Abstract
As the prevalence of antimicrobial resistance genes is increasing in microbes, we are facing the return of the pre-antibiotic era. Consecutively, the number of studies concerning antibiotic resistance and its spread in the environment is rapidly growing. Next generation sequencing technologies are widespread used in many areas of biological research and antibiotic resistance is no exception. For the rapid annotation of whole genome sequencing and metagenomic results considering antibiotic resistance, several tools and data resources were developed. These databases, however, can differ fundamentally in the number and type of genes and resistance determinants they comprise. Furthermore, the annotation structure and metadata stored in these resources can also contribute to their differences. Several previous reviews were published on the tools and databases of resistance gene annotation; however, to our knowledge, no previous review focused solely and in depth on the differences in the databases. In this review, we compare the most well-known and widely used antibiotic resistance gene databases based on their structure and content. We believe that this knowledge is fundamental for selecting the most appropriate database for a research question and for the development of new tools and resources of resistance gene annotation.
Highlights
Antimicrobial resistance (AMR) means an emerging threat on humanity
As the purpose of the database is to form a basis of the antimicrobial resistance genes (ARG) annotation of metagenomic reads that can be used to read abundance based analysis, the annotations are stored in the form of an acyclic graph which avoids that one read or contig is assigned to multiple nodes [27]
Several ARG database were constructed to form the bases of ARG annotation of whole-genome sequencing and metagenomic samples
Summary
2017 report, it is estimated that ~ 700,000 deaths can be attributed to AMR worldwide [1]. The number of tools and databases focusing on AMR has rapidly grown in recent years, and many review articles were published trying to summarize the information on these resources They put more emphasis on the different tools designed for ARG annotation rather than the databases supplying the information for these tasks [18,44,46–48]. The many available resources of ARGs are a blessing, but are a curse as well, as researchers need up-to-date and thorough understanding on them to select the most appropriate one for the task at hand This can be rather cumbersome as each database differs in structure and logic, especially in the way they store the annotation and metadata associated with ARG sequences. We review the structure of each database and we directly compare them by their content We present this comparison from the acquired and mutation based resistance mechanisms separately as databases can significantly differ in these regards. The following six databases are covered in detail only in this review: ARGminer, CARD, MEGARes, NDARO, ResFinder and SARG
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