[Inhibition of connexin 43-mediated hemichannel activity promotes odontoblast differentiation of human dental pulp cells induced by lipopolysaccharide].

PURPOSE: To investigate the role and mechanism of connexin 43（Cx43）in odontoblast differentiation of human dental pulp cells (hDPCs) induced by lipopolysaccharide (LPS). METHODS: The maxillary first molar injury model of SD rats was established. The expression pattern of Cx43 in dental pulp repair after injury was detected by immunofluorescence(IF) staining. hDPCs was respectively stimulated with 0, 1, 10, 100 and 1 000 ng/mL LPS for 6 h to screen the optimal concentration, and then the expression of Cx43 was inhibited and overexpressed in hDPCs. Quantitative real-time PCR(qRT-PCR) and Western blot(WB) were used to detect the expression of Cx43 and dentin sialophosphoprotein (DSPP), dental matrix protein-1 (DMP-1), osterix (Osx) and extracellular signal-regulated kinase (ERK) activity. Furthermore, hDPCs were treated with specific Cx43 channel inhibitors to investigate the effect of Cx43-mediated channel activity in odontoblast differentiation of hDPCs, and to explore the role and mechanism of Cx43 in regulating odontoblast differentiation of hDPCs induced by LPS. Statistical analysis was performed with SPSS 26.0 software package. RESULTS: IF results showed that Cx43 was mainly expressed in the odontoblast layer in healthy dental pulp tissues. At 3-24 h after tooth injury, the expression of Cx43 decreased and then gradually increased to the normal level; from 3 days to 2 weeks after injury, the expression of Cx43 tended to be down-regulated which was in the odontoblast layer and pulp proper. The expression of DSPP mRNA was significantly up-regulated in the hDPCs stimulated with 10 ng/mL LPS for 6 h(P＜0.01). Inhibition of Cx43 significantly up-regulated the expression of DSPP, DMP-1 and Osx mRNA induced by LPS in hDPCs(P＜0.05), while overexpression of Cx43 obviously inhibited the expression of factors related to LPS-induced odontoblast differentiation(P＜0.01) and the fluorescence intensity of DSPP. 10 ng/mL LPS activated ERK signal in hDPCs, and overexpression of Cx43 significantly attenuated the activity of ERK signal induced by LPS(P＜0.01). Inhibition of Cx43-mediated hemichannel (HC) promoted mRNA expression of factors related to odontoblast differentiation in hDPCs and the activity of ERK signal induced by LPS(P＜0.05), while blocking Cx43-mediated gap junction channel (GJC) inhibited odontoblast differentiation. CONCLUSIONS: Cx43 participates in the regulation of dental pulp repair after injury, and its expression shows a downward trend as a whole. Inhibition of Cx43 or blocking of HC promotes LPS-induced ERK signal activity and odontoblast differentiation of hDPCs.

Fast and accurate variant identification tool for sequencing-based studies.

BACKGROUND: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. RESULTS: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. CONCLUSIONS: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

Temporal dynamics of gut microbiomes in non-industrialized urban Amazonia.

Increasing levels of industrialization have been associated with changes in gut microbiome structure and loss of features thought to be crucial for maintaining gut ecological balance. The stability of gut microbial communities over time within individuals seems to be largely affected by these changes but has been overlooked among transitioning populations from low- to middle-income countries. Here, we used metagenomic sequencing to characterize the temporal dynamics in gut microbiomes of 24 individuals living an urban non-industrialized lifestyle in the Brazilian Amazon. We further contextualized our data with 165 matching longitudinal samples from an urban industrialized and a rural non-industrialized population. We show that gut microbiome composition and diversity have greater variability over time among non-industrialized individuals when compared to industrialized counterparts and that taxa may present diverse temporal dynamics across human populations. Enterotype classifications show that community types are generally stable over time despite shifts in microbiome structure. Furthermore, by tracking genomes over time, we show that levels of bacterial population replacements are more frequent among Amazonian individuals and that non-synonymous variants accumulate in genes associated with degradation of host dietary polysaccharides. Taken together, our results suggest that the stability of gut microbiomes is influenced by levels of industrialization and that tracking microbial population dynamics is important to understand how the microbiome will adapt to these transitions.IMPORTANCEThe transition from a rural or non-industrialized lifestyle to urbanization and industrialization has been linked to changes in the structure and function of the human gut microbiome. Understanding how the gut microbiomes changes over time is crucial to define healthy states and to grasp how the gut microbiome interacts with the host environment. Here, we investigate the temporal dynamics of gut microbiomes from an urban and non-industrialized population in the Amazon, as well as metagenomic data sets from urban United States and rural Tanzania. We showed that healthy non-industrialized microbiomes experience greater compositional shifts over time compared to industrialized individuals. Furthermore, bacterial strain populations are more frequently replaced in non-industrialized microbiomes, and most non-synonymous mutations accumulate in genes associated with the degradation of host dietary components. This indicates that microbiome stability is affected by transitions to industrialization, and that strain tracking can elucidate the ecological dynamics behind such transitions.

Ultrafine Pt Nanoparticles Anchored on 2D Metal-Organic Frameworks as Multifunctional Electrocatalysts for Water Electrolysis and Zinc-Air Batteries.

Multifunctional electrocatalysts are crucial to cost-effective electrochemical energy conversion and storage systems requiring mutual enhancement of disparate reactions. Embedding noble metal nanoparticles in 2D metal-organic frameworks (MOFs) are proposed as an effective strategy, however, the hybrids usually suffer from poor electrochemical performance and electrical conductivity in operating conditions. Herein, ultrafine Pt nanoparticles strongly anchored on thiophenedicarboxylate acid based 2D Fe-MOF nanobelt arrays (Pt@Fe-MOF) are fabricated, allowing sufficient exposure of active sites with superior trifunctional electrocatalytic activity for hydrogen evolution, oxygen evolution, and oxygen reduction reactions. The interfacial Fe─O─Pt bonds can induce the charge redistribution of metal centers, leading to the optimization of adsorption energy for reaction intermediates, while the dispersibility of ultrafine Pt nanoparticles contributes to the high mass activity. When Pt@Fe-MOF is used as bifunctional catalysts for water-splitting, a low voltage of 1.65 V is required at 100 mA cm-2 with long-term stability for 20 h at temperatures (65 °C) relevant for industrial applications, outperforming commercial benchmarks. Furthermore, liquid Zn-air batteries with Pt@Fe-MOF in cathodes deliver high open-circuit voltages (1.397 V) and decent cycling stability, which motivates the fabrication of flexible quasisolid-state rechargeable Zn-air batteries with remarkable performance.

Correlation analysis of carotid artery intima-media thickness, serum 25(OH)D and men with erectile dysfunction.

Our goal is to investigate the connection between serum 25(OH)D and carotid artery intima-media thickness (CIMT) in men with erectile dysfunction (ED).Serum 25(OH)D and CIMT were measured in 124 participants with erectile dysfunction and 39 healthy controls. The relationship between them and different patient-related parameters and disease-related parameters was studied. Compared with the control group and mild ED group, the level of serum 25(OH)D in moderate ED group and severe ED group decreased significantly(P<0.05). The CIMT values of moderate ED group and severe ED group were higher than those of the control group(P<0.05). The CIMT value of severe ED group was significantly higher than that of mild ED group(P<0.05). IIEF-5 score was positively correlated with serum 25(OH)D level, but negatively correlated with CIMT value(P<0.05). After adjusting for the influence of confounding factors, The CIMT values, 25(OH)D and IIEF-5 score were substantially associated(P<0.05). The serum level of 25(OH)D and IIEF-5 score were positively correlated, while the CIMT values and IIEF-5 score were negatively correlated. The level of serum 25(OH)D should be analyzed in men with ED, especially in patients with vasculogenic ED, and supplementation is recommended for those who were with vitamin D deficiency.

Gut Ruminococcaceae levels at baseline correlate with risk of antibiotic-associated diarrhea.

Antibiotic-associated diarrhea (AAD) affects a significant proportion of patients receiving antibiotics. We sought to understand if differences in the gut microbiome would influence the development of AAD. We administered a 3-day course of amoxicillin-clavulanate to 30 healthy adult volunteers, and analyzed their stool microbiome, using 16S rRNA gene sequencing, at baseline and up to 4 weeks post antibiotic administration. Lower levels of gut Ruminococcaceae were significantly and consistently observed from baseline until day 7 in participants who developed AAD. Overall, participants who developed AAD experienced a greater decrease in microbial diversity. The probability of AAD could be predicted based on qPCR-derived levels of Faecalibacterium prausnitzii at baseline. Our findings suggest that a lack of gut Ruminococcaceae influences development of AAD. Quantification of F. prausnitzii in stool prior to antibiotic administration may help identify patients at risk of AAD, and aid clinicians in devising individualized treatment regimens to minimize such adverse effects.

An omics-based framework for assessing the health risk of antimicrobial resistance genes.

Antibiotic resistance genes (ARGs) are widespread among bacteria. However, not all ARGs pose serious threats to public health, highlighting the importance of identifying those that are high-risk. Here, we developed an 'omics-based' framework to evaluate ARG risk considering human-associated-enrichment, gene mobility, and host pathogenicity. Our framework classifies human-associated, mobile ARGs (3.6% of all ARGs) as the highest risk, which we further differentiate as 'current threats' (Rank I; 3%) - already present among pathogens - and 'future threats' (Rank II; 0.6%) - novel resistance emerging from non-pathogens. Our framework identified 73 'current threat' ARG families. Of these, 35 were among the 37 high-risk ARGs proposed by the World Health Organization and other literature; the remaining 38 were significantly enriched in hospital plasmids. By evaluating all pathogen genomes released since framework construction, we confirmed that ARGs that recently transferred into pathogens were significantly enriched in Rank II ('future threats'). Lastly, we applied the framework to gut microbiome genomes from fecal microbiota transplantation donors. We found that although ARGs were widespread (73% of genomes), only 8.9% of genomes contained high-risk ARGs. Our framework provides an easy-to-implement approach to identify current and future antimicrobial resistance threats, with potential clinical applications including reducing risk of microbiome-based interventions.

Underrepresented high diversity of class 1 integrons in the environment uncovered by PacBio sequencing using a new primer.

Class 1 integrons (CL1s) are one of the major contributors to the horizontal transfer of antibiotic resistance genes (ARGs). However, our knowledge of CL1 in the environment is still very limited due to the limitations of the current PCR primers and the sequencing methods adopted. This study developed a new primer coupled with PacBio sequencing to investigate the underrepresented diversity of CL1s in a mixed environmental sample (i.e. activated sludge from wastewater treatment plant and pig feces from animal farm). The new primer successfully uncovered 20 extra ARGs subtypes and 57% (422/739) more unique integron array structures than the previous primers. Compared to the whole genome database, CL1s revealed in the environment in this study were of much greater diversity, having 93% (900/967) novel array structures. Antibiotic resistance is the predominant function (78.3% genes) carried by CL1, and a vast majority (98.6% genes) of them confer resistance to aminoglycoside, beta-lactam, trimethoprim, or chloramphenicol. Additionally, 78.5% unique CL1 arrays carried more than one ARGs, and 25.9% of them carried ARGs of clinical relevance with high transferability potential posing threat to the general public. Our results indicated the importance of CL1s in the spread of ARGs. Overall, combining PacBio sequencing with the new primer designed in this study largely broadened our knowledge of CL1s in the environment and their significance in the environmental proliferation of ARGs.

Evaluating Solid Lung Adenocarcinoma Anaplastic Lymphoma Kinase Gene Rearrangement Using Noninvasive Radiomics Biomarkers.

PURPOSE: To develop a radiogenomics classifier to assess anaplastic lymphoma kinase (ALK) gene rearrangement status in pretreated solid lung adenocarcinoma noninvasively. MATERIALS AND METHODS: This study consisted of 140 consecutive pretreated solid lung adenocarcinoma patients with complete enhanced CT scans who were tested for both EGFR mutations and ALK status. Pre-contrast CT and standard post-contrast CT radiogenomics machine learning classifiers were designed as two separate classifiers. In each classifier, dataset was randomly split into training and independent testing group on a 7:3 ratio, accordingly subjected to a 5-fold cross-validation. After normalization, best feature subsets were selected by Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) or recursive feature elimination (RFE), whereupon a radiomics classifier was built with support vector machine (SVM). The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: In classifier one, 98 cases were selected as training data set, 42 cases as independent testing data set. In classifier two, 87 cases were selected as training data set, 37 cases as independent testing data set. Both classifiers extracted 851 radiomics features. The top 25 pre-contrast features and top 19 post-contrast features were selected to build optimal ALK+ radiogenomics classifiers accordingly. The accuracies, AUCs, sensitivity, specificity, PPV, and NPV of pre-contrast CT classifier were 78.57%, 80.10% (CI: 0.6538-0.9222), 71.43%, 82.14%, 66.67%, and 85.19%, respectively. Those results of standard post-contrast CT classifier were 81.08%, 82.85% (CI: 0.6630-0.9567), 76.92%, 83.33%, 71.43%, and 86.96%. CONCLUSION: Solid lung adenocarcinoma ALK+ radiogenomics classifier of standard post-contrast CT radiomics biomarkers produced superior performance compared with that of pre-contrast one, suggesting that post-contrast CT radiomics should be recommended in the context of solid lung adenocarcinoma radiogenomics AI. Standard post-contrast CT machine learning radiogenomics classifier could help precisely identify solid adenocarcinoma ALK rearrangement status, which may act as a pragmatic and cost-efficient substitute for traditional invasive ALK status test.

Differentiation of Treatment-Related Effects from Glioma Recurrence Using Machine Learning Classifiers Based Upon Pre-and Post-Contrast T1WI and T2 FLAIR Subtraction Features: A Two-Center Study.

PURPOSE: We propose three support vector machine (SVM) classifiers, using pre-and post-contrast T2 fluid-attenuated inversion recovery (FLAIR) subtraction and/or pre-and post-contrast T1WI subtraction, to differentiate treatment-related effects (TRE) from glioma recurrence. MATERIALS AND METHODS: Fifty-six postoperative high-grade glioma patients with suspicious progression after radiotherapy and chemotherapy from two centers were studied. Pre-and post-contrast T1WI and T2 FLAIR were collected. Each pre-contrast image was voxel-wise subtracted from the co-registered post-contrast image. Dataset was randomly split into training, and testing on a 7:3 ratio, accordingly subjected to a five fold cross validation. Best feature subsets were selected by Pearson correlation coefficient and recursive feature elimination, whereupon a radiomics classifier was built with SVM. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: In all, 186 features were extracted on each subtraction map. Top nine T1WI subtraction features, top thirteen T2 FLAIR subtraction features and top thirteen combination features were selected to build optimal SVM classifiers accordingly. The accuracies/AUCs/sensitivity/specificity/PPV/NPV of SVM based on sole T1WI subtraction were 80.00%/80.00% (CI: 0.5370-1.0000)/100%/70.00%/62.50%/100%. Those results of SVM based on sole T2 FLAIR subtraction were 86.67%/84.00% (CI: 0.5962-1.0000)/100%/80%/71.43%/100%. Those results of SVM based on both T1WI subtraction and T2 FLAIR subtraction were 93.33%/94.00% (CI: 0.7778-1.0000)/100%/90%/83.33%/100%, respectively. CONCLUSION: Pre- and post-contrast T2 FLAIR subtraction provided added value for diagnosis between recurrence and TRE. SVM based on a combination of T1WI and T2 FLAIR subtraction maps was superior to the sole use of T1WI or T2 FLAIR for differentiating TRE from recurrence. The SVM classifier based on combination of pre-and post-contrast subtraction T2 FLAIR and T1WI imaging allowed for the accurate differential diagnosis of TRE from recurrence, which is of paramount importance for treatment management of postoperative glioma patients after radiation therapy.

Online searching platform for the antibiotic resistome in bacterial tree of life and global habitats.

Metagenomic analysis reveals that antibiotic-resistance genes (ARGs) are widely distributed in both human-associated and non-human-associated habitats. However, it is difficult to equally compare ARGs between samples without a standard method. Here, we constructed a comprehensive profile of the distribution of potential ARGs in bacterial tree of life and global habitats by investigating ARGs in 55 000 bacterial genomes, 16 000 bacterial plasmid sequences, 3000 bacterial integron sequences and 850 metagenomes using a standard pipeline. We found that >80% of all known ARGs are not carried by any plasmid or integron sequences. Among potential mobile ARGs, tetracycline and beta-lactam resistance genes (such as tetA, tetM and class A beta-lactamase gene) distribute in multiple pathogens across bacterial phyla, indicating their clinical relevance and importance. We showed that class 1 integrases (intI1) display a poor linear relationship with total ARGs in both non-human-associated and human-associated environments. Furthermore, both total ARGs and intI1 genes show little correlation with the degree of anthropogenicity. These observations highlight the need to differentiate ARGs of high clinical relevance. This profile is published on an online platform (ARGs-OSP, http://args-osp.herokuapp.com/) as a valuable resource for the most challenging topics in this field, i.e. the risk, evolution and emergence of ARGs.

Mining traits for the enrichment and isolation of not-yet-cultured populations.

BACKGROUND: The lack of pure cultures limits our understanding into 99% of bacteria. Proper interpretation of the genetic and the transcriptional datasets can reveal clues for the enrichment and even isolation of the not-yet-cultured populations. Unraveling such information requires a proper mining method. RESULTS: Here, we present a method to infer the hidden traits for the enrichment of not-yet-cultured populations. We demonstrate this method using Candidatus Accumulibacter. Our method constructs a whole picture of the carbon, electron, and energy flows in the not-yet-cultured populations from the genomic datasets. Then, it decodes the coordination across three flows from the transcriptional datasets. Based on it, our method diagnoses the status of the not-yet-cultured populations and provides strategy to optimize the enrichment systems. CONCLUSION: Our method could shed light to the exploration into the bacterial dark matter in the environments.

Genomic resolution of bacterial populations in saccharin and cyclamate degradation.

The benefits of extensive artificial sweeteners use come at a cost of their ubiquitous occurrence in the aquatic environment. Biodegradation is crucial for the removal of artificial sweeteners in the environment, yet comprehensive characterizations of the degradation consortia that degrade these compounds have not been initiated. Here, we performed metagenomic analysis of microbial communities fulfilling complete mineralization of two typical artificial sweeteners, i.e. saccharin and cyclamate. Genome-resolved metagenomics enabled the recovery and metabolic characterization of total 23 population genomes from 8 phyla in the two consortia, most of which represented novel species. The saccharin-degrading consortia was notably dominated by a betaproteobacterial genome from the family Rhodocyclaceae, accounting for 15.5% of total sequences. For the cyclamate enrichment, 28.1% of the total sequences were assigned to three similarly abundant Alphaproteobacteria population genomes belonging to the family Sphingomonadaceae and Methylobacteriaceae. The metabolic potential of these population genomes were examined to potentially identify the roles of these populations in biodegradation of artificial sweeteners, and focusing on the energy and nutrient metabolisms.

Conserved phylogenetic distribution and limited antibiotic resistance of class 1 integrons revealed by assessing the bacterial genome and plasmid collection.

BACKGROUND: Integrons, especially the class 1 integrons, are major contributors to the acquisition and dissemination of antibiotic resistance genes (ARGs). However, comprehensive knowledge of the types, content, and distribution of integrons in bacterial taxa is lacking to evaluate their contribution. RESULTS: We have constructed a new integrase database and developed a pipeline that provides comprehensive recovery of class 1 integrons. Previous PCR-based techniques might only detect one fourth of the integron-integrases and integrons recovered in this study. By exploring the class 1 integrons in over 73,000 currently available complete and draft bacterial genomes, the contribution of class 1 integrons in spreading and acquiring ARGs was evaluated. Firstly, the host species of class 1 integrons are highly conserved within (96%) in class Gammaproteobacteria, dominated by four pathogenic species of "ESKAPE." Secondly, more than half of class 1 integrons are embedded in chromosomes with less potential for horizontal gene transfer. Finally, ARGs that have been acquired by these integrons only cover 11% of all the ARG genotypes detected in bacterial genomes. CONCLUSIONS: The above observations indicated that there are both biological and ecological limitations to class 1 integrons in acquiring and spreading ARGs across different classes of the domain Bacteria.

Effects of sample preservation and DNA extraction on enumeration of antibiotic resistance genes in wastewater.

With the growing application of high-throughput sequencing-based metagenomics for profiling antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs), comparison of sample pretreatment and DNA extraction methods are needed to move toward standardized comparisons among laboratories. Three widely employed DNA extraction methods (FastDNA® Spin Kit for Soil, PowerSoil® DNA Isolation Kit and ZR Fecal DNA MiniPrep), with and without preservation in 50% ethanol and freezing, were applied to the influent, activated sludge and effluent of two WWTPs, in Hong Kong and in the USA. Annotated sequences obtained from the DNA extracted using the three kits shared similar taxonomy and ARG profiles. Overall, it was found that the DNA yield and purity, and diversity of ARGs captured were all highest when applying the FastDNA SPIN Kit for Soil for all three WWTP sample types investigated here (influent, activated sludge, effluent). Quantitative polymerase chain reaction of 16S rRNA genes confirmed the same trend as DNA extraction yields and similar recovery of a representative Gram-negative bacterium (Escherichia coli). Moreover, sample fixation in ethanol, deep-freezing and overseas shipment had no discernable effect on ARG profiles, as compared to fresh samples. This approach serves to inform future efforts toward global comparisons of ARG distributions in WWTPs.

Integrated biogeography of planktonic and sedimentary bacterial communities in the Yangtze River.

BACKGROUND: Bacterial communities are essential to the biogeochemical cycle in riverine ecosystems. However, little is presently known about the integrated biogeography of planktonic and sedimentary bacterial communities in large rivers. RESULTS: This study provides the first spatiotemporal pattern of bacterial communities in the Yangtze River, the largest river in Asia with a catchment area of 1,800,000 km2. We find that sedimentary bacteria made larger contributions than planktonic bacteria to the bacterial diversity of the Yangzte River ecosystem with the sediment subgroup providing 98.8% of 38,906 operational taxonomic units (OTUs) observed in 280 samples of synchronous flowing water and sediment at 50 national monitoring stations covering a 4300 km reach. OTUs within the same phylum displayed uniform seasonal variations, and many phyla demonstrated autumn preference throughout the length of the river. Seasonal differences in bacterial communities were statistically significant in water, whereas bacterial communities in both water and sediment were geographically clustered according to five types of landforms: mountain, foothill, basin, foothill-mountain, and plain. Interestingly, the presence of two huge dams resulted in a drastic fall of bacterial taxa in sediment immediately downstream due to severe riverbed scouring. The integrity of the biogeography is satisfactorily interpreted by the combination of neutral and species sorting perspectives in meta-community theory for bacterial communities in flowing water and sediment. CONCLUSIONS: Our study fills a gap in understanding of bacterial communities in one of the world's largest river and highlights the importance of both planktonic and sedimentary communities to the integrity of bacterial biogeographic patterns in a river subject to varying natural and anthropogenic impacts.

Development of Quantitative Real-time PCR Assays for Different Clades of "Candidatus Accumulibacter".

We designed novel quantitative real-time polymerase chain reaction (qPCR) primers for the polyphosphate kinase 1 (ppk1) gene, targeting eight individual "Candidatus Accumulibacter" (referred to as Accumulibacter) clades. An evaluation of primer sets was conducted regarding the coverage, specificity, and PCR efficiency. (i) All primer sets were designed to cover all available sequences of the target clade. (ii) The phylogenetic analysis of the sequences retrieved from the qPCR products by each primer set demonstrated a high level of specificity. (iii) All calibration curves presented high PCR efficiencies in the range of 85-112% (R(2) = 0.962-0.998). In addition, the possible interference of non-target amplicons was individually examined using the qPCR assay for 13 Accumulibacter clades, which were either undetected or showed negligible detection. With the primers designed by other research groups, a highly selective and sensitive qPCR-based method was developed to quantify all Accumulibacter clades, with the exception of Clade IE, in one assay, which enables more comprehensive insights into the community dynamics. The applicability to environmental samples was demonstrated by profiling the Accumulibacter clades in activated sludge samples of nine full-scale wastewater treatment plants.