Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score.

BACKGROUND: The extent to which the relationships between clinical risk factors and coronary artery disease (CAD) are altered by CAD polygenic risk score (PRS) is not well understood. Here, we determine whether the interactions between clinical risk factors and CAD PRS further explain risk for incident CAD. METHODS: Participants were of European ancestry from the UK Biobank without prevalent CAD. An externally trained genome-wide CAD PRS was generated and then applied. Clinical risk factors were ascertained at baseline. Cox proportional hazards models were fitted to examine the incident CAD effects of CAD PRS, risk factors, and their interactions. Next, the PRS and risk factors were stratified to investigate the attributable risk of clinical risk factors. FINDINGS: A total of 357,144 individuals of European ancestry without prevalent CAD were included. During a median of 11.1 years of follow-up (interquartile range 10.4-14.1 years), CAD PRS was associated with 1.35-fold (95% confidence interval [CI] 1.332-1.368) risk per SD for incident CAD. The prognostic relevance of the following risk factors was relatively diminished for those with high CAD PRS on a continuous scale: type 2 diabetes (hazard ratio [HR]interaction 0.91, 95% CIinteraction 0.88-0.94), increased body mass index (HRinteraction 0.97, 95% CIinteraction 0.96-0.98), and increased C-reactive protein (HRinteraction 0.98, 95% CIinteraction 0.96-0.99). However, a high CAD PRS yielded joint risk increases with low-density lipoprotein cholesterol (HRinteraction 1.05, 95% CIinteraction 1.04-1.06) and total cholesterol (HRinteraction 1.05, 95% CIinteraction 1.03-1.06). CONCLUSION: The CAD PRS is associated with incident CAD, and its application improves the prognostic relevance of several clinical risk factors. FUNDING: P.N. (R01HL127564, R01HL151152, and U01HG011719) is supported by the National Institutes of Health.

Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases.

Polygenic risk scores (PRSs) are an emerging tool to predict the clinical phenotypes and outcomes of individuals. We propose PRSmix, a framework that leverages the PRS corpus of a target trait to improve prediction accuracy, and PRSmix+, which incorporates genetically correlated traits to better capture the human genetic architecture for 47 and 32 diseases/traits in European and South Asian ancestries, respectively. PRSmix demonstrated a mean prediction accuracy improvement of 1.20-fold (95% confidence interval [CI], [1.10; 1.3]; p = 9.17 × 10-5) and 1.19-fold (95% CI, [1.11; 1.27]; p = 1.92 × 10-6), and PRSmix+ improved the prediction accuracy by 1.72-fold (95% CI, [1.40; 2.04]; p = 7.58 × 10-6) and 1.42-fold (95% CI, [1.25; 1.59]; p = 8.01 × 10-7) in European and South Asian ancestries, respectively. Compared to the previously cross-trait-combination methods with scores from pre-defined correlated traits, we demonstrated that our method improved prediction accuracy for coronary artery disease up to 3.27-fold (95% CI, [2.1; 4.44]; p value after false discovery rate (FDR) correction = 2.6 × 10-4). Our method provides a comprehensive framework to benchmark and leverage the combined power of PRS for maximal performance in a desired target population.

Polygenic Scores and Preclinical Cardiovascular Disease in Individuals With HIV: Insights From the REPRIEVE Trial.

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death among the 38.4 million people with HIV globally. The extent to which cardiovascular polygenic risk scores (PRSs) derived in non-HIV populations generalize to people with HIV is not well understood. METHODS AND RESULTS: PRSs for CAD (GPSMult) and lipid traits were calculated in a global cohort of people with HIV treated with antiretroviral therapy with low-to-moderate atherosclerotic cardiovascular disease risk enrolled in REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV). The PRSs were associated with baseline lipid traits in 4495 genotyped participants, and with subclinical CAD in a subset of 662 who underwent coronary computed tomography angiography. Among participants who underwent coronary computed tomography angiography (mean age, 50.9 [SD, 5.8] years; 16.1% women; 41.8% African, 57.3% European, 1.1% Asian), GPSMult was associated with plaque presence with odds ratio (OR) per SD in GPSMult of 1.42 (95% CI, 1.20-1.68; P=3.8×10-5), stenosis >50% (OR, 2.39 [95% CI, 1.48-3.85]; P=3.4×10-4), and noncalcified/vulnerable plaque (OR, 1.45 [95% CI, 1.23-1.72]; P=9.6×10-6). Effects were consistent in subgroups of age, sex, 10-year atherosclerotic cardiovascular disease risk, ancestry, and CD4 count. Adding GPSMult to established risk factors increased the C-statistic for predicting plaque presence from 0.718 to 0.734 (P=0.02). Furthermore, a PRS for low-density lipoprotein cholesterol was associated with plaque presence with OR of 1.21 (95% CI, 1.01-1.44; P=0.04), and partially calcified plaque with OR of 1.21 (95% CI, 1.01-1.45; P=0.04) per SD. CONCLUSIONS: Among people with HIV treated with antiretroviral therapy without documented atherosclerotic cardiovascular disease and at low-to-moderate calculated risk in REPRIEVE, an externally developed CAD PRS was predictive of subclinical atherosclerosis. PRS for low-density lipoprotein cholesterol was also associated with subclinical atherosclerosis, supporting a role for low-density lipoprotein cholesterol in HIV-associated CAD. REGISTRATION: URL: https://www.reprievetrial.org; Unique identifier: NCT02344290.

Profiling the inflammatory bowel diseases using genetics, serum biomarkers, and smoking information.

Crohn's disease (CD) and ulcerative colitis (UC) are two etiologically related yet distinctive subtypes of the inflammatory bowel diseases (IBD). Differentiating CD from UC can be challenging using conventional clinical approaches in a subset of patients. We designed and evaluated a novel molecular-based prediction model aggregating genetics, serum biomarkers, and tobacco smoking information to assist the diagnosis of CD and UC in over 30,000 samples. A joint model combining genetics, serum biomarkers and smoking explains 46% (42-50%, 95% CI) of phenotypic variation. Despite modest overlaps with serum biomarkers, genetics makes unique contributions to distinguishing IBD subtypes. Smoking status only explains 1% (0-6%, 95% CI) of the phenotypic variance suggesting it may not be an effective biomarker. This study reveals that molecular-based models combining genetics, serum biomarkers, and smoking information could complement current diagnostic strategies and help classify patients based on biologic state rather than imperfect clinical parameters.

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease.

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Genetic modification of inflammation- and clonal hematopoiesis-associated cardiovascular risk.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.

Birth Weight Is Associated With Clonal Hematopoiesis of Indeterminate Potential and Cardiovascular Outcomes in Adulthood.

Background High and low birth weight are independently associated with increased cardiovascular disease risk in adulthood. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic cells with preleukemic somatic mutations, predicts incident cardiovascular disease independent of traditional cardiovascular risk factors. Whether birth weight predicts development of CHIP later in life is unknown. Methods and Results A total of 221 047 adults enrolled in the UK Biobank with whole exome sequences and self-reported birth weight were analyzed. Of those, 22 030 (11.5%) had low (<2.5 kg) and 29 292 (14.7%) high birth weight (>4.0 kg). CHIP prevalence was higher among participants with low (6.0%, P=0.049) and high (6.3%, P<0.001) versus normal birth weight (5.7%, ref.). Multivariable-adjusted logistic regression analyses demonstrated that each 1-kg increase in birth weight was associated with a 3% increased risk of CHIP (odds ratio, 1.03 [95% CI, 1.00-1.06]; P=0.04), driven by a stronger association observed between birth weight and DNMT3A CHIP (odds ratio, 1.04 per 1-kg increase [95% CI, 1.01-1.08]; P=0.02). Mendelian randomization analyses supported a causal relationship of longer gestational age at delivery with DNMT3A CHIP. Multivariable Cox regression demonstrated that CHIP was independently and additively associated with incident cardiovascular disease or death across birth weight groups, with highest absolute risks in those with CHIP plus high or low birth weight. Conclusions Higher birth weight is associated with increased risk of developing CHIP in midlife, especially DNMT3A CHIP. These findings identify a novel risk factor for CHIP and provide insights into the relationships among early-life environment, CHIP, cancer, and cardiovascular disease.

Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases.

Polygenic risk scores (PRS) are an emerging tool to predict the clinical phenotypes and outcomes of individuals. Validation and transferability of existing PRS across independent datasets and diverse ancestries are limited, which hinders the practical utility and exacerbates health disparities. We propose PRSmix, a framework that evaluates and leverages the PRS corpus of a target trait to improve prediction accuracy, and PRSmix+, which incorporates genetically correlated traits to better capture the human genetic architecture. We applied PRSmix to 47 and 32 diseases/traits in European and South Asian ancestries, respectively. PRSmix demonstrated a mean prediction accuracy improvement of 1.20-fold (95% CI: [1.10; 1.3]; P-value = 9.17 × 10-5) and 1.19-fold (95% CI: [1.11; 1.27]; P-value = 1.92 × 10-6), and PRSmix+ improved the prediction accuracy by 1.72-fold (95% CI: [1.40; 2.04]; P-value = 7.58 × 10-6) and 1.42-fold (95% CI: [1.25; 1.59]; P-value = 8.01 × 10-7) in European and South Asian ancestries, respectively. Compared to the previously established cross-trait-combination method with scores from pre-defined correlated traits, we demonstrated that our method can improve prediction accuracy for coronary artery disease up to 3.27-fold (95% CI: [2.1; 4.44]; P-value after FDR correction = 2.6 × 10-4). Our method provides a comprehensive framework to benchmark and leverage the combined power of PRS for maximal performance in a desired target population.

PRSet: Pathway-based polygenic risk score analyses and software.

Polygenic risk scores (PRSs) have been among the leading advances in biomedicine in recent years. As a proxy of genetic liability, PRSs are utilised across multiple fields and applications. While numerous statistical and machine learning methods have been developed to optimise their predictive accuracy, these typically distil genetic liability to a single number based on aggregation of an individual's genome-wide risk alleles. This results in a key loss of information about an individual's genetic profile, which could be critical given the functional sub-structure of the genome and the heterogeneity of complex disease. In this manuscript, we introduce a 'pathway polygenic' paradigm of disease risk, in which multiple genetic liabilities underlie complex diseases, rather than a single genome-wide liability. We describe a method and accompanying software, PRSet, for computing and analysing pathway-based PRSs, in which polygenic scores are calculated across genomic pathways for each individual. We evaluate the potential of pathway PRSs in two distinct ways, creating two major sections: (1) In the first section, we benchmark PRSet as a pathway enrichment tool, evaluating its capacity to capture GWAS signal in pathways. We find that for target sample sizes of >10,000 individuals, pathway PRSs have similar power for evaluating pathway enrichment as leading methods MAGMA and LD score regression, with the distinct advantage of providing individual-level estimates of genetic liability for each pathway -opening up a range of pathway-based PRS applications, (2) In the second section, we evaluate the performance of pathway PRSs for disease stratification. We show that using a supervised disease stratification approach, pathway PRSs (computed by PRSet) outperform two standard genome-wide PRSs (computed by C+T and lassosum) for classifying disease subtypes in 20 of 21 scenarios tested. As the definition and functional annotation of pathways becomes increasingly refined, we expect pathway PRSs to offer key insights into the heterogeneity of complex disease and treatment response, to generate biologically tractable therapeutic targets from polygenic signal, and, ultimately, to provide a powerful path to precision medicine.

Measured Blood Pressure, Genetically Predicted Blood Pressure, and Cardiovascular Disease Risk in the UK Biobank.

Importance: Hypertension remains the major cardiovascular disease risk factor globally, but variability in measured blood pressure may result in suboptimal management. Whether genetic contributors to elevated blood pressure may complementarily inform cardiovascular disease risk assessment is unknown. Objective: To examine incident cardiovascular disease by blood pressure polygenic risk score independent of measured blood pressures and antihypertensive medication prescriptions. Design, Setting, and Participants: The cohort study (UK Biobank) recruited UK residents aged 40 to 69 years between March 2006 and August 2010. Participants without a prior physician diagnosis of cardiovascular disease, including myocardial infarction, stroke, or heart failure, were included. Excluded were individuals with mismatch between self-reported and genotypically inferred sex, sex aneuploidy, missing genotype rates of 1% or greater, and excess genotypic heterozygosity. Data analyses were performed from September 25, 2021, to July 21, 2022. Exposures: Measured blood pressure and externally derived blood pressure polygenic risk score stratified by hypertension diagnosis and management, which included normal blood pressure (<130/80 mm Hg without antihypertensives), untreated hypertension (systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥80 mm Hg without antihypertensives), and treated hypertension (current antihypertensives prescriptions). Main Outcomes and Measures: Composite of first incident myocardial infarction, stroke, heart failure, or cardiovascular-related death. Results: Of the 331 078 study participants included (mean [SD] age at enrollment, 56.9 [8.1] years; 178 824 female [54.0%]), 83 094 (25.1%) had normal blood pressure, 197 597 (59.7%) had untreated hypertension, and 50 387 (15.2%) had treated hypertension. Over a median (IQR) follow-up of 11.1 (10.4-11.8) years, the primary outcome occurred in 15 293 participants. Among those with normal blood pressure, untreated hypertension, and treated hypertension, each SD increase in measured systolic blood pressure was associated with hazard ratios of 1.08 (95% CI, 0.93-1.25), 1.20 (95% CI, 1.16-1.23), and 1.16 (95% CI, 1.11-1.20), respectively, for the primary outcome. Among these same categories, each SD increase in genetically predicted systolic blood pressure was associated with increased hazard ratios of 1.13 (95% CI, 1.05-1.20), 1.04 (95% CI, 1.01-1.07), and 1.06 (95% CI, 1.02-1.10), respectively, for the primary outcome independent of measured blood pressures and other covariates. Findings were similar for measured and genetically predicted diastolic blood pressure. Conclusions and Relevance: Blood pressure polygenic risk score may augment identification of individuals at heightened cardiovascular risk, including those with both normal blood pressure and hypertension. Whether it may also guide antihypertensive initiation or intensification requires further study.

Improving polygenic prediction in ancestrally diverse populations.

Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) have been conducted predominantly in individuals of European descent, the limited transferability of PRS reduces their clinical value in non-European populations, and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although most remain underpowered. Here, we present a new PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage (CS) prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures, cross-population genetic overlaps and discovery GWAS sample sizes in simulations, and improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

p.E95K mutation in Indian hedgehog causing brachydactyly type A1 impairs IHH/Gli1 downstream transcriptional regulation.

BACKGROUND: Brachydactyly type A1 (BDA1, OMIM 112500) is a rare inherited malformation characterized primarily by shortness or absence of middle bones of fingers and toes. It is the first recorded disorder of the autosomal dominant Mendelian trait. Indian hedgehog (IHH) gene is closely associated with BDA1, which was firstly mapped and identified in Chinese families in 2000. Previous studies have demonstrated that BDA1-related mutant IHH proteins affected interactions with its receptors and impaired IHH signaling. However, how the altered signaling pathway affects downstream transcriptional regulation remains unclear. RESULTS: Based on the mouse C3H10T1/2 cell model for IHH signaling activation, two recombinant human IHH-N proteins, including a wild type protein (WT, amino acid residues 28-202) and a mutant protein (MT, p.E95k), were analyzed. We identified 347, 47 and 4 Gli1 binding sites in the corresponding WT, MT and control group by chromatin immunoprecipitation and the overlapping of these three sets was poor. The putative cis regulated genes in WT group were enriched in sensory perception and G-protein coupled receptor-signaling pathway. On the other hand, putative cis regulated genes were enriched in Runx2-related pathways in MT group. Differentially expressed genes in WT and MT groups indicated that the alteration of mutant IHH signaling involved cell-cell signaling and cellular migration. Cellular assay of migration and proliferation validated that the mutant IHH signaling impaired these two cellular functions. CONCLUSIONS: In this study, we performed integrated genome-wide analyses to characterize differences of IHH/Gli1 downstream regulation between wild type IHH signaling and the E95K mutant signaling. Based on the cell model, our results demonstrated that the E95K mutant signaling altered Gli1-DNA binding pattern, impaired downstream gene expressions, and leaded to weakened cellular proliferation and migration. This study may help to deepen the understanding of pathogenesis of BDA1 and the role of IHH signaling in chondrogenesis.

Genetic Association of Drug Response to Erlotinib in Chinese Advanced Non-small Cell Lung Cancer Patients.

The efficacy of erlotinib treatment for advanced non-small cell lung cancer (NSCLC) is due to its action as an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI). Patients treated with erlotinib experience different drug responses. The effect of germline mutations on therapeutic responses and adverse drug responses (ADRs) to erlotinib in Chinese patients requires elucidation. Sixty Han Chinese advanced non-small cell lung cancer patients received erlotinib monotherapy and, for each participant, 76 candidate genes (related to EGFR signaling, drug metabolism and drug transport pathways) were sequenced and analyzed. The single-nucleotide polymorphisms (SNPs) rs1042640 in UGT1A10, rs1060463, and rs1064796 in CYP4F11, and rs2074900 in CYP4F2 were significantly associated with therapeutic responses to erlotinib. Rs1064796 in CYP4F11 and rs10045685 in UGT3A1 were significantly associated with adverse drug reaction. Moreover, analysis of a validation cohort confirmed the significant association between rs10045685 in UGT3A1 and erlotinib adverse drug response(unadjusted p = 0.015). This study provides comprehensive, systematic analyses of genetic variants associated with responses to erlotinib in Chinese advanced non-small cell lung cancer patients. Newly-identified SNPs may serve as promising markers to predict responses and safety in erlotinib-treated advanced non-small cell lung cancer patients after chemotherapy doublet.

Functional Characterization of Human CYP2C9 Allelic Variants in COS-7 Cells.

Variability in activity of CYP2C9, which is involved in the metabolism of approximately 15% of current therapeutic drugs, is an important contributor to interindividual differences in drug response. To evaluate the functional alternations of CYP2C9(*)2, CYP2C9(*)3, CYP2C9(*)8, CYP2C9(*)11 and CYP2C9(*)31, identified in our previous study in Chinese Han population, allelic variants as well as the wild-type CYP2C9 were transiently expressed in COS-7 cells. Kinetic parameters (Km, Vmax, and Clint) for S-warfarin 7-hydroxylation by these recombinant CYP2C9s were determined. Relative to CYP2C9.1, recombinant CYP2C9.3 and CYP2C9.11 exhibited significantly higher Km values, and all allelic variants showed significantly decreased Vmax and Clint values. Among all allelic variants, catalytic activity of CYP2C9.3 and CYP2C9.11 reduced the most (8.2% and 9.8% of Clint ratio, respectively; P < 0.001). These findings should be useful for predicting the phenotype profiles of CYP2C9 in Chinese Han population, comparing the functional results of these alleles accurately, and finally optimizing pharmacotherapy of drug treatment.

Genetic Association of Curative and Adverse Reactions to Tyrosine Kinase Inhibitors in Chinese advanced Non-Small Cell Lung Cancer patients.

Epidermal growth factor receptor (EGFR) Tyrosine kinase inhibitor (TKI) is an effective targeted therapy for advanced non-small cell lung cancer (NSCLC) but also causes adverse drug reactions (ADRs) e.g., skin rash and diarrhea. SNPs in the EGFR signal pathway, drug metabolism/ transport pathways and miRNA might contribute to the interpersonal difference in ADRs but biomarkers for therapeutic responses and ADRs to TKIs in Chinese population are yet to be fully investigated. We recruited 226 Chinese advanced NSCLC patients who received TKIs erlotinib, gefitinib and icotinib hydrochloride and systematically studied the genetic factors associated with therapeutic responses and ADRs. Rs884225 (T > C) in EGFR 3' UTR was significantly associated with lower risk of ADRs to erlotinib (p value = 0.0010, adjusted p value = 0.042). A multivariant interaction four-SNP model (rs884225 in EGFR 3'UTR, rs7787082 in ABCB1 intron, rs38845 in MET intron and rs3803300 in AKT1 5'UTR) was associated with ADRs in general and the more specific drug induced skin injury. The SNPs associated with both therapeutic responses and ADRs indicates they might share a common genetic basis. Our study provided potential biomarkers and clues for further research of biomarkers for therapeutic responses and ADRs in Chinese NSCLC patients.

An Engineered Rare Codon Device for Optimization of Metabolic Pathways.

Rare codons generally arrest translation due to rarity of their cognate tRNAs. This property of rare codons can be utilized to regulate protein expression. In this study, a linear relationship was found between expression levels of genes and copy numbers of rare codons inserted within them. Based on this discovery, we constructed a molecular device in Escherichia coli using the rare codon AGG, its cognate tRNA (tRNA(Arg) (CCU)), modified tRNA(Asp) (GUC → CCU), and truncated aspartyl-tRNA synthetase (TDRS) to switch the expression of reporter genes on or off as well as to precisely regulate their expression to various intermediate levels. To underscore the applicability of our work, we used the rare codon device to alter the expression levels of four genes of the fatty acid synthesis II (FASII) pathway (i.e. fabZ, fabG, fabI, and tesA') in E. coli to optimize steady-state kinetics, which produced nearly two-fold increase in fatty acid yield. Thus, the proposed method has potential applications in regulating target protein expression at desired levels and optimizing metabolic pathways by precisely tuning in vivo molar ratio of relevant enzymes.

Comparative genome analysis of Prevotella intermedia strain isolated from infected root canal reveals features related to pathogenicity and adaptation.

BACKGROUND: Many species of the genus Prevotella are pathogens that cause oral diseases. Prevotella intermedia is known to cause various oral disorders e.g. periodontal disease, periapical periodontitis and noma as well as colonize in the respiratory tract and be associated with cystic fibrosis and chronic bronchitis. It is of clinical significance to identify the main drive of its various adaptation and pathogenicity. In order to explore the intra-species genetic differences among strains of Prevotella intermedia of different niches, we isolated a strain Prevotella intermedia ZT from the infected root canal of a Chinese patient with periapical periodontitis and gained a draft genome sequence. We annotated the genome and compared it with the genomes of other taxa in the genus Prevotella. RESULTS: The raw data set, consisting of approximately 65X-coverage reads, was trimmed and assembled into contigs from which 2165 ORFs were predicted. The comparison of the Prevotella intermedia ZT genome sequence with the published genome sequence of Prevotella intermedia 17 and Prevotella intermedia ATCC25611 revealed that ~14% of the genes were strain-specific. The Preveotella intermedia strains share a set of conserved genes contributing to its adaptation and pathogenic and possess strain-specific genes especially those involved in adhesion and secreting bacteriocin. The Prevotella intermedia ZT shares similar gene content with other taxa of genus Prevotella. The genomes of the genus Prevotella is highly dynamic with relative conserved parts: on average, about half of the genes in one Prevotella genome were not included in another genome of the different Prevotella species. The degree of conservation varied with different pathways: the ability of amino acid biosynthesis varied greatly with species but the pathway of cell wall components biosynthesis were nearly constant. Phylogenetic tree shows that the taxa from different niches are scarcely distributed among clades. CONCLUSIONS: Prevotella intermedia ZT belongs to a genus marked with highly dynamic genomes. The specific genes of Prevotella intermedia indicate that adhesion, competing with surrounding microbes and horizontal gene transfer are the main drive of the evolution of Prevotella intermedia.