Metagenomic analysis of the saliva microbiome with merlin

In recent years, metagenomics has demonstrated to play an essential role on the study of the microorganisms that live in microbial communities, particularly those who inhabit the human body. Several bioinformatics tools and pipelines have been developed for the analysis of these data, but they usually only address one topic: to identify the taxonomic composition or to address the metabolic functional profile. This work aimed to implement a computational framework able to answer the two questions simultaneously. Merlin, a previously released software aiming at the reconstruction of genome-scale metabolic models for single organisms, was extended to deal with metagenomics data. It has an user-friendly and intuitive interface, being suitable for those with limited bioinformatics skills. The performance of the tool was evaluated with samples from the Human Microbiome Project, particularly from saliva. Overall, the results show the same patterns reported before: while the pathways needed for microbial life remain relatively stable, the community composition varies extensively among individuals

The effect of extrinsic mortality on genome size evolution in prokaryotes

Mortality has a significant role in prokaryotic ecology and evolution, yet the impact of variations in extrinsic mortality on prokaryotic genome evolution has received little attention. We used both mathematical and agent-based models to reveal how variations in extrinsic mortality affect prokaryotic genome evolution. Our results suggest that the genome size of bacteria increases with increased mortality. A high extrinsic mortality increases the pool of free resources and shortens life expectancy, which selects for faster reproduction, a phenotype we called ‘scramblers’. This phenotype is realised by the expansion of gene families involved in nutrient acquisition and metabolism. In contrast, a low mortality rate increases an individual’s life expectancy, which results in natural selection favouring tolerance to starvation when conditions are unfavourable. This leads to the evolution of small, streamlined genomes (‘stayers’). Our models predict that large genomes, gene family expansion and horizontal gene transfer should be observed in prokaryotes occupying ecosystems exposed to high abiotic stress, as well as those under strong predator- and/or pathogen-mediated selection. A comparison of genome size of cyanobacteria in relatively stable marine versus more turbulent freshwater environments corroborates our predictions, although other factors between these environments could also be responsible

Towards a Processual Microbial Ontology

types: ArticleStandard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely ‘‘processually equivalent’’ entities, ‘‘processually versatile’’ entities, and ‘‘stabilized’’ entities.Economic and Social Research Council, U

Gut microbiota functions: metabolism of nutrients and other food components

The diverse microbial community that inhabits the human gut has an extensive metabolic repertoire that is distinct from, but complements the activity of mammalian enzymes in the liver and gut mucosa and includes functions essential for host digestion. As such, the gut microbiota is a key factor in shaping the biochemical profile of the diet and, therefore, its impact on host health and disease. The important role that the gut microbiota appears to play in human metabolism and health has stimulated research into the identification of specific microorganisms involved in different processes, and the elucidation of metabolic pathways, particularly those associated with metabolism of dietary components and some host-generated substances. In the first part of the review, we discuss the main gut microorganisms, particularly bacteria, and microbial pathways associated with the metabolism of dietary carbohydrates (to short chain fatty acids and gases), proteins, plant polyphenols, bile acids, and vitamins. The second part of the review focuses on the methodologies, existing and novel, that can be employed to explore gut microbial pathways of metabolism. These include mathematical models, omics techniques, isolated microbes, and enzyme assays

The PathOlogist: an automated tool for pathway-centric analysis

<p>Abstract</p> <p>Background</p> <p>The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.</p> <p>Results</p> <p>Molecular abundance data is used to calculate two metrics - 'activity' and 'consistency' - for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, <url>http://pid.nci.nih.gov</url>). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features.</p> <p>Conclusions</p> <p>The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.</p

J Acquir Immune Defic Syndr

BackgroundCervical cancer is a major public health problem in resource-limited settings, particularly among HIV-infected women. Given the challenges of cytology-based approaches, the efficiency of new screening programs need to be assessed.SettingCommunity and hospital-based clinics in Gaborone, Botswana.ObjectiveTo determine the feasibility, and efficiency of the \u201cSee and Treat\u201d approach using Visual Inspection Acetic Acid (VIA) and Enhanced Digital Imaging (EDI) for cervical cancer prevention in HIV-infected women.MethodsA two-tier community-based cervical cancer prevention program was implemented. HIV-infected women were screened by nurses at the community using the VIA/EDI approach. Low-grade lesions were treated with cryotherapy on the same visit.ResultsFrom March 2009 through January 2011, 2,175 patients were screened for cervical cancer at our community-based clinic. 253 (11.6%) were found to have low-grade lesions and received same-day cryotherapy. 1,347 (61.9%) women were considered to have a normal examination and 575 (27.3%) were referred for further evaluation and treatment. Of the 1,347 women initially considered to have normal exams, 267 (19.8%) were recalled based on weekly quality control assessments. 210 (78.6%) of the 267 recalled women and 499 (86.8%) of the 575 referred women were seen at the referral clinic. Of these 709 women, 506 (71.4%) required additional treatment. Overall, 264 CIN stage 2 or 3 were identified and treated, and six micro-invasive cancers identified were referred for further management.ConclusionsOur \u201cSee and Treat\u201d cervical cancer prevention program using the VIA/EDI approach is a feasible, high-output and high-efficiency program, worthy of considering as an additional cervical cancer screening method in Botswana, especially for women with limited access to the current cytology-based screening services.20122014-01-08T00:00:00ZP30 AI045008/AI/NIAID NIH HHS/United StatesU2G PS001949/PS/NCHHSTP CDC HHS/United States1U2GPS001949/PHS HHS/United StatesIP30 AI 45008/AI/NIAID NIH HHS/United States22134146PMC388408

Mirror, mirror on the wall: which microbiomes will help heal them all?

BACKGROUND: Clinicians have known for centuries that there is substantial variability between patients in their response to medications—some individuals exhibit a miraculous recovery while others fail to respond at all. Still others experience dangerous side effects. The hunt for the factors responsible for this variation has been aided by the ability to sequence the human genome, but this just provides part of the picture. Here, we discuss the emerging field of study focused on the human microbiome and how it may help to better predict drug response and improve the treatment of human disease. DISCUSSION: Various clinical disciplines characterize drug response using either continuous or categorical descriptors that are then correlated to environmental and genetic risk factors. However, these approaches typically ignore the microbiome, which can directly metabolize drugs into downstream metabolites with altered activity, clearance, and/or toxicity. Variations in the ability of each individual’s microbiome to metabolize drugs may be an underappreciated source of differences in clinical response. Complementary studies in humans and animal models are necessary to elucidate the mechanisms responsible and to test the feasibility of identifying microbiome-based biomarkers of treatment outcomes. SUMMARY: We propose that the predictive power of genetic testing could be improved by taking a more comprehensive view of human genetics that encompasses our human and microbial genomes. Furthermore, unlike the human genome, the microbiome is rapidly altered by diet, pharmaceuticals, and other interventions, providing the potential to improve patient care by re-shaping our associated microbial communities