip-based confined cell invasion assay was performed. The assay recapitulates the dimensionality of pores and longitudinal channel-like tracks encountered by cancer cells during migration to investigate the effect of METRO-TOPO on cancer cell invasion and stemness. Flow cytometry and cell sorting with prostate cancer stemness-specific antibodies  were accomplished to identify differential percentages of stem-like cell populations  in all prostate cancer subtypes, including EA and AA, to evaluate the impact of METRO-TOPO in eroding “stem-like” (CD44+/CD133+) cell subpopulations. The effect of METRO-TOPO treatment on EMT gene expression (GE) and protein expression was determined, and a comparative analysis with whole-genome transcriptomics data and reverse matching DEGs from patients with prostate cancer were used to examine the potential clinical significance of METRO-TOPO treatments.Therefore, we performed pretreatment versus posttreatment bulk and single-cell RNA sequencing (scRNA-seq) to identify differentially expressed genes (DEG) for prostate cancer subtypes of EA and AA origin and potential molecular pathways associated with METRO-TOPO activity in aggressive variant prostate cancer  at the tumor and subclonal levels and to gain molecular insights into METRO-TOPO activity. Furthermore, our RNA-seq and scRNA-seq data showed that METRO-TOPO treatment was potentially effective against the development of prostate cancer subclones with a reduction of treatment-resistant stem-like genes. Using in vitro studies, and patient databases , we conclude that METRO-TOPO has the potential to improve the clinical outcome in AVPC chemotherapy by enhancing the therapeutic efficacy of standard-of-care drugs and abrogating the possibilities of development of drug resistance. Such an evidence-based approach promises to minimize the chances of trial failures and improve the probability of clinical success.Therefore, using an innovative approach that integrated advanced molecular techniques [next-generation mRNA sequencing (mRNA-seq) and single-cell-omics technologies] with microfluidics, flow cytometry, MoFlo XPD Flow high speed-based cell sorting, cytotoxicity profiling, immunoblotting as Chemicals and Reagents, details are provided in the Low mCRPC/NEPC , ARHigh EA mCSPC , ARHigh EA mCRPC (C4-2B), ARHigh AA mCSPC (MDA-Pca-2b), and normal prostate  cell lines were obtained from ATCC. AA-ARHigh CSPC  and AA-ARLow mCRPC (RC43T) were obtained from our collaborator's lab . Cells were subcultured when they reached approximately 80%–90% confluence. Cell lines were used until passage 30. After removing from the cryo-storage (passage 2–3), cells were cultured and passaged for 2–3 weeks before beginning studies.ARThree-dimensional (3D) spheroids were harvested and transferred into a 96-well plate in 100 μL of recommended media. After 2 days of acclimation, 100 μL of media ± drug/well were added to each well containing a spheroid. On days 3 and 5, 100 μL of media/well were removed and replaced with 100 μL of fresh media with/without (±) drug/well. On off-media exchange days, 10 μL of media/well was removed and replaced with 10 μL of media ± drug. METRO-TOPO dosing was simulated by using 20x TOPO directly spiked into the wells at 10 μL in 190 μL of media. The CONV-TOPO was added as a bolus dose on day 0. METRO/extended exposure (EE)-TOPO treatment was given daily as a fractionated dose at 1/7th the CONV-TOPO. Total topotecan dosing was 100 nmol/L during each week of therapy. Control and treated spheroid were collected and stored in RNAlaterer (Qiagen) for RNA-seq. Fresh/live samples were used for scRNA-seq.Low mCRPC/NEPC PC-3 tumor model (3D spheroid) were assessed using RNA-seq. Pre- and post-drug exposure, as described above, tumor cells were harvested, and high-quality RNA was extracted using QIAshredder and RNeasy kit (Qiagen). RNA concentration and integrity were assessed using a Nanodrop-8000 spectrophotometer and Agilent 2100 Bioanalyzer. An RNA integrity number threshold >8 was applied, and RNA-seq libraries were constructed using Illumina TruSeq RNA Sample Preparation kit v2. Libraries were then size-selected to generate inserts of approximately 200 bp. RNA-seq was performed on Illumina's NovaSeq platform using a 150 bp paired-end protocol with a depth of >20 million reads per sample. Average quality scores were above Q30 for all libraries in both R1 and R2  was assessed by RNA-seq. Furthermore, the effects of METRO-TOPO and CONV-TOPO exposure for 6 weeks on AR1 and R2 . AA cell1 and R2 . LibraryP < 0.05 were considered the threshold for reporting significant DEGs. Heat maps were generated using unsupervised hierarchical clustering (HC) analysis based on top DEGs. Sequencing data on AA cell lines were compiled as FastQ files for downstream analysis  and Partek Flow software. Briefly, reads were preprocessed and mapped to the hg38 human genome build using the STAR Aligner tool. Next, mapped read counts were counts per million (CPM) normalized, and differential Gene Expression Profile (GEP) analysis was performed. Genes with mean fold change >|1| and analysis .scRNA-seq analysis was assessed for prostate cancer cell lines at baseline and TOPO-METRO  in the PC-3 tumor model (3D spheroid). Automated single-cell capture and cDNA synthesis were performed using the 10X Genomics Chromium platform. scRNA-seq–based GE analysis was performed on an Illumina HiSeq 2500 next-generation sequencing (NGS) platform by paired-end sequencing technique at 2*125 bp and 100 cycles using v3 chemistry.scRNA-seq datasets were obtained as matrices in the Hierarchical Data Format (HDF5 or H5). CellRanger, Seurat, and Partek Flow software packages were used to preprocess the data analysis. Highly variable genes were selected for clustering analysis based on a graph-based cluster approach. The visualization of cell populations was performed by t-distributed stochastic neighbor embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) for dimension reduction analysis for biomarker-based identification of subclones representing CSC-EMT, taxane-resistant cells, potential METRO-TOPO targeted subclones, and METRO-TOPO treatment-induced erosion of these subclones.Ingenuity Pathway Analysis  was performed using top DEGs to reveal molecular pathways/mechanisms, upstream regulator molecules, downstream effects, biological processes, and predicted causal networks governing prostate cancer subtypes and METRO-TOPO functions in AVPC .http://ualcan.path.uab.edu/index.html), a web-based tool for analyzing TCGA RNA-seq and clinical data, was used to evaluate the association of GE and patient survival in 31 types of cancers, including prostate cancer (http://gepia.cancer-pku.cn/), an interactive web-based tool for survival analysis based on GE, was also used. According to the characteristics of gene normalization, GEPIA allowed two different genes to be input at the same time for survival analysis  were used to compare transcriptome data on target candidate pathway genes with tumor metastasis and patient survival from the prostate expression data matrix . GE profe cancer . Furtheranalysis .+, CD133+, and double-positive cells using a Beckman Coulter Analytical Flow Cytometer—a CytoFLEX LX flow cytometer at 50,000 events/measurement. “Stem-like” cell populations were measured by assessing the shift in the mean fluorescence intensity by flow cytometry. Data were analyzed (gates were set), normalizing to unstained cells of each prostate cancer subtype. Ghost Dye Red 780 was used to detect live cells in each cell population. Furthermore, ARLow cells were seeded in 6-well plates and exposed to CONV-TOPO, METRO-TOPO, and CONV-DTX+METRO-TOPO as combination treatments calculated on the basis of our earlier studies  for flow cytometry. For combination, prostate cancer cell lines were treated with estimated MTT IC50, IC50/2 for CONV-DTX and MTT IC50, IC50/2 for METRO-TOPO .Prostate cancer cells were labeled with a binding buffer containing stemness markers CD44, CD133, or both antibodies. Cells were collected and quantified as CD44 studies . We havell lines . Plated TRO-TOPO . After 7In vitro cytotoxicity assays were performed using the MTT assay. Briefly, cells were plated in a 96-well culture plate at 2 × 103 cells/well and incubated for 24 hours at 37°C with 5% CO2. We have determined IC50 for MERO-TOPO, CONV-TOPO, and CONV-DTX for 48 and 72 hours for all prostate cancer cell lines (50 and IC50/2 are provided in 50 and IC50/2 estimated by MTT for each treatment protocol (CONV and METRO) for single agent  relative to untreated controls was calculated at each drug concentration.ll lines . The spele agent . For comCell death by apoptosis was measured using a Caspase-Glo 3/7 kit. Briefly, cells were seeded and treated according to the MTT protocol  in 6-well plates and exposed to TOPO-CONV, TOPO-METRO, CONV-DTX as a single agent and in combination with CONV-DTX+METRO-TOPO according to MTT protocol  in a double-blind manner.Cellular morphology was assessed after cells were seeded at 2.5 × 104 prostate cancer cells were harvested and resuspended in Aldefluor assay buffer containing the ALDH substrate, BODIPY-amino acetaldehyde (BAAA). Negative control samples were treated with diethylamino-benzaldehyde (DEAB), an inhibitor of ALDH1 enzymatic activity. Cells were incubated at 37°C and suspended in Aldefluor assay buffer. The brightly fluorescent ALDH+ cells were detected by BD LSR II flow cytometry.Aldehyde dehydrogenase (ALDH1) activity was assessed using an Aldefluor assay kit. Briefly, 1 × 10https://imagej.nih.gov/ij/).Pretreatment and Posttreatment cells were lysed in RIPA Lysis and Extraction Buffer (Thermo Fisher Scientific). Briefly, cells were seeded and treated according to the MTT protocol  width × (H) height = 3 × 10 μm2] or partially confining (W × H = 10 × 10 μm2) microchannels. The devices were placed on an automated Nikon Ti2 Inverted Microscope equipped with a Tokai stage-top incubator. Cell entry into the channels was recorded via time-lapse microscopy. Images were recorded every 10 minutes for 8 hours with a 10x/0.45 NA Ph1 objective. The percentage of cell entry into microchannels was calculated by measuring the number of cells entering the channels divided by the total number of cells seeded adjacent to the microchannel entrances.The fabrication of the polydimethylsiloxane (PDMS)-based microchannel device using standard multilayer photolithography and replica molding has been reported earlier . Briefly4 cells (mL/well), incubated overnight, and treated with CONV-TOPO, METRO-TOPO, CONV-DTX as a single agent, and CONV-DTX+METRO-TOPO in combination according to the MTT protocol , sorted using CD44P values <0.05 were considered significant. ANOVA was performed for continuous outcomes, and the Benjamini–Hochberg multiple testing methods were used as a post hoc test. The two-group t test was used to perform differential GE analysis between groups and detect the DEGs. Genes with mean fold changes>|1| and P < 0.05 were considered as the threshold for reporting significant differential GE. Finally, heat maps were generated using unsupervised HC analysis based on the top DEGs. Kaplan–Meier curves were generated using survival time and censored data to plot survival against high versus low expression of significantly associated genes. All statistical analyses were performed using R v4.1.0 and GraphPad Prism v9.0.All tests were two sided. Differences with https://www.ncbi.nlm.nih.gov/geo/), accession number GSE233341 or from the corresponding author upon reasonable request.The datasets generated during or analyzed during the current study are available at the NCBI Gene Expression Omnibus , ARLow/mCRPC/NEPC  and normal prostate cell lines  DEGs for ARLow/mCRPC/NEPC cell lines were the majority of EMT markers (upregulated) such as Vimentin (VIM), hyaluronan synthase-3 (HAS3), Laminin subunit beta-3 (LAMB3), S100 calcium binding protein A6 (S100A6), Serpin-E2 (SERPINE2), insulin-like growth factor binding protein-4 (IGFBP4), Annexin A2 (ANXA2), Annexin A2 pseudogene-2 (ANXA2P2), G protein-coupled receptor class C-5A (GPRC5A), and CD55, whereas downregulated genes were included endothelial transcription factor GATA2, nerve growth factor inducible VGF/VGF, insulin-like growth factor binding protein-2 (IGFBP2), solute carrier family 44-A4 (SLC44A4), guanylate cyclase-1 alpha-1 (GUCY1A1), NK3 homeobox-1 (NKX3-1), kinesin-1A (KIF1A), prune homolog-2 with BCH domain (PRUNE2), transmembrane serine protease-2 (TMPRSS2), and acid phosphatase-3  and ARHigh/mCSPC-AA  showed discrete DEGs  of prostate cancer subtypes (Low/mCRPC/NEPC prostate cancer (P < 9.43E-06) and EMT (P < 5.63E-06) as key pathways associated with prostate cancer development in AA  associated with the development of more aggressive forms  and its taxane-resistant version ARLow/mCRPC/NEPCtaxane-resistant (PC-3TXR and DUTXR). GEP data from baseline DUTXR and PC3-TXR indicated 3,289 and 2,215 genes were uniquely expressed in PC-3TXR and DUTXR, respectively. Furthermore, GEP also identified 2,968 commonly expressed genes in both sensitive and TXR cell lines , and “stem-like” subclonal cell populations in ARLow/mCRPC/NEPC  compared with ARHigh/mCSPC  prostate cancer cell lines  in ARLow/mCRPC/NEPC  compared with ARHigh/mCSPC  prostate cancer cell lines was also noted  and the clonally derived acquired taxane-resistant mCRPC cell line DUTXR. Some common overlap in GE was observed between the DUTXR and DU145 subclones, as expected . Howeverve DU145 . While tth DUTXR . OverallTop genes representing single-cell clusters that were shared and which were unique between DU145 and DUTXR were further investigated using IPA pathway analysis and upstream prediction. The following clusters were unique to DU145: Cluster 1, Cluster 3, Cluster 5, and Cluster 7. Cluster 8 was shared between both the lines . On the VIM, AHNAK2, ANXA1, ANXA2, CD109, CD44, CD59, GPRC5A, HAS, S100A6, TGFBR2. Moreover, the taxane-resistant gene FSCN1 was also found to be a common gene in both cohorts of prostate cancer cell line models , IGF2R (receptor for both insulin-like growth factor 2), IL11RA (cytokine), SEMG2 (semenogelin proteins), CCR2 (chemokine receptor type 2), TRAF3IP3 , GGTI-2154 (inhibitor of geranylgeranyltransferase I), L778123 (inhibitor of FPTase and GGPTase-I), TGFB1, and CXCL5 , Kaplan–Meier curves (P = 0.00051). Low expression of FSCN1 was associated with longer DFS. In contrast, high expression of FSCN1 was associated with poor DFS. Another top EMT marker, TGFB1, showed similar trends. Low expression was associated with longer DFS, whereas high expression was associated with poor DFS  for “stem-like” cells in prostate cancer  using immunoblotting in all prostate cancer cell lines. These data indicated that the protein expression of these top EMT markers was concurrently higher in ARLow/mCRPC/NEPC  compared with ARHigh/mCSPC  and ARHigh/mCSPC  cells , and lower than ARLow/mCRPC/NEPC prostate cancer  and taxane-resistant ARLow/mCRPC/NEPC  cells . EMT proLow/mCRPC/NEPC  cell lines, were assessed by MTT assay at their estimated IC50 and IC50/2 drug concentrations  was more potent at reducing cell growth compared with CONV (high dose) treatments at IC50 and IC50/2 (Low/mCRPC/NEPC (DURXR) prostate cancer subtypes. Results showed similar trends, greater potency was observed in METRO-TOPO and combination treatments.Previously we reported the cytotoxicity of CONV-TOPO, CONV-DTX, and METRO-TOPO for all cell lines . In thisd IC50/2 . Furtherd IC50/2 . The effThe effect of METRO-TOPO on cell density and cellular morphology was determined. In agreement with MTT assays, micrographs of prostate cancer cells exposed to all dosing regimens showed decreases in cell density compared with control cells . Treatme50 and IC50/2  and acquired taxane-resistant ARLow/mCRPC/NEPC (DUTXR). A significant increase in caspase 3/7 activity following each treatment compared with controls (50 and IC50/2 dose for metronomic topotecan) compared with CONV-TOPO and DTX . The greatest treatment-induced apoptosis was observed in combination with CONV-DTX+METRO-TOPO  in all cell lines  activity. The level of apoptosis was estimated at the ICcontrols . A greatll lines . The relll lines .S100A9, ESRP1, ASPM, EPCAM, CLDN7, CDH1, INPP4B, CD70, FN1, CDH11) and drug metabolism or resistance markers  compared with CONV-TOPO treatment  compared with CONV-TOPO (69%–84%) treatment  representing control (no drug treatment), 6-week EE-TOPO (extended exposure of topotecan), and 6-week CONV-TOPO treatment . Furtherr trends . Taxane-reatment . RNA-seqreatment .Low/mCRPC/NEPC  were treated with CONV-TOPO, METRO-TOPO, and combination CONV-DTX+METRO-TOPO treatments. Pretreated and posttreated prostate cancer cell lines were stained with stemness markers CD44, CD133, and both CD44/133 antibodies. All cell lines showed a greater reduction in the CD44high (“stem-like”) cell population following METRO-TOPO treatment compared with CONV-TOPO treatment. Furthermore, combination treatment reduced the highest percent of the CD44high cell population  downregulated following METRO-TOPO compared with CONV-TOPO treatment in PC-3M. Combination treatment exhibited the greatest downregulation (17%–56%) of all EMT proteins compared to other treatments  microchannels was greater in PC-3M compared with PC-3, suggesting that PC3-M cells are more invasive into mechanically challenging microenvironments. For confined (W × H = 10 × 10 μm2) microchannels, cell entry was greater for PC-3M compared with PC-3 but the difference was not significant.This experiment allowed us to study the effect of drug and dosing schedule as a single agent and in combination on tumor cell motility through microchannels of dimensions that mimic the size of confining pores and channel-like tracks encountered by migrating cells in vivo . Figure in vivo  showed tThe effect of drug treatment on PC-3M migration was accessed. PC3-M entry into confining microchannels was markedly suppressed upon TOPO-METRO single-agent and TOPO-METRO+CONV-DTX combination treatment. Of note, combination therapy resulted in a higher reduction in the invasiveness of PC-3M compared with other treatments .high (“stem-like”) cell populations by METRO-TOPO (81.0%) compared with CONV-TOPO treatments (71.5%). Furthermore, combination treatment showed the greatest reduction (63.4%) of the “stem-like” CD44high cell populations , and analyzed by flow cytometry. These results showed a greater reduction in CD44ulations ; Table 2Low/mCSPC/NEPCtaxane-resistant (DUTXR) cell lines. Combination treatment (CONV-DTX+METRO-TOPO) exhibited the greatest downregulation (26%–61%) of EMT proteins compared with other treatments  treatments. A marked suppression in cell survival was observed in the combination treatment compared with other groups  and combination treatment (3.2%) compared with CONV-TOPO (54%) and CONV-DTX (31%) treatments  treatment effect on CD44eatments .Next, we evaluated the potential effect of CONV-TOPO, CONV-DTX, METRO-TOPO, and combination (METRO-TOPO+CONV-DTX) treatment on the proliferative capacity of the DUTXR cells using the colony-forming assay. TOPO-METRO treatment alone significantly reduced colony number (16.4%) as well as colony size when compared with control or CONV-TOPO (67.0%) or CONV-DTX (33.5%) treatment. Furthermore, colony-forming assay results also showed the combination of METRO-TOPO+CONV-DTX treatments further reduced the colony numbers (9.53%) and size .VIM, AHNAK2, ANXA1, ANXA2, CD109, CD44, CD59, GPRC5A, HAS, S100A6, TGFBR2 in both cohorts. Importantly, the taxane-resistant gene FSCN1 was also identified as a common gene in both cohorts of prostate cancer cell lines.Drug development for aggressive, lethal treatment-resistant prostate cancer poses a significant challenge with few therapeutic successes . We used+ and CD44+/CD133+) in aggressive metastatic prostate cancer subtypes, which was confirmed by the RNA-seq and subclonal overexpression of several EMT markers . We also identified top DEGs and subclonal populations between the taxane-sensitive and taxane-resistant prostate cancer subtypes. These data provide greater insights into the acquisition of drug resistance and possibly novel treatment targets.We identified “stem-like” cell populations  is an important constituent of the stem cell niche (HAS3 (4.8-fold upregulation) resulted in the secretion of large amounts of HA bound to CD44+ in the “stem-like” cell population and plays a critical role in the development CSCs by regulating cell adhesion, migration, proliferation, differentiation, cancer metastasis, and multidrug-resistant  of EMP1 in our aggressive prostate cancer subtypes which regulates the expression of CD44 to promote stemness (TGFB1-induced EMT (TGFB1 in aggressive prostate cancer (3.41-fold in GE and ∼2-fold protein). Furthermore, we identified a higher percentage of TGFB1 overexpressed subclonal population (scRNA-seq) in aggressive taxane-resistant DUTXR compared with taxane-sensitive DU145 prostate cancer subtypes. We reported that METRO-TOPO (6-week EE) treatment reduces TGFB1 expression in subclonal populations. On the basis of evaluation of TCGA database, the downregulation of TGFB1 is beneficial and associated with increased patient survival.Importantly, we identified ll niche . CD44 isesistant . In our stemness . Furtheruced EMT , and our+ cells (96%) frequency and protein expression were greatest in taxane-resistant mCRPC cell lines. Furthermore, we identified a higher percentage of CD44-overexpressed subclonal population (scRNA-seq) in aggressive taxane-resistant DUTXR compared with taxane-sensitive DU145 prostate cancer subtypes. The ability to reduce stemness offers a potential strategy to treat aggressive and resistant prostate cancer. In our study, METRO-TOPO and combination (METRO-TOPO+CONV-DTX) treatment downregulated CD44+ (71.7% and 63.4%) cells along with protein expression (55% and 29%). We also observed high percentages of CD44+ cell populations in mCRPC cell lines and METRO-TOPO following single agent and in combination therapy with DTX reduced the amount of CD44+ cells significantly after treatment. Furthermore, METRO-TOPO treatment significantly decreased cell invasion and colony formation in aggressive and taxane-resistant forms of prostate cancer. Further studies employing CRISPR knockdown of HAS3 (and other top genes) are needed to further explore the significance of these novel mechanisms and their impact on cancer stemness and its association with METRO-TOPO treatment-related efficacy.Previous studies have reported that CD44 expression is greater in prostate cancer, and involved in cancer cell proliferation, invasion, migration, and drug resistance . Some stVIM as a top common EMT marker from RNA-seq and scRNA-seq for aggressive prostate cancer subtypes. Earlier studies also identified its role in invasion and metastasis in prostate cancer  prostate cancer subtypes. Our microfluid-based migration assay showed high cell invasion for these prostate cancer cell lines. Furthermore, METRO-TOPO as a single agent and in combination with DTX significantly reduced cell invasion in the mCRPC cell line model.Furthermore, vimentin . In our e cancer . We obseCD55 also promotes prostate cancer cell survival and metastatic lesion formation  in aggressive mCRPC/NEPC and taxane-resistant mCRPC/NEPC subtypes. We also identified a higher percentage of subclonal cell populations in aggressive taxane resistance prostate cancer subtypes overexpressing CD55 and CD109.Furthermore, ormation . Recent arcinoma . Our scRANXA3, ANXA2, and its pseudogene ANXA2P2 are overexpressed in various cancers, including prostate cancer, and facilitated transcription of the stemness genes Nanog, Sox2, and Oct4  in aggressive mCRPC/NEPC and taxane-resistant mCRPC/NEPC subtypes. We also identified greater protein expression levels of Nanog, Sox2, and Oct4 genes in mCRPC/NEPC and taxane-resistant mCRPC/NEPC prostate cancer subtypes. METRO-TOPO downregulated Oct-4 (64%), Sox2 (60%), and Nanog (39%) in mCRPC/NEPC (PC-3M) prostate cancer cell line model. METRO-TOPO also downregulated Oct-4 (41%), Sox2 (56%), and Nanog (49%) in taxane-resistant mCRPC (DUTXR) prostate cancer cell line model. The combination of METRO-TOPO and DTX exhibited similar results. A downregulation of Oct-4 (57%), Sox2 (47%) and Nanog (17%) in mCRPC/NEPC (PC-3M), and downregulation of Oct-4 (28%), Sox2 (61%), and Nanog (35%) in taxane-resistant mCRPC/NEPC (DUTXR) prostate cancer cell line model was observed after combination treatment.Earlier studies reported that and Oct4 . AHNAK2 with EMT . Our scRALDH1 is another stemness marker in prostate cancer and overexpressed in mCRPC  for taxane resistance in aggressive prostate cancer. Our results also showed that the treatment of METRO-TOPO (6-weeks EE) downregulates FSCN1 expression in subclonal populations in aggressive mCRPC/NEPC 3D tumor models, whereas CONV-TOPO resulted in increased expression (P < 0.05). Furthermore, TCGA patient cohort also revealed lower expression of FSCN1 associated with better DFS (P = 0.00051).Recent studies identified e cancer . We idenC1orf116, TUBB2B are common genes in taxane-resistant prostate cancer subtypes. C1orf116 is a novel EMT biomarker for prostate cancer, and our study showed 17-fold and 24-fold downregulation of this gene in taxane-resistant prostate cancer subtypes DUTXR and PC-3TXR, respectively. Contrastingly, TUBB2B was upregulated in both taxane-resistant prostate cancer cell lines, approximately 12-fold in DUTXR and approximately 43-fold in PC-3TXR. An earlier study revealed downregulation of C1orf116 is associated with poor prognosis in patients with lung and prostate cancer  prostate cancer. Further preclinical validation and single-cell multi-omics strategies using CRISPR-based knockout xenograft models and patient-derived organoids/xenografts will be necessary. Our approach in this study promotes the understanding of subclonal molecular pathways underlying the differential patterns of prostate cancer aggressiveness and drug response among various prostate cancer subtypes. Overall, our study identified novel mechanisms of action that can serve as a pipeline to advance METRO-TOPO as a potent clinical-trial-ready therapeutic option for the management of lethal prostate cancer with stem-like features. These mechanisms will be key in identifying patients with molecular signatures that are sensitive to treatment, and, most importantly, can identify biomarkers that can be used to monitor treatment effectiveness and disease progression.Cell invasion is one of the major characteristics of EMT transition and cancer progression . Our micSupplementary MethodsSupplementary MethodsClick here for additional data file.Supplementary Tables 1-7Supplementary TablesClick here for additional data file.Supplementary Figure 1Supplementary Fig. 1 shows Differentially expressed gene signature (DEGs) based on next gene sequencing (mRNA sequencing) for ARLow /mCRPC/NEPC  vs ARHigh /mCSPC  prostate cancer (PCa) cell lines and normal prostate cell lines RWPE1 and RWPE2. Volcano plots representing mRNA expression for all cell lines. (blue p<0.05 and gray>0.05) HeatMap representing Differentially Expressed Gene Signature (DEGs) for ARLow/mCRPC/NEPC  vs ARHigh/mCSPC  PCa and normal prostate cell lines RWPE1 and RWPE2 (FDR<0.05 and TOP-100).Click here for additional data file.Supplementary Figure 2Supplementary Fig. 2 shows Ingenuity pathway analysis (IPA) predictions for European American/ Caucasian American (EA/CA) ARHigh/mCSPC , ARLow/mCRPC/NEPC  and African American (AA) ARHigh/mCSPC (MDA-Pca-2b) PCa cell lines as well as normal prostate cell lines RWPE1 and RWPE2.   IPA predicted A) Diseases and biological pathways for development of ARLow/mCRPC/NEPC. Major pathways are cell movement, morbidity, mortality, migration, invasion, survival, viability and development of vasculature- vasculogenesis and angiogenesis. B) Causal network pathway for development of ARLow/mCRPC/NEPC, which include oxidative phosphorylation, p70S6K, unfolded response, TREM1 signaling, NF-kB signaling, ERK5 signaling, IL-8 signaling, BAG2 signaling, Integrin signaling and VEGF signaling. C) IPA predicted HIF1α and EMT as key pathways associated with PCa development in African Americans (AA).Click here for additional data file.Supplementary Figure 3Supplementary Fig. 3 shows Differentially Expressed Gene Signatures (DEGs) based on next-gene sequencing (mRNA sequencing) for ARLow/mCRPC/NEPC (PC-3DU145), ARLow/mCSPC/NEPC taxane resistant (DUTXR and PC-3TXR) PCa cell lines. IPA predicted key pathways based on DEGs between Taxane resistant and sensitivity. Fig. 3A. Differentially expressed gene Signature was identified among DEGs for ARLow/mCRPC/NEPC (PC-3DU145), ARLow/mCSPC/NEPC taxane-resistant (DUTXR and PC-3TXR) PCa cell lines. Venn diagrams represent unique and common DEGs for ARLow/mCRPC/NEPC , and ARLow/mCSPC/NEPCtaxane-resistant (DUTXR and PC-3TXR) cell lines. Fig. 3B. IPA predicted key pathways based on DEGs between Taxane resistant and sensitivity. Cluster 2 (IPA predicted activation of PPARA), Cluster 4 , Cluster 6 .Click here for additional data file.Supplementary Figure 4Supplementary Fig. 4 shows Differentially Expressed Gene Signature (DEGs) based on next-gene sequencing (mRNA sequencing) and single cell RNA sequencing for all PCa cell lines. Differentially expressed gene Signature was identified among DEGs for RNS seq and scRNAseq.Click here for additional data file.Supplementary Figure 5Supplementary Fig. 5 shows Ingenuity pathway analysis (IPA) predictions for common DEGs among RNAseq vs. scRNAseq in all PCa cell lines IPA predicted A) Diseases and biological pathways for common DGEs. Major pathways are cell invasion, movement, neoplasia, migration, transformation, metastatic and growth B) Causal network pathway for common DEGS include LY2109761 (TGF-β receptor inhibitor), IGF2R (receptor for both insulin-like growth factor 2), IL11RA (cytokine), SEMG2 (semenogelin proteins), CCR2 (chemokine receptor type 2), TRAF3IP3 , GGTI-2154 (inhibitor of geranylgeranyltransferase I ), L778123 (inhibitor of FPTase and GGPTase-I), TGFB1 and CXCL5. C) upstream regulators for common DEGs were THBF1, RAF1, AGT, ER receptor, OSM, SLC15A4, JUN, and IL1B D) Canonical pathways for common DEGs were s100 family, Hepatic fibrosis, Rho family, RHOGDI and integrin singling pathway.Click here for additional data file.Supplementary Figure 6Supplementary Fig. 6 shows Cytotoxicity Profiling of ARLow/mCRPC/NEPC (PC-3 and PC-3M) and Taxane Resistance ARLow/mCRPC (DUTXR): PC-3, PC-3M and DUTXR cell lines were treated with CONV-TOPO, METRO-TOPO, CONV-DTX and combination (CONV-DTX+METRO-TOPO) treatment, and cell cytotoxicity and caspase3/7 levels ware assed A) Cytotoxicity profiling by MTT showed combination (CONV-DTX+METRO-TOPO) reduces highest cell survival compared with other treatments for all PCa cell lines, CONV-TOPO>CONV-DTX>METRO-TOPO B) Caspase3/7 activity showed combination (CONV-DTX+METRO-TOPO) treatment reduced apoptosis the greatest compared to other treatments in all cell lines. C) Cytation5 images showed treatment effects on the cell lines PC-3M and DUTXR. Results showed significantly higher cell death in METRO compared to CONV treatment for both the cell lines and combination (CONV-DTX+METRO-TOPO) treatment reduced cell death greater for both PCa cell lines. ImageJ analysis showed significant differences in cell density for CONV-TOPO, CONV-DTX, METRO-TOPO, and combination (CONV-DTX+METRO-TOPO) treatment in PC-3, PC-3M, and DUTXR cell lines. (*p ≤ 0.05).Click here for additional data file.Supplementary Figure 7Supplementary Fig. 7 shows Single-Cell transcriptomics; Identifies epithelial to mesenchymal transition (EMT) marker TGFB1 in ARLow/mCRPC/NEPC . Result showed TGFB1 expression decreases after EE compared to CONV treatment, which indicated EE moderated stemness in ARLow/mCRPC/NEPC. Single-cell RNA sequencing used the droplet sequencing method (10X Genomics). Each dot represents a single cell. t-distributed stochastic neighbor embedding (tSNE) plots showing the comparison between the single-cell clusters as shown.Click here for additional data file.Supplementary Figure 8Supplementary Fig. 8 shows Flow Cytometry; Prostate cancer cell lines stained with stemness markers  to determine the percent of CD44+, CD133+ and double positive cells among PCa subtypes.  Treatments with CONV-TOPO, METRO-TOPO and CONV-DTX+METRO-TOPO reduced stemness. METRO-TOPO reduced CD44+ cells to a greater extent compared to CONV-TOPO and CONV-DTX treatments, whereas combination treatment with CONV-DTX+METRO-TOPO reduced stemness (CD44+ cells) the most in ARHigh/mCRPC/NEPC. A) PC-3M, B) DU145 cell lines.Click here for additional data file.Supplementary Figure 9Supplementary Fig. 9 shows Fluorescent-Activated Cell Sorting CD44High: PC-3M cell line stained with stemness markers (CD44) and sorted CD44+ cells, followed by CONV-TOPO, METRO-TOPO, CONV-DTX, and combination (CONV-DTX+METRO-TOPO) therapy and cell cytotoxicity and caspase3/7 levels assessed A) Cytotoxicity profiling by MTT showed combination (CONV-DTX+METRO-TOPO) reduces cell survival compared with other treatments CONV-TOPO>CONV-DTX>METRO-TOPO B) AR-mCRPC- PC-3M showed combination (CONV-DTX+METRO-TOPO) reduces levels the most of apoptosis compared to other treatments (*p<0.05).Click here for additional data file.Supplementary Video 1Supplementary Video 1Click here for additional data file.Supplementary Video 2Supplementary Video 2Click here for additional data file.Supplementary Video 3Supplementary Video 3Click here for additional data file.Supplementary Video 4Supplementary Video 4Click here for additional data file.


Smyd2-deficient mice are more resistant to viral infection by producing more IFN-I and proinflammatory cytokines. Mechanistically, SMYD2 inhibits IRF3 phosphorylation in macrophages in response to viral infection independent of its methyltransferase activity. We found that SMYD2 interacts with the DNA-binding domain (DBD) and IRF association domain (IAD) domains of IRF3 by its insertion SET domain (SETi) and could recruit phosphatase PP1α to enhance its interaction with IRF3, which leads to decreased phosphorylation of IRF3 in the antiviral innate response. Our study identifies SMYD2 as a negative regulator of IFN-I production against virus infection. The new way of regulating IRF3 phosphorylation will provide insight into the understanding of IFN-I production in the innate response and possible intervention of the related immune disorders.Phosphorylation of IRF3 is critical to induce type I interferon (IFN-I) production in antiviral innate response. Here we report that lysine methyltransferase SMYD2 inhibits the expressions of IFN-I and proinflammatory cytokines in macrophages upon viral infections. The  Innate immune response is the first line that protects the host from pathogen infection. Pattern recognition receptors (PRRs), such as RIG-I, MDA5, and cGAS, expressed in both innate immune cells and other type of cells recognize pathogen-associated molecular patterns (PAMPs) to trigger signaling pathways, such as MAVS-TBK1-IRF3 pathway, and phosphorylated IRF3 (p-IRF3) translocates into nucleus, which induces the production of type I interferon (IFN-I) to eliminate the invading pathogens including viruses , 3. IRF3The previous studies have shown that phosphorylation of C-terminal region of IRF3 results in release of IAD to form dimers, which leads to its nucleus translocation for triggering the transcription of IFNs . PreviouLysine methyltransferases modify histone and no-histone protein by methylation, which has a critical function in a series of biological and immunological processes by regulation of chromatin remodeling and protein conformation , 18. SMYHere we demonstrated that SMYD2 suppresses the production of antiviral IFN-I by inhibition of IRF3 phosphorylation which is independent of its methyltransferase activity. Mechanistically, SMYD2 interacted with IRF3 via binding IAD domain of IRF3, and phosphatase PP1α was recruited by SMYD2 to IRF3 to decrease phosphorylation of IRF3. Overall, SMYD2 is a negative regulator of antiviral interferon in innate response.Prdm6, Prdm9, Setd1a, Setmar, Smyd1, Smyd4, Smyd5, Suv39h1, Suv39h2, and Whsc1/1, remained almost unchanged, while the expressions of lysine methyltransferases including Smyd2, Smyd3, Nsd1, Prdm2, Setd1b, Setd2, Setd3, Setd7, Setd8, Setdb1, Suv420h1, Suv420h2, and Whsc1 were decreased, and the expression of Setdb2 was increased in macrophages upon VSV infection  , we founSmyd2, Smyd3, Setdb1, and Setdb7  after silencing of ted Fig. , and theted Fig. . TherefoIn addition, overexpression of wild-type SMYD2 and lysine methyltransferases-dead mutant SMYD2Y240A  inhibiteSmyd2−/− mouse by deletion of Exon 7 flanked with floxp, which leads to frameshift mutation when crossed with 129 S/Sv-Tg (Prm-cre) 58Og/J  compared with control cells infected with VSV and SeV  infected with VSV and SeV  stimulation   and TBK1-driven 5D) Fig. , which iPMs Fig. . We furtner Fig. . In addiications , 19, 21,yd2 Fig. . VSV infant Fig. . We thenant Fig. . The actIfnb by methylation of histone, we then examined the status of H3K4me2 and H3K36me2 by CHIP assay in the promoter region of Ifnb after deletion of Smyd2. Our results showed that the abundance of H3K4me2 and H3K36me2 wasn’t influenced after deletion of Smyd2 in response to VSV infection  and CTD domain (268-433aa) still inhibited the transcriptional activity of Ifnb, while truncated mutant Smyd2Δ1-251aa including S domain, MYND domain, SETi domain, and ET domain, abrogated its inhibition of Ifnb expression  (1-140aa) significantly decreased the interaction with SMYD2, and deletion of IAD domain abrogated the interaction between SMYD2 and IRF3 , such as methylation, play critical roles in multiple biological processes, including innate immune response . Our oriSmyd2, and the activity of NF-κB signaling pathway was increased in Smyd2−/− peritoneal macrophages infected with VSV. Maybe the mechanisms involved in negative regulation of IL-6 and TNF-α production by SMYD2 in macrophages are similar between LPS stimulation and VSV infection. Further work needs to be performed to clarify the detailed molecular mechanisms involved in these innate processes.A previous study showed that the expressions of inflammatory cytokines IL-6 and TNF-α in bone marrow-derived macrophages are inhibited by SMYD2 in response to LPS stimulation, and SMYD2 is reported to modify the histone and inhibit NF-κB and ERK signaling pathways to regulate this process . While t3H SAM (NET155H001MC) was from PerkinElmer.Anti-Rabbit SMYD2 (#9734), Anti-Mouse Lamin A/C (#4777), Anti-Rabbit RIG-I (#3743), Anti-Rabbit Phospho-IRF-3 (Ser396) (#4764), Anti-Rabbit TBK1 (#3013), Anti-Rabbit Phospho-TBK1/NAK (Ser172) (#5483), Anti-Rabbit MAVS (#4983), Anti-Rabbit NF-kappa-B p65 (#4764), Anti-Rabbit Phospho-NF-kappa-B p65 (Ser536) (#3033), Anti-Mouse Phospho-I-kappa-B-alpha (Ser32) (#2859), Anti-Rabbit IKK-alpha (#2682), Anti-Rabbit IKK-beta (#2684), Phospho-IKK-alpha (Ser176)/IKK-beta (Ser177) (#2078) and Anti-rabbit IgG-488 (#4412) were from Cell Signaling Technology. Anti-PP1-alpha (sc-7482) was from Santa Cruz. APC anti-mouse CD11c (117310) was from Biolegend. Anti-Rabbit PP2-alpha (610555), Percp-Rat Anti-Mouse CD4 (553052), FITC-Rat Anti-Mouse CD49b (553857) and PE Rat Anti-CD11b (553311) were from BD PharMingen. PE anti-mouse CD8a Antibody (100708), APC anti-mouse CD11c Antibody (117310), PerCP/Cy5.5 anti-mouse CD19 Antibody (115534), FITC anti-mouse Ly-6G (127606), FITC anti-mouse CD3 (100204), anti-mouse F/480 FITC (123107) and PE anti-mouse I-A/I-E (107608) were from Biolegend. Recombinant Mouse GM-CSF (415-ML-050) and Recombinant Mouse IL-4 Protein (404-ML-01M) were from R&D Systems. Murine M-CSF (315-02-1000) was from PeproTech. LYY507 was donated by the University of Oxford. Camptothecin (#13637) was from Cell Signaling Technology. Smyd2 mice, and two floxps are located at the upstream and downstream intron of the 7th extron respectively, which leads to frameshift mutation after crossing with mice carrying Cre gene. Neo gene flanked with Frt was used to screen out the recombined ES clones. Targeted ES cells were identified by Southern blot and were injected into C57BL/6 blastocysts to generate high-percentage chimeras. Smyd2-floxed allele mice (Smyd2f/+) was obtained after deletion of Neo gene by crossing between Smyd2 chimeras with B6; SJL-Tg (ACTFLPe) 9205Dym/J mice   methionine (3H SAM) in SAM buffer  for 1 hour at 30 °C. GST protein was negative control, and incubation of GST-SMYD2 with p53 peptide and 2μCi S-adenosyl-L-[methyl-3H] methionine  was used as positive control. Then all samples were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), visualized by Coomassie staining. After de-staining, the gel was submerged with EN3HANCE (PerkinElmer) for 1.5 h, and then exposed to Kodak XAR film after 30 days at −80 °C.Purified recombinant GST-SMYD2 protein was incubated with purified recombinant GST-IRF3 and 2μCi S-adenosyl-L-[methyl-t test. P < 0.05 were considered to be significant . For mouse survival study, Kaplan–Meier survival curves were generated and analyzed for statistical significance with GraphPad Prism 4.0.Statistical significance between groups was determined by two-tailed Student’s Further information on research design is available in the Supplementary InformationUnprocessed gel and imagesReporting Summary


SARS-CoV-2 pandemic variants has not been reported. Machine learning identified clinical traits and their relative importance independently associated with mortality at index hospitalization. The purpose was to compare variance explained (VE%) by each trait during pandemic Wave 1: March 10, 2020 – June 18, 2021; Wave 2: June 19, 2021 – December 18, 2021; Wave 3: December 19, 2021 – March 30, 2022; and Wave 4: March 31, 2022 – April 14, 2023, at an 818-bed academic safety-net hospital.Adverse clinical outcomes have been associated with COVID-19 mortality, but predictive stability across Figure 1: SARS-CoV-2 Tests from March 20, 2020 to April 14, 2023Collected positive SARS-CoV-2 test results with color-shaded areas representing "waves" based on surges in positive tests and 7-day average positive rate. Discrete waves are titled based on the current predominant variant.2) of mortality risk. Continuous data summarized with median [IQR] were compared using Kruskal-Wallis. Discrete data summarized as proportions were compared with chi-square.Demographics, laboratory results, ICD-10-CM-based comorbidity, COVID-19 directed treatment and administrative data were extracted under IRB exemption from electronic medical records. Generalized regression with adaptive LASSO identified traits associated with mortality controlling for COVID-19 directed treatment in at least one of the waves. Univariate logistic regression for each trait created a within-variant receiver operating characteristic curve with optimal cut-point (Youden Index) associated with mortality. Boosted Tree computed within-variant proportion (VE%) contributed by clinical traits in the model’s representation (R6490 patients were distributed across Wave 1 (2249), Wave 2 (1196), Wave 3 (953) and Wave 4 (2092) with respective mortality of 3%, 2%, 1%, and 1% (p< .0001). The four waves were titled Alpha/Beta, Delta, Omicron, and Omicron BA.X based on predominant strains during dates of admissions. Table 1 displays patient demographics in each of the four waves. Tables 2-5 display VE% for 29 clinical traits in each respective wave.The developed longitudinal training models suggest that COVID-19 presentation risk tools may not generalize across pandemic surges. Limitations includes monocenter study with many patients self-reporting vaccination status. Study strength includes demonstrating utility of longitudinal machine modeling as a tool for learning healthcare system science. Future research may further examine co-morbid conditions and presentation severity.Manuel E. Gordillo, M.D., Regeneron: Was involved in the Regen Cov trial as a PI one one of the sites


Scientific Reports 10.1038/s41598-023-43448-5, published online 27 September 2023Correction to: The original version of this Article contained an error in the Funding section.“The Silesian Technical University, grant no: 10/010/RGH22/1125.”now reads:“The Silesian University of Technology, grant no: 10/010/RGH22/1125.”The original Article has been corrected.


Molecular Neurodegeneration (2023) 18:7410.1186/s13024-023-00663-yIn the original article [1] the following statement of funding acknowledgement was mistakenly omitted:“Preclinical studies have been supported by NIH grants P01AG017617 and R01AG062376 grants to RAN.”


Emerging SARS-CoV-2 variants, notably Omicron, continue to remain a formidable challenge to worldwide public health. The SARS-CoV-2 receptor-binding domain (RBD) is a hotspot for mutations, reflecting its critical role at the ACE2 interface during viral entry. Here, we comprehensively investigated the impact of RBD mutations, including 5 variants of concern (VOC) or interest—including Omicron (BA.2)—and 33 common point mutations, both on IgG recognition and ACE2-binding inhibition, as well as FcγRIIa- and FcγRIIIa-binding antibodies, in plasma from two-dose BNT162b2-vaccine recipients and mild-COVID-19 convalescent subjects obtained during the first wave using a custom-designed bead-based 39-plex array. IgG-recognition and FcγR-binding antibodies were decreased against the RBD of Beta and Omicron, as well as point mutation G446S, found in several Omicron sub-variants as compared to wild type. Notably, while there was a profound decrease in ACE2 inhibition against Omicron, FcγR-binding antibodies were less affected, suggesting that Fc functional antibody responses may be better retained against the RBD of Omicron in comparison to neutralization. Furthermore, while measurement of RBD–ACE2-binding affinity via biolayer interferometry showed that all VOC RBDs have enhanced affinity to human ACE2, we demonstrate that human ACE2 polymorphisms, E35K (rs1348114695) has reduced affinity to VOCs, while K26R (rs4646116) and S19P (rs73635825) have increased binding kinetics to the RBD of VOCs, potentially affecting virus–host interaction and, thereby, host susceptibility. Collectively, our findings provide in-depth coverage of the impact of RBD mutations on key facets of host–virus interactions.The online version contains supplementary material available at 10.1007/s00430-023-00773-w. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—the virus responsible for causing Coronavirus Disease 2019 (COVID-19)—remains an ongoing challenge for global public health, as genomic surveillance continues to identify new mutations within the SARS-CoV-2 genome. Mutations have previously given rise to new variant of concern (VOC) lineages, namely Alpha (B.1.1.7), Beta B.1.351), Gamma (P.1), Delta (B.1.617.2), and now currently Omicron (B.1.1.529), each demonstrating increased transmissibility, resulting in new waves of infections across the world 51, Gamma.Antibodies play crucial roles in the body’s immunological response against SARS-CoV-2 infection. Neutralizing antibodies block engagement to ACE2 receptor on host cells, thus protecting from symptomatic infection , 6. StroWhile RBD escape mutations can allow SARS-CoV-2 to evade neutralization, many of the antibodies elicited to the RBD are non-neutralizing , 14. AntMoreover, while mutations within the RBD can alter the virus’ affinity for ACE2, naturally occurring ACE-2 polymorphisms found within the human population, could also modulate host–pathogen dynamics during SARS-CoV-2 infection –25. NumeWith the rise of VOCs, it remains crucial to understand the impact of RBD mutations on key facets of host interactions that may contribute to SARS-CoV-2 infection dynamics. Neutralizing antibodies have been demonstrated to be important for protection against both ancestral SARS-CoV-2 and subsequent variants . In addin = 15)   . To acco10 (x + 1)) prior to being normalized using z-scoring. LASSO feature reduction was then employed on z-scored data and performed 1000-times with tenfold cross validation. Using LASSO-selected features, unsupervised principal component analysis (PCA) was then performed.Antibody features were selected using a least absolute shrinkage and selection operator (LASSO) reduction method as previously described using MATLAB version 9.6   and Eigenvector PLS toolbox  . In briePrism GraphPad version 9.0.2  were used to develop graphs and perform statistical analysis as described in respective figure legends.Sixteen individuals vaccinated with BNT162b2 had plasma samples drawn before vaccination (baseline) and two weeks  following the second dose . Unsupervised principal component analysis (PCA), used to broadly examine this repertoire of antibody responses, showed that baseline, BNT162b2 (2 weeks post dose two), and convalescent (mild-to-moderate) subjects were naturally separated into three distinct groups based on their antibody signatures . This analysis confirms that BNT162b2 vaccination induces more robust anti-ancestral spike IgG responses with greater FcγR-binding capacity, in comparison to our mild-to-moderate convalescent donors.First, plasma humoral profile to SARS-CoV-2 proteins  found in the ancestral wild-type virus was characterized using a SARS-CoV-2 multiplex bead assay. Robust antibody responses to NP were uniquely associated with convalescent COVID-19 individuals, indicating no prior infection in the BNT162b2-vaccinees . Convalescent and BNT162b2-vaccinees both elicited elevated levels of IgG to spike antigens; however as expected, BNT162b2-vaccinees demonstrated significantly greater responses in comparison to convalescent individuals which displayed more heterogenous responses ,  were observed in BNT162b2-vaccines compared to convalescent individuals across all RBDs assessed  and Gamma  by BNT162b2 plasma in comparison to the ancestral RBD   found in Omicron, E484K  found in Gamma and Beta, as well as F490S  and N501T   in comparison to convalescent plasma across all 39 RBDs  highlighting the evasive nature of this variant   in ACE2-blocking was also observed for L452R, despite having comparable IgG binding (p = ns) to the ancestral RBD. Furthermore, the RBD mutation N501Y, the prime mutation found in the RBD Alpha-VOC, demonstrated no significant decrease in IgG binding  but showed a significant drop in capacity to block ACE2 from binding   , Gamma  and Delta . Omicron (BA.2) demonstrated a 2.6-fold increase in binding , compared to ancestral RBD , which in turn could explain the drop in plasma-driven ACE2 inhibition . Likewise, using BLI, we observed that N501T had improved binding affinity  as compared to the ancestral RBD . As such, the combination of reduced IgG binding due loss of epitope and stronger ACE2 affinity for N501T could further impeded ACE2 inhibition by plasma samples. Together, these results suggest that beyond antibody recognition, affinity interactions between RBD and ACE2 exert another layer of influence on the potential for antibodies to effectively block ACE2-binding and achieve neutralization.Previously, we and others have shown single-point mutations in RBD  can enhance affinity to ACE2  and K26R (KD: 20.0) demonstrated a 2.04-fold and 1.47-fold increase in binding affinity, respectively, to ancestral RBD when compared to WT ACE2 (KD: 28.99 nM) , Omicron (BA.2)  and Delta  , Omicron (BA.2) (Kd: 18.50 nM), and Delta (Kd: 43.34 nM), suggesting that individuals harboring the E35K ACE2 polymorphism may demonstrate a more protective phenotype due to reduced ACE2 affinity for RBD . In particular, K26R has been observed at low frequencies across most populations, whereas low frequencies of S19P are predominantly detected within African/African American populations 0.3%) , 24. Pre% , 24. P50 vales) to engage both our FcγRIIa and FcγRIIIa-dimer constructs across all variants, in comparison to convalescent plasma  and FcγRIIIa-dimer-binding antibodies    , suggesting FcγR-binding antibodies may be more resistant to mutations found in Omicron than ACE2 inhibition  . FcγRIIa reciprocal ED50 values correlated well wit phagocytosis ED50 levels of ancestral RBD by THP-1 monocytes , as well as the RBD of Beta   correlated strongly with FcγRIIa-dimer , and phagocytosis levels  . We observed a significant decrease in ADCP activity against ancestral vs Beta RBD (p = 0.0026), supporting the mutations found in VOCs are detrimental to FcγR-binding antibodies  bind WT ACE2 with enhanced affinity, reflecting evolutionary mutations that enhance viral entry and transmission , 42. HowAssessing single-point mutations found in the RBD can provide valuable insights into the importance of these mutations on overall viral fitness. Our study showed numerous point mutations imparted little impact on anti-RBD IgG recognition as well as FcγR-binding engagement. This was observed for RBD point mutations L452R and T478K , which may account for the limited reduction in total IgG binding and FcγR-binding observed against Delta RBD. However, we noted that L452R-RBD had a longer binding half-life to WT ACE2, which could contribute to the observed loss of ACE2 neutralization. Indeed, it has been described that L452R increases SARS-CoV-2 infectivity and fusogenicity and, thus, may confer an evolutionary advantage previously observed with Delta and, more recently, the Omicron sub-lineages BA.4 and BA.5 , 26. We , when low neutralizing antibody titers but competent Fc activity is retained [Several future studies are suggested by our work. While our cohort of BNT162b2-individuals received two doses of vaccine, the current approved regimen is now expanded to three doses in Australia and many other countries. Three doses enhance antibody responses to VOCs overall and it will be important to dissect particular mutations for their impact on improved RBD-specific antibody responses. Interestingly, Irrgang et al., recently reported enhanced class-switching to IgG4 following repeated BNT162b2 vaccination associated with reduced Fc functional activity . While tretained . Conversretained –60. Imporetained .Overall, our data show that RBD mutations, both common point mutations as well as combinations of mutations in VOCs, not only have an impact on affinity to receptor ACE2, but also IgG binding and the Fc functional antibody response, thereby providing an important site for viral adaptions.https://gnomad.broadinstitute.org) (PPTX 3590 KB)Supplementary file1 Supplementary Figure 1. Schematic representation of duplex phagocytosis assay with gating strategy and reciprocal ED50 analysis. (A) Schematic of the antibody dependent phagocytosis (ADCP) duplex assay. Briefly, APC fluorescent beads coated with ancestral RBD, while FITC fluorescent beads coated with RBD Beta were added to wells and incubated with plasma for 2 hours at 37OC. Following incubation, THP-1 monocytes were added to wells and incubated with opsonised beads for 2 hours under cell culture conditions before fixing cells for flow cytometry. (B) Representative gating strategy using pooled 2-week post vaccination plasma (blue), pooled baseline plasma (red) and no plasma (grey). Gating was performed by gating on THP-1 monocytes, single cells and finally cells positive for RBDWT beads and RBD Beta beads. (C) Visualization of single and double bead positive cells as dot plots for representative samples. ADCP by THP-1 monocytes induced by the plasma of BNT162b2  against the ancestral and Beta RBD shown as phagocytic score reciprocal ED50. Reciprocal ED50 values of ADCP duplex assay (D) without baseline correction using no plasma control (no baseline correction) and (E) with baseline correction using matched plasma samples collected prior to vaccination (baseline correction). (F) Pearson correlation of ED50 values calculated with no baseline correction and baseline correction. Supplementary Figure 2. SARS-CoV-2 serological signatures distinguish BNT162b2 vaccinated, convalescent, and baseline individuals. Plasma humoral responses were profiled via multiplex for convalescent mild/moderate COVID-19 patients  and BNT162b2-vaccinated individuals at baseline  and two-weeks following second dose . Radar plots show the median MFI (median fluorescence intensity) value of each antibody signature  to NP (A), trimeric spike (B), S1 (C), and RBD (D). The median MFI for each feature was normalised using z-scoring prior to plotting. (E) Unsupervised principal component analysis comparing convalescent COVID-19 individuals and BNT162b2-vaccinated individuals at baseline and two-weeks following second dose of 15-SARS-CoV2 antibody features selected by a dimensionality reduction method (LASSO). 95% confidence intervals for each group are depicted by a coloured eclipse. (F) PC1 and PC2 loadings of LASSO selected features for NP (yellow triangle), trimeric spike (red circle), spike subunit-1 (S1) (orange inverted triangle) and receptor binding domain (RBD) (brown square) of the PCA. Supplementary Figure 3. IgG subclass recognition of SARS-CoV-2 antigens and correlations to FcγR engagement. Plasma antibody isotype response  (A-C), IgG subclass responses  (D-G) and FcγR engagement (FcγR3av and FcγR2aH) (H-I) to NP, RBD, S1 and spike trimer were profiled via multiplex. Convalescent mild/moderate COVID-19 patients  and BNT162b2-vaccinated individuals at baseline  and two-weeks following second dose  were assessed. (J) Pearson R correlation matrix of IgG subclass binding  and FcγR engagement (FcγR3aV and FcγR2aH) with R values in bold and P-values described in italics. Supplementary Figure 4. Affinity of wild-type (WT) hACE2 to the RBD mutations. Sensograms of WT-human ACE2 (hACE2) binding affinity to (A) K417N, (B) K417T, (C) G446S, (D) L452R (E) L452R E484Q, (F) Y453F, (G) S477N, (H) T478K, (I) E484D, (J) E484K and (K) 484Q , (L) S494P and (M) N501T as measured by biolayer interferometry (BLI). Binding of 2-fold serial dilutions of each SARS-CoV-2 RBD variant (100 nM (red), 50 nM (yellow), 25 nM (green), 12 nM (blue), and 6 nM (pink)) was measured to immobilised hACE2 (3μg/ml). Binding curves representative of 2 independent experiments for each variant are plotted (solid-colored lines), globally fitted to a 1:1 binding model (black line). Supplementary Figure 5. IgG-binding correlates with FcγRIIa-H131 and FcγRIIIa-V158-dimer binding. BNT162b2  and mild/moderate convalescent COVID-19 patients  as measured by multiplex to RBD variants. Reciprocal ED50/ID50 values respectively were calculated using the normalized binding MFI-value for an 8-point serial plasma titration. Spearman correlations of multiplexed (A) FcRIIa-H131 data  and (B) FcRIIIa-V158 dimer-binding data  against IgG  against ancestral RBD and variant RBD. All corresponding p values were below 0.005. Supplementary Figure 6. IgG-binding correlates with ADCP. Spearman correlations of IgG-binding  with multiplex FcRIIa-H131 data  of (A) Ancestral and (C) Beta RBD. Spearman correlations of IgG-binding  phagocytosis activity  using THP-1 monocytes against (B) ancestral and (D) Beta RBD. Supplementary Table 1 Antigens used in SARS-CoV-2-specific array. Supplementary Table 2 RBD recombinant proteins (variants and single point mutations) used in RBD array. Supplementary Table 3 Friedmans Test using Dunn’s multiple comparisons statistical values for comparison of IgG-binding, ACE2-inhibition, FcRIIa-binding and FcRIIIa-binding of RBD-variants to ancestral RBD. Supplementary Table 4. Affinity constants of wild-type (WT) hACE2 to RBD with single point mutations. Measured via BLI, calculated from 2 independent experiments. Supplementary Table 5. Affinity of human ACE2 polymorphisms to SARS-CoV-2 RBD Variants. Measured via BLI, calculated from 2 independent experiments. Supplementary Figure 6. Frequency of human ACE2 polymorphisms  found within human populations.  Polymorphism data collated from Genome Aggregation Database (gnomAD; Below is the link to the electronic supplementary material.


Six promoters resulted in ubiquitous expression, three did not drive detectable expression, and nine were germline-specific. Several promoters drove stronger germline expression than the commonly-usedmex-5promoter. The promoters range across expression levels and facilitate, for example, low expression of toxic transgenes or high expression of gene editing enzymes, and their compactness facilitates gene synthesis.A core tenet of synthetic biology is that well-characterized regulatory elements are essential for engineering biological systems. Here, we characterize the specificity and expression levels of 18 short (254 to 880 bp) candidate germline promoters using a single-copy C. elegans,overexpression of the microtubule force regulatorGPR-1by codon adaptation was able to change Mendelian inheritance by forcing premature cell division in the early embryogpr-1::gfpinsertions and relied on position effect variegation to isolate viable lines with "Goldilocks" expression: stable and exactly enough expression to generate a high frequency of non-Mendelian inheritance but no obvious toxicity. Moreover, while two germline promoters (mex-5pandpie-1p) are frequently used inC. elegans, ubiquitous promoters with high germline expression (eef-1A.1p(prior nomenclatureeft-3p),smu-1p, andsmu-2p) are often used for efficient genome editing . These examples highlight the importance of controlling transgene expression to engineer biological systems and generate desired outcomes. We reasoned that advances in tissue-specific sequencing provide new opportunities for the rational identification of regulatory components with particular characteristics. Here, we characterize short putative germline promoters across a range of expression levels inC. elegans.The precise manipulation of biological systems requires a versatile synthetic biology toolkit of regulatory elements. Libraries of standardized genetic “parts” have permitted control over complex metabolic pathways to produce valuable chemicals or introduce novel traits in various biological systems, including bacteria, yeast, and plants). To facilitate synthesis and cloning, we modified homopolymers of 10 bp or more andBsaI recognition sites using single nucleotide substitutions. We cloned candidates and controls (ubiquitouseef-1A.1pand germlinemex-5p) into vectors containing a codon-optimizedgfp with nuclear localization signals and a germline permissive 3’ UTR (tbb-2) using Golden Gate AssemblyWe identified candidate promoters using tissue-specific RNA-seq data from Serizay et al. (2020) and selected short promoters (less than 1 kb) from genes with high absolute and relative germline expression in addition to the germline . Expression in the soma fromhis-61p,his-64p, andhil-4pwas limited compared to the broad expression found usingrla-0p,rpl-7Ap, andY37E3.8p. The specificity of these promoters reflects the relative germline expression measurements from RNA-seq data . Although multiple candidates are expressed in the soma and the germline, promoters such ashis-61p(327 bp) andhis-64p(254 bp) provide shorter alternatives toeef-1A.1p(579 bp).We verified that the constructs and insertion strategy produce ubiquitous and germlinepuf-11p,F23A7.8p,andclec-87preporter constructs , despite the high germline RNA expression forclec-87 and the highest fractional germline expression forF23A7.8p(72%) . The discrepancy with RNA-seq data could be due to regulation in the native genomic context outside the selected promoter region. ATAC-seq data show potential germline enhancers forclec-87andpuf-11near their 3' UTRF23A7.8locus.F23A7.8is the only candidate gene selected from chromosome X, which is mostly silenced in the germlineWe observed no detectable GFP expression fromklp-19p,his-68p,W05F2.3p,spn-4p,pos-1p,Y75B12B.1p,puf-5p,mei-2p, andmesp-1p) produced GFP expression that was specific to the germline . We quantified GFP expression levels using two assays: a blinded visual screen under a fluorescence dissection microscope and using a COPAS flow cytometer . The relative expression levels generally correlated across the two quantification methods, with the exception ofmei-2pandmex-5p. The quantification revealed a range of expression levels in the germline. Notably,klp-19pandhis-68pconsistently produced GFP that is brighter thanmex-5p. These promoters provide promising options to enhance gene editing efficiency and limit somatic background with high and specific expression levels in the germline.puf-5p,pos-1p, andY75B12B.1poffer medium expression levels, andmei-2pandmesp-1poffer relatively low expression levels. These promoters are well-suited for experiments that require modest protein levels or to reduce transgene toxicity in the germline. The relatively short length of these promoters makes them practical for gene synthesis. Therefore, we have incorporated the sequences ofhis-64pfor ubiquitous andklp-19p(high),Y75B12B.1p(medium), andmesp-1p(low) for germline expression in an online application (https://www.wormbuilder.org/transgenebuilder/)  for convenient transgene design and synthesis.Nine promoters  plates seeded with eitherTable 1 |Strains used in this study.Molecular Biologyin silico using the molecular biology editor ApEBsaI restriction enzyme sites from endogenous sequences. We flanked all promoters with donorBsaI restriction sites and overhangs and synthesized them as gene fragments . We synthesized the destination plasmid as a clonal vector  and included the appropriate acceptorBsaI sites, a consensus start site (aaaa), agfp with two nuclear localization signals (SV40 andegl-13), atbb-23’ UTR) that contains a non-rescuingcbr-unc-119fragment and homology arms targeting a MosTI safe-harbor landing site on chromosome IIgfp was codon optimized as in Fielmich et al. (2018) and designed following guidelines in Aljohani et al. (2020) but without PATC-rich introns. We generated repair templates using NEBridge® BsaI-HFv2 Golden Gate Assembly (New England Biolabs Cat. # E1601S)gfp. All vectors were verified using restriction digestion and Sanger sequencing.We designed all vectorsTable 2 | Candidate promoter sequences. The promoters contained 15 bp preceding thegfp (underlined). Substitutions to modify ≥ 10 bp homopolymers andBsaI sites are in bold. The consensus start site is underlined and in bold. The start codon ofgfp is in uppercase.SoftwareAn online application for designing transgenes is available at www.wormbuilder.org/transgenebuilder. A manuscript detailing the application is in preparation by the authors . The version described in this manuscript has been archived in Caltech Data - 10.22002/qs7eh-g0669.Single-Copy Insertionscbr-unc-119fragments: one located in the genome in a safe-harbor landing site while the other fragment is co-inserted with a transgene of choice using CRISPR-Cas9. Following a double-strand break and homology-directed repair, successful single-copy insertions events are marked by the phenotypic rescue of theunc-119genesmu-2p::Cas9::gpd-2::tagRFP-T), 10 ng/μl pSEM235 (mlc- 1p::mCherry), 10 ng/μl pSEM238 (snt-1p:: HisCl1), 15 ng/μl pSEM318 (MosTI sgRNA), 10 ng/μl repair template, and 30 ng/μl 1 Kb Plus DNA Ladder (ThermoFisher Cat. # 10787026) for a final DNA concentration of 100 ng/μlCFJ42(-)] II;unc-119(ed3) IIIkstSi42[) animals that were maintained at 20°C onHB101. After injection, we placed single animals on NGM plates seeded withOP50at 25°C until starvation. We added 500 μl of 50 mM histamine dihydrochloride (GoldBio Cat. # H-110-100) to plates withunc-119rescued animals. After 1 hour, we screened plates for sensitivity to the negative histamine selection markerunc-119rescued animals lacking pan-muscular,mCherry, co-marker expressionOP50plates and propagated insertion lines until homozygous. We generated one to four independent insertions for each transgene (exact numbers are in parenthesis) and detected no observable differences across independent lines:eef-1A.1p(1),mex-5p(3),his-61p(2),his-64p(2),hil-4p(3),rla-0p(3),rpl-7Ap(1),Y37E3.8p(1),klp-19p(1),his-68p(1),W05F2.3p(3),spn-4p(3),pos-1p(4),Y75B12B.1p(1),puf-5p(4),mei-2p(1),mesp-1p(3),puf-11p(2),F23A7.8p(3),clec-87p(3).We generated single-copy insertion of candidate germline reporter transgenes using MosTI. The technique relies on the reconstitution of two non-rescuingFluorescence Quantificationpuf-11promoter that was rapidly silenced. We, therefore, grew the strains for multiple generations to ensure stable transgene expression. In order to minimize bias during quantification, we blindedN2and transgenic insertion lines to their genotype. We then synchronized them by egg prep in a drop of bleaching solutionOP50plates per strain and cultured them at 25°C for five days.Visual Quantification: We scored three plates per strain with a mixed-stage population by eye on a Kramer Scientific FBS10 LX microscope equipped with objectives 2x (Plan APO Objective 0.055NA), 10x (Plan APO Objective 0.3NA), and 20x (Plan APO Objective 0.42NA) and an X-Cite 200DC illuminator using the following scale: 0 (no detectable expression at 20x), 1 (detectable at 10x with zoom), 2 (detectable at 10x without zoom), 3 (detectable at 2x with zoom), and 4 (detectable at 2x without zoom).Flow Cytometry: We washed seven plates per strain with M9 to remove particles and bacteria twice. We measured the fluorescence of a mixed-stage population using a COPAS FP-250 μm large-particle flow cytometer (Union Biometrica) equipped with 488 nm and 561 nm excitation lasers. To select adult worms, we filtered raw data by TOF (time of flight) between 1500 and 1800 and peak-height extinction below 35,000 using Microsoft Excel for Mac (v16.70). We subtracted the mean peak-height GFP measurement from non-transgenicN2animals from all reported values. We generated plots using GraphPad Prism 9 for macOS (v9.5.1).We selected one independent insertion line for each candidate promoter for fluorescence quantification. We noted early germline GFP expression using theImagingWe immobilized animals using a 50 mM sodium-azide in M9 solution and mounted them on 2% agarose pads. We took images on an upright, non-motorized, compound microscope (Leica DM2500 with a Leica DFC7000 GT camera and Leica SFL4000 LED light source) with a 20x air objective. We maintained constant exposure time, gain, and binning in all images.Table 3 |Plasmids generated in this study (sequences available on request).


Despite their importance, natural killer (NK) cell responses are frequently dysfunctional during human immunodeficiency virus-1 (HIV-1) and simian immunodeficiency virus (SIV) infections, even irrespective of antiretroviral therapies, with poorly understood underlying mechanisms. NK cell surface receptor modulation in lentivirus infection has been extensively studied, but a deeper interrogation of complex cell signaling is mostly absent, largely due to the absence of any comprehensive NK cell signaling assay. To fill this knowledge gap, we developed a novel multiplex signaling analysis to broadly assess NK cell signaling. Using this assay, we elucidated that NK cells exhibit global signaling reduction from CD16 both in people living with HIV-1 (PLWH) and SIV-infected rhesus macaques. Intriguingly, antiretroviral treatment did not fully restore diminished CD16 signaling in NK cells from PLWH. As a putative mechanism, we demonstrated that NK cells increased surface ADAM17 expression via elevated plasma IL-18 levels during HIV-1 infection, which in turn reduced surface CD16 downregulation. We also illustrated that CD16 expression and signaling can be restored by ADAM17 perturbation. In summary, our multiplex NK cell signaling analysis delineated unique NK cell signaling perturbations specific to lentiviral infections, resulting in their dysfunction. Our analysis also provides mechanisms that will inform the restoration of dysregulated NK cell functions, offering potential insights for the development of new NK cell-based immunotherapeutics for HIV-1 disease. Natural killer (NK) cells exert critical innate effector responses against human immunodeficiency virus-1 (HIV-1) and simian immunodeficiency virus (SIV) infections, but their functions are often dysregulated during chronic lentiviral infection with understudied mechanisms. Specifically, the effect on NK cell signaling linked to this immune dysfunction has not been comprehensively elucidated. To fill the gap in knowledge, we developed a novel multiplex signaling assay for NK cells and applied it to NK cells from people living with HIV-1 (PLWH) or SIV-infected rhesus macaques (RM). We illustrated the signaling activation downstream of CD16, a critical receptor for NK cell function, is systemically downregulated in NK cells in chronic lentiviral infection regardless of antiretroviral treatment, which is mediated by inflammatory responses triggered by HIV-1/SIV infection. Taken together, we demonstrated global CD16 signaling downregulation in NK cells in HIV-1 and SIV infection using our novel multiplex signaling assay and elucidated the putative mechanism of impaired NK cell activities. These data are beneficial to further advance NK cell-based immunotherapeutics for an HIV-1 cure. Natural killer (NK) cells are important innate effector cells for limiting human immunodeficiency virus-1 (HIV-1) and simian immunodeficiency virus (SIV) transmission and pathogenesis . Lack of-CD16+ NK cell subsets that elicit weaker cytokine production and cytotoxicity [Despite their significance, NK cell responses are frequently dysregulated in HIV-1/SIV infections. Regardless of antiretrovirals (ART), PLWH accumulate CD56toxicity . Presumatoxicity ,22. NK ctoxicity . In agretoxicity . Besidestoxicity ,26. Constoxicity . Our rectoxicity ,24,28. Wtoxicity .NK cells integrate signals from activating and inhibitory receptors to orchestrate a variety of functions . EngagemNK cell signaling activation has been traditionally monitored by classical techniques including western blotting and phosphoflow . While t-) infection through multiple activating receptors including CD16 (Fc receptor), NKp46 , NKG2D (NKG2 family of C-type lectin-like receptors), and CD2 (co-receptor), and tested our composite Luminex signaling assay to assess the activation of several canonical signaling cascades, including ITAM-based signaling , STAT signaling (p-STAT3 and p-STAT5), MAP kinase (MAPK) signaling , NF-κB signaling (p-NF-κB), and mTOR signaling (p-Akt and p-p70S6K). CD16 and CD2 crosslinking triggered the robust activation of ITAM-based signaling, MAPK, and STAT signaling  derived from individuals without HIV-1   in NK cells by receptor engagement using phospho-flow. As with the Luminex platform, we observed an elevation of p-Sykctively) . Consistctively) . Taken t- individuals, PLWH on virally suppressive ART (HIV-ART), and PLWH either off ART or with unsuccessful viremic control (HIV-viremic)  . Previouviremic) . Interesviremic) . Conversviremic) . Signaliviremic)  Figs.+ animals. Downstream signaling of NKp46 and NKG2D was not significantly modulated by SIV infection   (p<0.05). Others have demonstrated that PLWH accumulate dysfunctional CD56-CD16+ NK cell populations, unlike a comparative healthy control group [-CD16+ NK cells in these individuals   This CD1 cohorts . Conversctively) , p<0.05.ol group . In accoividuals . The levividuals .+ RM    . Additioctively) . Whereasctively) . To summ- and SIV+, respectively)  . Among tctively) . Conversctively) . We alsoctively) .Several studies have implied the roles of a disintegrin and metalloprotease-17 (ADAM17) in CD16 shedding , which iWe next investigated whether reduced CD16 expression induced by IL-18/ADAM17 affects ITAM-based signaling activation in the CD16 pathway. Corresponding with diminished CD16 expression, IL-18 dampened ITAM-based signaling activation by CD16 stimulation in NK cells . Subsequex vivo, we investigated the role of ADAM17 on systemic downregulation of CD16 signaling in blood specimens derived from HIV-ART and HIV-viremic groups. We demonstrated that total NK cells from PLWH had higher percentages of ADAM17+ NK cells compared to HIV- donors, regardless of ART status   . This in+ NK cells in PLWH   . Taken t-CD16+ NK cells from PLWH. To explore the potential mechanism, we developed an in vitro system to assess CD16 downregulation, and we found that IL-18 significantly decreased NK cell CD16 expression and subsequent ITAM-based signaling activation. Additionally, we found these changes to be dependent on IL-18-induced ADAM17, which cleaves the surface domain of CD16 [Herein, we have established a multiplex NK cell signaling assay with the capability to extensively characterize both human & RM NK cell signaling activation. Using this assay, we elucidated that ITAM-based signaling in the CD16 pathway was globally downregulated in PLWH and SIV-infected RM. Intriguingly, JNK and STAT3 activation by CD16 stimulation was modestly enhanced NK cells derived from PLWH. For SIV-infected RM, increased STAT5 activation upon CD2 stimulation was illustrated in addition to modulated CD16 signaling. We further demonstrated that altered signaling profiles were directly related to surface CD16 and CD2 expression profiles while moderate SHP-1 upregulation was observed specifically in CD56 of CD16 , and thaOur study highlights several critical findings for NK cell biology. First, our multiplex signaling assay was able to provide evidence for a more thorough intracellular NK cell signaling profile during lentiviral infection than has ever been characterized. While the diminished phosphorylation of CD3ζ, Syk, and ZAP70 by CD16 stimulation has been reported in NK cells from PLWH and SIV-infected RM ,53, thesSecondly, our study demonstrated that human and RM NK cells exhibit similar signaling activation profiles upon receptor crosslinking. Several groups reported that RM NK cells rigorously recapitulate human NK cell responses ,71, but In addition to the comparable signaling activation between human and RM NK cells, our study revealed that downregulated CD16 expression coincides with reduced downstream signaling pathway activation. Many groups have comprehensively characterized dysfunctional NK cell responses associated with altered NK cell surface receptor expression ,24,28, b-CD16+ NK cell populations [Along with the link between surface receptor expression and downstream intracellular signaling, this study explicated the reduction of CD16 via an IL-18/ADAM17-driven mechanism in HIV-1/SIV infection, as seen in other viral infections. Individuals with herpes simplex virus infection have been reported to exhibit reduced CD16 expression on NK cells . Diminisulations  from PLWulations , an IL-1+ animals in this experiment, CD2 elevation would be expected to become more apparent on NK cells during SIV infection similar to PLWH NK cells.While PLWH NK cells decreased CD16 expression, they significantly elevated CD2 expression. This could result from accumulation of adaptive NK cell subsets in PLWH, which are characterized by increased CD2 expression ,74. ConvdimCD16+ NK cells in Rituximab recipients 12 months after treatment [Our findings indicate that ADAM17 could be considered a promising target for NK cell HIV-1 immunotherapies similar to cancer immunotherapies. ADAM17-mediated CD16 reduction has been increasingly studied for NK cell-based cancer immunotherapy as a strategy to optimize NK cell ADCC . While treatment . To overreatment . Furtherreatment . While treatment . Howeverreatment . Given treatment , ADAM17-In conclusion, our multiplex NK cell signaling assay delineated distinct CD16 signaling downregulation during HIV-1/SIV infection, which corresponded with surface CD16 and CD2 expression. We also elucidated that ADAM17 upregulation by IL-18 reduces NK cell surface CD16 expression and subsequent intracellular signaling activation. These findings will inform future NK cell-based HIV-1 immunotherapeutics aimed at both restoring and enhancing NK cell activity against HIV-1.Macaca mulatta) were housed at Biomere, Inc., Worcester, MA in compliance with the rules and regulations of the Committee on the Care and Use of Laboratory Animal Resources. The housing of animals was performed following the American Association for Accreditation of Laboratory Animal Care standards and The Guide for the Care and Use of Laboratory Animals. All animal experiments were reviewed and approved by the Biomere Institutional Animal Care and Use Committee (IACUC) under protocols #16–08, 17–02, and 20–02, and in agreement with ARRIVE  guidelines. Standard monkey chow diet supplemented daily with fruit and vegetables and water ad libitum was supplied for animals tested. Veterinary staff provided social enrichment and monitored overall animal health. Clinically significant signs of weight loss, disease, or distress were assessed for each animal, and dietary supplementation, analgesics, and/or therapeutics were supplied if necessary. RM were humanely euthanized by an overdose of barbiturates as recommended by the guidelines of the American Veterinary Medical Association. IACUC protocols 20–02, 17–02, and 16–08 were reviewed and approved by the Biomere standing IACUC. If needed, immobilization of animals was performed by intramuscularly injecting ketamine HCl (Parke-Davis) at approximately 10mg/kg following overnight fasting. Venipuncture was used to harvest blood samples.All Indian-origin RM  were used for these experiments. The animals were infected with SIVmac251, and blood collection was performed prior to SIV infection and at the chronic stage of infection when sacrificing animals . PBMC weHealthy human blood was sampled under protocols approved by Research Blood Components Institutional Review Board  and Zen-Bio Inc. Institutional Review Board . PBMC were separated by Ficoll-Hypaque-based density gradient centrifugation. Cohorts of additional HIV-1-uninfected subjects and PLWH were established and approved by University of Alabama at Birmingham Hospital Institutional Review Board, Duke University Hospital Institutional Review Board, and University of Hawaii Hospital Institutional Review Board . All parHuman NK cells were isolated from PBMC by EasySep Human NK cell isolation kit (STEMCELL technology) or Human NK cell Isolation kit (Miltenyi) and AutoMACS Separator (Miltenyi) following the manufacturer’s recommended protocols. NK cells from RM PBMC or spleens were enriched by the previously described protocol ,81.Harvested NK cells were incubated with 200ng/ml anti-human CD16, , 20μg/ml anti-human NKp46 , 20μg/ml anti-human NKG2D , or 2μg/ml anti-human CD2 antibody . 20 minutes after incubation, goat anti-mouse IgG F(ab)’2 fragments  were added to crosslink antibodies for 5 minutes at 37°C. The doses of each stimulant and the length of crosslinking were determined by antibody titration and time course experiments and also referenced from our previously published study . Since tThe levels of 10 phosphorylated (p) proteins  in NK cell lysates were quantified using Milliplex Multi Pathway Magnetic Bead 9-Plex (EMD Millipore) and Milliplex T cell receptor signaling Magnetic Bead kit 7-plex (EMD Millipore) following manufacturer’s recommended protocols and data was collected on the MAGPIX System and Luminex 200 system (Luminex Corp). The raw mean fluorescent intensities (MFI) of phosphorylated proteins were normalized by the amount of GAPDH in each sample measured by Milliplex MAP Total GAPDH Magnetic Bead MAPMATE (EMD Millipore). ΔMFI was calculated using cells stimulated with anti-β2M antibody for background subtraction. Signals lower than β2M-‘stimulated’ conditions were normalized to an MFI of one. We also separately analyzed GAPDH-normalized MFI values without background subtraction for each experiment, which is illustrated in Plasma IL-18 levels in the plasma of SIV-uninfected or -infected RM were measured using IL-18 Non-Human Primate Procarta Simplex kit (ThermoFisher) following manufacturer’s recommended instructions. Luminex 200 system (Luminex Corp) was used for data acquisition, and the concentration of IL-18 in each sample was calculated by ProcartaPlex Analyzer App (ThermoFisher) based on the standard curve generated from the same experiment. Undetectable cytokine concentrations were normalized to 0.01pg/ml, the limit of detection for this assay.Mononuclear cells and PBMC were stained with viability dye Aqua 500 solution (ThermoFisher) for 30 minutes followed by the staining of surface receptors: anti-CD3-BV786 , CD14-BUV737 , CD20-BUV395 , CD56-BV605 , HLADR-APC-Cy7 , CD16-BUV496 , NKp46-PE-Cy5.5 , NKG2D-APC , CD2-PE-CF594 , anti-NKG2A-PE-Cy7 , and anti-ADAM17-Pacific Blue. Anti-ADAM17-Pacific Blue antibodies were generated by conjugating fluorophore to anti-human ADAM17 antibody  using the Pacific Blue conjugation kit (ThermoFisher). 20 minutes after surface receptor staining, cells were permeabilized with the Fix & Perm buffer kit (ThermoFisher) and stained with an intracellular staining antibody cocktail including anti-Syk-PE (Life Technologies), anti-Fc receptor γ chain (FcRγ)–Alexa Fluor 700 , and anti-SHP-1-FITC  for 20 minutes. Cells were then fixed with 2% paraformaldehyde and data were collected by LSR II and A5 Symphony (BD Biosciences), and FlowJo v.9.9.6 (Flowjo) was used for analysis. The gating strategies for NK cells in human and RM PBMC were summarized in Human or RM PBMC were thawed and incubated with 200ng/ml of anti-CD16 , 20μg/ml of anti-NKp46 antibody , or 2μg/ml anti-human CD2 antibody  at room temperature. 20 minutes after incubation, antibodies on cells were crosslinked with 40μg/ml of GAM for 2.5 minutes at 37°C. PBMC were then fixed with BD fixation buffer I (BD Biosciences) for 10 minutes at 37°C and blocked with normal mouse serum (ThermoFisher) for 10 minutes. After blocking, surface receptors were stained using anti-CD3-BV786 , anti-CD14-BUV737 , anti-CD20-BUV395 , anti-CD56-BV605 BD Pharmingen, clone NCAM16.2), anti-HLADR-ECD  for 20 minutes at room temperature. Stained cells were then permeabilized by BD Perm buffer III (BD Biosciences) for 30 minutes on ice and stained with anti-CD3ζ-PE-Cy5.5 , anti-phospho (p)-CD3ζ-APC , anti-Syk-PE , anti-p-Syk-AlexaFluor 488 , and FcRγ- AlexaFluor 700 . 20 minutes after staining, cells were fixed with 2% paraformaldehyde. Data were acquired by LSR II and A5 Symphony (BD Biosciences), and the analysis was performed using FlowJo v.9.9.6.Human PBMC were cultured in RPMI Medium (Corning) with 10% Fetal Bovine Serum (ThermoFisher) (R10) in the presence or absence of 1ng/ml recombinant human IL-15 (Miltenyi Biotec), 10ng/ml recombinant human IL-18 (R&D systems), 6μg/ml human IgG1 kappa isotype control , 6μg/ml anti-TACE antibody , and 25μM ADAM17 inhibitor TAPI-1 (Selleckchem) ,68 overnIn parallel, NK cells were isolated from PBMC after overnight culture using human NK cell isolation kit (Miltenyi) and AutoMACS Separator (Miltenyi). Cells were coated with 20μg/ml anti-human β2-microbulin , 200ng/ml anti-human CD16  for 20 minutes followed by antibody crosslinking using 40μg/ml GAM for 5 minutes at 37°C. Cells were then lysed and the levels of phosphorylated molecules in ITAM-based signaling  were quantified by the Luminex 200 system (Luminex Corp) using Milliplex T cell receptor signaling Magnetic Bead kit 7-plex (EMD Millipore) and Milliplex MAP Total GAPDH Magnetic Bead MAPMATE (EMD Millipore).For RM PBMC, cells were incubated in R10 with or without 10ng/ml recombinant RM IL-18 (R&D systems), 6μg/ml anti-TACE antibody , and 25μM ADAM17 inhibitor TAPI-1 (Selleckchem). The next day, cells were stained with the same surface & intracellular antibody panel as with human PBMC, and the levels of CD16 on NK cells were measured via flow cytometry.P-values of less than 0.05 were considered to be statistically significant. For unpaired samples, One-way ANOVA tests were used to determine statistically significant differences in experiments with more than three conditions. For experiments between two groups, Mann-Whitney U tests were applied to evaluate statistically significant differences for unpaired analysis, and Wilcoxon matched-paired signed rank tests or paired t tests were performed for paired analyses. When analyzing the correlation between two parameters, Spearman correlation coefficient was calculated using GraphPad Prism 9.0 software.Statistical analyses were performed using GraphPad Prism 9.0 software (GraphPad software). S1 TableDemographic information on HIV-uninfected individuals and PLWH with or without antiretroviral treatments  were tabulated. VL: viral load, NA: not applicable.(XLSX)Click here for additional data file.S1 Fig(A) and experimentally naïve RM PBMC (B) were crosslinked with anti-CD16 or NKp46 antibody and the percentages of p-Syk+ cells in live CD3-CD14-CD20-CD56+Syk+ were quantified. Representative flow plots are shown.Healthy human PBMC (TIF)Click here for additional data file.S2 Fig(A) and RM PBMC with or without SIV infection (B).Shown are representative gating strategies to analyze surface and intracellular marker expression on HIV-1-uninfected or PLWH human PBMC (TIF)Click here for additional data file.S3 Fig(A) NK cell isolation was performed for PBMC from HIV-1 uninfected individuals (n = 5), PLWH on (n = 6) or off ART (n = 5) and crosslinked with anti-CD16, NKp46, NKG2D, and CD2 antibodies. The levels of phosphorylated proteins were measured by Luminex technology. MFI values of each analyte were normalized by GAPDH MFI, and summary boxplots were shown. (B) NK cells were enriched from naïve (n = 8) and SIV chronically-infected RM (n = 6) and stimulated via CD16, NKp46, NKG2D, and CD2 crosslinking. The amount of phosphorylated analytes was quantified by Luminex platform. normalized MFI by GAPDH levels were plotted in the summary boxplots.(TIF)Click here for additional data file.S4 Fig(A) NK cells were purified from PBMC from HIV-1 uninfected subjects (n = 5), PLWH with (n = 6) or without ART (n = 5) and stimulated with NKp46 and NKG2D. the levels of phospho-proteins were measured by Luminex platform. (B) PBMC from SIV-uninfected (n = 8) and chronically infected (n = 2) were enriched for NK cells. Cells were then crosslinked with anti-NKp46 and anti-NKG2D antibodies and the magnitude of phosphorylation of seven signaling molecules was assessed by Luminex assay. ΔMFI was calculated by normalization of raw MFI by GAPDH values followed by background subtraction using β2M- ‘stimulated’ cells. The summary boxplots are depicted, and each dot represents different donors or animals.(TIF)Click here for additional data file.S5 Fig(A) PBMC from HIV-1 uninfected individuals (n = 46), and PLWH receiving ART (n = 58) were stained and %CD56dimCD16+ NK cells of live CD3-CD4-CD14-CD19- were calculated by flow cytometry. (B) The percentages of CD56brightCD16- NK cells were correlated with the expression of CD16 on total NK cells. Spearman correlation coefficient was calculated.  The levels of SHP-1 (C) and total Syk (D) in total NK cells from HIV-1-uninfected subjects (n = 5), PLWH with (n = 6) or without ART (n = 5) were measured by flow cytometry. (E) PBMC from SIV-uninfected or infected (n = 20) RM were stained and %CD56-CD16+ cells was measured for live CD3-CD14-CD20-HLADR-NKG2A/C+ cells. Each dot represents different animals or subjects. (***: p<0.005). (F) The expression of total Syk, ZAP70, CD3ζ, and FcRγ in total NK cells from SIV-uninfected (n = 7), and chronically infected (n = 6) macaques were quantified by flow cytometry.(TIF)Click here for additional data file.S6 Fig(A) Healthy human PBMC were left untreated (n = 12) or incubated with IL-18 (n = 10), IL-15 (n = 6), or both IL-15 & IL-18 (n = 6). After overnight culture, cells were then stained and analyzed by flow cytometry. The MFI of CD2 and SHP-1 on live total NK cells were quantified. Summary boxplots of CD2 and SHP-1 MFI on live total NK cells were shown, where respective dots represent different subjects. (B) Healthy human PBMC were cultured in the presence or absence of IL-1β, IL-33, and IL-18 overnight and the expression of CD16 on total NK cells were measured by flow cytometry. The statistically significant differences were evaluated using paired t tests. .(TIF)Click here for additional data file.S7 FigSIV-uninfected RM PBMC were incubated with or without IL-18, ADAM17 blocking antibody (aADAM17), and TAPI-1 (n = 2 for each). Following incubation, cells were stained and flow cytometric analysis was performed to assess the levels of CD16 on NK cells.(TIF)Click here for additional data file.S8 Fig(A) Healthy human PBMC were cultured in the presence or absence of 10ng/mL IL-18 (n = 8) and 25μM TAPI-1 (n = 8) along with IL-15 overnight. NK cells were then isolated and then applied with CD16 stimulation. The levels of phospho-proteins were measured using the Luminex platform. MFI values of each analyte were normalized by GAPDH MFI, and normalized MFI was plotted in the summary boxplot . (B) Spearman correlation was analyzed between the MFI of CD16 on total NK cells and raw MFI of p-Syk following CD16 stimulation with or without IL-18 and TAPI-1 treatment.(TIF)Click here for additional data file.