Explore the Most Comprehensive Set of Acinetobacter baumannii Genomes on Solu

The most diverse A. baumannii dataset is now available in Solu

Our genome analysis platform is now open for anyone to view! To celebrate this feature, we're making the most comprehensive dataset of A. baumannii genomes accessible in a Solu workspace.

Click here to view the genomes on Solu!

This dataset, sourced from the 2020 article A Diverse Panel of Clinical Acinetobacter baumannii for Research and Development by Galac and colleagues, is part of a grand undertaking. Here's how the study went:

• 3,505 A.baumannii isolates were sequenced between 2001 and 2017
• The authors selected a diverse panel of 100 strains based on cgMLST and SNP-based phylogenetic analyses
• The end result represents the genetic diversity of the collection
• Additionally, they performed comprehensive antibiotic susceptibility testing on all 100 isolates using 14 clinically relevant antibiotics.
• Read the entire study here

The authors conclude that this dataset “provides the most diverse and comprehensive set of A. baumannii strains for use in developing solutions for combating antibiotic resistance.”

What you can do with Solu

Here are some examples what you can do with Solu to analyze this dataset.

Species and MLST

Solu identifies all samples as Acinetobacter baumannii and finds 68 different STs (based on PubMLST). The most common sequence types are ST2 (13 samples), ST1 (9 samples), and ST32 (5 samples). Most samples are the only representative of their ST, and even samples within a ST group are genetically different, confirming that the dataset is very diverse.

Read and assembly quality

As this collection contains 100 isolates from around the world, and we don’t have access to the raw reads, we can't run quality analyses for the raw reads. We can assume that different sequencing and library preparations may have been used in the extremely large original dataset.

Solu automatically runs the QUAST genome assembly checking tool. To gauge the assembly quality (which is also a proxy for sequencing and read quality), we can take a look at the results of 10 randomly selected isolates from the set. We've collated some assembly stats into the table below:

While genome sizes are within the expected range, some assemblies clearly have less contiguity than others. This doesn’t need to mean bad quality; but sequencing and assembly quality should always be considered when drawing conclusions from the genomic data.

Download genomes

When you find a genome of interest, you can navigate to the Files tab to download the assembled genome.

Antimicrobial resistance

Overall, this dataset contains a whopping 167 different AMR genes or mutations that Solu Platform finds. Most of them are intrinsic, such as different blaACD subtypes, and a there are an additional 18 efflux and metal resistance genes found in this dataset.

By exporting the samples to Excel, we get an easy-to-analyze version of the resistome. Some gene highlights include:

• Multiple blaOXA families, ESBL variants and blaCTX-M
• 4 isolates with blaNDM
• 1 isolate with blaIMP

Panresistant isolate MRSN17493

According to the original publication, one of the isolates, MRSN17493 was panresistant (to 14 tested drugs) and the only colistin-resistant sample in this dataset. This is what Solu’s AMR result view looks like for MRSN17493:

The authors suspect that a guanine-to-adenine-mutation in in pmrB at position 788 (G788A) would be the reason for colistin resistance. They argue that this leads to a ”substitution of an arginine for a histidine at amino acid 263 (R263H) in the PmrB kinase that has previously been reported as the only mutation present in a colistin-resistant A. baumannii”.

As the prmB_G788A mutation in not featured in the major AMR databases, Solu does not find or report colistin resistance genes for this sample. This highlights the need for continuous updating and curation of antimicrobial resistance gene (ARG) databases. However, we can easily download the genome and perform additional annotation or BLASTing for it to dive deeper.

Pansusceptible isolate MRSN30912

Now let’s look at the opposite end of the resistance spectrum: pansusceptible strains. There were many isolates susceptible to 14 drug classes, and MRSN30912 pictured below is one example.

We see that Solu finds multiple resistance genes for this sample, even though it was phenotypically susceptible. These findings highlight that while phenotypic prediction is, AMR results don’t directly map 1:1 to antibiotic susceptibility testing results. This dataset can be useful for testing hypotheses of phenotypic resistance, or developing more intricate models of resistance.

Explore and download the data

Visit the workspace by clicking this link to go explore this dataset yourself!

We highly encourage feedback, feature ideas, and collaboration with the microbiology community to further explore and analyze the Acinetobacter baumannii genomes. Your input and insights can contribute to a better understanding of this pathogen and aid in the development of solutions against antibiotic resistance. Together, we can make significant strides in combating this global health challenge.

References

Galac MR, Snesrud E, Lebreton F, Stam J, Julius M, Ong AC, Maybank R, Jones AR, Kwak YI, Hinkle K, Waterman PE Lesho EP, Bennett JW, Mc Gann P. 2020. A Diverse Panel of Clinical Acinetobacter baumannii for Research and Development. Antimicrob Agents Chemother 64:10.1128/aac.00840-20. https://doi.org/10.1128/aac.00840-20

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