Abstract:Background: Thousands of different microorganisms affect the health, safety, and economic stability of populations. Many different medical and governmental organizations have created lists of the pathogenic microorganisms relevant to their missions; however, the nomenclature for biological agents on these lists and pathogens described in the literature is inexact. This ambiguity can be a significant block to effective communication among the diverse communities that must deal with epidemics or bioterrorist att… Show more
“…These discoveries fill some major gaps in our knowledge, and allow the tree of viral relationships to be updated. For example, this latest work confirms that the viruses of the Arenaviridae genus—which generally infect rodents—belong to the Bunyaviridae family along with two previously unclassified genera of viruses that infect plants ( Ecker et al 2005 ; Kormelink et al 2011 ). Figure 1.…”
supporting
confidence: 58%
“…Amongst the virus family Orthomyxoviridae, for example, they identified many relatives of the Quaranja viruses, which infect ticks, but none that are closely related to the Influenza viruses that infect vertebrates. Similarly, no lineages were found to be closely related to Ebola and other Filoviruses, which belong to a lineage that apparently only infects mammals ( Ecker et al 2005 ). It is therefore interesting to speculate that these virus groups may genuinely display some long–term association with mammals.…”
The huge diversity of negative-sense RNA viruses in insects, spiders and other arthropods suggests that these animals could be central to virus origin and evolution.
“…These discoveries fill some major gaps in our knowledge, and allow the tree of viral relationships to be updated. For example, this latest work confirms that the viruses of the Arenaviridae genus—which generally infect rodents—belong to the Bunyaviridae family along with two previously unclassified genera of viruses that infect plants ( Ecker et al 2005 ; Kormelink et al 2011 ). Figure 1.…”
supporting
confidence: 58%
“…Amongst the virus family Orthomyxoviridae, for example, they identified many relatives of the Quaranja viruses, which infect ticks, but none that are closely related to the Influenza viruses that infect vertebrates. Similarly, no lineages were found to be closely related to Ebola and other Filoviruses, which belong to a lineage that apparently only infects mammals ( Ecker et al 2005 ). It is therefore interesting to speculate that these virus groups may genuinely display some long–term association with mammals.…”
The huge diversity of negative-sense RNA viruses in insects, spiders and other arthropods suggests that these animals could be central to virus origin and evolution.
“…The taxonomic distribution proportion of currently available genomes of identified pathogens was reflected in the toxin database, with Proteobacteria and Firmicutes accounting for the majority of the genomes. However, the CCA results may also indicate, at least in part, a proportional lack of pathogens in some phyla, such as Crenarchaeota, Euryarchaeota, Verrucomicrobia, and Bacteroidetes [69]. Table 1 Archaea cannot easily absorb phage particles because of their extracellular structures, which differ from bacteria [70].…”
Background: Human pathogens are widespread in the environment, and examination of pathogen-enriched environments in a rapid and high-throughput fashion is important for development of pathogen-risk precautionary measures. In this study, a Local BLASTP procedure for metagenomic screening of pathogens in the environment was developed using a toxin-centered database. A total of 69 microbiomes derived from ocean water, freshwater, soils, feces, and wastewater were screened using the Local BLASTP procedure. Bioinformatic analysis and Canonical Correspondence Analysis were conducted to examine whether the toxins included in the database were taxonomically associated. Results: The specificity of the Local BLASTP method was tested with known and unknown toxin sequences. Bioinformatic analysis indicated that most toxins were phylum-specific but not genus-specific. Canonical Correspondence Analysis implied that almost all of the toxins were associated with the phyla of Proteobacteria, Nitrospirae and Firmicutes. Local BLASTP screening of the global microbiomes showed that pore-forming RTX toxin, ornithine carbamoyltransferase ArgK, and RNA interferase Rel were most prevalent globally in terms of relative abundance, while polluted water and feces samples were the most pathogen-enriched. Conclusions: The Local BLASTP procedure was applied for rapid detection of toxins in environmental samples using a toxin-centered database built in this study. Screening of global microbiomes in this study provided a quantitative estimate of the most prevalent toxins and most pathogen-enriched environments. Feces-contaminated environments are of particular concern for pathogen risks.
“…These genes may be potential drug targets in the future. To identify such cases, we considered 3 different criteria that the missed genes have to satisfy: (i) the missed gene should belong to a pathogenic organism (according to The Microbial Rosetta Stone Database of Pathogens [20]); (ii) the missed gene should be assigned to a protein cluster with at least 50 members (based on ComBlast results); and (iii) the missed gene should possess significant sequence similarity to any essential gene within COMBREX (based on ComBlast results). By this method, we found 359 missed genes, belonging to 88 different pathogenic organisms, that satisfied all the above criteria and thus might be interesting drug targets (Figure 3B).…”
BackgroundThe dramatic reduction in the cost of sequencing has allowed many researchers to join in the effort of sequencing and annotating prokaryotic genomes. Annotation methods vary considerably and may fail to identify some genes. Here we draw attention to a large number of likely genes missing from annotations using common tools such as Glimmer and BLAST.ResultsBy analyzing 1,474 prokaryotic genome annotations in GenBank, we identify 13,602 likely missed genes that are homologs to non-hypothetical proteins, and 11,792 likely missed genes that are homologs only to hypothetical proteins, yet have supporting evidence of their protein-coding nature from COMBREX, a newly created gene function database. We also estimate the likelihood that each potential missing gene found is a genuine protein-coding gene using COMBREX.ConclusionsOur analysis of the causes of missed genes suggests that larger annotation centers tend to produce annotations with fewer missed genes than smaller centers, and many of the missed genes are short genes <300 bp. Over 1,000 of the likely missed genes could be associated with phenotype information available in COMBREX. 359 of these genes, found in pathogenic organisms, may be potential targets for pharmaceutical research. The newly identified genes are available on COMBREX’s website.ReviewersThis article was reviewed by Daniel Haft, Arcady Mushegian, and M. Pilar Francino (nominated by David Ardell).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
