A faecal microbiota signature with high specificity for pancreatic cancer.

BACKGROUND: Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression. OBJECTIVE: To explore the faecal and salivary microbiota as potential diagnostic biomarkers. METHODS: We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase. RESULTS: Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation. CONCLUSION: Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Combinatorial, additive and dose-dependent drug-microbiome associations.

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study

BACKGROUND: Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients. METHODS: We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital discharge or in-hospital death. RESULTS: A total of 2546 participants were included (mean age 65 years; 60.3% male). Overall, 70.8% were admitted to intensive care units and 54.2% had elevated troponin levels. In-hospital mortality was 41.7%. An interaction among sex, age and mortality was found (p = 0.007). Younger women presented higher rates of death than men (30.0% vs 22.9%), while older men presented higher rates of death than women (57.6% vs 49.2%). The strongest factors associated with in-hospital mortality were need for mechanical ventilation (odds ratio [OR] 8.2, 95% confidence interval [CI] 5.4­12.7), elevated C-reactive protein (OR 2.3, 95% CI 1.7­2.9), cancer (OR 1.8, 95 %CI 1.2­2.9), and elevated troponin levels (OR 1.8, 95% CI 1.4­2.3). A risk score was developed for risk assessment of in-hospital mortality. CONCLUSIONS: This cohort showed that patients with COVID-19 and high risk features have an elevated rate of in-hospital mortality with differences according to age and sex. These results highlight unique aspects of this population and might help identifying patients who may benefit from more careful initial surveillance and potential subsequent interventional therapies

High risk coronavirus disease 2019: The primary results of the CoronaHeart multi-center cohort study.

BACKGROUND: Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients. METHODS: We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital discharge or in-hospital death. RESULTS: A total of 2546 participants were included (mean age 65 years; 60.3% male). Overall, 70.8% were admitted to intensive care units and 54.2% had elevated troponin levels. In-hospital mortality was 41.7%. An interaction among sex, age and mortality was found (p = 0.007). Younger women presented higher rates of death than men (30.0% vs 22.9%), while older men presented higher rates of death than women (57.6% vs 49.2%). The strongest factors associated with in-hospital mortality were need for mechanical ventilation (odds ratio [OR] 8.2, 95% confidence interval [CI] 5.4-12.7), elevated C-reactive protein (OR 2.3, 95% CI 1.7-2.9), cancer (OR 1.8, 95 %CI 1.2-2.9), and elevated troponin levels (OR 1.8, 95% CI 1.4-2.3). A risk score was developed for risk assessment of in-hospital mortality. CONCLUSIONS: This cohort showed that patients with COVID-19 and high risk features have an elevated rate of in-hospital mortality with differences according to age and sex. These results highlight unique aspects of this population and might help identifying patients who may benefit from more careful initial surveillance and potential subsequent interventional therapies.

Antibiotics-induced monodominance of a novel gut bacterial order.

OBJECTIVE: The composition of the healthy human adult gut microbiome is relatively stable over prolonged periods, and representatives of the most highly abundant and prevalent species have been cultured and described. However, microbial abundances can change on perturbations, such as antibiotics intake, enabling the identification and characterisation of otherwise low abundant species. DESIGN: Analysing gut microbial time-series data, we used shotgun metagenomics to create strain level taxonomic and functional profiles. Community dynamics were modelled postintervention with a focus on conditionally rare taxa and previously unknown bacteria. RESULTS: In response to a commonly prescribed cephalosporin (ceftriaxone), we observe a strong compositional shift in one subject, in which a previously unknown species, UBorkfalki ceftriaxensis, was identified, blooming to 92% relative abundance. The genome assembly reveals that this species (1) belongs to a so far undescribed order of Firmicutes, (2) is ubiquitously present at low abundances in at least one third of adults, (3) is opportunistically growing, being ecologically similar to typical probiotic species and (4) is stably associated to healthy hosts as determined by single nucleotide variation analysis. It was the first coloniser after the antibiotic intervention that led to a long-lasting microbial community shift and likely permanent loss of nine commensals. CONCLUSION: The bloom of UB. ceftriaxensis and a subsequent one of Parabacteroides distasonis demonstrate the existence of monodominance community states in the gut. Our study points to an undiscovered wealth of low abundant but common taxa in the human gut and calls for more highly resolved longitudinal studies, in particular on ecosystem perturbations.

inTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis.

BACKGROUND: Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data. RESULTS: We developed inTB, a web-based system for integrated warehousing and analysis of clinical, socio-demographic and molecular data for Mycobacterium sp. isolates. As a database it can organize and display data from any of the standard genotyping methods (SNP, MIRU-VNTR, RFLP and spoligotype), as well as an extensive array of clinical and socio-demographic variables that are used in multiple countries to characterize the disease. Through the inTB interface it is possible to insert and download data, browse the database and search specific parameters. New isolates are automatically classified into strains according to an internal reference, and data uploaded or typed in is checked for internal consistency. As an analysis framework, the system provides simple, point and click analysis tools that allow multiple types of data plotting, as well as simple ways to download data for external analysis. Individual trees for each genotyping method are available, as well as a super tree combining all of them. The integrative nature of inTB grants the user the ability to generate trees for filtered subsets of data crossing molecular and clinical/socio-demografic information. inTB is built on open source software, can be easily installed locally and easily adapted to other diseases. Its design allows for use by research laboratories, hospitals or public health authorities. The full source code as well as ready to use packages is available at http://www.evocell.org/inTB. CONCLUSIONS: To the best of our knowledge, this is the only system capable of integrating different types of molecular data with clinical and socio-demographic data, empowering researchers and clinicians with easy to use analysis tools that were not possible before.

The superfamily of heme-copper oxygen reductases: types and evolutionary considerations.

Heme-copper oxygen reductases (HCO) reduce O(2) to water being the last enzymatic complexes of most aerobic respiratory chains. These enzymes promote energy conservation coupling the catalytic reaction to charge separation and charge translocation across the prokaryotic cytoplasmatic or mitochondrial membrane. In this way they contribute to the establishment and maintenance of the transmembrane difference of electrochemical potential, which is vital for solute/nutrient cell import, synthesis of ATP and motility. The HCO enzymes most probably share with the nitric oxide reductases, NORs, a common ancestor. We have proposed the classification of HCOs into three different types, A, B and C; based on the constituents of their proton channels (Pereira, Santana and Teixeira (2001) Biochim Biophys Acta, 1505, 185-208). This classification was recently challenged by the suggestion of other different types of HCOs. Using an enlarged sampling we performed an exhaustive bioinformatic reanalysis of HCOs family. Our results strengthened our previously proposed classification and showed no need for the existence of more divisions. Now, we analyze the taxonomic distribution of HCOs and NORs and the congruence of their sequence trees with the 16S rRNA tree. We observed that HCOs are widely distributed in the two prokaryotic domains and that the different types of enzymes are not confined to a specific taxonomic group or environmental niche.

A bioinformatics classifier and database for heme-copper oxygen reductases.

BACKGROUND: Heme-copper oxygen reductases (HCOs) are the last enzymatic complexes of most aerobic respiratory chains, reducing dioxygen to water and translocating up to four protons across the inner mitochondrial membrane (eukaryotes) or cytoplasmatic membrane (prokaryotes). The number of completely sequenced genomes is expanding exponentially, and concomitantly, the number and taxonomic distribution of HCO sequences. These enzymes were initially classified into three different types being this classification recently challenged. METHODOLOGY: We reanalyzed the classification scheme and developed a new bioinformatics classifier for the HCO and Nitric oxide reductases (NOR), which we benchmark against a manually derived gold standard sequence set. It is able to classify any given sequence of subunit I from HCO and NOR with a global recall and precision both of 99.8%. We use this tool to classify this protein family in 552 completely sequenced genomes. CONCLUSIONS: We concluded that the new and broader data set supports three functional and evolutionary groups of HCOs. Homology between NORs and HCOs is shown and NORs closest relationship with C Type HCOs demonstrated. We established and made available a classification web tool and an integrated Heme-Copper Oxygen reductase and NOR protein database (www.evocell.org/hco).

Loss of genetic redundancy in reductive genome evolution.

Biological systems evolved to be functionally robust in uncertain environments, but also highly adaptable. Such robustness is partly achieved by genetic redundancy, where the failure of a specific component through mutation or environmental challenge can be compensated by duplicate components capable of performing, to a limited extent, the same function. Highly variable environments require very robust systems. Conversely, predictable environments should not place a high selective value on robustness. Here we test this hypothesis by investigating the evolutionary dynamics of genetic redundancy in extremely reduced genomes, found mostly in intracellular parasites and endosymbionts. By combining data analysis with simulations of genome evolution we show that in the extensive gene loss suffered by reduced genomes there is a selective drive to keep the diversity of protein families while sacrificing paralogy. We show that this is not a by-product of the known drivers of genome reduction and that there is very limited convergence to a common core of families, indicating that the repertoire of protein families in reduced genomes is the result of historical contingency and niche-specific adaptations. We propose that our observations reflect a loss of genetic redundancy due to a decreased selection for robustness in a predictable environment.

Ausência de efeito do captopril no metabolismo de uma emulsão lipídica artificial semelhante aos quilomícrons em pacientes hipertensos e hipercolesterolêmicos / Lack of effect of captopril on the metabolism of an artificial lipid emulsion similar to chylomicrons in hypertensive hypercholesterolemic patients

OBJETIVO: Avaliar o efeito do captopril, sobre o metabolismo dos quilomícrons e de seus remanescentes e as possíveis alterações nas concentrações dos lípides plasmáticos em hipertensos e hipercolesterolêmicos. MÉTODOS: O metabolismo dos quilomícrons foi testado pelo método da emulsão lipídica artificial de quilomícrons marcada com 3H-oleato de colesterol, foi injetada intravenosamente em 10 pacientes com hipertensão arterial leve-moderada antes e após 45 dias de tratamento com captopril (50 mg/dia). Após injeção, foram coletadas amostras de sangue durante 60min em intervalos de tempo pré-estabelecidos para determinar a curva de decaimento e a taxa fracional de remoção (TFR em min-1), bem como o tempo de residência no plasma, da emulsão lipídica artificial, por análise compartimental. As concentrações dos lípides do plasma também foram avaliadas antes e após o tratamento. RESULTADOS: A taxa fracional de remoção (em min-1) da emulsão lipídica antes e após o tratamento com captopril (0,012±0,003 e 0,011±0,003, respectivamente; p=0,85, n.s.) ou o tempo de permanência da emulsão no plasma (83,3±20,8 e 90,9± 22,5 min, n.s.) não se alteraram, mas os níveis de colesterol total e de LDL-c reduziram-se em 7 por cento e 10 por cento respectivamente (p=0,02). As concentrações de HDL-c, triglicérides, Lp(a) e apolipoproteínas AI e B não se modificaram. CONCLUSÃO: O tratamento com captopril, avaliado pelo método da emulsão lipídica artificial, não provoca alterações deletérias no metabolismo dos quilomícrons e seus remanescentes.

Lack of effect of captopril on the metabolism of an artificial lipid emulsion similar to chylomicrons in hypertensive hypercholesterolemic patients.

OBJECTIVE: To assess the effect of captopril, an angiotensin-converting enzyme inhibitor, on the metabolism of chylomicrons and their remnants and the possible alterations in the concentrations of plasma lipids caused by the drug in hypertensive hypercholesterolemic individuals. METHODS: The metabolism of chylomicrons was tested with the method of artificial lipid emulsion of chylomicrons labeled with 3H-cholesteryl oleate. The emulsion was injected intravenously in 10 patients with mild-moderate arterial hypertension before and 45 days after treatment with captopril (50 mg/day). After injection, blood samples were collected during 60 minutes at pre-established time intervals for determining the decay curve, the fractional catabolic rate (FCR in min-1), and the plasma residence time of the artificial lipid emulsion by analyzing different compartments. The plasma concentrations of the lipids were also assessed before and after treatment. RESULTS: The fractional catabolic rate (min-1) of the lipid emulsion before and after treatment with captopril (0.012 +/- 0.003 and 0.011 +/- 0.003, respectively; p = 0.85, n.s.) and the plasma residence time of the emulsion (83.3 +/- 20.8 and 90.9 +/- 22.5 min, n.s.) did not change, but the total cholesterol and LDL-C levels decreased by 7% and 10%, respectively (p = 0.02). The concentrations of HDL-C, triglycerides, Lp(a), and apolipoproteins AI and B did not change. CONCLUSION: Treatment with captopril, evaluated with the artificial lipid emulsion method, does not cause deleterious changes in the metabolism of chylomicrons and their remnants.