Tracking down insertion sequences causing polymixin resistance in Acinetobacter baumannii

The first plasmid-borne colistin resistance gene was reported late last year. This was big news, but the vast majority of clinically relevant resistance to colistin and related polymixin drugs, which arises frequently in human patients being treated with these drugs, is due to de novo mutations in chromosomal genes. This has been studied quite a lot recently in Acinetobacter baumannii and Klebsiella pneumoniae, where colistin is frequently used to treat patients who are infected with carbapanem resistant strains that are also resistant to pretty much all the other antibiotics as well.

There have been quite a few studies looking for the causative mutations that underly colistin resistance in Acinetobacter and Klebsiella, by comparing the genomes of resistant and susceptible forms of the ‘same strain’ sequenced with high throughput, short read sequencing platforms like Illumina. The typical approach is to catalogue all the differences between strains and look for SNPs and other differences between them. However colistin resistance is usually associated with upregulating pmr activity via point mutations or inactivating the regulator mgrB, or by inactivating the lpx cluster in Acinetobacter. A very common way for gene inactivation to occur is by an insertion sequence (IS) hopping into the open reading frame and disrupting it. IS insertions can also cause resistance by upregulating the expression of intrinsic efflux pump or beta-lactamase genes, for example the ampC gene in A. baumannii. These insertions can be tricky to find using short read data, and are sometimes missed by regular mapping or assembly based approaches.

Luckily we now have two great tools for tracking down such mutations – ISMapper and Bandage – which were critical to tracking down polymixin resistance mutations in a recent study of A. baumannii with colleagues in Singapore. The paper is published in Antimicrobial Agents and Chemotherapy, but unfortunately is paywalled… so quick summary: basically, our clinical researcher friends in Singapore (hello Li Yang!) had 10 pairs of A. baumannii isolates, consisting of a susceptible parent isolate and a derived polymixin isolate (2 that evolved in vivo during treatment with polymixins, and 8 that evolved in vitro during polymixin exposure).

Simply screening for point mutations and deletions identified causative mutations in pmr and/or lpx clusters for 8/10 genomes, but two remained unexplained. A quick screen of the genome assemblies for IS using ISfinder identified several different IS that were present in the 10 A. baumannii genomes. However as these tend to be multi-copy in the genome, they were mostly separated into their own contigs in the assemblies. Enter ISMapper and Bandage, two open source software packages from Jane Hawkey and Ryan Wick in my lab.

First we used ISMapper to identify the locations of all IS sequences in each genome… this involves passing ISMapper each of the different IS sequences, a reference genome to compare to, and the Illumina read sets for the various strains. The isolates were all from global clones 1 or 2 (GC1, GC2), so to get the best results we used a GC1 reference genome for typing IS in the GC1 strains, and a GC2 reference for the GC2 strains. A quick tabulation of the results reveals all the locations of the various IS in each sequence. This identified differential IS insertions in lpx genes (lpxA, lpxC) in three strain pairs, including one in which no other causative mutations had been identified. There was also an IS15 insertion in the mutS gene in one isolate that had many more SNPs and deletions than the others.

ISMapper results

ISMapper results for GC2 strain pairs, showing IS that differed within susceptible-resistant pairs.

ISMapper results for GC1

ISMapper results for GC1 strain pairs, showing IS that differed within susceptible-resistant pairs.

Cool! But what about that one last pair, where ISMapper didn’t find any differences at all between the resistant and susceptible read sets? This time we turned to Bandage, to inspect the genome assemblies and see if we could find a smoking gun. Now we had a clear hypothesis too – we were looking explicitly for interruptions in lpx genesSo we created new assemblies for these read sets using SPAdes. We loaded the graph of the susceptible isolate in Bandage first, and used the inbuilt BLAST search to locate the lpx genes within the graph – all were intact as expected, sitting happily in the middle of long contigs.

Bandage screenshot

Contig containing the lpxC gene (blue) in SPAdes assembly of the susceptible isolate

Then we loaded the graph of the polymixin resistant isolate in Bandage first, and did the BLAST searches. The pmrB locus was intact, but the lpxC gene was interrupted. Very interrupted! No wonder ISMapper didn’t find this as it’s not an IS insertion at all, but rather the gene is interrupted by a large sequence, in an event that appears to involved the translocation of the entire genomic resistance island AbaR4 into the middle of the lpxC open reading frame.

Bandage screenshot

Interruption of lpxC associated with movement of the antibiotic resistance related genomic island, AbaR

The above image is created by doing BLAST searches (within Bandage) for the lpxC gene, AbaR4 gene and ISAba1 gene like this…

Bandage Screen Shot

BLAST search within an assembly graph using Bandage

…and then selecting ‘BLAST hits (solid)’ under the ‘Graph display’ settings on the left hand side of the Bandage viewer.

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Oh and just in case you think this is a weird one-off event that maybe you don’t need to worry about in your own genome data… check out the recent report from Scott Beaston and David Paterson in Queensland, who sequenced a nasty Klebsiella strain that was resistant to everything under the sun including carbapenems and colistin. They sequenced the genome with PacBio, and found the ISEcp1blaOXA-181 mobile element (which confers resistance to carbapenems) inserted into the mgrB regulatory gene in the chromosome, whose inactivation is responsible for colistin resistance. Oh and they also found another mobile element, ISEcp1blaCTX-M-15, inserted into the gene ompK35. Guess what inactivating this gene gives you? Cephalosporin resistance.


SEE ALSO: this post on using ISMapper and Bandage to track down multidrug resistance in Salmonella Typhi, the causative agent of typhoid

Population genomics of Klebsiella

Well, after almost 6 years, our Klebsiella pneumoniae genomics paper is finally out!

It’s a beast of a thing and there are still a million and one questions to address just from this one data set. For those interested in looking at the data for themselves, the raw reads are available under accession ERP000165, the assemblies are in Sylvain Brisse’s Klebsiella pneumoniae BIGSdb at the Pasteur Institute, and the tree + metadata are available for your interactive viewing pleasure in MicroReact.

The paper itself is open access in PNAS, you can read it here.

Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health

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Whole genome diversity in K. pneumoniae

There have been lots of really nice Klebs genomics papers out in the last 18 months or so, examining the evolution of the ST258 clone that carries the KPC gene (K. pneumoniae carbapaenemase) and is wreaking havoc in hospitals all over the place (including recently in Melbourne), and also several hospital-based studies tracking transmission and evolution of local drug-resistant outbreaks.

But that is just the tip of the K. pneumoniae iceberg.

Our paper asks a completely different set of questions, which you could basically sum up as “what the hell is Klebsiella pneumoniae anyway?”

To do this, we sequenced ~300 genomes of really diverse K. pneumoniae strains. We didn’t have much information about genetic diversity to go on, so we chose strains with different phenotypes (antimicrobial resistance patterns, capsular serotypes or sequence types where known), from different sources (human and animal, asymptomatic carriage and infections of various kinds), and from different geographical locations.

This was done by an international group of collaborators who pooled their resources, not only sharing their precious strain collections but also digging through hospital and other records to find as much information about the strains as possible.

You can view the tree and associated metadata, including geographical origin and source information, over on Microreact.Screen Shot 2015-06-18 at 4.09.33 pm

We found out some pretty interesting things about Klebsiella pneumoniae, including the fact that what’s identified as K. pneumoniae using standard tests is actually a mixed bag of three related species, that now have their own names: K. pneumoniae (KpI group, which includes the majority of clinical isolates and all the stuff you might have heard of like the clone that causes rhinoscleromatis, and the KPC clone ST258, and the hypervirulent clone ST23); K. quasipneumoniae; and K. variicola (plant associated and usually nitrogen-fixing).

By now, this species stuff has been nutted out (mainly by co-author Sylvain Brisse from Institut Pasteur) by analysing marker gene sequences, but it’s really important to be able to show that those patterns hold at the whole-genome level, and we found some interesting things about the distribution of the rarer species (see the paper for details).


Importantly, we did the whole pan-genome analysis thing and found that as a population, K. pneumoniae has more genes than humans. Almost 30,000 in fact. Each individual strain has ~5,500 genes, but <2,000 of those are core genes that are common to all K. pneumoniae. The rest are accessory genes that can come and go, helping the bug to adapt to new environments.


One of the cool things we were able to do with our data set, which you just can’t do with genomic studies focused on specific clones or outbreaks, was to look at statistical associations between accessory genes and phenotypes. Admittedly our available phenotypes were pretty limited, but we found a few important things.


We screened for genes associated with virulence in humans by focusing in on invasive infections, and comparing gene frequencies in human isolates from invasive community-acquired infections (i.e. the kind of infections that land you in hospital) vs. those in human carriage isolates or hospital acquired infections (i.e. the kind of infections that get you when you are already in hospital for something else and are particularly vulnerable to infection).

The only genes that were significantly associated with invasive infection in humans were rmpA and rmpA2, which upregulate capsule production, and genes related to iron acquisition (specifically acquired siderophore systems that can help to steal iron from animal hosts – see paper for details). These genes have been known about for some time, based on mouse models and knowledge of other pathogens, however we were able to show that these genes are significantly associated with invasive K. pneumoniae disease in humans, which is not something that can be proven directly using experimental systems. (The siderophore story actually goes a bit deeper than the iron issue… it’s a bit too complex to go into here but I recommend reading Michael Bachman’s work e.g. “Interaction of lipocalin 2, transferrin, and siderophores determines the replicative niche of Klebsiella pneumoniae during pneumonia” in MBio, 2012).


Interestingly, doing the same test in bovine isolates showed that the story is very different: we had a lot of isolates from dairy herds, including clinical and subclinical mastitis; asymptomatic carriage isolates and strains from the farm environment… and found that an acquired lactose operon was almost perfectly associated with mastitis in cows! Something similar has been observed before in Streptococcus agalactiae.


Resistance genes were associated with human hospital isolates and human carriage isolates. This is far from an ideal study design to test this, as we had different types of collections from different geographical regions; however, even when you look within different local collections you see the same patterns: (a) comparing bovine and human isolates from NY state, the resistance genes were all in human isolates not cow isolates; (b) comparing human carriage and infection isolates (both nosocomial and community acquired) in Vietnam, the resistance genes were mainly in human carriage and hospital isolates, not in community infections; (c) in the remaining countries, isolates from infections acquired in hospital had more resistance genes than those that were considered nosocomial (diagnosed within 48 hours of admission).

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What’s really interesting is that while resistance genes and virulence genes are both highly mobile components of the accessory genome, they were essentially orthogonal in their distribution. The resistance genes were mainly in hospital acquired infections and carriage isolates, whereas the virulence strains were mainly found in isolates from community acquired infections.

resistance-virulence-axis-2So far, this has resulted in the emergence of two very different kinds of K. pneumoniae clones of importance to human health: hypervirulent clones, and multidrug resistant clones. This is pretty lucky, as it means the hypervirulent clones are generally sensitive to antibiotics (although antimicrobial treatment is difficult for some conditions, like liver abscess), and the problem of untreatable highly drug resistant Klebs infections has not spread outside of hospitals.

Unfortunately, our luck appears to be runnning out and we are already starting to see the convergence of virulence and resistance. Hypervirulent ST23 strains, which have all four of the acquired siderophore systems, are accumulating antibiotic resistance genes. And about half of the KPC Klebs ST258 strains causing problems in hospitals globally have one of the siderophore gene clusters, yersiniabactin, which has been shown in clinical ST258 isolates to confer enhanced ability to cause pneumonia. How long till the other virulence genes creep in? We need to be watching!

Also, our data indicates that there are plenty of other hypervirulent or multidrug resistant Klebs clones emerging out there… convergence of virulence and resistance could happen in any one of them, so we need to be thinking and monitoring beyond the well-known ST23 and ST258 strains.

In any case, genomic surveillance is going to become really important for Klebsiella