Metagenomic Research Articles

Microbial insight into rhizosphere of arecanut palms of Wayanad using metagenomics

Microbial insight into rhizosphere of arecanut palms of Wayanad using metagenomics

Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials.

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms (microbes) obtained from a common habitat. Metagenomics and other "omics" disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. There are plenty of studies using metagenomics which examine microorganisms that inhabit niches in the human body, sometimes causing disease, and are often correlated with multiple treatment conditions. No matter from which environment it comes, the analyses are often aimed at determining either the presence or absence of specific species of interest in a given metagenome or comparing the biological diversity and the functional activity of a wider range of microorganisms within their communities. The importance increases for comparison within different environments such as multiple patients with different conditions, multiple drugs, and multiple time points of same treatment or same patient. Thus, no matter how many hypotheses we have, we need a good understanding of genomics, bioinformatics, and statistics to work together to analyze and interpret these datasets in a meaningful way. This chapter provides an overview of different data analyses and statistical approaches (with example scenarios) to analyze metagenomics samples from different medical projects or clinical trials.

Occurrence Of The Co-Selection Phenomenon In Non-Clinical Environments

Abstract Multi-resistant bacterial strains currently present the main health problem worldwide. Numerous public health organizations call for the prevention, and control the spread, of antibiotic resistance from any sources. From the literature data, it is well known that agricultural areas are a source of antibiotic resistance because of the use of antibiotics and heavy metals to promote plant and animal growth. Moreover, natural water reservoirs and soil not used for agriculture are also sources of multi-drug resistant bacteria. In recent years bacteria resistant to antibiotics and heavy metals have been isolated from heavy-metal contaminated soils and from metallophytes. Therefore, it seems that heavy metals, an environmental pollutant, may also be a selection factor that promotes the spread of antibiotic resistance. The co-selection phenomenon of resistant genes is most often connected with the lack of bacterial susceptibility to antibiotics and heavy metals. Co-selection occurs when different resistant genes that enable resistance to different stress conditions are located on the same mobile genetic elements, or when the same genes determine resistance to different stress conditions. This article presents the current state of knowledge about the co-selection phenomenon observed in bacteria isolated from nonclinical environments. 1. Introduction. 2. Co-selection mechanisms. 2.1. Cross-resistance. 2.2. Co-resistance. 2.3. Co-regulation. 3. Factors promoting spread of co-selection. 4. Occurrence of co-selection in non-clinical environments. 4.1. Areas used for agriculture. 4.2. Areas not used agriculturally. 4.3. Natural water reservoirs. 4.4. Plant endosphere. 5. Co-occurence of resistant genes in different environmental genomes. 6. Summary

Pharmacogenomic Resources In Latin America And Ongoing Studies

BackgroundAlthough atypical antipsychotics most effectively decrease positive symptoms with a lower incidence of side effects, in Mexico and Latin America (LA) in general typical antipsychotics continue to be prescribed frequently. One of the mainly prescribed antipsychotics as a first treatment for a psychotic outbreak in Mexico is haloperidol. The response to haloperidol treatment is affected by environmental variables such as genetics. The study of genetic variants that affect the response to drugs is known as pharmacogenetics. The pharmacogenetics of psychotropic agents is a particular active field of study in LA. However, the providers of these services are small private companies, employing sample references in Caucasian populations, since very few analyses of these variants have been in the LA population. However, there is some data on the pharmacogenetics of psychopharmacologic drugs in LA, which we will discuss. We will present in addition a review of some of the studies that have been done in mapping mental illnesses and epigenetics in LA populations. MethodsWe will review studies generated in Latin America from different sources of information such as Psych Info, Redalyc, and Pubmed. ResultsWhen the physician is faced with a clinical decision based on pharmacogenetics it may be useful to take into account the patterns of prescription nearly new throughout the region, specific patterns of diet and lifestyle coupled with genotypic, epigenome and meta genome data generated from the LA population. All this information may help to have a better understanding response to psychiatric medications in a more comprehensive way. ConclusionsPharmacological treatment in psychiatric diseases is not always completely effective. It may vary depending on the therapeutic class or population studied. A lack of control over drug safety and efficacy motivates research to pinpoint markers to predict them. The use of genetic polymorphisms represents an approach, to address these predictions in the Latin American population.

Embracing Environmental Genomics and Machine Learning for Routine Biomonitoring.

Genomics is fast becoming a routine tool in medical diagnostics and cutting-edge biotechnologies. Yet, its use for environmental biomonitoring is still considered a futuristic ideal. Until now, environmental genomics was mainly used as a replacement of the burdensome morphological identification, to screen known morphologically distinguishable bioindicator taxa. While prokaryotic and eukaryotic microbial diversity is of key importance in ecosystem functioning, its implementation in biomonitoring programs is still largely unappreciated, mainly because of difficulties in identifying microbes and limited knowledge of their ecological functions. Here, we argue that the combination of massive environmental genomics microbial data with machine learning algorithms can be extremely powerful for biomonitoring programs and pave the way to fill important gaps in our understanding of microbial ecology.

Multiomic Strategies Reveal Diversity and Important Functional Aspects of Human Gut Microbiome.

It is well accepted that dysbiosis of microbiota is associated with disease; however, the biological mechanisms that promote susceptibility or resilience to disease remain elusive. One of the major limitations of previous microbiome studies has been the lack of complementary metatranscriptomic (functional) data to complement the interpretation of metagenomics (bacterial abundance). The purpose of this study was twofold, first to evaluate the bacterial diversity and differential gene expression of gut microbiota using complementary shotgun metagenomics (MG) and metatranscriptomics (MT) from same fecal sample. Second, to compare sequence data using different Illumina platforms and with different sequencing parameters as new sequencers are introduced, and to determine if the data are comparable on different platforms. In this study, we perform ultradeep metatranscriptomic shotgun sequencing for a sample that we previously analyzed with metagenomics shotgun sequencing. We performed sequencing analysis using different Illumina platforms, with different sequencing and analysis parameters. Our results suggest that use of different Illumina platform did not lead to detectable bias in the sequencing data. The analysis of the sample using MG and MT approach shows that some species genes are highly represented in the MT than in the MG, indicating that some species are highly metabolically active. Our analysis also shows that ~52% of the genes in the metagenome are in the metatranscriptome and therefore are robustly expressed. The functions of the low and rare abundance bacterial species remain poorly understood. Our observations indicate that among the low abundant species analyzed in this study some were found to be more metabolically active compared to others, and can contribute distinct profiles of biological functions that may modulate the host-microbiota and bacteria-bacteria interactions.

Insights on the freshwater microbiomes metabolic changes associated with the world's largest mining disaster

To evaluate the impacts of the Fundão tailings dam failure (Minas Gerais, Brazil) on water quality of the Doce River, we analyzed metagenomics and physicochemical parameters during the month of the disaster and again 6 and 10 months after the disaster. To compare dam conditions before and after the failure, we performed a meta-analysis of physicochemical data from a public database. Immediately after the failure, suspended particulate matter (SPM) in the Doce River was 225–1877 mg L−1. Turbidity and dissolved aluminum and iron concentrations were extremely high, whereas dissolved oxygen was below Brazilian legislation norm (<5 mg L−1) in several locations. Six months later, physicochemical values were below thresholds set by Brazilian guidelines (e.g., SPM = 8–166 mg L−1). Short-term impacts on microbial communities included an increase in Actinobacteria and Bacteroidetes and gene sequences related to microbial virulence, motility, respiration, membrane transport, iron and nitrogen metabolism, suggesting changes in microbial metabolic profiles. The 11 recovered partial genomes from metagenomes (MAGs) had genes related to Fe cycle and metal resistance.

IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes.

The Integrated Microbial Genome/Virus (IMG/VR) system v.2.0 (https://img.jgi.doe.gov/vr/) is the largest publicly available data management and analysis platform dedicated to viral genomics. Since the last report published in the 2016, NAR Database Issue, the data has tripled in size and currently contains genomes of 8389 cultivated reference viruses, 12 498 previously published curated prophages derived from cultivated microbial isolates, and 735 112 viral genomic fragments computationally predicted from assembled shotgun metagenomes. Nearly 60% of the viral genomes and genome fragments are clustered into 110 384 viral Operational Taxonomic Units (vOTUs) with two or more members. To improve data quality and predictions of host specificity, IMG/VR v.2.0 now separates prokaryotic and eukaryotic viruses, utilizes known prophage sequences to improve taxonomic assignments, and provides viral genome quality scores based on the estimated genome completeness. New features also include enhanced BLAST search capabilities for external queries. Finally, geographic map visualization to locate user-selected viral genomes or genome fragments has been implemented and download options have been extended. All of these features make IMG/VR v.2.0 a key resource for the study of viruses.

Peculiarities and biotechnological potential of environmental adaptation by Geobacillus species.

The genus Geobacillus comprises thermophilic bacilli capable of endospore formation. The members of this genus provide thermostable proteins and can be used in whole cell applications at elevated temperatures; therefore, these organisms are of biotechnological importance. While these applications have been described in previous reviews, the present paper highlights the environmental adaptations and genome diversifications of Geobacillus spp. and their applications in evolutionary-protein engineering. Despite their obligate thermophilic properties, Geobacillus spp. are widely distributed in nature. Because several isolates demonstrate remarkable properties for cell reproduction in their respective niches, they seem to exist not only as endospores but also as vegetative cells in diverse environments. This suggests their excellence in environmental adaptation via genome diversification; in fact, evidence suggests that Geobacillus spp. were derived from Bacillus spp. while diversifying their genomes via horizontal gene transfer. Moreover, when subjected to an environmental stressor, Geobacillus spp. diversify their genomes using inductive mutations and transposable elements to produce derivative cells that are adaptive to the stressor. Notably, inductive mutations in Geobacillus spp. occur more rapidly and frequently than the stress-induced mutagenesis observed in other microorganisms. Owing to this, Geobacillus spp. can efficiently generate mutant genes coding for thermostable enzyme variants from the thermolabile enzyme genes under appropriate selection pressures. This phenomenon provides a new approach to generate thermostable enzymes, termed as thermoadaptation-directed enzyme evolution, thereby expanding the biotechnological potentials of Geobacillus spp. In this review, we have discussed this approach using successful examples and major challenges yet to be addressed.

Viral metagenomic analysis of fecal samples from diarrhea children with positive picobirnaviruses

Objective To investigate positive picobirnaviruses(PVBs) infection and its association with unexplained diarrhea in children. Methods From January to December 2015, the Clinical Microbiology Testing Center of Xuzhou Central Hospital as the sampling location, 7 PVB reverse transcription-polymerase chain reaction(RT-PCR)-positive fecal samples with diarrhea were collected from children under 6 years old and 4 samples from healthy children were obtained and all the samples were analyzed by viral metagenomics to investigate the relationship between PVBs and diarrhea in children.Phylogenetic analysis of RdRp in the isolated PVB sequences was carried out to clarify the relationship between PVB classification and diarrhea. Results All the 7 diarrhea feces contained high titers of PVB sequences, while 3 of the controls were negative, and 1 with low titers of PVB.RdRp analysis was carried out on the isolated PVB sequences, which displayed that 7 RdRp sequences caming from 7 fecal samples separately, so named ChXz -1 to ChXz -7 respectively.Phylogenetic analysis based on the predicted amino acid sequences of RdRp from this study and whole RdRp sequences available in the GenBank database indicated that the 7 RdRp sequences belonged to 3 genogroups, in which ChXz-1, ChXz-2, ChXz-3 belonging to genogroup Ⅰ, ChXz-4, ChXz-5, ChXz-7 belonging to genogroup Ⅱ, and ChXz-6 belonging to genogroup Ⅲ. Conclusions PVBs might be the cause of diarrhea in children in this study, and all the 3 different PVBs may lead to diarrhea. Key words: Picobirnaviruses; Diarrhea; Viral metagenomics

Abstracts from the Environmental Mutagenesis and Genomics Society 49th Annual Meeting; September 22–26, 2018, Hyatt Regency San Antonio Riverwalk, San Antonio, Texas

Abstracts from the Environmental Mutagenesis and Genomics Society 49th Annual Meeting; September 22–26, 2018, Hyatt Regency San Antonio Riverwalk, San Antonio, Texas

Genome-wide DNA methylation changes in two Brassicaceae species sampled alongside a radiation gradient in Chernobyl and Fukushima

The long-term radiological impact to the environment of the nuclear accidents in Chernobyl and Fukushima is still under discussion. In the course of spring of 2016 we sampled two Brassicacea plants, Arabidopsis thaliana and Capsella bursa-pastoris native to Ukraine and Japan, respectively, alongside a gradient of radiation within the exclusion and difficult to return zones of Chernobyl (CEZ) and Fukushima (FEZ). Ambient dose rates were similar for both sampling gradients ranging from 0.5 to 80 μGy/h at plant height. The hypothesis was tested whether a history of several generations of plants growing in enhanced radiation exposure conditions would have led to changes in genome-wide DNA methylation. However, no differences were found in the global percentage of 5-methylated cytosines in Capsella bursa pastoris plants sampled in FEZ. On the other hand a significant decrease in whole genome methylation percentage in Arabidopsis thaliana plants was found in CEZ mainly governed by the highest exposed plants. These data support a link between exposure to changed environmental conditions and changes genome methylation. In addition to methylation the activity concentration of different radionuclides, 137Cs, 90Sr, 241Am and Pu-238,239,240 for CEZ and 137, 134Cs for FEZ, was analysed in both soil and plant samples. The ratio of 5.6 between 137Cs compared to 134Cs was as expected five years after the FEZ accident. For CEZ 137Cs is the most abundant polluting radionuclide in soil followed by 90Sr. Whereas 241Am and Pu-isotopes are only marginally present. In the plant tissue, however, higher levels of Sr than Cs were retrieved due to a high uptake of 90Sr in the plants. The 90Sr transfer factors ranged in CEZ from 5 to 20 (kg/kg) depending on the locality. Based on the activity concentrations of the different radionuclides the ERICA tool was used to estimate the total dose rates to the plants. It was found that for FEZ the doses was mainly contributable to the external Cs-isotopes and as such estimated total dose rates (0.13–38 μGy/h) were in the same range as the ambient measured dose rates. In strong contrast this was not true for CEZ where the total dose rate was mainly due to high uptake of the 90Sr leading to dose rates ranging from 1 to 370 μGy/h. Hence our data clearly indicate that not taking into account the internal contamination in CEZ will lead to considerable underestimation of the doses to the plants. Additionally they show that it is hard to compare the two nuclear accidental sites and one of the main reasons is the difference in contamination profile.

Succession of the MAR-databases and marine metagenomics portal (MMP), coordination of marine sequenced data

Succession of the MAR-databases and marine metagenomics portal (MMP), coordination of marine sequenced data

Plant microbiota: from model plants to Mediterranean crops

Plants live in ecosystems where they interact with complex microbial communities instigating a wide range of relationships. These communities constitute the ‘microbiota’, a term initially coined to describe host-symbiont systems that has been extended to cover non-symbiotic, but mostly beneficial interactions. Through the development of innovative ‘-omics’ technologies such as high-throughput sequencing, study of plant microbiota has advanced rapidly, allowing scientists to increase understanding of plant primary functions and how these can be positively impacted by microbes. In addition, basic knowledge of plant-microbe interactions offers novel potential applications for sustainable agriculture. This review outlines new concepts of the ’plant metagenome‘, then summarizes major advances related to plant root-associated microbial communities, from model plants, such as Arabidopsis thaliana, to important Mediterranean crops. Arbuscular mycorrhizal fungi are crucial components of root microbiota: they are acknowledged as relevant tools for improving plant mineral nutrition in agricultural environments. Particular attention is given to their impacts on plant hosts, particularly tomato, which has been widely used as valuable model, both in plant biology and crop sciences, due to its importance in Mediterranean agriculture.

Landscape Genomic Conservation Assessment of a Narrow-Endemic and a Widespread Morning Glory From Amazonian Savannas.

Although genetic diversity ultimately determines the ability of organisms to adapt to environmental changes, conservation assessments like the widely used International Union for Conservation of Nature (IUCN) Red List Criteria do not explicitly consider genetic information. Including a genetic dimension into the IUCN Red List Criteria would greatly enhance conservation efforts, because the demographic parameters traditionally considered are poor predictors of the evolutionary resilience of natural populations to global change. Here we perform the first genomic assessment of genetic diversity, gene flow, and patterns of local adaptation in tropical plant species belonging to different IUCN Red List Categories. Employing RAD-sequencing we identified tens of thousands of single-nucleotide polymorphisms in an endangered narrow-endemic and a least concern widespread morning glory (Convolvulaceae) from Amazonian savannas, a highly threatened and under-protected tropical ecosystem. Our results reveal greater genetic diversity and less spatial genetic structure in the endangered species. Whereas terrain roughness affected gene flow in both species, forested and mining areas were found to hinder gene flow in the endangered plant. Finally we implemented environmental association tests and genome scans for selection, and identified a higher proportion of candidate adaptive loci in the widespread species. These mainly contained genes related to pathogen resistance and physiological adaptations to life in nutrient-limited environments. Our study emphasizes that IUCN Red List Criteria do not always prioritize species with low genetic diversity or whose genetic variation is being affected by habitat loss and fragmentation, and calls for the inclusion of genetic information into conservation assessments. More generally, our study exemplifies how landscape genomic tools can be employed to assess the status, threats and adaptive responses of imperiled biodiversity.

Targeted gene disruption by use of CRISPR/Cas9 ribonucleoprotein complexes in the water flea Daphnia pulex.

The microcrustacean Daphnia pulex is an important model for environmental, ecological, evolutionary and developmental genomics because its adaptive life history displays plasticity in response to environmental changes. Even though the whole-genome sequence is available and omics data have actively accumulated for this species, the available tools for analyzing gene function have thus far been limited to RNAi (RNA interference) and TALEN (the transcription activator-like effector nuclease) systems. The development of the CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated 9) system is thus expected to further increase the genetic tractability of D.pulex and to advance the understanding of this species. In this study, we developed a genome editing system for D.pulex using CRISPR/Cas9 ribonucleoprotein complexes (Cas9 RNPs). We first assembled a CRISPR single-guide RNA (sgRNA) specific to the Distal-less gene (Dll), which encodes a homeodomain transcription factor essential for distal limb development in invertebrates and vertebrates. Then, we injected Cas9 RNPs into eggs and evaluated its activity in vivo by a T7 endonuclease I assay. Injected embryos showed defective formation of the second antenna and disordered development of appendages, and indel mutations were detected in Dll loci, indicating that this technique successfully knocked out the target gene.

Metagenomic analysis reveals reduction in antibiotic resistance gene carriage in breastfed infants supplemented with activated Bifidobacterium longum subsp. infantis.

Human milk contains crucial substrates to shape the development of the gut microbiome in newborns. Particularly, milk oligosaccharides have favored evolutionary relationships with select members of the genus Bifidobacterium. This mutualistic symbiosis fosters positive health outcomes, and has been linked to a decrease in autoimmune disease in early life. In this trial, we hypothesized that infants supplemented with an activated Bifidobacterium longum subsp. infantis would favorably remodel the infant gut microbiome, with significant changes to the gut metagenome. The rapid emergence of antibiotic-resistant (AR) pathogens is a major public health …

Metabolomes from metagenomics and modeling

Metabolomes from metagenomics and modeling

Increase in Bacterial Resistance to Antibiotics after Cancer Therapy with Platinum-Based Drugs

The use of platinum-based anticancer drugs is limited by both their side effects and their effect on normal microflora's metagenome. Drugs that possess mutagenic and genotoxic properties may cause mutations in microbial genomes that contribute to the emergence of resistance to antimicrobial preparations and the development of complications after chemotherapy. The effects of cisplatin and oxaliplatin on microorganisms were studied using bacterial biosensors - E. coli strains MG1655 pKatG-lux, which reacts to the generation of hydrogen peroxide; MG1655 pSoxS-lux, which reacts to the superoxide anion radical; and the MG1655 pColD-lux strain, which detects DNA damage. The biosensor tests demonstrated high levels of genotoxicity for both drugs and some differences in the spectrum of reactive oxygen species generated. Ascor-bate reduced genotoxicity of cisplatin by 41%. Nonlethal doses of cisplatin induced a three- to sevenfold increase in the frequency of the mutations that confer the resistance of E. coli to rifampicin and ciprof loxacin. Ascorbate also reduced frequency of the mutations by 65%. Thus, the effect of these drugs was probably associated with the generation of reactive oxygen species and induction of SOS response. The risk of secondary antibiotic-resistant infections may be decreased by applying antioxidants and antimutagens. At the same time, these increases may also decrease the anti-tumoral action of these compounds.

GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models.

MotivationThe vast number of available sequenced bacterial genomes occasionally exceeds the facilities of comparative genomic methods or is dominated by a single outbreak strain, and thus a diverse and representative subset is required. Generation of the reduced subset currently requires a priori supervised clustering and sequence-only selection of medoid genomic sequences, independent of any additional genome metrics or strain attributes.ResultsThe Gaussian Genome Representative Selector with Prioritization (GGRaSP) R-package described below generates a reduced subset of genomes that prioritizes maintaining genomes of interest to the user as well as minimizing the loss of genetic variation. The package also allows for unsupervised clustering by modeling the genomic relationships using a Gaussian mixture model to select an appropriate cluster threshold. We demonstrate the capabilities of GGRaSP by generating a reduced list of 315 genomes from a genomic dataset of 4600 Escherichia coli genomes, prioritizing selection by type strain and by genome completeness.Availability and implementaion GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/.Supplementary information Supplementary data are available at Bioinformatics online.