scholarly journals From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer

mSystems ◽  
2016 ◽  
Vol 1 (6) ◽  
Author(s):  
Aaron Weimann ◽  
Kyra Mooren ◽  
Jeremy Frank ◽  
Phillip B. Pope ◽  
Andreas Bremges ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Human Health ◽  
Bacterial Communities ◽  
Genome Sequences ◽  
Bacterial Genomes ◽  
Human Gut ◽  
Polluted Soils ◽  
Lab Experiments ◽  
Wet Lab ◽  
Biotechnological Processes

ABSTRACT Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required. The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar . IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.

scholarly journals The capacity of wastewater treatment plants drives bacterial community structure and its assembly

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Young Kyung Kim ◽  
Keunje Yoo ◽  
Min Sung Kim ◽  
Il Han ◽  
Minjoo Lee ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Community Structure ◽  
Bacterial Community ◽  
Activated Sludge ◽  
Community Assembly ◽  
Bacterial Communities ◽  
Wastewater Treatment Plants ◽  
High Capacity ◽  
Operating Conditions ◽  
Rrna Gene

Abstract Bacterial communities in wastewater treatment plants (WWTPs) affect plant functionality through their role in the removal of pollutants from wastewater. Bacterial communities vary extensively based on plant operating conditions and influent characteristics. The capacity of WWTPs can also affect the bacterial community via variations in the organic or nutrient composition of the influent. Despite the importance considering capacity, the characteristics that control bacterial community assembly are largely unknown. In this study, we discovered that bacterial communities in WWTPs in Korea and Vietnam, which differ remarkably in capacity, exhibit unique structures and interactions that are governed mainly by the capacity of WWTPs. Bacterial communities were analysed using 16S rRNA gene sequencing and exhibited clear differences between the two regions, with these differences being most pronounced in activated sludge. We found that capacity contributed the most to bacterial interactions and community structure, whereas other factors had less impact. Co-occurrence network analysis showed that microorganisms from high-capacity WWTPs are more interrelated than those from low-capacity WWTPs, which corresponds to the tighter clustering of bacterial communities in Korea. These results will contribute to the understanding of bacterial community assembly in activated sludge processing.

The first sequenced Sphaerotilus natans bacteriophage– characterization and potential to control its filamentous bacterium host

2021 ◽  
Vol 97 (4) ◽  
Author(s):  
Rute Ferreira ◽  
Rui Amado ◽  
Jorge Padrão ◽  
Vânia Ferreira ◽  
Nicolina M Dias ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Bacterial Communities ◽  
Potential Application ◽  
Deleterious Effect ◽  
Wastewater Treatment Plants ◽  
Lytic Phage ◽  
Filamentous Bacterium ◽  
Sphaerotilus Natans ◽  
Isolation And Characterization

ABSTRACT Bacteriophages (phages) are ubiquitous entities present in every conceivable habitat as a result of their bacterial parasitism. Their prevalence and impact in the ecology of bacterial communities and their ability to control pathogens make their characterization essential, particularly of new phages, improving knowledge and potential application. The isolation and characterization of a new lytic phage against Sphaerotilus natans strain DSM 6575, named vB_SnaP-R1 (SnaR1), is here described. Besides being the first sequenced genome of a Sphaerotilus natans infecting phage, 99% of its 41507 bp genome lacks homology with any other sequenced phage, revealing its uniqueness and previous lack of knowledge. Moreover, SnaR1 is the first Podoviridae phage described infecting this bacterium. Sphaerotilus natans is an important filamentous bacterium due to its deleterious effect on wastewater treatment plants (WWTP) and thus, phages may play a role as novel biotechnological tools against filamentous overgrowth in WWTP. The lytic spectrum of SnaR1 was restricted to its host strain, infecting only one out of three S. natans strains and infection assays revealed its ability to reduce bacterial loads. Results suggest SnaR1 as the prototype of a new phage genus and demonstrates its potential as a non-chemical alternative to reduce S. natans DSM 6575 cells.

scholarly journals Bacterial diversity and predicted enzymatic function in a multipurpose surface water system – from wastewater effluent discharges to drinking water production

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ananda Tiwari ◽  
Anna-Maria Hokajärvi ◽  
Jorge Santo Domingo ◽  
Michael Elk ◽  
Balamuralikrishna Jayaprakash ◽  
...  
Keyword(s):  
Drinking Water ◽  
Surface Water ◽  
Bacterial Community ◽  
Human Health ◽  
Bacterial Diversity ◽  
Water Samples ◽  
Bacterial Communities ◽  
Treatment Process ◽  
Pollution Sources ◽  
Production Well

Abstract Background Rivers and lakes are used for multiple purposes such as for drinking water (DW) production, recreation, and as recipients of wastewater from various sources. The deterioration of surface water quality with wastewater is well-known, but less is known about the bacterial community dynamics in the affected surface waters. Understanding the bacterial community characteristics —from the source of contamination, through the watershed to the DW production process—may help safeguard human health and the environment. Results The spatial and seasonal dynamics of bacterial communities, their predicted functions, and potential health-related bacterial (PHRB) reads within the Kokemäenjoki River watershed in southwest Finland were analyzed with the 16S rRNA-gene amplicon sequencing method. Water samples were collected from various sampling points of the watershed, from its major pollution sources (sewage influent and effluent, industrial effluent, mine runoff) and different stages of the DW treatment process (pre-treatment, groundwater observation well, DW production well) by using the river water as raw water with an artificial groundwater recharge (AGR). The beta-diversity analysis revealed that bacterial communities were highly varied among sample groups (R = 0.92, p <  0.001, ANOSIM). The species richness and evenness indices were highest in surface water (Chao1; 920 ± 10) among sample groups and gradually decreased during the DW treatment process (DW production well; Chao1: 320 ± 20). Although the phylum Proteobacteria was omnipresent, its relative abundance was higher in sewage and industrial effluents (66–80%) than in surface water (55%). Phyla Firmicutes and Fusobacteria were only detected in sewage samples. Actinobacteria was more abundant in the surface water (≥13%) than in other groups (≤3%). Acidobacteria was more abundant in the DW treatment process (≥13%) than in others (≤2%). In total, the share of PHRB reads was higher in sewage and surface water than in the DW treatment samples. The seasonal effect in bacterial communities was observed only on surface water samples, with the lowest diversity during summer. Conclusions The low bacterial diversity and absence of PHRB read in the DW samples indicate AGR can produce biologically stable and microbiologically safe drinking water. Furthermore, the significantly different bacterial communities at the pollution sources compared to surface water and DW samples highlight the importance of effective wastewater treatment for protecting the environment and human health.

scholarly journals Graph contextualized attention network for predicting synthetic lethality in human cancers

2021 ◽  
Author(s):  
Yahui Long ◽  
Min Wu ◽  
Yong Liu ◽  
Jie Zheng ◽  
Chee Keong Kwoh ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Critical Role ◽  
Design Feature ◽  
Cost Effective ◽  
Attention Network ◽  
New Genes ◽  
Lab Experiments ◽  
Proposed Model ◽  
Multiple Feature ◽  
Wet Lab

Abstract Motivation Synthetic Lethality (SL) plays an increasingly critical role in the targeted anticancer therapeutics. In addition, identifying SL interactions can create opportunities to selectively kill cancer cells without harming normal cells. Given the high cost of wet-lab experiments, in silico prediction of SL interactions as an alternative can be a rapid and cost-effective way to guide the experimental screening of candidate SL pairs. Several matrix factorization-based methods have recently been proposed for human SL prediction. However, they are limited in capturing the dependencies of neighbors. In addition, it is also highly challenging to make accurate predictions for new genes without any known SL partners. Results In this work, we propose a novel graph contextualized attention network named GCATSL to learn gene representations for SL prediction. First, we leverage different data sources to construct multiple feature graphs for genes, which serve as the feature inputs for our GCATSL method. Second, for each feature graph, we design node-level attention mechanism to effectively capture the importance of local and global neighbors and learn local and global representations for the nodes, respectively. We further exploit multi-layer perceptron (MLP) to aggregate the original features with the local and global representations and then derive the feature-specific representations. Third, to derive the final representations, we design feature-level attention to integrate feature-specific representations by taking the importance of different feature graphs into account. Extensive experimental results on three datasets under different settings demonstrated that our GCATSL model outperforms 14 state-of-the-art methods consistently. In addition, case studies further validated the effectiveness of our proposed model in identifying novel SL pairs. Availability Python codes and dataset are freely available on GitHub (https://github.com/longyahui/GCATSL) and Zenodo (https://zenodo.org/record/4522679) under the MIT license.

scholarly journals Recombinant transfer in the basic genome ofEscherichia coli

2015 ◽  
Vol 112 (29) ◽  
pp. 9070-9075 ◽  
Author(s):  
Purushottam D. Dixit ◽  
Tin Yau Pang ◽  
F. William Studier ◽  
Sergei Maslov
Keyword(s):  
Common Ancestor ◽  
Recipient Cell ◽  
Gene Clusters ◽  
Selective Advantage ◽  
Last Common Ancestor ◽  
Genome Sequences ◽  
Bacterial Genomes ◽  
Basic Genome ◽  
Single Base Pair ◽  
Generalized Transduction

An approximation to the ∼4-Mbp basic genome shared by 32 strains ofEscherichia colirepresenting six evolutionary groups has been derived and analyzed computationally. A multiple alignment of the 32 complete genome sequences was filtered to remove mobile elements and identify the most reliable ∼90% of the aligned length of each of the resulting 496 basic-genome pairs. Patterns of single base-pair mutations (SNPs) in aligned pairs distinguish clonally inherited regions from regions where either genome has acquired DNA fragments from diverged genomes by homologous recombination since their last common ancestor. Such recombinant transfer is pervasive across the basic genome, mostly between genomes in the same evolutionary group, and generates many unique mosaic patterns. The six least-diverged genome pairs have one or two recombinant transfers of length ∼40–115 kbp (and few if any other transfers), each containing one or more gene clusters known to confer strong selective advantage in some environments. Moderately diverged genome pairs (0.4–1% SNPs) show mosaic patterns of interspersed clonal and recombinant regions of varying lengths throughout the basic genome, whereas more highly diverged pairs within an evolutionary group or pairs between evolutionary groups having >1.3% SNPs have few clonal matches longer than a few kilobase pairs. Many recombinant transfers appear to incorporate fragments of the entering DNA produced by restriction systems of the recipient cell. A simple computational model can closely fit the data. Most recombinant transfers seem likely to be due to generalized transduction by coevolving populations of phages, which could efficiently distribute variability throughout bacterial genomes.

scholarly journals Relationship between Nutrient Intake and Human Gut Microbiota in Monozygotic Twins

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 275
Author(s):  
Natsuko Matsumoto ◽  
Jonguk Park ◽  
Rie Tomizawa ◽  
Hitoshi Kawashima ◽  
Koji Hosomi ◽  
...  
Keyword(s):  
Individual Differences ◽  
Environmental Factors ◽  
Gut Microbiota ◽  
Human Health ◽  
Negative Correlation ◽  
Nutrient Intake ◽  
Monozygotic Twins ◽  
Human Gut ◽  
Positive Correlation ◽  
Human Gut Microbiota

Background and Objectives: The gut microbiota is associated with human health and dietary nutrition. Various studies have been reported in this regard, but it is difficult to clearly analyze human gut microbiota as individual differences are significant. The causes of these individual differences in intestinal microflora are genetic and/or environmental. In this study, we focused on differences between identical twins in Japan to clarify the effects of nutrients consumed on the entire gut microbiome, while excluding genetic differences. Materials and Methods: We selected healthy Japanese monozygotic twins for the study and confirmed their zygosity by matching 15 short tandem repeat loci. Their fecal samples were subjected to 16S rRNA sequencing and bioinformatics analyses to identify and compare the fluctuations in intestinal bacteria. Results: We identified 12 genera sensitive to environmental factors, and found that Lactobacillus was relatively unaffected by environmental factors. Moreover, we identified protein, fat, and some nutrient intake that can affect 12 genera, which have been identified to be more sensitive to environmental factors. Among the 12 genera, Bacteroides had a positive correlation with retinol equivalent intake (rs = 0.38), Lachnospira had a significantly negative correlation with protein, sodium, iron, vitamin D, vitamin B6, and vitamin B12 intake (rs = −0.38, −0.41, −0.39, −0.63, −0.42, −0.49, respectively), Lachnospiraceae ND3007 group had a positive correlation with fat intake (rs = 0.39), and Lachnospiraceae UCG-008 group had a negative correlation with the saturated fatty acid intake (rs = −0.45). Conclusions: Our study is the first to focus on the relationship between human gut microbiota and nutrient intake using samples from Japanese twins to exclude the effects of genetic factors. These findings will broaden our understanding of the more intuitive relationship between nutrient intake and the gut microbiota and can be a useful basis for finding useful biomarkers that contribute to human health.

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