Sigma Promoter Research Articles

AI and Knowledge-Based Method for Rational Design of Escherichia coli Sigma70 Promoters.

Expanding sigma70 promoter libraries can support the engineering of metabolic pathways and enhance recombinant protein expression. Herein, we developed an artificial intelligence (AI) and knowledge-based method for the rational design of sigma70 promoters. Strong sigma70 promoters were identified by using high-throughput screening (HTS) with enhanced green fluorescent protein (eGFP) as a reporter gene. The features of these strong promoters were adopted to guide promoter design based on our previous reported deep learning model. In the following case study, the obtained strong promoters were used to express collagen and microbial transglutaminase (mTG), resulting in increased expression levels by 81.4% and 33.4%, respectively. Moreover, these constitutive promoters achieved soluble expression of mTG-activating protease and contributed to active mTG expression in Escherichia coli. The results suggested that the combined method may be effective for promoter engineering.

Deep Learning-Assisted Design of Novel Promoters in Escherichia coli.

Deep learning (DL) approaches have the ability to accurately recognize promoter regions and predict their strength. Here, the potential for controllably designing active Escherichia coli promoter is explored by combining multiple deep learning models. First, "DRSAdesign," which relies on a diffusion model to generate different types of novel promoters is created, followed by predicting whether they are real or fake and strength. Experimental validation showed that 45 out of 50 generated promoters are active with high diversity, but most promoters have relatively low activity. Next, "Ndesign," which relies on generating random sequences carrying functional -35 and -10 motifs of the sigma70 promoter is introduced, and their strength is predicted using the designed DL model. The DL model is trained and validated using 200 and 50 generated promoters, and displays Pearson correlation coefficients of 0.49 and 0.43, respectively. Taking advantage of the DL models developed in this work, possible 6-mers are predicted as key functional motifs of the sigma70 promoter, suggesting that promoter recognition and strength prediction mainly rely on the accommodation of functional motifs. This work provides DL tools to design promoters and assess their functions, paving the way for DL-assisted metabolic engineering.

Sigma70Pred: A highly accurate method for predicting sigma70 promoter in Escherichia coli K-12 strains.

Sigma70 factor plays a crucial role in prokaryotes and regulates the transcription of most of the housekeeping genes. One of the major challenges is to predict the sigma70 promoter or sigma70 factor binding site with high precision. In this study, we trained and evaluate our models on a dataset consists of 741 sigma70 promoters and 1,400 non-promoters. We have generated a wide range of features around 8,000, which includes Dinucleotide Auto-Correlation, Dinucleotide Cross-Correlation, Dinucleotide Auto Cross-Correlation, Moran Auto-Correlation, Normalized Moreau-Broto Auto-Correlation, Parallel Correlation Pseudo Tri-Nucleotide Composition, etc. Our SVM based model achieved maximum accuracy 97.38% with AUROC 0.99 on training dataset, using 200 most relevant features. In order to check the robustness of the model, we have tested our model on the independent dataset made by using RegulonDB10.8, which included 1,134 sigma70 and 638 non-promoters, and able to achieve accuracy of 90.41% with AUROC of 0.95. Our model successfully predicted constitutive promoters with accuracy of 81.46% on an independent dataset. We have developed a method, Sigma70Pred, which is available as webserver and standalone packages at https://webs.iiitd.edu.in/raghava/sigma70pred/. The services are freely accessible.

Transcriptional Landscape of Staphylococcus aureus Kayvirus Bacteriophage vB_SauM-515A1.

The Twort-like myoviruses (Kayvirus genus) of S. aureus are promising agents for bacteriophage therapy due to a broad host range and high killing activity against clinical isolates. This work improves the current understanding of the phage infection physiology by transcriptome analysis. The expression profiles of a typical member of the Kayvirus genus (vB_SauM-515A1) were obtained at three time-points post-infection using RNA sequencing. A total of 35 transcription units comprising 238 ORFs were established. The sequences for 58 early and 12 late promoters were identified in the phage genome. The early promoters represent the strong sigma-70 promoters consensus sequence and control the host-dependent expression of 26 transcription units (81% of genes). The late promoters exclusively controlled the expression of four transcription units, while the transcription of the other five units was directed by both types of promoters. The characteristic features of late promoters were long -10 box of TGTTATATTA consensus sequence and the absence of -35 boxes. The data obtained are also of general interest, demonstrating a strategy of the phage genome expression with a broad overlap of the early and late transcription phases without any middle transcription, which is unusual for the large phage genomes (>100 kbp).

IPromoter-BnCNN: a novel branched CNN-based predictor for identifying and classifying sigma promoters.

Promoter is a short region of DNA which is responsible for initiating transcription of specific genes. Development of computational tools for automatic identification of promoters is in high demand. According to the difference of functions, promoters can be of different types. Promoters may have both intra- and interclass variation and similarity in terms of consensus sequences. Accurate classification of various types of sigma promoters still remains a challenge. We present iPromoter-BnCNN for identification and accurate classification of six types of promoters-σ24,σ28,σ32,σ38,σ54,σ70. It is a CNN-based classifier which combines local features related to monomer nucleotide sequence, trimer nucleotide sequence, dimer structural properties and trimer structural properties through the use of parallel branching. We conducted experiments on a benchmark dataset and compared with six state-of-the-art tools to show our supremacy on 5-fold cross-validation. Moreover, we tested our classifier on an independent test dataset. Our proposed tool iPromoter-BnCNN web server is freely available at http://103.109.52.8/iPromoter-BnCNN. The runnable source code can be found https://colab.research.google.com/drive/1yWWh7BXhsm8U4PODgPqlQRy23QGjF2DZ. Supplementary data are available at Bioinformatics online.

Isolation and Characterization of Pectobacterium Phage vB_PatM_CB7: New Insights into the Genus Certrevirus.

To date, Certrevirus is one of two genera of bacteriophage (phage), with phages infecting Pectobacterium atrosepticum, an economically important phytopathogen that causes potato blackleg and soft rot disease. This study provides a detailed description of Pectobacterium phage CB7 (vB_PatM_CB7), which specifically infects P. atrosepticum. Host range, morphology, latent period, burst size and stability at different conditions of temperature and pH were examined. Analysis of its genome (142.8 kbp) shows that the phage forms a new species of Certrevirus, sharing sequence similarity with other members, highlighting conservation within the genus. Conserved elements include a putative early promoter like that of the Escherichia coli sigma70 promoter, which was found to be shared with other genus members. A number of dissimilarities were observed, relating to DNA methylation and nucleotide metabolism. Some members do not have homologues of a cytosine methylase and anaerobic nucleotide reductase subunits NrdD and NrdG, respectively. Furthermore, the genome of CB7 contains one of the largest numbers of homing endonucleases described in a single phage genome in the literature to date, with a total of 23 belonging to the HNH and LAGLIDADG families. Analysis by RT-PCR of the HNH homing endonuclease residing within introns of genes for the large terminase, DNA polymerase, ribonucleotide reductase subunits NrdA and NrdB show that they are splicing competent. Electrospray ionization-tandem mass spectrometry (ESI-MS/MS) was also performed on the virion of CB7, allowing the identification of 26 structural proteins—20 of which were found to be shared with the type phages of the genera of Vequintavirus and Seunavirus. The results of this study provide greater insights into the phages of the Certrevirus genus as well as the subfamily Vequintavirinae.

Genome rearrangements induce biofilm formation in Escherichia coli C \u2013 an old model organism with a new application in biofilm research

BackgroundEscherichia coli C forms more robust biofilms than other laboratory strains. Biofilm formation and cell aggregation under a high shear force depend on temperature and salt concentrations. It is the last of five E. coli strains (C, K12, B, W, Crooks) designated as safe for laboratory purposes whose genome has not been sequenced.ResultsHere we present the complete genomic sequence of this strain in which we utilized both long-read PacBio-based sequencing and high resolution optical mapping to confirm a large inversion in comparison to the other laboratory strains. Notably, DNA sequence comparison revealed the absence of several genes thought to be involved in biofilm formation, including antigen 43, waaSBOJYZUL for lipopolysaccharide (LPS) synthesis, and cpsB for curli synthesis. The first main difference we identified that likely affects biofilm formation is the presence of an IS3-like insertion sequence in front of the carbon storage regulator csrA gene. This insertion is located 86 bp upstream of the csrA start codon inside the − 35 region of P4 promoter and blocks the transcription from the sigma32 and sigma70 promoters P1-P3 located further upstream. The second is the presence of an IS5/IS1182 in front of the csgD gene. And finally, E. coli C encodes an additional sigma70 subunit driven by the same IS3-like insertion sequence. Promoter analyses using GFP gene fusions provided insights into understanding this regulatory pathway in E. coli.ConclusionsBiofilms are crucial for bacterial survival, adaptation, and dissemination in natural, industrial, and medical environments. Most laboratory strains of E. coli grown for decades in vitro have evolved and lost their ability to form biofilm, while environmental isolates that can cause infections and diseases are not safe to work with. Here, we show that the historic laboratory strain of E. coli C produces a robust biofilm and can be used as a model organism for multicellular bacterial research. Furthermore, we ascertained the full genomic sequence of this classic strain, which provides for a base level of characterization and makes it useful for many biofilm-based applications.

Comparative Analysis of Mycoplasma gallisepticum vlhA Promoters.

Mycoplasma gallisepticum is an intracellular parasite affecting respiratory tract of poultry that belongs to class Mollicutes. M. gallisepticum features numerous variable lipoprotein hemagglutinin genes (vlhA) that play a role in immune escape. The vlhA promoters have a set of distinct properties in comparison to promoters of the other genes. The vlhA promoters carry a variable GAA repeats region at approximately 40 nts upstream of transcription start site. The promoters have been considered active only in the presence of exactly 12 GAA repeats. The mechanisms of vlhA expression regulation and GAA number variation are not described. Here we tried to understand these mechanisms using different computational methods. We conducted a comparative analysis among several M. gallisepticum strains. Nucleotide sequences analysis showed the presence of highly conserved regions flanking repeated trinucleotides that are not linked to GAA number variation. VlhA genes with 12 GAA repeats and their orthologs in 12 M. gallisepticum strains are more conserved than other vlhA genes and have narrower GAA number distribution. We conducted comparative analysis of physicochemical profiles of M. gallisepticum vlhA and sigma-70 promoters. Stress-induced duplex destabilization (SIDD) profiles showed that sigma-70 group is characterized by the common to prokaryotic promoters sharp maxima while vlhA promoters are hardly destabilized with the region between GAA repeats and transcription start site having zero opening probability. Electrostatic potential profiles of vlhA promoters indicate the presence of the distinct patterns that appear to govern initial stages of specific DNA-protein recognition. Open state dynamics profiles of vlhA demonstrate the pattern that might facilitate transcription bubble formation. Obtained data could be the basis for experimental identification of mechanisms of phase variation in M. gallisepticum.

Identification of a Novel Small RNA srvg23535 in Vibrio alginolyticus ZJ-T and Its Characterization With Phenotype MicroArray Technology.

Small non-coding RNAs (sRNAs) are important modulators of gene expression and are involved in the pathogenesis and survival of prokaryotes. However, few studies have been conducted with Vibrio alginolyticus, which limits our ability to probe the regulation of virulence and environmental adaptation by sRNAs in this opportunistic pathogen. In this study, the sRNA candidate srvg23535 was identified in V. alginolyticus ZJ-T. The precise transcript end, secondary structure, and sequence conservation were determined. A srvg23535 null mutant was constructed and characterized by using Phenotype MicroArray (PM) technology. In silico target prediction was conducted by IntaRNA and TargetRNA2. Subsequently, a 107 nt transcript was validated with a sigma70 promoter at the 5′ end and a Rho-independent terminator at the 3′ end. The sRNA srvg23535 had four stem-loop structures and was conserved among Vibrio harveyi, Vibrio parahaemolyticus, and Vibrio splendidus. Deletion of srvg23535 in V. alginolyticus ZJ-T led to a weaker utilization of D-mannose, D-melibiose, lactulose, and inosine as carbon sources but stronger utilization of L-cysteine as nitrogen source. Moreover, the srvg2353 mutant showed stronger resistance to osmotic stress but weaker resistance to pH stress. Additionally, a total of 22 common targets were identified and several were related to the observed phenotype of the mutant. This study indicated that the novel sRNA, srvg23535, is conserved and restricted to Vibrio spp., affecting the utilization of several carbon and nitrogen sources and the response to osmotic and pH stress. These results extend our understanding of sRNA regulation in V. alginolyticus and provide a significant resource for the further study of the precise target mRNAs of srvg23535, which may provide targets for antibacterial therapeutic or attenuated vaccines against Vibrio spp.

IPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features.

In bacterial DNA, there are specific sequences of nucleotides called promoters that can bind to the RNA polymerase. Sigma70 ([Formula: see text]) is one of the most important promoter sequences due to its presence in most of the DNA regulatory functions. In this paper, we identify the most effective and optimal sequence-based features for prediction of [Formula: see text] promoter sequences in a bacterial genome. We used both short-range and long-range DNA sequences in our proposed method. A very small number of effective features are selected from a large number of the extracted features using multi-window of different sizes within the DNA sequences. We call our prediction method iPro70-FMWin and made it freely accessible online via a web application established at http://ipro70.pythonanywhere.com/server for the sake of convenience of the researchers. We have tested our method using a standard benchmark dataset. In the experiments, iPro70-FMWin has achieved an area under the curve of the receiver operating characteristic and accuracy of 0.959 and 90.57%, respectively, which significantly outperforms the state-of-the-art predictors.

IPromoter-FSEn: Identification of bacterial σ70 promoter sequences using feature subspace based ensemble classifier

Sigma promoter sequences in bacterial genomes are important due to their role in transcription initiation. Sigma 70 is one of the most important and crucial sigma factors. In this paper, we address the problem of identification of σ70 promoter sequences in bacterial genome. We propose iPromoter-FSEn, a novel predictor for identification of σ70 promoter sequences. Our proposed method is based on a feature subspace based ensemble classifier. A large set of of features extracted from the sequence of nucleotides are divided into subsets and each subset is given to individual single classifiers to learn. Based on the decisions of the ensemble an aggregate decision is made by the ensemble voting classifier. We tested our method on a standard benchmark dataset extracted from experimentally validated results. Experimental results shows that iPromoter-FSEn significantly improves over the state-of-the art σ70 promoter sequence predictors. The accuracy and area under receiver operating characteristic curve of iPromoter-FSEn are 86.32% and 0.9319 respectively. We have also made our method readily available for use as an web application from: http://ipromoterfsen.pythonanywhere.com/server.

Identification of novel MITEs (miniature inverted-repeat transposable elements) in Coxiella burnetii: implications for protein and small RNA evolution

BackgroundCoxiella burnetii is a Gram-negative gammaproteobacterium and zoonotic agent of Q fever. C. burnetii’s genome contains an abundance of pseudogenes and numerous selfish genetic elements. MITEs (miniature inverted-repeat transposable elements) are non-autonomous transposons that occur in all domains of life and are thought to be insertion sequences (ISs) that have lost their transposase function. Like most transposable elements (TEs), MITEs are thought to play an active role in evolution by altering gene function and expression through insertion and deletion activities. However, information regarding bacterial MITEs is limited.ResultsWe describe two MITE families discovered during research on small non-coding RNAs (sRNAs) of C. burnetii. Two sRNAs, Cbsr3 and Cbsr13, were found to originate from a novel MITE family, termed QMITE1. Another sRNA, CbsR16, was found to originate from a separate and novel MITE family, termed QMITE2. Members of each family occur ~ 50 times within the strains evaluated. QMITE1 is a typical MITE of 300-400 bp with short (2-3 nt) direct repeats (DRs) of variable sequence and is often found overlapping annotated open reading frames (ORFs). Additionally, QMITE1 elements possess sigma-70 promoters and are transcriptionally active at several loci, potentially influencing expression of nearby genes. QMITE2 is smaller (150-190 bps), but has longer (7-11 nt) DRs of variable sequences and is mainly found in the 3′ untranslated region of annotated ORFs and intergenic regions. QMITE2 contains a GTAG repetitive extragenic palindrome (REP) that serves as a target for IS1111 TE insertion. Both QMITE1 and QMITE2 display inter-strain linkage and sequence conservation, suggesting that they are adaptive and existed before divergence of C. burnetii strains.ConclusionsWe have discovered two novel MITE families of C. burnetii. Our finding that MITEs serve as a source for sRNAs is novel. QMITE2 has a unique structure and occurs in large or small versions with unique DRs that display linkage and sequence conservation between strains, allowing for tracking of genomic rearrangements. QMITE1 and QMITE2 copies are hypothesized to influence expression of neighboring genes involved in DNA repair and virulence through transcriptional interference and ribonuclease processing.

70ProPred: a predictor for discovering sigma70 promoters based on combining multiple features

BackgroundPromoter is an important sequence regulation element, which is in charge of gene transcription initiation. In prokaryotes, σ70 promoters regulate the transcription of most genes. The promoter recognition has been a crucial part of gene structure recognition. It’s also the core issue of constructing gene transcriptional regulation network. With the successfully completion of genome sequencing from an increasing number of microbe species, the accurate identification of σ70 promoter regions in DNA sequence is not easy.ResultsIn order to improve the prediction accuracy of sigma70 promoters in prokaryote, a promoter recognition model 70ProPred was established. In this work, two sequence-based features, including position-specific trinucleotide propensity based on single-stranded characteristic (PSTNPss) and electron-ion potential values for trinucleotides (PseEIIP), were assessed to build the best prediction model. It was found that 79 features of PSTNPSS combined with 64 features of PseEIIP obtained the best performance for sigma70 promoter identification, with a promising accuracy and the Matthews correlation coefficient (MCC) at 95.56% and 0.90, respectively.ConclusionThe jackknife tests showed that 70ProPred outperforms the existing sigma70 promoter prediction approaches in terms of accuracy and stability. Additionally, this approach can also be extended to predict promoters of other species. In order to facilitate experimental biologists, an online web server for the proposed method was established, which is freely available at http://server.malab.cn/70ProPred/.

Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes. Therefore, the prediction of the promoters for a particular sigma factor is essential for interpreting functional genomic data and observation. This paper develops a new method to predict sigma-54 promoters in bacterial genomes. The new method organically integrates motif finding and machine learning strategies to capture the intrinsic features of sigma-54 promoters. The experiments on E. coli benchmark test set show that our method has good capability to distinguish sigma-54 promoters from surrounding or randomly selected DNA sequences. The applications of the other three bacterial genomes indicate the potential robustness and applicative power of our method on a large number of bacterial genomes. The source code of our method can be freely downloaded at https://github.com/maqin2001/PromotePredictor.

Hidden Secrets of Sigma54 Promoters Revealed

Bacterial sigma54 (σ54) promoters are the DNA-binding motif for σ54-containing RNA polymerase (RNAP) holoenzymes. A recent study using a combination of synthetic oligonucleotide library screening, biochemical characterization, and bioinformatics has uncovered a new and unexpected role for σ54 promoters, encoding a form of bacterial 'insulator sequence' to dampen unwanted translation.

Identifying Sigma70 Promoters with Novel Pseudo Nucleotide Composition.

Promoters are DNA regulatory elements located directly upstream or at the 5' end of the transcription initiation site (TSS), which are in charge of gene transcription initiation. With the completion of a large number of microorganism genomics, it is urgent to predict promoters accurately in bacteria by using the computational method. In this work, a sequence-based predictor named "iPro70-PseZNC" was designed for identifying sigma70 promoters in prokaryote. In the predictor, the samples of DNA sequences are formulated by a novel pseudo nucleotide composition, called PseZNC, into which the multi-window Z-curve composition and six local DNA structural properties are incorporated. In the 5-fold cross-validation, the area under the curve of receiver operating characteristic of 0.909 was obtained on our benchmark dataset, indicating that the proposed predictor is promising and will provide an important guide in this area. Further studies showed that the performance of PseZNC is better than it of multi-window Z-curve composition. For the sake of convenience for researchers, a user-friendly online service was established and can be freely accessible at http://lin.uestc.edu.cn/server/iPro70-PseZNC. The PseZNC approach can be also extended to other DNA-related problems.

Pro54DB: a database for experimentally verified sigma-54 promoters.

In prokaryotes, the σ54 promoters are unique regulatory elements and have attracted much attention because they are in charge of the transcription of carbon and nitrogen-related genes and participate in numerous ancillary processes and environmental responses. All findings on σ54 promoters are favorable for a better understanding of their regulatory mechanisms in gene transcription and an accurate discovery of genes missed by the wet experimental evidences. In order to provide an up-to-date, interactive and extensible database for σ54 promoter, a free and easy accessed database called Pro54DB (σ54 promoter database) was built to collect information of σ54 promoter. In the current version, it has stored 210 experimental-confirmed σ54 promoters with 297 regulated genes in 43 species manually extracted from 133 publications, which is helpful for researchers in fields of bioinformatics and molecular biology. Pro54DB is freely available on the web at http://lin.uestc.edu.cn/database/pro54db with all major browsers supported. greatchen@ncst.edu.cn or hlin@uestc.edu.cn

A novel sigma factor reveals a unique regulon controlling cell-specific recombination in Mycoplasma genitalium.

The Mycoplasma genitalium MG428 protein shows homology to members of the sigma-70 family of sigma factors. Herein, we found that MG428 activates transcription of recA, ruvA and ruvB as well as several genes with unknown function. Deletion of MG_428 or some of the up-regulated unknown genes led to severe recombination defects. Single cell analyses revealed that activation of the MG428-regulon is a rare event under laboratory growth conditions. A conserved sequence with sigma-70 promoter architecture (TTGTCA-N18/19-ATTWAT) was identified in the upstream region of all of the MG428-regulated genes or operons. Primer extension analyses demonstrated that transcription initiates immediately downstream of this sigma70-type promoter in a MG428-dependent manner. Furthermore, mutagenesis of the conserved −10 and −35 elements corroborated the requirement of these regions for promoter function. Therefore, a new mycoplasma promoter directs transcription of a unique recombination regulon. Additionally, MG428 was found to interact with the RNAP core enzyme, reinforcing the predicted role of this protein as an alternative sigma factor. Finally, our results indicate that MG428 contributes to the generation of genetic diversity in this model organism. Since recombination is an important mechanism to generate antigenic variation, MG428 emerges as a novel factor contributing to M. genitalium virulence.

IPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.

The σ54 promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the σ54 promoters. Here, a predictor called ‘iPro54-PseKNC’ was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called ‘pseudo k-tuple nucleotide composition’, which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at http://lin.uestc.edu.cn/server/iPro54-PseKNC. For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the σ54 promoters.

Abstract A67: Methylation of ESR1 and 14-3-3 sigma promoter in serum as possible biomarkers for screening and diagnosis for breast cancer

Abstract Background: To investigate the association between gene hypermethylation and the major clinico-pathological features of breast cancer, including diagnosis and treatment response. Material and Methods: 107 women with breast cancer and 108 control subjects were recruited. Real Time QMS-PCR SYBR green (methylation-specific PCR) was used to analyze the utility of circulating DNA with CpG island hypermethylation of APC, RAR-β, E-Cadherin, ESR1 and 14-3-3 sigma; gene promoter regions as breast cancer biomarkers. Sera were collected in 107 operable breast cancer patients (pts) previously surgery and in 60 of those pts after treatment. Respect controls, 34 had benign breast disease and 74 with no evidence of breast disease. Results: We found significant differences between breast cancer patients and healthy controls in relative serum levels of methylated gene promoters ESR1 (p = 0.0112) and 14-3-3sigma (p=0.0047). We observed that hypermethylation of these combined two genes differentiated between breast cancer patients and healthy controls (p <0.0001) with a sensitivity of 81% (95% CI: 72–88%) and specificity of 88% (95% CI: 78–94 %). Presence of methylated ESR1 in serum of breast cancer patients was associated with ER-negative phenotype (p = 0.0179); and presence of methylated 14-3-3-sigma was associated with T3-4 stage (OMS) (p< 0.05) and nodal positive status (p< 0.05). We observed lower methylated ERS1 or 14-3-3-sigma values after surgery, respect pretreatment levels, but without an overall statistically significant difference. With a median follow up of 6 years, we found that patients with a significant decrease of sera methylated levels of both genes after surgery had better time to progression an overall survival respect patients without this observation. Conclusions: this panel of genes detected in ductal lavage and blood specimens could be useful as markers for early detection of breast carcinoma. These findings cast some doubts on the utility for early cancer diagnosis of highly sensitive techniques to identify hypermethylation of specific gene promoters in DNA extracted from serum. Although numerous issues remain to be resolved, the quantitative measurement of circulating methylated DNA is a promising tool for cancer risk assessment. Note: This abstract was not presented at the conference. Citation Format: Joaquina Martinez-Galan, Blanca Torres-Torres, Juan Ramón Delgado. Methylation of ESR1 and 14-3-3 sigma promoter in serum as possible biomarkers for screening and diagnosis for breast cancer. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A67.