scholarly journals Evaluating performance of metagenomic characterization algorithms using in silico datasets generated with FASTQSim

2016 ◽  
Author(s):  
Anna Shcherbina ◽  
Darrell O. Ricke ◽  
Nelson Chiu
Keyword(s):  
In Silico ◽  
Microbial Community Composition ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Decision Makers ◽  
Emerging Pathogens ◽  
Read Mapping ◽  
Algorithm Performance ◽  
True Source ◽  
Organism Identification

AbstractBackgroundIn silico bacterial, viral, and human truth datasets were generated to evaluate available metagenomics algorithms. Sequenced datasets include background organisms, creating ambiguity in the true source organism for each read. Bacterial and viral datasets were created with even and staggered coverage to evaluate organism identification, read mapping, and gene identification capabilities of available algorithms. These truth datasets are provided as a resource for the development and refinement of metagenomic algorithms. Algorithm performance on these truth datasets can inform decision makers on strengths and weaknesses of available algorithms and how the results may be best leveraged for bacterial and viral organism identification and characterization.Source organisms were selected to mirror communities described in the Human Microbiome Project as well as the emerging pathogens listed by the National Institute of Allergy and Infectious Diseases. The six in silico datasets were used to evaluate the performance of six leading metagenomics algorithms: MetaScope, Kraken, LMAT, MetaPhlAn, MetaCV, and MetaPhyler.ResultsAlgorithms were evaluated on runtime, true positive organisms identified to the genus and species levels, false positive organisms identified to genus and species level, read mapping, relative abundance estimation, and gene calling. No algorithm out performed the others in all categories, and the algorithm or algorithms of choice strongly depends on analysis goals. MetaPhlAn excels for bacteria and LMAT for viruses. The algorithms were ranked by overall performance using a normalized weighted sum of the above metrics, and MetaScope emerged as the overall winner, followed by Kraken and LMAT.ConclusionsSimulated FASTQ datasets with well-characterized truth data about microbial community composition reveal numerous insights about the relative strengths and weaknesses of the metagenomics algorithms evaluated. The simulated datasets are available to download from the Sequence Read Archive (SRP062063).

scholarly journals What's in a Name? New Bacterial Species and Changes to Taxonomic Status from 2012 through 2015

2016 ◽  
Vol 55 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Erik Munson ◽  
Karen C. Carroll
Keyword(s):  
Susceptibility Testing ◽  
Novel Species ◽  
Bacterial Species ◽  
Human Microbiome ◽  
Taxonomic Status ◽  
Emerging Pathogens ◽  
Taxonomic Changes ◽  
Clinically Significant ◽  
Organism Identification ◽  
Evolutionary Microbiology

ABSTRACTTechnological advancements in fields such as molecular genetics and the human microbiome have resulted in an unprecedented recognition of new bacterial genus/species designations by theInternational Journal of Systematic and Evolutionary Microbiology. Knowledge of designations involving clinically significant bacterial species would benefit clinical microbiologists in the context of emerging pathogens, performance of accurate organism identification, and antimicrobial susceptibility testing. In anticipation of subsequent taxonomic changes being compiled by theJournal of Clinical Microbiologyon a biannual basis, this compendium summarizes novel species and taxonomic revisions specific to bacteria derived from human clinical specimens from the calendar years 2012 through 2015.

scholarly journals A microbial survey of the International Space Station (ISS)

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4029 ◽  
Author(s):  
Jenna M. Lang ◽  
David A. Coil ◽  
Russell Y. Neches ◽  
Wendy E. Brown ◽  
Darlene Cavalier ◽  
...  
Keyword(s):  
Microbial Ecology ◽  
16S Rdna ◽  
International Space Station ◽  
Microbial Community Composition ◽  
Space Station ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Small Sample ◽  
International Space ◽  
16S Rdna Pcr

BackgroundModern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the “buildings” in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons.ResultsSterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project.ConclusionsWhile significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036–4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

scholarly journals Sequence Comparison of Vaginolysin from Different Gardnerella Species

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 86
Author(s):  
Erin M. Garcia ◽  
Myrna G. Serrano ◽  
Laahirie Edupuganti ◽  
David J. Edwards ◽  
Gregory A. Buck ◽  
...  
Keyword(s):  
Amino Acid ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Distinct Species ◽  
Vaginal Swab ◽  
Metagenomic Data ◽  
Gardnerella Vaginalis ◽  
Vaginal Epithelial Cells ◽  
Species Specific

Gardnerella vaginalis has recently been split into 13 distinct species. In this study, we tested the hypotheses that species-specific variations in the vaginolysin (VLY) amino acid sequence could influence the interaction between the toxin and vaginal epithelial cells and that VLY variation may be one factor that distinguishes less virulent or commensal strains from more virulent strains. This was assessed by bioinformatic analyses of publicly available Gardnerella spp. sequences and quantification of cytotoxicity and cytokine production from purified, recombinantly produced versions of VLY. After identifying conserved differences that could distinguish distinct VLY types, we analyzed metagenomic data from a cohort of female subjects from the Vaginal Human Microbiome Project to investigate whether these different VLY types exhibited any significant associations with symptoms or Gardnerella spp.-relative abundance in vaginal swab samples. While Type 1 VLY was most prevalent among the subjects and may be associated with increased reports of symptoms, subjects with Type 2 VLY dominant profiles exhibited increased relative Gardnerella spp. abundance. Our findings suggest that amino acid differences alter the interaction of VLY with vaginal keratinocytes, which may potentiate differences in bacterial vaginosis (BV) immunopathology in vivo.

scholarly journals Competition among Nasal Bacteria Suggests a Role for Siderophore-Mediated Interactions in Shaping the Human Nasal Microbiota

2018 ◽  
Vol 85 (10) ◽  
Author(s):  
Reed M. Stubbendieck ◽  
Daniel S. May ◽  
Marc G. Chevrette ◽  
Mia I. Temkin ◽  
Evelyn Wendt-Pienkowski ◽  
...  
Keyword(s):  
Nasal Cavity ◽  
Iron Acquisition ◽  
Interference Competition ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Siderophore Production ◽  
Coagulase Negative Staphylococci ◽  
Exploitation Competition ◽  
Content Type

ABSTRACTResources available in the human nasal cavity are limited. Therefore, to successfully colonize the nasal cavity, bacteria must compete for scarce nutrients. Competition may occur directly through interference (e.g., antibiotics) or indirectly by nutrient sequestration. To investigate the nature of nasal bacterial competition, we performed coculture inhibition assays between nasalActinobacteriaandStaphylococcusspp. We found that isolates of coagulase-negative staphylococci (CoNS) were sensitive to growth inhibition byActinobacteriabut thatStaphylococcus aureusisolates were resistant to inhibition. AmongActinobacteria, we observed thatCorynebacteriumspp. were variable in their ability to inhibit CoNS. We sequenced the genomes of 10Corynebacteriumspecies isolates, including 3Corynebacterium propinquumisolates that strongly inhibited CoNS and 7 otherCorynebacteriumspecies isolates that only weakly inhibited CoNS. Using a comparative genomics approach, we found that theC. propinquumgenomes were enriched in genes for iron acquisition and harbored a biosynthetic gene cluster (BGC) for siderophore production, absent in the noninhibitoryCorynebacteriumspecies genomes. Using a chrome azurol S assay, we confirmed thatC. propinquumproduced siderophores. We demonstrated that iron supplementation rescued CoNS from inhibition byC. propinquum, suggesting that inhibition was due to iron restriction through siderophore production. Through comparative metabolomics and molecular networking, we identified the siderophore produced byC. propinquumas dehydroxynocardamine. Finally, we confirmed that the dehydroxynocardamine BGC is expressedin vivoby analyzing human nasal metatranscriptomes from the NIH Human Microbiome Project. Together, our results suggest that bacteria produce siderophores to compete for limited available iron in the nasal cavity and improve their fitness.IMPORTANCEWithin the nasal cavity, interference competition through antimicrobial production is prevalent. For instance, nasalStaphylococcusspecies strains can inhibit the growth of other bacteria through the production of nonribosomal peptides and ribosomally synthesized and posttranslationally modified peptides. In contrast, bacteria engaging in exploitation competition modify the external environment to prevent competitors from growing, usually by hindering access to or depleting essential nutrients. As the nasal cavity is a nutrient-limited environment, we hypothesized that exploitation competition occurs in this system. We determined thatCorynebacterium propinquumproduces an iron-chelating siderophore, and this iron-sequestering molecule correlates with the ability to inhibit the growth of coagulase-negative staphylococci. Furthermore, we found that the genes required for siderophore production are expressedin vivo. Thus, although siderophore production by bacteria is often considered a virulence trait, our work indicates that bacteria may produce siderophores to compete for limited iron in the human nasal cavity.

scholarly journals MetaCompass: Reference-guided Assembly of Metagenomes

2017 ◽  
Author(s):  
Victoria Cepeda ◽  
Bo Liu ◽  
Mathieu Almeida ◽  
Christopher M. Hill ◽  
Sergey Koren ◽  
...  
Keyword(s):  
De Novo ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Bacterial Genomes ◽  
Guided Assembly ◽  
Metagenomic Assembly

ABSTRACTMetagenomic studies have primarily relied on de novo approaches for reconstructing genes and genomes from microbial mixtures. While database driven approaches have been employed in certain analyses, they have not been used in the assembly of metagenomes. Here we describe the first effective approach for reference-guided metagenomic assembly of low-abundance bacterial genomes that can complement and improve upon de novo metagenomic assembly methods. When combined with de novo assembly approaches, we show that MetaCompass can generate more complete assemblies than can be obtained by de novo assembly alone, and improve on assemblies from the Human Microbiome Project (over 2,000 samples).

scholarly journals Misclassification of a whole genome sequence reference defined by the Human Microbiome Project: a detrimental carryover effect to microbiome studies

2019 ◽  
Author(s):  
DJ Darwin R. Bandoy ◽  
B Carol Huang ◽  
Bart C. Weimer
Keyword(s):  
Human Microbiome ◽  
Human Microbiome Project ◽  
Outbreak Detection ◽  
Whole Genome Sequence ◽  
Reference Database ◽  
Whole Genome ◽  
Reference Species ◽  
Genome Sequences ◽  
Genome Homology ◽  
Microbiome Data

AbstractTaxonomic classification is an essential step in the analysis of microbiome data that depends on a reference database of whole genome sequences. Taxonomic classifiers are built on established reference species, such as the Human Microbiome Project database, that is growing rapidly. While constructing a population wide pangenome of the bacterium Hungatella, we discovered that the Human Microbiome Project reference species Hungatella hathewayi (WAL 18680) was significantly different to other members of this genus. Specifically, the reference lacked the core genome as compared to the other members. Further analysis, using average nucleotide identity (ANI) and 16s rRNA comparisons, indicated that WAL18680 was misclassified as Hungatella. The error in classification is being amplified in the taxonomic classifiers and will have a compounding effect as microbiome analyses are done, resulting in inaccurate assignment of community members and will lead to fallacious conclusions and possibly treatment. As automated genome homology assessment expands for microbiome analysis, outbreak detection, and public health reliance on whole genomes increases this issue will likely occur at an increasing rate. These observations highlight the need for developing reference free methods for epidemiological investigation using whole genome sequences and the criticality of accurate reference databases.

scholarly journals An Evaluation of “I, Pancreas” Algorithm Performance In Silico

2009 ◽  
Vol 3 (4) ◽  
pp. 857-862 ◽  
Author(s):  
Malgorzata E. Wilinska ◽  
Marianna Nodale
Keyword(s):  
In Silico ◽  
Algorithm Performance
Sign in / Sign up

Export Citation Format

Share Document