The Microbe Directory: An annotated, searchable inventory of microbes’ characteristics

Abstract

The Microbe Directory is a collective research effort to profile and annotate more than 7,500 unique microbial species from the MetaPhlAn2 database that includes bacteria, archaea, viruses, fungi, and protozoa. By collecting and summarizing data on various microbes’ characteristics, the project comprises a database that can be used downstream of large-scale metagenomic taxonomic analyses, allowing one to interpret and explore their taxonomic classifications to have a deeper understanding of the microbial ecosystem they are studying. Such characteristics include, but are not limited to: optimal pH, optimal temperature, Gram stain, biofilm-formation, spore-formation, antimicrobial resistance, and COGEM class risk rating. The database has been manually curated by trained student-researchers from Weill Cornell Medicine and CUNY—Hunter College, and its analysis remains an ongoing effort with open-source capabilities so others can contribute. Available in SQL, JSON, and CSV (i.e. Excel) formats, the Microbe Directory can be queried for the aforementioned parameters by a microorganism’s taxonomy. In addition to the raw database, The Microbe Directory has an online counterpart ( https://microbe.directory/) that provides a user-friendly interface for storage, retrieval, and analysis into which other microbial database projects could be incorporated. The Microbe Directory was primarily designed to serve as a resource for researchers conducting metagenomic analyses, but its online web interface should also prove useful to any individual who wishes to learn more about any particular microbe.

Microbial Strain Engraftment, Persistence and Replacement after Fecal Microbiota Transplantation

“…We additionally generated taxonomic profiles for rarefied data which were subsampled to 5M reads (after QC) per sample (seqtk) before processing with MetaPhlAn2, confirming representativeness of microbial communities as indicated by very strong correlations of Shannon Index (diversity, vegan) between data. For taxonomic analyses we further aggregated functional metadata on bacterial species (Table S5) from (Browne et al, 2016), (Vatanen et al, 2019), List of Prokaryotes according to their Aerotolerant or Obligate Anaerobic Metabolism (OXYTOL 1.3, Mediterranean institute of infection in Marseille), bacDive (Reimer et al, 2019), FusionDB (Zhu et al, 2017), The Microbe Directory v 1.0 (Shaaban et al, 2018), and the expanded Human Oral Microbiome Database (Escapa et al, 2018). Metadata aggregated at the genus-level (Figure 5C) are shaded based on the fraction of detected species of each genus, for which a specific feature annotation could be made.…”

The Impact of Heterogeneity on Single-Cell Sequencing

“…Although stochastic gene expression is a significant contributor to heterogeneity, it is not the only cause. The sub-state of any given genome/cell depends on a number of factors, including epigenetics, alternative splicing sites, post-translational modifications, and sometimes even microbial interactions (Shabaan et al, 2018). These processes are not always stochastic, and can therefore lead to “directed” heterogeneity, instead of the more random “non-directed” heterogeneity of stochastic gene expression (Chang and Marshall, 2017).…”

ADAPTABLE: a comprehensive web platform of antimicrobial peptides tailored to the user’s research

“…ADAPTABLE incorporates automated tools to periodically download, process, and merge data to keep synched with data sources: ADAM (Lee et al, 2015), ANTISTAPHYBASE (Zouhir et al, 2017), APD (Wang & Wang, 2004; Wang et al, 2009; Wang et al, 2016), AVPdb (Qureshi et al, 2014), BaAMPs (Di Luca et al, 2015), BACTIBASE (Hammami et al, 2007, 2010), CAMPR3 (Waghu et al, 2016), CancerPPD (Tyagi et al, 2015), ConoServer (Kaas et al, 2008, 2012), CPPsite (Gautam et al, 2012; Agrawal et al, 2016), DADP (Novković et al, 2012), DBAASP (Gogoladze et al, 2014; Pirtskhalava et al, 2016), Defensins (Seebah et al, 2007), DRAMP (Fan et al, 2016; Kang et al, 2019), Hemolytik (Gautam et al, 2014), HIPdb (Qureshi et al, 2013), InverPep (Gómez et al, 2017), LAMP (Zhao et al, 2013), MilkAMP (Théolier et al, 2014), ParaPep (Mehta et al, 2014), Peptaibol (Whitmore & Wallace, 2004), PhytAMP (Hammami et al, 2009), SATPdb (Singh et al, 2016), UniProt (The UniProt Consortium, 2018), YADAMP (Piotto et al, 2012), PubChem (Kim et al, 2019), The Microbe Directory (Shaaban et al, 2018), and the Protein Data Bank (Berman et al, 2000).…”

“…ADAPTABLE takes the standardization process one step forward, thanks to its inclusion of data from a specialized microbiology database (“The Microbe directory” [Shaaban et al, 2018]). This allows the inclusion of potentially missing information such as the full names of organisms, their nature (i.e., Gram positive or negative bacteria, fungi, or virus, among others), and some of their properties (i.e., ability to form biofilms).…”