Vegetation type, not the legacy of warming, modifies the response of microbial functional genes and greenhouse gas fluxes to drought in Oro-Arctic and alpine regions.

Climate warming and summer droughts alter soil microbial activity, affecting greenhouse gas (GHG) emissions in Arctic and alpine regions. However, the long-term effects of warming, and implications for future microbial resilience, are poorly understood. Using one alpine and three Arctic soils subjected to in situ long-term experimental warming, we simulated drought in laboratory incubations to test how microbial functional-gene abundance affects fluxes in three GHGs: carbon dioxide, methane, and nitrous oxide. We found that responses of functional gene abundances to drought and warming are strongly associated with vegetation type and soil carbon. Our sites ranged from a wet, forb dominated, soil carbon-rich systems to a drier, soil carbon-poor alpine site. Resilience of functional gene abundances, and in turn methane and carbon dioxide fluxes, was lower in the wetter, carbon-rich systems. However, we did not detect an effect of drought or warming on nitrous oxide fluxes. All gene-GHG relationships were modified by vegetation type, with stronger effects being observed in wetter, forb-rich soils. These results suggest that impacts of warming and drought on GHG emissions are linked to a complex set of microbial gene abundances and may be habitat-specific.

Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data.

The identification of microbial characteristics associated with diseases is crucial for disease diagnosis and therapy. However, the presence of heterogeneity, high dimensionality, and large amounts of microbial data presents tremendous challenges in discovering key microbial features. In this paper, we present IDAM, a novel computational method for inferring disease-associated gene modules from metagenomic and metatranscriptomic data. This method integrates gene context conservation (uber-operons) and regulatory mechanisms (gene co-expression patterns) within a mathematical graph model to explore gene modules associated with specific diseases. It alleviates reliance on prior meta-data. We applied IDAM to publicly available datasets from inflammatory bowel disease, melanoma, type 1 diabetes mellitus, and irritable bowel syndrome. The results demonstrated the superior performance of IDAM in inferring disease-associated characteristics compared to existing popular tools. Furthermore, we showcased the high reproducibility of the gene modules inferred by IDAM using independent cohorts with inflammatory bowel disease. We believe that IDAM can be a highly advantageous method for exploring disease-associated microbial characteristics. The source code of IDAM is freely available at https://github.com/OSU-BMBL/IDAM, and the web server can be accessed at https://bmblx.bmi.osumc.edu/idam/.

Microbial Gene Ontology informed deep neural network for microbe functionality discovery in human diseases.

The human microbiome plays a crucial role in human health and is associated with a number of human diseases. Determining microbiome functional roles in human diseases remains a biological challenge due to the high dimensionality of metagenome gene features. However, existing models were limited in providing biological interpretability, where the functional role of microbes in human diseases is unexplored. Here we propose to utilize a neural network-based model incorporating Gene Ontology (GO) relationship network to discover the microbe functionality in human diseases. We use four benchmark datasets, including diabetes, liver cirrhosis, inflammatory bowel disease, and colorectal cancer, to explore the microbe functionality in the human diseases. Our model discovered and visualized the novel candidates' important microbiome genes and their functions by calculating the important score of each gene and GO term in the network. Furthermore, we demonstrate that our model achieves a competitive performance in predicting the disease by comparison with other non-Gene Ontology informed models. The discovered candidates' important microbiome genes and their functions provide novel insights into microbe functional contribution.

Microbial genes outperform species and SNVs as diagnostic markers for Crohn's disease on multicohort fecal metagenomes empowered by artificial intelligence.

Dysbiosis of gut microbial community is associated with the pathogenesis of CD and may serve as a promising noninvasive diagnostic tool. We aimed to compare the performances of the microbial markers of different biological levels by conducting a multidimensional analysis on the microbial metagenomes of CD. We collected fecal metagenomic datasets generated from eight cohorts that altogether include 870 CD patients and 548 healthy controls. Microbial alterations in CD patients were assessed at multidimensional levels including species, gene, and SNV level, and then diagnostic models were constructed using artificial intelligence algorithm. A total of 227 species, 1047 microbial genes, and 21,877 microbial SNVs were identified that differed between CD and controls. The species, gene, and SNV models achieved an average AUC of 0.97, 0.95, and 0.77, respectively. Notably, the gene model exhibited superior diagnostic capability, achieving an average AUC of 0.89 and 0.91 for internal and external validations, respectively. Moreover, the gene model was specific for CD against other microbiome-related diseases. Furthermore, we found that phosphotransferase system (PTS) contributed substantially to the diagnostic capability of the gene model. The outstanding performance of PTS was mainly explained by genes celB and manY, which demonstrated high predictabilities for CD with metagenomic datasets and was validated in an independent cohort by qRT-PCR analysis. Our global metagenomic analysis unravels the multidimensional alterations of the microbial communities in CD and identifies microbial genes as robust diagnostic biomarkers across geographically and culturally distinct cohorts.

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota.

Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

MODERN ETIOLOGICAL STRUCTURE OF ACUTE GASTROENTEROCOLITIS IN THE SOUTHERN UKRAINE.

The etiological structure of the acute diarrhoeal infections among the population of the Odessa region during 2015-2017 was analyzed. Based on the registered cases, an assessment of the frequency of hospitalization of sick persons from different age groups was undertaken. The most frequent pathogens from 18 detected bacterial causative agents were St. aureus, Kl. pneumoniae, Ps. aeruginosa, E. coli, Pr. vulgaris, Ent.cloacae. During 2016-2017 the mixed infection was detected in 54 fecal samples. Bacterial-virus associations were detected in 20 samples and were presented in St. aureus, Kl. pneumoniae, Ps. Aeruginosa and Rotavirus. During the summer period of 2016, the detection rate of rota-, noro-, adenovirus antigens in the examined fecal samples of adult patients was 13.60%. According to the results of genotyping of the circulating rotaviruses strains in 2016, strains G1P[8] (46.70%) and G3P[8] (26.70%) are most commonly detected.

Disruption of sleep architecture in Prevotella enterotype of patients with obstructive sleep apnea-hypopnea syndrome.

INTRODUCTION: Intermittent hypoxia and sleep fragmentation are critical pathophysiological processes involved in obstructive sleep apnea-hypopnea syndrome (OSAHS). Those manifestations independently affect similar brain regions and contribute to OSAHS-related comorbidities that are known to be related to the host gut alteration microbiota. We hypothesized that gut microbiota disruption may cross talk the brain function via the microbiota-gut-brain axis. Thus, we aim to survey enterotypes and polysomnographic data of patients with OSAHS. METHODS: Subjects were diagnosed by polysomnography, from whom fecal samples were obtained and analyzed for the microbiome composition by variable regions 3-4 of 16S rRNA pyrosequencing and bioinformatic analyses. We examined the fasting levels of interleukin-6 and tumor necrosis factor-alpha of all subjects. RESULTS: Three enterotypes Bacteroides, Ruminococcus, and Prevotella were identified in patients with OSAHS. Arousal-related parameters or sleep stages are significantly disrupted in apnea-hypopnea index (AHI) ≥15 patients with Prevotella enterotype; further analysis this enterotype subjects, obstructive, central, and mixed apnea indices, and mean heart rate are also significantly elevated in AHI ≥15 patients. However, blood cytokines levels of all subjects were not significantly different. CONCLUSIONS: This study indicates the possibility of pathophysiological interplay between enterotypes and sleeps structure disruption in sleep apnea through a microbiota-gut-brain axis and offers some new insight toward the pathogenesis of OSAHS.

A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data.

The microbiome research is going through an evolutionary transition from focusing on the characterization of reference microbiomes associated with different environments/hosts to the translational applications, including using microbiome for disease diagnosis, improving the effcacy of cancer treatments, and prevention of diseases (e.g., using probiotics). Microbial markers have been identified from microbiome data derived from cohorts of patients with different diseases, treatment responsiveness, etc, and often predictors based on these markers were built for predicting host phenotype given a microbiome dataset (e.g., to predict if a person has type 2 diabetes given his or her microbiome data). Unfortunately, these microbial markers and predictors are often not published so are not reusable by others. In this paper, we report the curation of a repository of microbial marker genes and predictors built from these markers for microbiome-based prediction of host phenotype, and a computational pipeline called Mi2P (from Microbiome to Phenotype) for using the repository. As an initial effort, we focus on microbial marker genes related to two diseases, type 2 diabetes and liver cirrhosis, and immunotherapy efficacy for two types of cancer, non-small-cell lung cancer (NSCLC) and renal cell carcinoma (RCC). We characterized the marker genes from metagenomic data using our recently developed subtractive assembly approach. We showed that predictors built from these microbial marker genes can provide fast and reasonably accurate prediction of host phenotype given microbiome data. As understanding and making use of microbiome data (our second genome) is becoming vital as we move forward in this age of precision health and precision medicine, we believe that such a repository will be useful for enabling translational applications of microbiome data.

Molecular characterization of Phytophthora palmivora responsible for bud rot disease of oil palm in Colombia.

Bud rot disease is a damaging disease of oil palm in Colombia. The pathogen responsible for this disease is a species of oomyctes, Phytophthora palmivora which is also the causal pathogen of several tropical crop diseases such as fruit rot and stem canker of cocoa, rubber, durian and jackfruit. No outbreaks of bud rot have been reported in oil palm in Malaysia or other Southeast Asian countries, despite this particular species being present in the region. Analysis of the genomic sequences of several genetic markers; the internal transcribe spacer regions (ITS) of the ribosomal RNA gene cluster, beta-tubulin gene, translation elongation factor 1 alpha gene (EF-1α), cytochrome c oxidase subunit I & II (COXI and COXII) gene cluster along with amplified fragment length polymorphism (AFLP) analyses have been carried out to investigate the genetic diversity and variation of P. palmivora isolates from around the world and from different hosts in comparison to Colombian oil palm isolates, as one of the steps in understanding why this species of oomycetes causes devastating damage to oil palm in Latin America but not in other regions. Phylogenetic analyses of these regions showed that the Colombian oil palm isolates were not separated from Malaysian isolates. AFLP analysis and a new marker PPHPAV, targeting an unclassified hypothetical protein, was found to be able to differentiate Malaysian and Colombian isolates and showed a clear clade separations. Despite this, pathogenicity studies did not show any significant differences in the level of aggressiveness of different isolates against oil palm in glasshouse tests.

Microbial functional gene patterns related to soil greenhouse gas emissions in oil contaminated areas.

Linking microbial community structure to physiology and ecological processes is a critical focus of microbial ecology. To understand the microbial functional gene patterns related to soil greenhouse gas [carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)] emissions under oil contamination, we used functional gene array (GeoChip 5.0) analysis and network methods to investigate the feedback responses of soil microbial functional gene patterns and identify keystone genes in Shengli Oilfield, China. The microbial functional gene number, relative abundance and diversity involved in carbon degradation and nitrogen cycling decreased consistently with the reduced CO2 and N2O flux in oil contaminated soils, whereas the gene number and relative abundance of methane-production related genes increased with contamination. Functional molecular ecological networks were built based on random matrix theory, where network structures and properties showed significantly variation between oil contaminated and uncontaminated soils (P<0.05). Network nodes, connectivity and complexity all reduced under oil contamination. The sensitive and the highest connective genes in the network were identified as keystone genes, based on Mann-Whitney U tests and network analysis. Our findings improved the understanding of the microbe-mediated mechanisms affecting soil greenhouse gas emissions.

A massive incorporation of microbial genes into the genome of Tetranychus urticae, a polyphagous arthropod herbivore.

A number of horizontal gene transfers (HGTs) have been identified in the spider mite Tetranychus urticae, a chelicerate herbivore. However, the genome of this mite species has at present not been thoroughly mined for the presence of HGT genes. Here, we performed a systematic screen for HGT genes in the T. urticae genome using the h-index metric. Our results not only validated previously identified HGT genes but also uncovered 25 novel HGT genes. In addition to HGT genes with a predicted biochemical function in carbohydrate, lipid and folate metabolism, we also identified the horizontal transfer of a ketopantoate hydroxymethyltransferase and a pantoate ß-alanine ligase gene. In plants and bacteria, both genes are essential for vitamin B5 biosynthesis and their presence in the mite genome strongly suggests that spider mites, similar to Bemisia tabaci and nematodes, can synthesize their own vitamin B5. We further show that HGT genes were physically embedded within the mite genome and were expressed in different life stages. By screening chelicerate genomes and transcriptomes, we were able to estimate the evolutionary histories of these HGTs during chelicerate evolution. Our study suggests that HGT has made a significant and underestimated impact on the metabolic repertoire of plant-feeding spider mites.

Mechanism of 1,4-dioxane microbial degradation revealed by 16S rRNA and metatranscriptomic analyses.

1,4-Dioxane (dioxane), a probable human carcinogen, often exists in industrial wastewater and domestic sewage. In this study, we applied 16S rRNA and metatranscriptomic methods to analyze the dioxane biodegradation mechanism by activated sludge. Tetrahydrofuran (THF) was added as an essential co-metabolite to promote the degradation of dioxane. We found the dioxane removal ratio increased with increasing THF concentrations. When the THF concentration increased from 60.0 to 200.0 mg/L, the dioxane degradation rate was stable. Three additions of ∼60.0 mg/L THF resulted in better dioxane degradation than one addition of 200 mg/L THF. Ammonia-oxidizing and denitrifying bacteria with methane monooxygenases (MOs) and ammonia MOs played the most important roles during the degradation of dioxane. Kyoto Encyclopedia of Genes and Genomes metabolic pathway and functional genes analyses showed that the activated sludge system was complex and stable when dioxane was added. In future studies, primers should be designed to identify specific bacteria and functional MO genes, which would help reveal the function of various bacteria and their MOs during dioxane degradation.

Volatile Gas Production by Methyl Halide Transferase: An In Situ Reporter Of Microbial Gene Expression In Soil.

Traditional visual reporters of gene expression have only very limited use in soils because their outputs are challenging to detect through the soil matrix. This severely restricts our ability to study time-dependent microbial gene expression in one of the Earth's largest, most complex habitats. Here we describe an approach to report on dynamic gene expression within a microbial population in a soil under natural water levels (at and below water holding capacity) via production of methyl halides using a methyl halide transferase. As a proof-of-concept application, we couple the expression of this gas reporter to the conjugative transfer of a bacterial plasmid in a soil matrix and show that gas released from the matrix displays a strong correlation with the number of transconjugant bacteria that formed. Gas reporting of gene expression will make possible dynamic studies of natural and engineered microbes within many hard-to-image environmental matrices (soils, sediments, sludge, and biomass) at sample scales exceeding those used for traditional visual reporting.

Sequence-based identification of microbial contaminants in non-parenteral products

ABSTRACT Phenotypic profiles for microbial identification are unusual for rare, slow-growing and fastidious microorganisms. In the last decade, as a result of the widespread use of PCR and DNA sequencing, 16S rRNA sequencing has played a pivotal role in the accurate identification of microorganisms and the discovery of novel isolates in microbiology laboratories. The 16S rRNA region is universally distributed among microorganisms and is species-specific. Accordingly, the aim of our study was the genotypic identification of microorganisms isolated from non-parenteral pharmaceutical formulations. DNA was separated from five isolates obtained from the formulations. The target regions of the rRNA genes were amplified by PCR and sequenced using suitable primers. The sequence data were analyzed and aligned in the order of increasing genetic distance to relevant sequences against a library database to achieve an identity match. The DNA sequences of the phylogenetic tree results confirmed the identity of the isolates as Bacillus tequilensis, B. subtilis, Staphylococcus haemolyticus and B. amyloliqueficians. It can be concluded that 16S rRNA sequence-based identification reduces the time by circumventing biochemical tests and also increases specificity and accuracy.

RESUMO Os perfis fenotípicos para identificação microbiana são incomuns para micro-organismos raros, de crescimento lento e exigentes. Na última década, em resultado do uso generalizado de PCR e sequenciação de DNA, a sequenciação do rRNA 16S tem desempenhado papel crucial na identificação precisa do micro-organismo e a descoberta de novos isolados em laboratórios de microbiologia. A região de rRNA 16S é universalmente distribuída entre micro-organismos e é espécie-específica. A genotipagem foi realizada sobre os organismos isolados a partir de formulações farmacêuticas não parenterais. O DNA foi separado dos cinco isolados obtidos a partir das formulações. As regiões alvo dos genes de rRNA foram amplificados por PCR e sequenciados utilizando os iniciadores adequados. Os dados dos sequência foram analisados e alinhados na ordem crescente de distância genética de sequências relevantes contra biblioteca de dados para obter a identidade. A sequência de DNA de árvores filogenéticas confirma a identidade dos isolados como Bacillus-tequilensis, B. subtilis, Staphylococcus haemolyticus e B. amyloliqueficians. Pode-se concluir identificação baseada na sequência do rRNA 16S reduz o tempo por evitar testes bioquímicos e também aumenta a especificidade e a precisão.

Finding Pathogenic Nucleic Acid Sequences in Next Generation Sequencing Data.

Viruses and bacteria are established as one of the main causes of human diseases from hepatitis to cancer. Recently, the presence of such pathogens has been extensively studied using human whole genome and transcriptome sequencing data. However, detecting and studying pathogens via next generation sequencing data is a challenging task in terms of time and computational resources. In this protocol we give instructions for a simple and quick method to find pathogenic DNA or RNA and detect possible integration of the pathogen genome into the host genome.

A mutation screening of oncogenes, tumor suppressor gene TP53 and nuclear encoded mitochondrial complex I genes in oncocytic thyroid tumors.

BACKGROUND: Thyroid neoplasias with oncocytic features represent a specific phenotype in non-medullary thyroid cancer, reflecting the unique biological phenomenon of mitochondrial hyperplasia in the cytoplasm. Oncocytic thyroid cells are characterized by a prominent eosinophilia (or oxyphilia) caused by mitochondrial abundance. Although disruptive mutations in the mitochondrial DNA (mtDNA) are the most significant hallmark of such tumors, oncocytomas may be envisioned as heterogeneous neoplasms, characterized by multiple nuclear and mitochondrial gene lesions. We investigated the nuclear mutational profile of oncocytic tumors to pinpoint the mutations that may trigger the early oncogenic hit. METHODS: Total DNA was extracted from paraffin-embedded tissues from 45 biopsies of oncocytic tumors. High-resolution melting was used for mutation screening of mitochondrial complex I subunits genes. Specific nuclear rearrangements were investigated by RT-PCR (RET/PTC) or on isolated nuclei by interphase FISH (PAX8/PPARγ). Recurrent point mutations were analyzed by direct sequencing. RESULTS: In our oncocytic tumor samples, we identified rare TP53 mutations. The series of analyzed cases did not include poorly- or undifferentiated thyroid carcinomas, and none of the TP53 mutated cases had significant mitotic activity or high-grade features. Thus, the presence of disruptive TP53 mutations was completely unexpected. In addition, novel mutations in nuclear-encoded complex I genes were identified. CONCLUSIONS: These findings suggest that nuclear genetic lesions altering the bioenergetics competence of thyroid cells may give rise to an aberrant mitochondria-centered compensatory mechanism and ultimately to the oncocytic phenotype.

Contrasting microbial functional genes in two distinct saline-alkali and slightly acidic oil-contaminated sites.

To compare the functional gene structure and diversity of microbial communities in saline-alkali and slightly acidic oil-contaminated sites, 40 soil samples were collected from two typical oil exploration sites in North and South China and analyzed with a comprehensive functional gene array (GeoChip 3.0). The overall microbial pattern was significantly different between the two sites, and a more divergent pattern was observed in slightly acidic soils. Response ratio was calculated to compare the microbial functional genes involved in organic contaminant degradation and carbon, nitrogen, phosphorus, and sulfur cycling. The results indicated a significantly low abundance of most genes involved in organic contaminant degradation and in the cycling of nitrogen and phosphorus in saline-alkali soils. By contrast, most carbon degradation genes and all carbon fixation genes had similar abundance at both sites. Based on the relationship between the environmental variables and microbial functional structure, pH was the major factor influencing the microbial distribution pattern in the two sites. This study demonstrated that microbial functional diversity and heterogeneity in oil-contaminated environments can vary significantly in relation to local environmental conditions. The limitation of nitrogen and phosphorus and the low degradation capacity of organic contaminant should be carefully considered, particularly in most oil-exploration sites with saline-alkali soils.

Glycogenomics as a mass spectrometry-guided genome-mining method for microbial glycosylated molecules.

Glycosyl groups are an essential mediator of molecular interactions in cells and on cellular surfaces. There are very few methods that directly relate sugar-containing molecules to their biosynthetic machineries. Here, we introduce glycogenomics as an experiment-guided genome-mining approach for fast characterization of glycosylated natural products (GNPs) and their biosynthetic pathways from genome-sequenced microbes by targeting glycosyl groups in microbial metabolomes. Microbial GNPs consist of aglycone and glycosyl structure groups in which the sugar unit(s) are often critical for the GNP's bioactivity, e.g., by promoting binding to a target biomolecule. GNPs are a structurally diverse class of molecules with important pharmaceutical and agrochemical applications. Herein, O- and N-glycosyl groups are characterized in their sugar monomers by tandem mass spectrometry (MS) and matched to corresponding glycosylation genes in secondary metabolic pathways by a MS-glycogenetic code. The associated aglycone biosynthetic genes of the GNP genotype then classify the natural product to further guide structure elucidation. We highlight the glycogenomic strategy by the characterization of several bioactive glycosylated molecules and their gene clusters, including the anticancer agent cinerubin B from Streptomyces sp. SPB74 and an antibiotic, arenimycin B, from Salinispora arenicola CNB-527.

Participação da resposta inflamatória induzida por Chlamydophila pneumoniae e Mycoplasma pneumoniae no infarto agudo do miocárdio / Participation of the inflammatory response induced by Chlamydophila pneumoniae and Mycoplasma pneumoniae in acute myocardial infarction

Os agentes infecciosos têm sido considerados iniciadores da desestabilização da placa de ateroma. Este mecanismo pode estar relacionado a uma intensificação do processo inflamatório através da interação dos receptores de membrana CD14 e TLR com os microorganismos. Para avaliar esta hipótese, estudou-se a participação da resposta inflamatória induzida por Chlamydophila pneumoniae (Cp) e Mycoplasma pneumoniae (Mp) em indivíduos com infarto agudo do miocárdio (IAM). Avaliou-se também, a possível associação entre polimorfismos dos genes CD14, TLR2, TLR4 e TNFA e a expressão dos genes IL6, TLR2, TLR4 e TNFA em leucócitos do sangue periférico, assim como a sua associação com o IAM. Para isso, foi realizado um estudo caso-controle constituído por pacientes com IAM e por indivíduos sem evidência de doença cardiovascular (grupo controle). As imunoglobulinas IgM e IgG séricas anti-Cp foram detectadas por imunofluorescência indireta. O DNA dos agentes infecciosos foi detectado no sangue periférico pela PCR em tempo real. A genotipagem dos polimorfismos TNFA -308G>A, IL6 -174G>C, CD14 -260C>T, TLR4 (Asp299Gli e Thr39911e) e TLR2 Arg753Gln e a quantificação relativa da expressão gênica nas células sanguíneas foram analisados pela PCR em tempo real. A porcentagem de positividade para DNA de Cp foi de 18,0% e 8,1% nos grupos IAM e controle (p=0,071), respectivamente, (p=0,071). Foram positivos para DNA de Mp, 5,0% e 11,2% dos indivíduos nos grupos IAM e controle, respectivamente (p=0,318). Sete indivíduos (7,1%) do grupo IAM tiveram títulos anti-Cp IgG positivos (1:512) e 3,9% dos indivíduos do grupo controle (p=0,718). A expressão do TLR4 foi significantemente menor no grupo IAM (0,00113±0,00102) comparado ao grupo controle (0,00144±0,000806; p=0,003). As frequências genotípicas e alelicas dos polimorfismos TNFA -308G>A, CD14 -260C>T, TLR4 (Asp299GIi e Thr39911e) e TLR2 Arg753Gln foram similares entre os grupos estudados (p>0,05) sugerindo que esses polimorfismos não estão associados com IAM nesta amostra populacional. No grupo IAM, houve associação entre o genótipo -260CT+TI CD14 com títulos IgG anti-Cp detectados na diluição 1:16 (p=0,042). Da mesma forma, o alelo A do polimorfismo -308G>A TNF-α foi associado com títulos positivos de IgG anti-Cp na diluição 1:512 (p=0,0058). No grupo IAM, pacientes positivos para DNA de Cp tiveram maiores concentrações de fibrinogênio do que pacientes negativos para este agente infeccioso (541,8±161,5mg/dL e 450,5±196,8mg/dL, respectivamente; p=0.043). Os agentes infecciosos Chlamydophila pneumoniae e Mycoplasma pneumoniae não foram significantemente mais frequentes em indivíduos que tiveram infarto agudo do miocárdio em relação ao grupo controle, porém houve uma associação, no grupo IAM, entre positividade para DNA de C. pneumoniae e concentrações mais elevadas de fibrinogênio

Atheroma plaque instability has been attributed to the presence of some infectious agents. This mechanism may be related with increased stimulus of inflammatory process through interactions of CD14 and TLR with infectious agents. In this present study, it was evaluated the association of the presence of Chlamydophila pneumoniae and Mycoplasma pneumonia with acute myocardial infarction (AMI). A case-control study was conducted with AMI patients and non-AMI individuais as controls. Immunoglobulin G (lgG) and IgM antibodies anti-Chlamydophila pneumoniae were detected by indirect immunifluorescent assay and the Cp DNA and Mp DNA were detected by real time PCR (RT-PCR) in peripheral blood cells. Using the same method, the individuals were genotyped and the gene expressions of TLR2, TLR4, IL-6 e TNF-α were evaluated by RT-qPCR. In AMI patients, Cp DNA and Mp DNA were positive in 18,0% and 5,0% samples, respectively. In controls, 8,1% and 11,2% were positive for Cp DNA and Mp DNA, respectively. TLR4 expression was significantly decreased in AMI patients (0.00113±0.001 02) compared with controls (0.00144±0.000S06; p=0.003). The frequencies of -308G>A TNF-α., -260C>T CD14, Asp299Gli TLR4, Thr39911e TLR4e Arg753Gln TLR2 SNPs in AMI group were similar to those found in controls. On the other hand, In AMI group, the -260CT+TT CD14 genotype was associated with anti-CP IgG antibody titer of 1/16. Likewise, the rare allele of -308G>A TNF-α was associated with anti-CP IgG antibody titer of 1/16. Cp DNA positive patients had high concentration of fibrinogen when compared with negative patients. In conclusion, Cp DNA and Mp DNA positivity were not associated with AMI