Lineage calling can identify antibiotic resistan t clones ...An example is given by the pneumococcus...
Transcript of Lineage calling can identify antibiotic resistan t clones ...An example is given by the pneumococcus...
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Lineage calling can identify antibiotic resistant clones within minutes
Karel Břinda1,2, Alanna Callendrello1, Lauren Cowley1, Themoula Charalampous3, Robyn S Lee1,
Derek R MacFadden1,4, Gregory Kucherov5,6, Justin O’Grady7,3, Michael Baym2,8, and William P
Hanage1
1 Center for Communicable Disease Dynamic, Department of Epidemiology, Harvard T.H. Chan School of Public
Health, Boston, USA
2 Department of Biomedical Informatics, Harvard Medical School, Boston, USA
3 University of East Anglia, Norwich Research Park, Norwich, UK
4 Division of Infectious Diseases, Department of Medicine, University of Toronto, Canada
5 CNRS/LIGM Université Paris-Est, Marne-la-Vallée, France
6 Skolkovo Institute of Science and Technology, Moscow, Russia
7 Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
8 Laboratory of Systems Pharmacology, Harvard Medical School, Boston, USA
Correspondence to [email protected]
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Introductory Paragraph
Surveillance of circulating drug resistant bacteria is essential for healthcare providers to deliver
effective empiric antibiotic therapy. However, the results of surveillance may not be available
on a timescale that is optimal for guiding patient treatment. Here we present a method for
inferring characteristics of an unknown bacterial sample by identifying the presence of
sequence variation across the genome that is linked to a phenotype of interest, in this case drug
resistance. We demonstrate an implementation of this principle using sequence k-mer content,
matched to a database of known genomes. We show this technique can be applied to data
from an Oxford Nanopore device in real time and is capable of identifying the presence of a
known resistant strain in 5 minutes, even from a complex metagenomic sample. This flexible
approach has wide application to pathogen surveillance and may be used to greatly accelerate
diagnoses of resistant infections.
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Introduction
Antibiotic-resistant infections pose multiple challenges to healthcare systems, contributing to
higher mortality, morbidity, and escalating cost. Clinicians must regularly make rapid decisions
on empiric antibiotic treatment without knowing if a patient’s clinical syndrome is due to a drug
resistant organism. In some cases, this is directly linked to poor outcomes; in the case of septic
shock, the risk of death increases by an estimated 10% with every 60 minutes delay in initiating
effective treatment1.
Hence, there is interest in developing rapid, point-of-care techniques to detect the presence of
a resistant strain in a sample, for diagnostics and surveillance purposes. The continuing
development of sequencing technologies suggests that genomic data are particularly promising
for this purpose2. In principle, if a resistance gene or mutation can be detected in a sample, this
could be sufficient to inform treatment decisions. However for this to be applicable in practice,
several conditions must be satisfied: foremost, the resistance determinant must be already
identified, it must be sufficiently different from susceptible variants, and the genomic context
must be known, as loci with homology to known resistance determinants are also found in non-
pathogens3. Furthermore, to make diagnosis truly point-of-care, one must sequence as directly
as possible from clinical samples, without time-consuming culture steps. This implies a
metagenomic sample containing sequences from many different taxa, and so the genomic
context of the resistance locus may be obscured if we use short read technologies for
sequencing. An ideal approach would not depend on access to expensive, sophisticated
sequencing equipment, making it deployable close to the point of care and in resource-poor
settings.
The clinical question of whether an antibiotic is likely to work, i.e. the pathogen is susceptible, is
not equivalent to identifying whether a pathogen carries those mutations or genes that are
known to confer resistance. Prescription has long been informed by correlative features when
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causative ones are difficult to measure, for example whether the same syndrome (or ideally
pathogen) occurring in other patients from the same clinical environment have responded (or
were susceptible to) to a particular antibiotic. This also has been observed at the genetic level
as well, as a result of genetic linkage between resistance elements and the rest of the genome.
An example is given by the pneumococcus (Streptococcus pneumoniae), a major pathogen,
responsible for approximately 1.6 million deaths per year. The Centers for Disease Control have
rated the threat level of drug resistant pneumococcus as ‘serious’ 4. While resistance arises in
pneumococci through a variety of mechanisms and genes, approximately 90% of the variance in
the minimal inhibitory concentration (MIC) for multiple antibiotics of different classes, could be
explained by the loci determining the strain type alone5. This is particularly interesting, as none
of the loci used for strain classification themselves causes resistance. Thus, in the overwhelming
majority of cases, resistance can be accurately predicted from coarse strain typing based on
population structure.
This population structure can be leveraged to offer an alternative approach to detecting
resistance in which rather than detecting high-risk genes, we identify high-risk lineages. The
additional information available from genomic data allows a better definition of those closely
related parts of the population associated with resistance or susceptibility, which we call
‘phylogroups’. High-risk phylogroups can be readily determined by analysis of existing high-
quality draft genome assemblies, together with suitable metadata on MICs. Thus, given
sufficient correlation between the phylogroup and phenotype of interest (for example drug
resistance), rapid identification of the phylogroup alone can be sufficient for diagnostic
purposes.
An attractive option for this approach is to use long-read sequencing, such as nanopore
technology (Oxford Nanopore Technology (ONT)), given its additional correlative structure.
Although the ONT MinION device has a high (~10%) per base error rate6, it is also highly
portable and deployable in field conditions7. Furthermore, sequencing reads are streamed the
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computer as they are produced, so the results can be analyzed and reported in real time.
Recently, nanopore sequencing has been shown to provide rapid re-identification of human
samples within minutes8, predict antibiotic resistance of pathogens within hours9–14, or predict
sequence types of bacterial isolates within an hour15.
Here we present a method to match data from bacterial isolate sequencing and clinical
metagenomics against a genomic database of known isolates for which resistance has already
been determined, and predict antibiotic resistance based on the resistance profiles of the
matches. We demonstrate, using the example of pneumococcus and five antibiotics
(benzylpenicillin, ceftriaxone, trimethoprim-sulfamethoxazole, erythromycin, and tetracycline),
that we can identify known resistant clones, and their serotype, on a standard laptop within 5
minutes even from metagenomic data. Moreover, our solution is suitable for applications in
resource-poor contexts, making it not only useful for diagnosing infections, but also for
enhancing surveillance.
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Results
A database of resistance-associated sequence elements
To predict resistance in isolates and clinical samples we built a database of Resistance
Associated Sequence Elements (RASE). We generated a k-mer-based representation of lineages
for use to predict resistance by approximate matching. Following an analysis of the S.
pneumoniae genome and characteristics of nanopore reads, we set k-mer length to 18 (see
Methods). Our method depends on the initial availability of good quality data, and so we used
genomes of pneumococci sampled from a carriage study in Massachusetts children16,17 as the
main reference dataset; it consists of 616 carriage samples isolated from Massachusetts
children and comprises resistance data together with high quality draft genome assemblies
from Illumina HiSeq reads. These isolates have already been classified using Multi-Locus
Sequence Typing18,19 (MLST), which is the current ‘gold standard’ for defining clones and clonal
complexes used by the Pneumococcal Molecular Epidemiology Network20 (PMEN).
Based on the measured MICs, we assigned each isolate to an antibiotic-specific resistance
category using standard breakpoints (see Methods). Where data on MICs were not available,
we estimated the likely resistance phenotype of an isolate using ancestral state reconstruction
(see Methods). This was the case for a total of 494 records, concentrated in the data for
tetracycline (291 records) and ceftriaxone (176 records) susceptibility. A further advantage of
the dataset we chose was that we had access to the original isolates, and so additional
resistance testing was possible; in our subsequent experiments, if original MIC data were not
available for the best match in the RASE database, the relevant isolate was tested to confirm
resistance phenotype (see Methods). In all of 8 cases tested, ancestral state reconstruction
provided the correct resistance phenotype (shown in bold in Table 1). Out of all 616 isolates,
341 were associated with susceptibility to benzylpenicillin, 485 to ceftriaxone, 480 to
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trimethoprim-sulfamethoxazole, 484 to erythromycin, and 551 to tetracycline (Supplementary
Tables 1 and 2).
The constructed database occupies 320 MB RAM (4.3× compression rate) and can be further
compressed to 47 MB (29× compression rate) (Supplementary Figure 1). The RASE database
can be therefore used on portable devices and easily transmitted to the point of care over links
with a limited bandwidth.
Lineage calling using inexact matching
We developed an approach that we term ‘lineage calling’ (Figure 1) to match a nanopore read
to the phylogroup from which it came – where, as described above, phylogroup is a clade
associated with either resistance or susceptibility. We then used a modified version of
ProPhyle21, an accurate, resource-frugal and deterministic phylogeny-based DNA classification
tool based on the Burrows-Wheeler Transform22, to assign nanopore reads to positions on
phylogenetic trees and identify the closest match. Reads were assigned scores based on their
similarity to known sequences in the database. Generally speaking, longer reads, such as those
covering multiple accessory genes, tend to be specific and have high scores; whereas short
reads from the core genome, tend to be non-specific and have low scores, being found in many
genomes. Cumulative scores, which we call weights, are then used to measure how similar a
sample is to known genomes associated with resistance, already in the database. We compute
two metrics: the ‘phylogroup score’ and the ‘susceptibility score’ (described in more detail in
methods). These are ratios comparing the weights of the best match in the database, with the
weight of the next best match of a different phylogroup or susceptibility category respectively.
Intuitively the scores measure the confidence with which a sample is assigned to a given
phylogroup and quantify the risk of resistance based on the matching samples in the RASE
database.
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Results of prediction are reported in real time as the best matching genomes in the database,
together with the phylogroup score and the susceptibility scores to the antibiotics being tested
(examples shown in Figures 2 and 3). As the run progresses, these scores fluctuate and
eventually stabilize.
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Testing isolates present in the RASE database
We examined two isolates that were used to build the RASE database (SP01 and SP02 in Table
1A). They were selected to test whether we can correctly assign phylogroup even under the
best circumstances, given the relatively high error rate of nanopore sequencing6. The profile
obtained from the fully susceptible isolate is shown in Figure 2. Due to errors in the nanopore
sequence, only 20% of the bases matched k-mers in the RASE database – yet despite this, the
correct phylogroup was assigned within 1 minute. The best match stabilized within 7 minutes,
and this matched the isolate used in the test. The second tested isolate was predicted even
faster, with phylogroup and best match correctly detected and stabilized within 1 minute.
These experiments provide a proof of principle that lineage calling can be accurate and fast
even using sequence data with a relatively high per base error rate.
We also evaluated how long it took for resistance genes to be reliably detected in nanopore
reads. For SP02 we observed that at least 15 minutes was needed to detect resistance,
assuming that the genes in question can be unambiguously identified in nanopore data despite
the high per base error rate, and that the presence of the loci is directly linked to the resistance
phenotype (Supplementary Figure 2). If this is not the case, further delays would be expected.
Thus, lineage calling can offer a time advantage compared to methods based on identifying the
presence of resistance genes even in a sample of DNA from a purified isolate as opposed to a
metagenome, potentially allowing for more rapid changes to antimicrobial therapy.
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Testing isolates not present in the RASE database
We then examined four additional isolates (SP03–SP06 in Table 1A) for which the serotype and
limited antibiogram data were known, but the lineage was unknown. To identify the lineages of
these isolates we sequenced them by Illumina Miniseq, and confirmed the antibiogram of the
antibiotics being tested in this study. We compared three characteristics of the sample to
assess our performance: the serotype, the sequence type (ST) and the antibiograms
(benzylpenicillin, ceftriaxone, trimethoprim-sulfamethoxazole, erythromycin, and tetracycline
resistance according to EUCAST breakpoints23). Multi-locus Sequence Typing18 (MLST) is the
gold standard for strain assignment and divides the pathogen population into clonal complexes
(equivalent to lineages).
In all cases, the correct clonal complex was identified within five minutes, even if the correct ST
was absent from the RASE database, indicating the strength of the lineage calling method in
rapidly detecting similarity. However, this also illustrates the importance of a high quality and
suitable database for comparison, which contains the clones that are likely to be encountered
in disease. The two 23F samples (SP03 and SP06) were correctly called as being closely related
to the Tennessee 23F-4 clone identified by PMEN, a clone strongly associated with macrolide
resistance20. Consistent with this, the two samples were indeed resistant to erythromycin, as
was the closest match in the RASE database constructed from the Massachusetts sample. In the
case of SP05, the phylogroup score was borderline, reflecting divergence of the sample
undertest from the database, even though the susceptibility scores were accurate for the
antibiotics tested.
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Metagenomic sample testing
Because culture introduces significant delays, direct metagenomic sequencing of clinical
samples would be preferable. We therefore analyzed nanopore metagenomics data from
sputum samples obtained from patients suffering from lower respiratory tract infections2,
selecting 6 samples from the study that were already known to contain Streptococcus
pneumoniae (Table 1B, sorted by the estimated proportion of S. pneumoniae reads).
The sample displayed in Figure 3 (SP10) contains DNA from multiple bacterial species, and as a
result, few of the reads match to the k-mers in the RASE database (7% in contrast with 20% for
the sample used for proof of principle above). However, the sample was still inferred, again
within 5 minutes, to contain DNA identified as belonging to the Swedish 15A-25 clone (ST63)
which is also known to be associated with resistance phenotypes including macrolides and
tetracyclines24. This sample was confirmed to be resistant to the erythromycin, as well as
clindamycin, tetracycline and oxacillin2 according to EUCAST23. The result for oxacillin is
especially noteworthy, as the initial report of this clone did not report resistance to penicillin
antibiotics24. However, resistance to this class has subsequently emerged in this lineage, and so
the database used in this work correctly identified the risk of penicillin resistance in this sample.
The metagenomes SP11 and SP12 contain an estimated >20% reads that matched to S.
pneumoniae, and their serotypes were identified to be 15A and 3, respectively. The
susceptibility scores of the best matches were fully consistent with the susceptibility profiles
found in the samples, with the exception of tetracycline resistance of SP12. Further analysis of
the reads from SP12 using Krocus15 suggested that the pneumococcal DNA present was from
the ST180 clonal complex, and matched specifically either to the sequence type ST180 or
ST3798. This is consistent with identification as serotype 3, because this clonal complex
contains the great majority of isolates with this capsule type, which historically has not been
associated with resistance25. However, improved sampling and study of this lineage has
recently found highly divergent subclades that are associated with resistance. These lineages
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were previously rare, and thus were less likely to be included in our database, but now are
increasing in frequency26. In this case, ST 3798 is found to be in clade 1B, which is notable for
exhibiting sporadic tetracycline resistance. Again, the failure to match to this is a result of the
original database not containing a suitable example for comparison.
The last remaining samples, SP07–SP09, contained less than 5% unambiguously pneumococcal
reads, and as a result the phylogroup was not securely identified in these. Nevertheless, all
predicted phenotypes were concordant with phenotypic tests, with the exception of SP07
which matches the same isolate as SP12 (discussed above).
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Discussion
Effective methods for detecting resistance, or susceptibility from gene sequences do not need
to perform GWAS in reverse – using lineage calling, there is no requirement to detect the
variation that causes the phenotype, only that it be sufficiently strongly associated with the
phenotype to make reliable predictions. The results presented here show that if an identical
genome is present in the database, ProPhyle accurately matches it in 5 minutes and accurately
predicts resistance/susceptibility, and if the genome is not present the closest relative is
identified within a similar time span. Moreover, ProPhyle can be used successfully with
metagenomic data, here identifying the presence of the Sweden 15A-23 clone in a sputum
sample taken from a patient with lower respiratory tract infection in the UK. Together, these
results suggest that we can achieve robust lineage calling, even from complex data, within
minutes of nanopore sequencing.
A key advantage of this approach is that it is not limited by the relatively high error rate of
nanopore sequencing; it is not attempting to define the exact genome sequence of the sample
being tested, but merely which lineage it comes from. As a result, even when a small fraction of
k-mers in the read are informative in matching to the RASE database, this is sufficient to call the
lineage. This has the benefit of being faster than gene detection by virtue of the informative k-
mers being distributed throughout the genome, and so more likely to appear in the first few
reads sequenced by the nanopore. Therefore, the approach we present here can be seen as an
application of compressed sensing: by measuring a sparse signal distributed broadly across our
data we can identify it with comparatively few error-tolerant measurements.
Lineage calling has several advantages over methods that aim to detect the presence of the
specific sequences that confer resistance. Most importantly, we can identify clones that are
associated with susceptibility as well as resistance. The relevant loci need not be known in
advance, and because we are seeking to identify the lineage rather than the loci, it is much
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quicker. In our experiments it consistently took longer for a single copy of a resistance gene of
interest to pass through the pore and be identified than to identify the lineage. This is
particularly important when detecting mutational resistance that requires high genome
coverage (>30x). Finally, when resistance is plasmid-borne, identifying the lineage may be more
reliable at predicting susceptibility/resistance by lineage calling in metagenomic data, as the
source organism of plasmids in a metagenome is hard to identify.
These results suggest a two-step model for resistance diagnostics, in which the first is to
characterize the important pathogens in the population with highly accurate, high quality draft
genomes together with metadata on resistance or other phenotypes of interest, and then to
analyze clinical samples directly using nanopore-based metagenomics and the RASE software.
The importance of a high quality and representative database is shown by the failure to
accurately call erythromycin resistance for SP03 and SP06; the closest match to these two in the
RASE database was relatively distantly related to them and had diverged in its antibiogram.
Given the value and importance of an appropriate database, which is evident from our results,
it is notable that health laboratories are increasingly collecting datasets suitable for use with
RASE. The US Centers for Disease Control and Prevention have started using WGS to
characterize samples from their Active Bacterial Core Surveillance system, which obtains
isolates and MIC data from all isolates of S. pneumoniae causing invasive disease in a
population of more than 23 million. As a result of this initiative, raw reads and resistance data
for 1781 isolates collected from 2015 already exists27,28. While it is unlikely that a random
patient presenting with disease would be infected by a lineage not present in this sample, it is
possible. In the event that the sequenced isolate belongs to a clade that is absent from the
database or the confidence in cluster assignment to the studied species is not sufficiently
strong, RASE reports comparable similarity for multiple different phylogroups and the
phylogroup score drops accordingly (see experiments SP05 and SP07–SP09 in supplementary
online material). This will allow attention to rapidly be concentrated on any examples of
bacteria that are not present in the database. If we are to move away from culture towards
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metagenomic-based infection diagnosis in future, this feature of RASE will be extremely
valuable, pointing us toward clinical samples containing unusual lineages that can be cultured
and characterized.
A more serious issue, which we have not encountered in this study, but which may limit the
application of our approach to other pathogen-drug combinations, is the degree of linkage
between resistance and a specific lineage. If this is low, such that there is very weak association
between lineage and resistance phenotype, then we would not expect our approach to work.
This is particularly the case if resistance can arise from a single mutation during the course of
treatment (e.g., porin mutations which confer diminished susceptibility to carbapenems27).
Such an eventuality would not be detectable by any sequence-based method, but we note this
would also mislead conventional gold standard susceptibility testing if the mutation has not
already arisen at time of sample collection. In the case of the pneumococcus the degree of
linkage between resistance and the rest of the genome is high, as shown by the success of
ancestral state reconstruction in inferring the resistance status of isolates for which MIC data
were not originally reported. This suggests that perfect resistance data for all isolates may not
be necessary in all circumstances, however this will require further work to fully define, as will
how the RASE approach scales with increasing database size.
Another limitation of this approach for point-of-care use is the complexity and time required for
sample preparation, which currently includes human DNA depletion, DNA isolation and library
preparation, taking a total of 4 hours. However, we note that ONT Voltrax technology can be
used for automated library preparation and, potentially in the future, host depletion and DNA
extraction. Automation will simplify and speed up the sample preparation turnaround time. It
should be noted that this has been further reduced, with a Rapid Sequencing Kit offering library
preparation in 10 minutes29. Further advances in this space, including reduced costs, will be
required to bring the method closer to the bedside. For instance, the ONT Flongle flowcell
($100 as of August 2018) may help to address this issue.
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The benefits of lineage calling are in identifying high-risk clones earlier. It is easy to see how our
approach may be extended to include calling specific resistance loci, where they are known, but
a key advantage of our approach is that it is not limited by the requirement to know them in
advance. Lineage calling can be used to detect any phenotype that is sufficiently tightly linked
to a phylogeny, for instance to identify highly virulent strains that might merit closer attention.
Further applications may include rapid outbreak investigations, as the closely related isolates
involved in the outbreak will all be predicted to match to the same strain in the RASE database.
The approach also lends itself to enhanced surveillance, including field work situations; the
recent Ebola outbreak in West Africa, for example, saw MinION devices used in remote
locations without centralized and advance healthcare facilities. Finally, this approach is not at
present intended to supplant empiric therapies. Given the urgency of instituting appropriate
therapies, prescriptions should be made as early as possible. However, we may be able,
through lineage calling of samples taken when the tentative diagnosis is made, to institute
effective therapy at the second dose when the initial therapy is inadequate, long before it
would become clinically apparent the patient is not responding. The combination of high
quality RASE databases with lineage calling hence offers an alternative model for diagnostics
and surveillance, with wide applications for the management of infectious disease.
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Methods
Overview
RASE uses rapid approximate k-mer-based matching of long sequencing reads against a
database of genomes to predict resistance via lineage calling, using two key components: a
database containing genomic data and associated antibiograms, and a prediction pipeline. The
database contains a highly compressed lossless k-mer index, a representation of the tree
population structure, and metadata such as a phylogroup, serotype, sequence type and
resistance profiles (see ‘Resistance profiles’). The pipeline iterates over reads from the
nanopore sequencer and provides real-time predictions of phylogroup and resistance
(Figure 1).
Resistance profiles
For all antibiotics, RASE associates individual isolates with a resistance category, susceptible or
non-susceptible. First, MIC values are mined using regular expressions from the available
textual antibiograms, i.e., strings describing an interval of possible MIC values. Second, the
acquired intervals are compared to the antibiotic-specific breakpoints (Supplementary
Figure 3). If a given breakpoint is above or below the interval, susceptibility or non-
susceptibility is reported, respectively. However, no category can be assigned at this step if the
breakpoint lies within the extracted interval, an antibiogram is entirely missing, or an
antibiogram is present, but parsing failed. Third, missing categories are inferred using ancestral
state reconstruction on the associated phylogenetic tree while maximizing parsimony (i.e.,
minimizing the number of nodes switching its resistance category) breakpoints (Supplementary
Figure 4). When the solution is not unique, non-susceptibility is assigned.
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The RASE database was constructed with the standard EUCAST breakpoints23 ([g/ml]):
benzylpenicillin (PEN): 0.06, ceftriaxone (CRO): 0.25, trimethoprim-sulfamethoxazole (TMP):
1.00, Erythromycin (ERY): 0.25, and Tetracycline (TET): 1.00. While we have used the above
values in the present work, others may be readily defined and the database rapidly updated.
This is especially useful in the case where breakpoints may vary depending on the site of
infection (as is the case with pneumococcal meningitis and otitis media, where lower MICs are
considered to be resistant23).
K-mer-based matching
RASE uses the ProPhyle classifier21 (version 0.3.1.0) and its ProPhex component30 to identify the
most similar genomes in the database for every sequencing read. Its index stores k-mers of all
isolates’ assemblies in a highly compressed form, reducing the required memory footprint. The
database k-mers are first propagated along the phylogenetic tree and then greedily assembled
to contigs. The obtained contigs are then placed into a single text file, for which a BWT-index31
is constructed. The index can be searched for individual k-mers, retrieving a list of nodes whose
descending leaves correspond to isolates containing that k-mers.
In course of sequencing, every read is matched against the index and matches for all read’s k-
mers retrieved. These matches are then propagated to the level of leaves and isolates with the
highest number of shared k-mers identified.
Predicting resistance from phylogroups
All isolates in the database are associated with similarity weights that are set to zero at the start
of the run. Each time a new read is matched against the DB, the weights for the best match are
increased according to the read’s ‘information content’, calculated as the number of shared k-
mers between a genome and the read, divided by the number of best hits.
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Predictions are calculated based on the current state of the weights and the lineage or
phylogroup in which the best-matched isolate is found. First, a phylogroup is predicted as the
phylogroup of the best matching isolate. Then, a phylogroup score is calculated PGS=2f/(f+t)-1,
where f and t denote the scores of the best matches in the first (‘predicted’) and second best
(‘alternative’) phylogroup respectively. If PGS is higher than a specified threshold (0.6 in default
settings), the call is considered successful. If the score is lower than this, the read cannot be
securely assigned to a phylogroup, and this counts as a failure. Reads that do not match are not
used in subsequent analysis to predict resistance.
Resistance is predicted for individual antibiotics independently, using weights within the
predicted phylogroup. While certain phylogroups are certainly associated with susceptibility,
some others are not. For the latter, we propose the use of the susceptibility scores that
combine the resistance characteristics of the most similar strains in the RASE database. A
susceptibility score is calculated as SUS=s/(s+r), where s and r denote the score of the best
susceptible and non-susceptible strains within the predicted phylogroup. If SUS is greater than a
specified threshold (0.6 in default settings), susceptibility to the antibiotic is reported, non-
susceptibility otherwise. In most of cases, this algorithm predicts non-susceptibility or
susceptibility as the one of the best match. Nevertheless, when two genomes with different
resistance categories are of similar weights, non-susceptibility may be reported even though
the best match is susceptible.
To determine how RASE works with nanopore data generated in real time, the timestamps of
individual reads were first extracted and then used for sorting the base-called nanopore reads.
When the RASE pipeline was applied, the timestamps were used for expressing the predictions
as a function of time. The times of ProPhyle assignments were also compared to the original
timestamps to ensure that the prediction pipeline was not slower than sequencing.
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Optimizing k-mer length
First, the subword complexity function32 of pneumococcus was calculated using JellyFish33
(version 2.2.10) (Supplementary Figure 5). Then, based on the characteristics of the function
and technical limitations of ProPhyle, the possible range of k was determined as [17, 32]. For
these k-mer lengths, RASE indexes were constructed and their performance evaluated using the
RASE prediction pipeline and selected experiments. All these lengths k-mer lengths led to
similar predictions, but different prediction delays (Supplementary Figure 6). Based on the
obtained timing data, we set k to 18.
Lower time bounds on resistance gene detection
A complete genome assembly of the multidrug resistant SP02 isolate was computed from the
Nanopore reads using the CANU34 (version 1.5, with default parameters). Prior to the assembly
step, reads were filtered using SAMsift35 based on the matching quality with the RASE
database: only reads at least 1000bp long with at least 10% 18-mers shared with some of the
reference draft assemblies were used. The obtained assembly was further corrected by Pilon36
(version 1.2, default parameters) using Illumina reads from the same isolate (taxid ‘1QJAP’ in
the SPARC dataset17) mapped to the nanopore assembly using BWA-MEM37 (version 0.7.17,
with the default parameters) and sorted using SAMtools38.
The obtained assembly was searched for resistance-causing genes using the online CARD tool39
(as of 2018/08/01). All of the original nanopore reads were then mapped using Minimap240
(version 2.11, with ‘-x map-ont’) to the corrected assembly and resistance genes in the reads
identified using BEDtools–intersect41 (version 2.27.1, with ‘-F 95’). Timestamps of the
resistance-informative reads were extracted and associated with the genes. Only reads longer
than 2kbp were used in the analysis.
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21
Library preparation
For experiments SP01-SP06, cultures were grown in Todd–Hewitt medium with 0.5% yeast
extract (THY; Becton Dickinson and Company, Sparks, MD) at 37°C in 5% CO2 for 24 hrs. High
molecular weight (>1ug) genomic DNA was extracted and purified from cultures using DNeasy
Blood and Tissue kit (QIAGEN, Valencia CA). DNA concentration was measured using Qubit
fluorometer (Invitrogen, Grand Island NY). Library preparation was performed using the Oxford
Nanopore Technologies 1D ligation sequencing kit SQK LSK108.
For experiments SP07-SP12, library preparation was performed using the ONT Rapid Low-Input
Barcoding kit SQK-RLB001, with saponin-based host DNA depletion used for reducing the
proportion of human reads. More details can be found in the original manuscript2.
MinION sequencing
Sequencing was performed on the MinION MK1 device using R9.4/FLO-MIN106 flowcells,
according to the manufacturer’s instructions. For experiments SP01-SP06, base-calling was
performed using ONT Metrichor (versions 1.6.11 (SP01), 1.7.3 (SP02), 1.7.14 (SP03–SP06))
simultaneously with sequencing and all reads passing Metrichor quality check were used in the
further analysis. For experiments SP07-SP09, ONT MinKNOW software (versions 1.4-1.13.1) was
used to collect raw sequencing data and ONT Albacore (versions 1.2.2-2.1.10) was used for local
base-calling of the raw data after sequencing runs were completed.
Testing resistance phenotype
Additional retesting of SPARC isolates was done using microdilution. Organism suspensions
were prepared from overnight growth on blood agar plates to the density of a 0.5 McFarland
standard. This organism suspension was then diluted to provide a final inoculum of 105 to 106
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CFU/ml. Microdilution trays were prepared according to the NCCLS methodology with cation-
adjusted Mueller-Hinton broth (Sigma-Aldrich) supplemented with 5% lysed horse blood
(Hemostat Laboratories)42,43. Penicillin (TRC Canada) and chloramphenicol (USB) concentrations
ranged from 0.016 to 16 μg/ml. Erythromycin (Enzo Life Sciences), tetracycline (Sigma-Aldrich),
and trimethoprim-sulfamethoxazole (MP Biomedicals) concentrations ranged from 0.0625 to 64
μg/ml. Ceftriaxone (Sigma-Aldrich) concentrations ranged from 0.007 to 8 μg/ml. The
microdilution trays were incubated in ambient air at 35°C for 24 h. The MICs were then visually
read and breakpoints applied. A list of individual microdilution measurements and the obtained
resistance categories is provided in Supplementary Table 3.
Resistance of streptococcus in the metagenomic samples (SP07–SP12) was determined by agar
diffusion using the EUCAST methodology23. First, the inoculated agar plates were incubated at
37 °C overnight and then examined for growth with the potential for re-incubation up to 48
hours. Then, the samples were screened to oxacillin: if the zone diameter r was >20mm, the
isolate was considered sensitive to benzylpenicillin, otherwise a full MIC measurement to
benzylpenicillin was done. Finally, the isolate was screened for resistance to tetracycline
(r≥25mm for sensitive, r<22mm for resistant) and erythromycin (r≥22mm for sensitive, r<19mm
for resistant); when the isolate showed intermediate resistance, a full MIC measurement was
done.
Results for all tested samples – isolates and metagenomes – are summarized in Supplementary
Table 4.
Data, implementation and availability
RASE was developed using Python, GNU Make, GNU Parallel44, Snakemake45, and the ETE346
and PySam libraries. Bioconda47 was used to ensure reproducibility of the software
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23
environments. The code for constructing databases, together with the default RASE DB, is
available from http://github.com/c2-d2/rase-db; the RASE prediction pipeline is located at
http://github.com/c2-d2/rase-pipeline; and additional material to this paper can be found on
http://github.com/c2-d2/rase-supplement. All code is available under the MIT license.
Sequencing data for all experiments from this study can be downloaded from
http://doi.org/10.5281/zenodo.1405173; for the metagenomic experiments, only the filtered
datasets (i.e., after removing the remaining human reads in silico) were made publicly available.
Acknowledgements
This work was supported by the Bill & Melinda Gates Foundation (GCGH GCE OPP1151010, KB
and WPH), NIH – National Institute of Allergy and Infectious Diseases (R01 AI106786-05, KB),
the Canadian Institutes of Health Research (FRN 152448, RSL), and the Canadian Institutes for
Health Research (a fellowship grant, DRM). This paper presents independent research funded
by the National Institute for Health Research (NIHR) under its Programme Grants for Applied
Research Programme (Reference Number RP-PG-0514-20018, JOG), the UK Antimicrobial
Resistance Cross Council Initiative (MR/N013956/1, JOG), Rosetrees Trust (A749, JOG), the
University of East Anglia (JOG, TC), and Oxford Nanopore Technologies (JOG, TC). Portions of
this research were conducted on the O2 and Odyssey high performance compute clusters,
supported by the Research Computing Groups at Harvard Medical School and at the Harvard
Faculty of Arts and Sciences, respectively. The authors thank Joshua Metlay for providing the
test isolates for experiments SP03–SP06, which were collected as part of a population-wide
surveillance study done in the Philadelphia region, supported by NIH (R01 AI46645). The
authors also thank Yonatan H Grad, Brian J Arnold, Taj Azarian, and Cristina M Herren for useful
comments in various stages of this project.
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24
Transparency declarations
JOG received financial support for attending ONT and other conferences and an honorarium for
speaking at ONT headquarters. JOG received funding and consumable support from ONT for
TC’s PhD studentship.
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25
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Sample PG detected Serotype Antibiogram - PEN
Antibiogram - CRO
Antibiogram - TMP
Antibiogram - ERY
Antibiogram - TET
ST match
CC match
Actual Best match
Actual Best match
Actual Best match
Actual Best match
Actual Best match
Actual Best match
sp01 yes 11D 11D S S S S S S S S S(1) S(1) Yes Yes sp02 yes 19A 19A R R R R R R R R R(2) R(2) Yes Yes sp03 yes 23F 23F R R R R R R R S(3) S S OoD Yes sp04 yes 19A 19A R R R R R R R R R R(4) OoD Yes sp05 no (borderline) 19F 19F R R R R R R R R R R OoD Yes sp06 yes 23F 23F R R R R R R R S(3) S S OoD Yes
Sample PG detected
SP Antibiogram - PEN
Antibiogram - ERY
Antibiogram - TET
sp07 no 2.3% S S NA S R S(5) sp08 no|yes 2.5% S S(!) S S S S(6) sp09 no 4.0% S S NA S S S(7) sp10 yes 21% R R R R R R(8) sp11 yes 70% R R R R R R(8) sp12 yes 86% S S S S R S(5)
A)
Legend
S Susceptible S(!) Best match S, but high
risk of R reported R Non-susceptible NA Not available OoD Out-of-database (…) ID of a retested sample …|… Original | filtered sample
(when the results differ) SP Fraction of S. pneumoniae
reads
Correct prediction
Incorrect prediction
Cannot be evaluated
B)
Table 1: Predicted phenotypes for (A) isolates and (B) metagenomes. The table displays actual and predicted
resistance phenotypes (S = susceptible, R = non-susceptible) for individual experiments, as well as information
on match of the predicted sequence type and clonal complex. Resistance categories in bold were inferred using
ancestral reconstruction and were also confirmed using phenotypic testing (seeMethods andSupplementary Table
3).
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Match againstthe database
Read nextnanoporeread
Predict and report
Updateweights
Load the RASEdatabase
time
Predict strain and phylogroup
Best PG
2ndbest PG
f
t
PGS = 2f/(f+t)-1
Predict susceptibility
Non-susceptibleSusceptible
s
rSUS = s/(s+r)
3An
tibio
tics
Strains
Phylogroups
Susceptible
21
A B C D E F G H I J K L M N O P Q R
Non-susceptible
RASE database
Match to all strains
K-mers
Nanopore read
Similarityscores
A B C D E F GH I J K L MNO P QR
A B C D E F GH I J K L MNO P QR
A B C D E F GH I J K L MNO P QR
A B C D E F GH I J K L MNO P QR
ProPhyle
Figure 1: Overview of the RASE approach. The RASE approach uses three components: the RASE database,
an approximate k-mer-based matching component based on ProPhyle, and a prediction component interpreting
the risk based on the resistance of strains of the assigned phylogroup. In the load step, the precomputed RASE
database is loaded into memory. The RASE pipeline iterates over reads streamed from the nanopore sequencer.
Each read is matched against the database using ProPhyle. Retrieved assignments are propagated to the leaves
and similarity scores computed. These are used to identify best-matching strains (possibly many) and to update
weights associated with these strains. Indeed, a single read is rarely specific, it typically matches equally scored
multiple nodes. The best phylogroup is identified and a phylogroup score calculated (PGS). Based on the resistance
profiles of strains in this phylogroup, susceptibility to each of the antibiotics is predicted from the best match and
reported together with a susceptibility score quantifying the risk of resistance.
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TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
0.05
Rel
ative
sim
ilarit
y to
sam
ple
R34−3203 263137 R34−3080 E4NSI NKLJL J1LX6 9ABKR R34−3149 R34−3071 F1ODP RQ6NH 303656 R34−3102 F7IXH 386329 5J97G STPDE R34−3170 3YFA4 459747 QHXZZ R34−3095 R52DJ 6ZCAZ DFS2Q 28I7H XCJ97 R34−3208 242588 389109 R34−3136 F1G5R RAV85 6CO3C R34−3228 FP9DM H3Q9M 8G3XE R34−3214 R34−3054 8AH8E HWJVH 335574 K9N0O R34−3156 T14BF R34−3173 7NA98 OZJ9F ZPN7P KYDZM R34−3147 074124 R34−3043 102720 R34−3052 R34−3081 R34−3155 X703J 302649 187406 R34−3121 132571 14YE5 R34−3118 R34−3151 R34−3181 R34−3031 R34−3075 144370
Isolate
Reads: 263 Bps: 491,264 Useful bps: 18%
Susceptibilitynon−susceptiblesusceptible
Phylogroup210Others
2017−06−06 17:17:17
TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
Rel
ative
sim
ilarit
y to
sam
ple
263137 R34−3203 E4NSI K9N0O 5J97G R34−3080 QHXZZ 242588 F1ODP 6ZCAZ R34−3208 R34−3149 9ABKR FP9DM 459747 J1LX6 RQ6NH H3Q9M F7IXH 8G3XE 28I7H F1G5R 3YFA4 HWJVH R34−3170 8AH8E RAV85 R34−3156 335574 R34−3095 DFS2Q XCJ97 R52DJ R34−3228 6CO3C R34−3054 303656 R34−3214 386329 R34−3081 R34−3071 389109 T14BF R34−3102 R34−3155 R34−3052 R34−3147 KYDZM 074124 102720 3XUC4 ZPN7P OZJ9F R34−3121 R34−3173 NKLJL 187406 ODNWT STPDE R34−3206 GJ6MQ 436915 G2Z0B R34−3136 R34−3196 SHTPB DALR8 103453 8QTW4 R34−3118
Isolate
Reads: 1,270 Bps: 2,267,820 Useful bps: 19%
Susceptibilitynon−susceptiblesusceptible
Phylogroup216Others
2017−06−06 17:21:17
TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
0.05
0.06
Rel
ative
sim
ilarit
y to
sam
ple
E4NSI 459747 H3Q9M R34−3203 QHXZZ R34−3095 R34−3149 389109 FP9DM 8AH8E T14BF XCJ97 3YFA4 6CO3C R34−3208 RAV85 F1ODP 8G3XE R34−3214 F7IXH R34−3054 28I7H R52DJ 6ZCAZ J1LX6 263137 HWJVH R34−3071 5J97G 335574 F1G5R RQ6NH K9N0O R34−3228 DFS2Q 9ABKR R34−3080 242588 R34−3156 R34−3170 R34−3081 KYDZM R34−3155 R34−3052 102720 386329 R34−3147 074124 R34−3102 187406 303656 R34−3121 R34−3118 OZJ9F R34−3173 ZPN7P VODW3 NKLJL SLXY1 8QTW4 110093 119571 R34−3176 18FDW R34−3199 BL0SN 397079 3XUC4 HB7S5 W5HGR
Isolate
Reads: 470,165 Bps: 780,049,681 Useful bps: 16%
Susceptibilitynon−susceptiblesusceptible
Phylogroup216Others
2017−06−07 08:58:17
0
100
200
300
400
#rea
ds (t
hous
ands
) Predicted PG stabilizedAlternative PG stabilizedIsolate stabilized
0.0
0.2
0.4
0.6
0.8
1.0
PG s
core
fail
pass
0.0
0.2
0.4
0.6
0.8
1.0
PEN
sus
c sc
ore
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
CRO
sus
c sc
ore
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
TMP
susc
sco
re
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
ERY
susc
sco
re
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
TET
susc
sco
re
non−
susc
susc
0 5 10 15minutes
14.0 15.5hours
b) t=1
min
c) t=5
min
d) t=1
5.5h
...
...
...
...
...
...
...
b
a
c
d
Figure 2: Timeline and rank plots for an isolate. a) Number of reads, phylogroup score, and susceptibility scores
for individual antibiotics as a function of time from the start of sequencing. The point markers depict the times of
stabilization for the predicted phylogroup, the alternative phylogroup and the most similar isolate, respectively. b)-d)
Similarity rank plots for selected time points (1 minute, 5 minutes, and the end of sequencing). The bars correspond
to 70 best matching isolates in the database and display the predicted level of sample-to-strain relative similarity (i.e.,
normalized weights). They are arranged by rank and colored according to the presence in the predicted, alternative
or another phylogroup. The bottom panels display the susceptibility profiles of the isolates.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.10
Rel
ative
sim
ilarit
y to
sam
ple
8QTW4 R34−3064 R34−3199 HB7S5 R34−3126 R34−3179 XVMDP Z4952 R34−3130 XCB66 R34−3040 SLXY1 CSI7H R34−3225 R34−3226 IB8MW R34−3036 R34−3150 UJECB KRHYA R34−3138 W5HGR R34−3077 R34−3158 T8K26 R34−3016 BA5TC 333793 M66VO 28PCJ FU8OL 397079 STPDE 5Z52R P0N8K LOOXY R34−3197 Z60YP 044744 103453 323485 AFVC5 160986 R34−3098 R34−3075 R34−3189 R34−3026 W9GKO 187406 R34−3121 277394 5MZ1D NJ41D R34−3109 132571 14YE5 R34−3198 304793 F5UY4 0NWX9 NIPQY R34−3081 R34−3088 072782 217475 483391 R34−3160 R34−3212 303656 R34−3102
Isolate
Reads: 370 Bps: 867,246 Useful bps: 6%
Susceptibilitynon−susceptiblesusceptible
Phylogroup35Others
2017−05−26 17:30:52
TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Rel
ative
sim
ilarit
y to
sam
ple
8QTW4 HB7S5 IB8MW XVMDP R34−3199 R34−3064 XCB66 Z4952 R34−3138 W5HGR T8K26 R34−3126 R34−3225 R34−3179 R34−3150 R34−3226 KRHYA UJECB R34−3130 CSI7H R34−3036 SLXY1 R34−3040 R34−3158 R34−3077 R34−3088 18FDW 9LUM5 018044 397079 277394 2W7ME 34YLE WG60C 28PCJ R34−3026 F5UY4 R34−3170 R34−3027 044744 333793 160986 304793 342672 R34−3108 VODW3 R34−3183 403790 VPPXV 255210 CM917 218229 334847 173015 388483 1TR6C R34−3023 R34−3029 427937 R34−3016 STPDE GJ6MQ 436915 R34−3037 KYDZM 6GU7V N5O68 7NA98 AFVC5 R34−3098
Isolate
Reads: 1,909 Bps: 4,576,796 Useful bps: 6%
Susceptibilitynon−susceptiblesusceptible
Phylogroup312Others
2017−05−26 17:34:52
TETERYTMPCROPEN
0.00
0.01
0.02
0.03
0.04
0.05
0.06
Rel
ative
sim
ilarit
y to
sam
ple
8QTW4 T8K26 HB7S5 SLXY1 R34−3199 XCB66 W5HGR CSI7H UJECB XVMDP Z4952 R34−3138 IB8MW KRHYA R34−3158 R34−3225 R34−3179 R34−3040 R34−3130 R34−3126 R34−3226 R34−3064 R34−3036 R34−3150 R34−3077 R34−3088 WG60C 34YLE 18FDW 277394 403790 397079 255210 R34−3023 160986 R34−3026 R34−3108 R34−3136 VODW3 R34−3194 044744 R34−3183 388483 F5UY4 304793 R34−3021 28PCJ M66VO 2W7ME 342672 R34−3029 R34−3012 110093 R34−3176 018044 R34−3037 H3Q9M R34−3027 R34−3028 427937 436154 333793 334847 218229 R34−3013 173015 103453 9LUM5 R34−3014 1LQKE
Isolate
Reads: 70,792 Bps: 164,972,098 Useful bps: 5%
Susceptibilitynon−susceptiblesusceptible
Phylogroup312Others
2017−05−27 11:01:52
010203040506070
#rea
ds (t
hous
ands
) Predicted PG stabilizedAlternative PG stabilizedIsolate stabilized
0.0
0.2
0.4
0.6
0.8
1.0
PG s
core
fail
pass
0.0
0.2
0.4
0.6
0.8
1.0
PEN
sus
c sc
ore
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
CRO
sus
c sc
ore
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
TMP
susc
sco
re
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
ERY
susc
sco
re
non−
susc
susc
0.0
0.2
0.4
0.6
0.8
1.0
TET
susc
sco
re
non−
susc
susc
0 5 10 15minutes
13.5 15.0hours
b) t=1
min
c) t=5
min
d) t=1
7.5h
...
...
...
...
...
...
...
b
a
c
d
Figure 3: Timeline and rank plots for a metagenome. The figure is of the same format as Figure 2.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
seq−fa seq−fagz ind−mem ind−transm
Size of the RASE database
Siz
e [M
B]
050
010
0015
00
1380
384320
47
Supplementary Figure 1: Size and memory footprint of the RASE database and index. The graph compares
the size of the ProPhyle RASE index to the size of the original sequences: original draft assemblies (seq−fa), original
draft assemblies compressed using gzip (seq−fagz), memory footprint of ProPhyle with the RASE index (ind−mem),
and size of the ProPhyle RASE index compressed for transmission (ind−transm).
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
0 10 20 30 40 50 60
05
1015
20
Time (minutes)
# ge
ne o
ccur
renc
es
tetmelmefAermB
Supplementary Figure 2: Timeline of resistance genes. Number of occurrences of individual resistance genes
in reads of SP02, as a function of time for the first hour of nanopore sequencing.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
100 200 300 400 500 600
−8
−6
−4
−2
02
46
Isolate
log
2 P
EN
_M
IC
PG 8 PG 16 PG 7 PG 16 PG 15 PG 16 PG 11 PG 16 PG 6 PG 16 PG 3 PG 16 PG 2 PG 14 PG 16 PG 4 PG 9 PG 12 PG 16 PG 1 PG 16 PG 10 PG 5 PG 13 PG 16 PG 8
non−susc.
susceptible
inferred non−susc.
inferred susc.
R3
4−
30
63
36
51
52
R3
4−
31
88
R3
4−
30
34
PC
KM
OIM
AP
Y5
09
36
5E
SB
KM
PN
3IH
8P
Y5
X4
92
70
6K
51
SW
TG
9A
8A
YF
PY
IRE
4I
P4
GIC
R3
4−
31
75
09
53
44
YQ
UA
QR
34
−3
07
9R
34
−3
12
4F
UO
YQ
08
01
04
2E
AK
R3
66
29
3W
LTN
82
10
16
21
48
05
6D
PG
ZI
31
20
34
R3
4−
31
03
05
71
44
RC
BG
R0
OH
1I
AT
BL
M6
EO
69
RM
EO
XR
L3
6E
6U
UP
J6
JS
Y8
R3
4−
30
68
RE
QG
JV
QC
7K
RZ
PN
F1
35
77
11
60
44
91
V4
ME
R3
4−
31
16
Z6
0Y
PL
OO
XY
R3
4−
31
85
WN
YE
LK
MM
CT
R3
4−
32
18
21
81
86
R3
4−
30
73 2
66
03
5R
34
−3
19
7B
HC
QB
6F
XS
QR
34
−3
04
9R
34
−3
11
0R
34
−3
06
1IZ
QW
IL
IW2
81
03
45
3R
34
−3
12
2R
34
−3
22
3R
34
−3
02
31
10
09
3W
9G
4K
2V
BT
KR
34
−3
10
8R
34
−3
11
3Q
IKY
SQ
04
13
TJR
UQ
DA
LR
80
27
99
9R
34
−3
04
3R
34
−3
07
04
39
69
9S
QA
DW
27
73
94
R3
4−
31
93 R
34
−3
22
4R
34
−3
13
7R
34
−3
02
82
09
46
42
84
96
8R
34
−3
19
8G
WT
K7
R3
4−
30
56
E3
GX
Y 3X
UC
4R
34
−3
16
3B
4R
32
D8
RP
Y5
5N
O4
R3
4−
32
19
UF
G1
AY
89
K0
7R
CF
0 3B
DE
MR
JB
FJ
30
47
93
F5
UY
4R
34
−3
08
4R
34
−3
21
7R
34
−3
10
10
72
51
1R
34
−3
20
2P
21
3M
06
56
45
R3
4−
31
90
LD
D8
7R
34
−3
07
83
69
82
06
GU
7V
R3
4−
31
41
R3
4−
31
42
R3
4−
30
85
41
61
85
50
35
74
9S
KO
TC
HP
0M
LA
BT
O0
6U
RQ
NF
PT
SD
H8
X5
−1 1
QJA
PO
QT
RJ
R3
4−
32
21
R3
4−
32
07
10
55
42
R3
4−
30
94
R3
4−
32
00
R3
4−
30
98
40
44
63
20
88
66
20
99
30
R3
4−
30
58
WM
K3
TR
34
−3
02
6 04
47
44
R3
4−
30
37
06
70
94
R3
4−
30
25
4K
4C
9R
34
−3
09
78
1L
MX
O0
RH
BO
61
U7
0U
64
IB
1K
MB
1V
DX
86
89
3Z
R3
4−
32
29
CC
V1
HL
S3
OB
4P
YM
00
NW
X9
R3
4−
30
87 R
34
−3
08
3U
TE
DZ
R3
4−
31
64
R3
4−
31
39
AF
VC
5F
77
ZH
QW
SZ
TR
34
−3
13
1R
34
−3
20
4W
AM
FH
R3
4−
32
27
BZ
2I7 R
34
−3
17
2P
1N
M2
R3
4−
30
74
T8
Z8
OO
8I1
E0
07
64
9R
34
−3
16
5W
9G
KO JB
YF
YR
34
−3
04
4 RE
AO
U3
79
67
8R
34
−3
11
9R
34
−3
06
9R
S9
D2
9D
25
HW
8IH
X3
4Y
LE
WG
60
CR
34
−3
04
84
38
18
0R
34
−3
11
5N
A0
3L
DR
1P
D 6JT
2I
R3
4−
30
86
14
YE
51
32
57
1U
3E
O1
R3
4−
31
36
17
47
02
R3
4−
31
94
48
16
43
1T
R6
C1
53
43
8U
B6
XH
R3
4−
31
86
48
78
27
22
38
32
01
ZW
MB
JF
60
HR
2T
30
FQ
8K
H8
YK
WA
12
WS
R3
4−
30
47
R3
4−
32
09
0G
B6
KR
34
−3
12
32
8P
CJ
O3
45
21
LQ
KE
5X
CD
5U
NU
OJ
DN
B9
0O
SE
Y6
TV
66
E3
97
07
9 18
FD
W8
QT
W4
XV
MD
PZ
49
52
R3
4−
31
79
HB
7S
5R
34
−3
19
9C
SI7
HR
34
−3
04
0R
34
−3
15
0R
34
−3
03
6IB
8M
WR
34
−3
07
7X
CB
66
SL
XY
1R
34
−3
12
6R
34
−3
13
0R
34
−3
15
8R
34
−3
06
4 R3
4−
31
38
KR
HY
AW
5H
GR
UJE
CB
T8
K2
6R
34
−3
22
5R
34
−3
22
6R
34
−3
10
23
03
65
6Z
PN
7P
OZ
J9
FR
34
−3
17
3R
34
−3
12
11
87
40
6R
34
−3
14
9R
34
−3
17
0H
3Q
9M
10
27
20
R3
4−
30
52
R3
4−
30
81
KY
DZ
M0
74
12
43
86
32
9R
34
−3
14
7R
34
−3
15
5R
34
−3
07
1R
34
−3
20
3R
34
−3
20
82
8I7
HF
1O
DP
F1
G5
RE
4N
SI
45
97
47
QH
XZ
ZR
34
−3
21
4T
14
BF
R3
4−
30
54
RA
V8
56
CO
3C
8G
3X
E8
AH
8E
33
55
74
J1
LX
6D
FS
2Q
R5
2D
J3
YFA
42
63
13
7F
P9
DM
XC
J9
72
42
58
8H
WJV
HR
34
−3
09
5 38
91
09
6Z
CA
ZR
34
−3
15
69
AB
KR
RQ
6N
HR
34
−3
22
8R
34
−3
08
0F
7IX
H5
J9
7G
K9
N0
O3
42
67
2C
XQ
2T
R3
4−
32
01
06
54
35
17
97
43
10
84
80
05
17
15
44
86
43
R3
4−
31
71 R
34
−3
16
8A
I3G
Z2
RL
C4
R3
4−
31
76
43
07
72
34
13
65
R3
4−
32
31
R3
4−
32
30
26
86
60
30
64
35
14
25
34
R3
4−
30
12
R3
4−
30
90
R3
4−
30
82
R3
4−
31
87
FJZ
ZW
38
53
85
FB
PN
SR
WZ
JE
16
32
86
12
05
81
R3
4−
31
67
DQ
KY
E0
35
10
0Q
3H
1U
12
0T
71
53
40
8R
34
−3
01
7 R3
4−
31
43
R3
4−
30
91
I0U
ZQ
R3
4−
31
89
ZX
PK
HR
34
−3
17
7C
JIS
L 94
OR
HY
01
60
9T
42
WR
34
−3
05
1R
34
−3
05
72
AH
BE
ON
38
ST
EF
7S
R3
4−
30
50
DP
07
VR
34
−3
07
64
62
95
60
25
31
02
03
69
22
39
43
4R
34
−3
02
9F
OR
95
T7
IZ1
8A
4V
RQ
RP
PW
R3
4−
30
13
15
16
84
42
79
37
R3
4−
31
81
C3
W4
1R
34
−3
02
27
LL
CL
BD
GW
M0
4W
B3
LF
B1
5W
CU
LS
DY
JG
LR
34
−3
19
5R
34
−3
11
4R
34
−3
16
92
48
73
4R
34
−3
01
9R
34
−3
02
03
MB
4Z
WY
MQ
IL
IT4
QJ9
GM
MR
34
−3
12
7R
34
−3
05
5R
34
−3
17
4R
34
−3
06
7Y
HP
D0
27
64
30
36
55
02
04
94
70
35
45
57
15
43
89
5Z
S1
X4
03
79
0R
34
−3
08
82
55
21
0W
VC
E6
R3
4−
30
32
R3
4−
30
39
R3
4−
30
15
68
G2
D4
62
74
65
08
90
7E
KR
1O
P0
N8
KR
34
−3
14
6K
81
21
J2
9X
81
44
37
0R
34
−3
04
6 14
75
87
R3
4−
30
65
HU
4A
A8
PN
F1
2W
7M
EM
66
VO
X7
03
J SH
TP
BR
D7
KX
BA
5T
C2
Y1
CQ
R3
4−
30
62
00
19
96
R3
4−
31
66
33
68
50
06
20
31
R3
4−
30
75 4
72
69
90
89
84
80
42
39
7C
V6
JA
13
56
31
38
37
39
R3
4−
32
22
R3
4−
30
18
R3
4−
30
35 4
46
37
61
18
03
9R
34
−3
22
02
99
80
1P
KM
M4
27
93
88
N6
I98
00
13
34
R3
4−
30
24
R3
4−
30
21
R3
4−
31
57
G2
Z0
BN
5O
68
5Z
52
RR
34
−3
18
4R
N3
X8
R3
4−
31
82
R3
4−
31
11
RU
J9
0 29
OR
IQ
7F
26 UV
VW
AB
L0
SN
7C
7G
1R
34
−3
19
1 R3
4−
32
13
4H
UA
7 B5
0V
6N
IPQ
YR
34
−3
11
8 12
75
30
R3
4−
32
16
47
39
37
0C
NY
CR
34
−3
17
84
D0
HZ
R3
4−
31
12
R3
4−
31
20
MF
II0
X7
1H
5 Y6
BS
G6
U8
ZJ
3U
TO
8F
RIZ
42
6IE
T3
GW
V1
R3
4−
30
59
04
02
41
R3
4−
31
96
7N
A9
83
33
79
3Y
SO
FP
R3
4−
30
33
N8
YA
4E
0Z
KK
VO
DW
31
19
57
1N
B8
E4
R3
4−
30
72
PH
Y0
3Q
D0
ZV
8C
RC
EV
5V
F1
29
18
80
6P
U3
9R
34
−3
08
9R
34
−3
09
23
JK
7Y
R3
4−
31
25
05
7G
3R
34
−3
04
1Q
U2
WM
LY2
88
OD
NW
T4
XIL
AQ
QK
9Y
NK
LJL
09
32
09
R3
4−
30
60
R3
4−
30
53
SE
OT
TP
WG
X0
ST
PD
EN
J4
1D
3F
BX
JR
34
−3
10
95
MZ
1D
R3
4−
30
93
F8
P2
5R
34
−3
21
5X
QR
0B
VP
PX
V2
34
32
33
12
94
2R
34
−3
04
54
22
26
4R
34
−3
01
65
W9
08
04
28
61
R3
4−
31
80
10
10
58
R3
4−
31
00
CM
91
7F
U8
OL
R3
4−
30
27
16
66
37
R3
4−
30
99
42
08
81
R3
4−
32
11 R
34
−3
21
00
15
44
50
TN
5H
R3
4−
30
96
R3
4−
31
51 3
59
37
01
81
27
21
60
98
64
36
15
40
18
04
43
88
48
3R
34
−3
03
83
02
64
93
23
48
51
73
01
52
18
22
93
34
84
74
36
91
5G
J6
MQ
9L
UM
5R
34
−3
18
3R
34
−3
21
2R
34
−3
16
04
83
39
10
72
78
2R
34
−3
19
22
17
47
5D
H8
X5
−2
XZ
HZ
PR
34
−3
03
1 R3
4−
31
40
WQ
9G
VR
34
−3
15
9F
QP
LS
PX
B8
VR
34
−3
20
6R
34
−3
20
53
62
41
23
72
29
71
46
06
6R
34
−3
14
4 R3
4−
30
14
EH
2W
NR
34
−3
01
1Q
LC
SW
IZC
EG
LJ6
JL
WW
C1
TR
34
−3
15
3M
6A
JV
5Q
BR
PR
34
−3
15
4R
34
−3
03
0
100 200 300 400 500 600
−6
−4
−2
02
46
Isolate
log
2 C
RO
_M
IC
PG 8 PG 16 PG 7 PG 16 PG 15 PG 16 PG 11 PG 16 PG 6 PG 16 PG 3 PG 16 PG 2 PG 14 PG 16 PG 4 PG 9 PG 12 PG 16 PG 1 PG 16 PG 10 PG 5 PG 13 PG 16 PG 8
non−susc.
susceptible
inferred non−susc.
inferred susc.
R3
4−
30
63
36
51
52
R3
4−
31
88
R3
4−
30
34
PC
KM
OIM
AP
Y5
09
36
5E
SB
KM PN
3IH
8P
Y5
X4
92
70
6 K5
1S
WT
G9
A8
AY
FP
YIR
E4
IP
4G
ICR
34
−3
17
50
95
34
4Y
QU
AQ
R3
4−
30
79
R3
4−
31
24
FU
OY
Q0
80
10
4 2E
AK
R3
66
29
3W
LTN
82
10
16
21
48
05
6D
PG
ZI
31
20
34
R3
4−
31
03
05
71
44
RC
BG
R0
OH
1I
AT
BL
M 6E
O6
9R
ME
OX
RL
36
E6
UU
PJ
6JS
Y8
R3
4−
30
68
RE
QG
JV
QC
7K
RZ
PN
F1
35
77
11
60
44
9 1V
4M
ER
34
−3
11
6Z
60
YP
LO
OX
YR
34
−3
18
5W
NY
EL
KM
MC
TR
34
−3
21
82
18
18
6R
34
−3
07
32
66
03
5R
34
−3
19
7B
HC
QB
6F
XS
QR
34
−3
04
9R
34
−3
11
0R
34
−3
06
1IZ
QW
IL
IW2
81
03
45
3R
34
−3
12
2R
34
−3
22
3R
34
−3
02
31
10
09
3W
9G
4K
2V
BT
KR
34
−3
10
8R
34
−3
11
3Q
IKY
SQ
04
13
TJR
UQ
DA
LR
80
27
99
9R
34
−3
04
3R
34
−3
07
04
39
69
9S
QA
DW
27
73
94
R3
4−
31
93
R3
4−
32
24
R3
4−
31
37
R3
4−
30
28
20
94
64
28
49
68
R3
4−
31
98
GW
TK
7R
34
−3
05
6E
3G
XY 3X
UC
4R
34
−3
16
3B
4R
32
D8
RP
Y5
5N
O4
R3
4−
32
19
UF
G1
AY
89
K0
7R
CF
03
BD
EM
RJB
FJ
30
47
93
F5
UY
4R
34
−3
08
4R
34
−3
21
7R
34
−3
10
10
72
51
1R
34
−3
20
2P
21
3M
06
56
45
R3
4−
31
90
LD
D8
7R
34
−3
07
83
69
82
06
GU
7V
R3
4−
31
41
R3
4−
31
42
R3
4−
30
85
41
61
85
50
35
74
9S
KO
TC
HP
0M
LA
BT
O0
6U
RQ
NF
PT
SD
H8
X5
−1
1Q
JA
PO
QT
RJ
R3
4−
32
21
R3
4−
32
07
10
55
42
R3
4−
30
94
R3
4−
32
00
R3
4−
30
98
40
44
63
20
88
66
20
99
30
R3
4−
30
58
WM
K3
TR
34
−3
02
60
44
74
4R
34
−3
03
70
67
09
4R
34
−3
02
54
K4
C9
R3
4−
30
97 8
1L
MX
O0
RH
BO
61
U7
0U
64
IB
1K
MB
1V
DX
86
89
3Z
R3
4−
32
29
CC
V1
HL
S3
OB
4P
YM
00
NW
X9
R3
4−
30
87 R
34
−3
08
3U
TE
DZ
R3
4−
31
64
R3
4−
31
39
AF
VC
5F
77
ZH
QW
SZ
TR
34
−3
13
1R
34
−3
20
4W
AM
FH
R3
4−
32
27
BZ
2I7
R3
4−
31
72
P1
NM
2R
34
−3
07
4 T8
Z8
OO
8I1
E0
07
64
9R
34
−3
16
5W
9G
KO
JB
YF
YR
34
−3
04
4R
EA
OU
37
96
78
R3
4−
31
19
R3
4−
30
69 R
S9
D2
9D
25
HW
8IH
X3
4Y
LE
WG
60
CR
34
−3
04
84
38
18
0R
34
−3
11
5N
A0
3L
DR
1P
D 6JT
2I
R3
4−
30
86
14
YE
51
32
57
1U
3E
O1
R3
4−
31
36
17
47
02
R3
4−
31
94
48
16
43
1T
R6
C1
53
43
8U
B6
XH
R3
4−
31
86
48
78
27
22
38
32
01
ZW
MB
JF
60 H
R2
T3
0F
Q8
KH
8Y
KW
A1
2W
SR
34
−3
04
7R
34
−3
20
90
GB
6K
R3
4−
31
23
28
PC
JO
34
52
1L
QK
E5
XC
D5
UN
UO
JD
NB
90
OS
EY
6T
V6
6E
39
70
79
18
FD
W8
QT
W4
XV
MD
PZ
49
52
R3
4−
31
79
HB
7S
5R
34
−3
19
9C
SI7
HR
34
−3
04
0R
34
−3
15
0R
34
−3
03
6IB
8M
WR
34
−3
07
7X
CB
66
SL
XY
1R
34
−3
12
6R
34
−3
13
0R
34
−3
15
8R
34
−3
06
4R
34
−3
13
8K
RH
YA
W5
HG
RU
JE
CB T
8K
26
R3
4−
32
25
R3
4−
32
26
R3
4−
31
02
30
36
56
ZP
N7
PO
ZJ9
FR
34
−3
17
3R
34
−3
12
11
87
40
6R
34
−3
14
9R
34
−3
17
0H
3Q
9M
10
27
20
R3
4−
30
52
R3
4−
30
81
KY
DZ
M0
74
12
43
86
32
9R
34
−3
14
7R
34
−3
15
5R
34
−3
07
1R
34
−3
20
3R
34
−3
20
82
8I7
HF
1O
DP
F1
G5
RE
4N
SI
45
97
47
QH
XZ
ZR
34
−3
21
4T
14
BF
R3
4−
30
54
RA
V8
56
CO
3C
8G
3X
E8
AH
8E
33
55
74
J1
LX
6D
FS
2Q
R5
2D
J3
YFA
42
63
13
7F
P9
DM
XC
J9
72
42
58
8H
WJV
HR
34
−3
09
53
89
10
96
ZC
AZ
R3
4−
31
56
9A
BK
RR
Q6
NH
R3
4−
32
28
R3
4−
30
80
F7
IXH
5J9
7G
K9
N0
O3
42
67
2C
XQ
2T
R3
4−
32
01
06
54
35
17
97
43
10
84
80
05
17
15
44
86
43
R3
4−
31
71
R3
4−
31
68
AI3
GZ
2R
LC
4R
34
−3
17
64
30
77
23
41
36
5R
34
−3
23
1R
34
−3
23
02
68
66
03
06
43
51
42
53
4R
34
−3
01
2R
34
−3
09
0R
34
−3
08
2R
34
−3
18
7F
JZ
ZW
38
53
85
FB
PN
SR
WZ
JE
16
32
86
12
05
81
R3
4−
31
67
DQ
KY
E0
35
10
0Q
3H
1U
12
0T
71
53
40
8R
34
−3
01
7R
34
−3
14
3R
34
−3
09
1I0
UZ
QR
34
−3
18
9Z
XP
KH
R3
4−
31
77
CJIS
L9
4O
RH Y0
16
09
T4
2W
R3
4−
30
51
R3
4−
30
57
2A
HB
EO
N3
8S
TE
F7
SR
34
−3
05
0D
P0
7V
R3
4−
30
76
46
29
56
02
53
10
20
36
92
23
94
34
R3
4−
30
29
FO
R9
5T
7IZ
18
A4
VR
QR
PP
WR
34
−3
01
31
51
68
44
27
93
7R
34
−3
18
1C
3W
41
R3
4−
30
22
7L
LC
LB
DG
WM
04
WB
3L
FB
15
WC
UL
SD
YJG
LR
34
−3
19
5R
34
−3
11
4R
34
−3
16
92
48
73
4R
34
−3
01
9R
34
−3
02
03
MB
4Z
WY
MQ
IL
IT4
QJ9
GM
MR
34
−3
12
7R
34
−3
05
5R
34
−3
17
4R
34
−3
06
7Y
HP
D0
27
64
30
36
55
02
04
94
70
35
45
57
15
43
89
5Z
S1
X4
03
79
0R
34
−3
08
82
55
21
0W
VC
E6
R3
4−
30
32
R3
4−
30
39
R3
4−
30
15
68
G2
D4
62
74
65
08
90
7E
KR
1O
P0
N8
KR
34
−3
14
6K
81
21
J2
9X
81
44
37
0R
34
−3
04
61
47
58
7R
34
−3
06
5H
U4
AA 8P
NF
12
W7
ME
M6
6V
OX
70
3J S
HT
PB
RD
7K
XB
A5
TC
2Y
1C
QR
34
−3
06
20
01
99
6R
34
−3
16
63
36
85
00
62
03
1R
34
−3
07
54
72
69
90
89
84
80
42
39
7 CV
6JA
13
56
31
38
37
39
R3
4−
32
22
R3
4−
30
18
R3
4−
30
35
44
63
76
11
80
39
R3
4−
32
20
29
98
01
PK
MM
42
79
38
8N
6I9
8 00
13
34
R3
4−
30
24
R3
4−
30
21
R3
4−
31
57
G2
Z0
BN
5O
68
5Z
52
RR
34
−3
18
4R
N3
X8
R3
4−
31
82
R3
4−
31
11
RU
J9
0 29
OR
IQ
7F
26
UV
VW
AB
L0
SN 7C
7G
1R
34
−3
19
1R
34
−3
21
34
HU
A7
B5
0V
6N
IPQ
YR
34
−3
11
81
27
53
0R
34
−3
21
64
73
93
70
CN
YC
R3
4−
31
78
4D
0H
ZR
34
−3
11
2R
34
−3
12
0M
FII
0 X7
1H
5Y
6B
SG
6U
8Z
J3
UT
O8
FR
IZ4
26
IET
3G
WV
1R
34
−3
05
90
40
24
1R
34
−3
19
67
NA
98
33
37
93
YS
OF
PR
34
−3
03
3N
8Y
A4
E0
ZK
KV
OD
W3
11
95
71
NB
8E
4R
34
−3
07
2P
HY
03
QD
0Z
V8
CR
CE
V5
VF
12
91
88
06
PU
39
R3
4−
30
89
R3
4−
30
92
3JK
7Y
R3
4−
31
25
05
7G
3R
34
−3
04
1Q
U2
WM
LY2
88
OD
NW
T4
XIL
AQ
QK
9Y
NK
LJL
09
32
09
R3
4−
30
60
R3
4−
30
53
SE
OT
TP
WG
X0
ST
PD
EN
J4
1D 3F
BX
JR
34
−3
10
95
MZ
1D
R3
4−
30
93
F8
P2
5R
34
−3
21
5X
QR
0B
VP
PX
V2
34
32
33
12
94
2R
34
−3
04
54
22
26
4R
34
−3
01
65
W9
08
04
28
61
R3
4−
31
80
10
10
58
R3
4−
31
00
CM
91
7F
U8
OL
R3
4−
30
27
16
66
37
R3
4−
30
99
42
08
81
R3
4−
32
11
R3
4−
32
10
01
54
45
0T
N5
HR
34
−3
09
6R
34
−3
15
13
59
37
01
81
27
21
60
98
64
36
15
40
18
04
43
88
48
3R
34
−3
03
83
02
64
93
23
48
51
73
01
52
18
22
93
34
84
74
36
91
5G
J6
MQ
9L
UM
5R
34
−3
18
3R
34
−3
21
2R
34
−3
16
04
83
39
10
72
78
2R
34
−3
19
22
17
47
5 DH
8X
5−
2X
ZH
ZP
R3
4−
30
31
R3
4−
31
40
WQ
9G
VR
34
−3
15
9F
QP
LS
PX
B8
VR
34
−3
20
6R
34
−3
20
53
62
41
23
72
29
71
46
06
6R
34
−3
14
4R
34
−3
01
4E
H2
WN
R3
4−
30
11
QL
CS
WIZ
CE
GL
J6
JL
WW
C1
TR
34
−3
15
3M
6A
JV 5Q
BR
PR
34
−3
15
4R
34
−3
03
0
100 200 300 400 500 600
−4
−2
02
46
Isolate
log
2 T
MP
_M
IC
PG 8 PG 16 PG 7 PG 16 PG 15 PG 16 PG 11 PG 16 PG 6 PG 16 PG 3 PG 16 PG 2 PG 14 PG 16 PG 4 PG 9 PG 12 PG 16 PG 1 PG 16 PG 10 PG 5 PG 13 PG 16 PG 8
non−susc.
susceptible
inferred non−susc.
inferred susc.
R3
4−
30
63
36
51
52
R3
4−
31
88
R3
4−
30
34
PC
KM
OIM
AP
Y5
09
36
5E
SB
KM
PN
3IH
8P
Y5
X4
92
70
6 K5
1S
WT
G9
A8
AY
FP
YIR
E4
IP
4G
ICR
34
−3
17
50
95
34
4 YQ
UA
QR
34
−3
07
9R
34
−3
12
4F
UO
YQ
08
01
04
2E
AK
R3
66
29
3W
LTN
82
10
16
21
48
05
6D
PG
ZI
31
20
34
R3
4−
31
03
05
71
44
RC
BG
R0
OH
1I
AT
BL
M6
EO
69
RM
EO
X RL
36
E6
UU
PJ
6JS
Y8
R3
4−
30
68
RE
QG
JV
QC
7K
RZ
PN
F1
35
77
11
60
44
91
V4
ME
R3
4−
31
16
Z6
0Y
PL
OO
XY
R3
4−
31
85
WN
YE
LK
MM
CT
R3
4−
32
18
21
81
86
R3
4−
30
73
26
60
35
R3
4−
31
97
BH
CQ
B6
FX
SQ
R3
4−
30
49
R3
4−
31
10
R3
4−
30
61
IZQ
WI
LIW
28
10
34
53
R3
4−
31
22
R3
4−
32
23
R3
4−
30
23
11
00
93
W9
G4
K2
VB
TK
R3
4−
31
08
R3
4−
31
13
QIK
YS
Q0
41
3T
JR
UQ
DA
LR
80
27
99
9R
34
−3
04
3R
34
−3
07
04
39
69
9S
QA
DW
27
73
94
R3
4−
31
93
R3
4−
32
24
R3
4−
31
37
R3
4−
30
28
20
94
64
28
49
68
R3
4−
31
98
GW
TK
7R
34
−3
05
6E
3G
XY
3X
UC
4R
34
−3
16
3B
4R
32
D8
RP
Y5
5N
O4
R3
4−
32
19
UF
G1
AY
89
K0
7R
CF
03
BD
EM R
JB
FJ
30
47
93
F5
UY
4R
34
−3
08
4R
34
−3
21
7R
34
−3
10
10
72
51
1R
34
−3
20
2P
21
3M
06
56
45
R3
4−
31
90
LD
D8
7R
34
−3
07
83
69
82
06
GU
7V
R3
4−
31
41
R3
4−
31
42
R3
4−
30
85
41
61
85
50
35
74
9S
KO
TC
HP
0M L
AB
TO
06
UR
QN
FP
TS
DH
8X
5−
11
QJA
PO
QT
RJ
R3
4−
32
21
R3
4−
32
07
10
55
42
R3
4−
30
94
R3
4−
32
00
R3
4−
30
98
40
44
63
20
88
66
20
99
30
R3
4−
30
58
WM
K3
TR
34
−3
02
60
44
74
4R
34
−3
03
70
67
09
4R
34
−3
02
54
K4
C9
R3
4−
30
97
81
LM
XO
0R
HB
O6
1U
70
U6
4I
B1
KM
B1
VD
X8
68
93
ZR
34
−3
22
9C
CV
1H
LS
3O
B 4P
YM
00
NW
X9
R3
4−
30
87
R3
4−
30
83
UT
ED
ZR
34
−3
16
4R
34
−3
13
9A
FV
C5
F7
7Z
HQ
WS
ZT
R3
4−
31
31
R3
4−
32
04
WA
MF
HR
34
−3
22
7B
Z2
I7R
34
−3
17
2P
1N
M2
R3
4−
30
74
T8
Z8
OO
8I1
E0
07
64
9R
34
−3
16
5W
9G
KO
JB
YF
YR
34
−3
04
4R
EA
OU
37
96
78
R3
4−
31
19
R3
4−
30
69
RS
9D
2 9D
25
HW
8IH
X3
4Y
LE
WG
60
CR
34
−3
04
84
38
18
0R
34
−3
11
5N
A0
3L
DR
1P
D6
JT
2I
R3
4−
30
86
14
YE
51
32
57
1U
3E
O1
R3
4−
31
36
17
47
02
R3
4−
31
94
48
16
43
1T
R6
C1
53
43
8U
B6
XH
R3
4−
31
86
48
78
27
22
38
32
01
ZW
MB
JF
60
HR
2T
30
FQ
8K
H8
YK
WA
12
WS
R3
4−
30
47
R3
4−
32
09
0G
B6
KR
34
−3
12
32
8P
CJ
O3
45
21
LQ
KE
5X
CD
5 UN
UO
JD
NB
90
OS
EY
6T
V6
6E
39
70
79
18
FD
W 8Q
TW
4X
VM
DP
Z4
95
2R
34
−3
17
9H
B7
S5
R3
4−
31
99
CS
I7H
R3
4−
30
40
R3
4−
31
50
R3
4−
30
36
IB8
MW
R3
4−
30
77
XC
B6
6S
LX
Y1
R3
4−
31
26
R3
4−
31
30
R3
4−
31
58
R3
4−
30
64
R3
4−
31
38
KR
HY
AW
5H
GR
UJE
CB
T8
K2
6R
34
−3
22
5R
34
−3
22
6R
34
−3
10
23
03
65
6Z
PN
7P
OZ
J9
FR
34
−3
17
3R
34
−3
12
11
87
40
6R
34
−3
14
9R
34
−3
17
0H
3Q
9M
10
27
20
R3
4−
30
52
R3
4−
30
81
KY
DZ
M0
74
12
43
86
32
9R
34
−3
14
7R
34
−3
15
5R
34
−3
07
1R
34
−3
20
3R
34
−3
20
82
8I7
HF
1O
DP
F1
G5
RE
4N
SI
45
97
47
QH
XZ
ZR
34
−3
21
4T
14
BF
R3
4−
30
54
RA
V8
56
CO
3C 8
G3
XE
8A
H8
E3
35
57
4J1
LX
6D
FS
2Q
R5
2D
J3
YFA
42
63
13
7F
P9
DM
XC
J9
72
42
58
8H
WJV
HR
34
−3
09
53
89
10
96
ZC
AZ
R3
4−
31
56
9A
BK
RR
Q6
NH
R3
4−
32
28
R3
4−
30
80
F7
IXH 5J9
7G
K9
N0
O3
42
67
2C
XQ
2T
R3
4−
32
01
06
54
35
17
97
43
10
84
80
05
17
15
44
86
43
R3
4−
31
71
R3
4−
31
68
AI3
GZ
2R
LC
4R
34
−3
17
64
30
77
23
41
36
5R
34
−3
23
1R
34
−3
23
02
68
66
03
06
43
51
42
53
4R
34
−3
01
2R
34
−3
09
0R
34
−3
08
2R
34
−3
18
7F
JZ
ZW
38
53
85
FB
PN
SR
WZ
JE
16
32
86
12
05
81
R3
4−
31
67
DQ
KY
E0
35
10
0Q
3H
1U
12
0T
71
53
40
8R
34
−3
01
7R
34
−3
14
3R
34
−3
09
1I0
UZ
QR
34
−3
18
9Z
XP
KH
R3
4−
31
77
CJIS
L9
4O
RH
Y0
16
09
T4
2W
R3
4−
30
51
R3
4−
30
57
2A
HB
EO
N3
8S
TE
F7
SR
34
−3
05
0D
P0
7V
R3
4−
30
76
46
29
56
02
53
10
20
36
92
23
94
34
R3
4−
30
29
FO
R9
5T
7IZ
18
A4
VR
QR
PP
WR
34
−3
01
31
51
68
44
27
93
7R
34
−3
18
1C
3W
41
R3
4−
30
22
7L
LC
LB
DG
WM
04
WB
3L
FB
15
WC
UL
SD
YJG
LR
34
−3
19
5R
34
−3
11
4R
34
−3
16
92
48
73
4R
34
−3
01
9R
34
−3
02
03
MB
4Z
WY
MQ
IL
IT4
QJ9
GM
MR
34
−3
12
7R
34
−3
05
5R
34
−3
17
4R
34
−3
06
7Y
HP
D0
27
64
30
36
55
02
04
94
70
35
45
57
15
43
89
5Z
S1
X4
03
79
0R
34
−3
08
82
55
21
0W
VC
E6
R3
4−
30
32
R3
4−
30
39
R3
4−
30
15
68
G2
D4
62
74
65
08
90
7E
KR
1O
P0
N8
KR
34
−3
14
6K
81
21
J2
9X
81
44
37
0R
34
−3
04
61
47
58
7R
34
−3
06
5H
U4
AA
8P
NF
12
W7
ME
M6
6V
OX
70
3J
SH
TP
BR
D7
KX
BA
5T
C2
Y1
CQ
R3
4−
30
62
00
19
96
R3
4−
31
66
33
68
50
06
20
31
R3
4−
30
75
47
26
99
08
98
48
04
23
97
CV
6JA
13
56
31
38
37
39
R3
4−
32
22
R3
4−
30
18
R3
4−
30
35
44
63
76
11
80
39
R3
4−
32
20
29
98
01
PK
MM
42
79
38
8N
6I9
80
01
33
4R
34
−3
02
4R
34
−3
02
1R
34
−3
15
7G
2Z
0B
N5
O6
85
Z5
2R
R3
4−
31
84
RN
3X
8R
34
−3
18
2R
34
−3
11
1R
UJ9
02
9O
RI
Q7
F2
6 UV
VW
AB
L0
SN
7C
7G
1R
34
−3
19
1R
34
−3
21
34
HU
A7
B5
0V
6 NIP
QY
R3
4−
31
18
12
75
30
R3
4−
32
16
47
39
37
0C
NY
CR
34
−3
17
84
D0
HZ
R3
4−
31
12
R3
4−
31
20
MF
II0
X7
1H
5Y
6B
SG
6U
8Z
J3
UT
O8 F
RIZ
42
6IE
T3
GW
V1
R3
4−
30
590
40
24
1R
34
−3
19
67
NA
98
33
37
93 Y
SO
FP
R3
4−
30
33
N8
YA
4E
0Z
KK
VO
DW
31
19
57
1N
B8
E4
R3
4−
30
72
PH
Y0
3Q
D0
ZV 8
CR
CE
V5
VF
12
91
88
06
PU
39
R3
4−
30
89
R3
4−
30
92
3JK
7Y
R3
4−
31
25
05
7G
3R
34
−3
04
1Q
U2
WM
LY2
88
OD
NW
T4
XIL
AQ
QK
9Y
NK
LJL
09
32
09
R3
4−
30
60
R3
4−
30
53
SE
OT
TP
WG
X0
ST
PD
EN
J4
1D
3F
BX
JR
34
−3
10
95
MZ
1D
R3
4−
30
93
F8
P2
5R
34
−3
21
5X
QR
0B
VP
PX
V2
34
32
33
12
94
2R
34
−3
04
54
22
26
4R
34
−3
01
65
W9
08
04
28
61
R3
4−
31
80
10
10
58
R3
4−
31
00
CM
91
7 FU
8O
LR
34
−3
02
71
66
63
7R
34
−3
09
94
20
88
1R
34
−3
21
1R
34
−3
21
00
15
44
50
TN
5H
R3
4−
30
96
R3
4−
31
51
35
93
70
18
12
72
16
09
86
43
61
54
01
80
44
38
84
83
R3
4−
30
38
30
26
49
32
34
85
17
30
15
21
82
29
33
48
47
43
69
15 G
J6
MQ
9L
UM
5R
34
−3
18
3R
34
−3
21
2R
34
−3
16
04
83
39
10
72
78
2R
34
−3
19
22
17
47
5 DH
8X
5−
2X
ZH
ZP
R3
4−
30
31
R3
4−
31
40
WQ
9G
VR
34
−3
15
9F
QP
LS
PX
B8
VR
34
−3
20
6R
34
−3
20
53
62
41
23
72
29
71
46
06
6R
34
−3
14
4R
34
−3
01
4E
H2
WN
R3
4−
30
11
QL
CS
W IZC
EG
LJ6
JL W
WC
1T
R3
4−
31
53
M6
AJV
5Q
BR
PR
34
−3
15
4R
34
−3
03
0
100 200 300 400 500 600
−5
05
Isolate
log
2 E
RY
_M
IC
PG 8 PG 16 PG 7 PG 16 PG 15 PG 16 PG 11 PG 16 PG 6 PG 16 PG 3 PG 16 PG 2 PG 14 PG 16 PG 4 PG 9 PG 12 PG 16 PG 1 PG 16 PG 10 PG 5 PG 13 PG 16 PG 8
non−susc.
susceptible
inferred non−susc.
inferred susc.
R3
4−
30
63
36
51
52
R3
4−
31
88
R3
4−
30
34
PC
KM
OIM
AP
Y5
09
36
5E
SB
KM
PN
3IH
8P
Y5
X4
92
70
6K
51
SW
TG
9A
8A
YF
PY
IRE
4I
P4
GIC
R3
4−
31
75
09
53
44
YQ
UA
QR
34
−3
07
9R
34
−3
12
4F
UO
YQ
08
01
04
2E
AK
R3
66
29
3W
LTN
82
10
16
21
48
05
6D
PG
ZI
31
20
34
R3
4−
31
03
05
71
44
RC
BG
R0
OH
1I
AT
BL
M6
EO
69
RM
EO
XR
L3
6E 6U
UP
J6
JS
Y8
R3
4−
30
68
RE
QG
JV
QC
7K
RZ
PN
F1
35
77
11
60
44
91
V4
ME
R3
4−
31
16
Z6
0Y
P LO
OX
YR
34
−3
18
5W
NY
EL
KM
MC
TR
34
−3
21
82
18
18
6R
34
−3
07
32
66
03
5R
34
−3
19
7B
HC
QB
6F
XS
QR
34
−3
04
9R
34
−3
11
0R
34
−3
06
1IZ
QW
IL
IW2
81
03
45
3R
34
−3
12
2R
34
−3
22
3R
34
−3
02
31
10
09
3W
9G
4K
2V
BT
KR
34
−3
10
8R
34
−3
11
3Q
IKY
SQ
04
13
TJR
UQ
DA
LR
80
27
99
9R
34
−3
04
3R
34
−3
07
04
39
69
9S
QA
DW
27
73
94
R3
4−
31
93
R3
4−
32
24
R3
4−
31
37
R3
4−
30
28
20
94
64
28
49
68
R3
4−
31
98 G
WT
K7
R3
4−
30
56
E3
GX
Y3
XU
C4
R3
4−
31
63
B4
R3
2 D8
RP
Y5
5N
O4
R3
4−
32
19
UF
G1
AY
89
K0
7R
CF
03
BD
EM
RJB
FJ
30
47
93
F5
UY
4R
34
−3
08
4R
34
−3
21
7R
34
−3
10
10
72
51
1R
34
−3
20
2P
21
3M
06
56
45
R3
4−
31
90
LD
D8
7R
34
−3
07
83
69
82
06
GU
7V
R3
4−
31
41
R3
4−
31
42
R3
4−
30
85
41
61
85
50
35
74
9S
KO
TC
HP
0M
LA
BT
O0
6U
RQ
NF
PT
SD
H8
X5
−1
1Q
JA
PO
QT
RJ
R3
4−
32
21
R3
4−
32
07
10
55
42
R3
4−
30
94
R3
4−
32
00
R3
4−
30
98
40
44
63
20
88
66
20
99
30
R3
4−
30
58
WM
K3
TR
34
−3
02
60
44
74
4R
34
−3
03
70
67
09
4R
34
−3
02
54
K4
C9
R3
4−
30
97
81
LM
XO
0R
HB
O6
1U
70
U6
4I
B1
KM
B1
VD
X8
68
93
ZR
34
−3
22
9C
CV
1H
LS
3O
B4
PY
M0
0N
WX
9R
34
−3
08
7R
34
−3
08
3U
TE
DZ
R3
4−
31
64
R3
4−
31
39
AF
VC
5F
77
ZH
QW
SZ
TR
34
−3
13
1R
34
−3
20
4W
AM
FH
R3
4−
32
27
BZ
2I7
R3
4−
31
72
P1
NM
2R
34
−3
07
4T
8Z
8O O8
I1E
00
76
49
R3
4−
31
65
W9
GK
OJB
YF
YR
34
−3
04
4R
EA
OU
37
96
78
R3
4−
31
19
R3
4−
30
69
RS
9D
29
D2
5H
W8
IHX
34
YL
EW
G6
0C
R3
4−
30
48
43
81
80
R3
4−
31
15
NA
03
LD
R1
PD
6JT
2I
R3
4−
30
86
14
YE
51
32
57
1 U3
EO
1R
34
−3
13
61
74
70
2R
34
−3
19
44
81
64
31
TR
6C
15
34
38 UB
6X
HR
34
−3
18
64
87
82
72
23
83
20
1Z
WM
BJF
60
HR
2T
30
FQ
8K H8
YK
WA
12
WS
R3
4−
30
47
R3
4−
32
09
0G
B6
KR
34
−3
12
32
8P
CJ
O3
45
21
LQ
KE
5X
CD
5U
NU
OJ
DN
B9
0O
SE
Y6
TV
66
E3
97
07
91
8F
DW
8Q
TW
4X
VM
DP
Z4
95
2R
34
−3
17
9H
B7
S5
R3
4−
31
99
CS
I7H
R3
4−
30
40
R3
4−
31
50
R3
4−
30
36
IB8
MW
R3
4−
30
77
XC
B6
6S
LX
Y1
R3
4−
31
26
R3
4−
31
30
R3
4−
31
58
R3
4−
30
64
R3
4−
31
38
KR
HY
AW
5H
GR
UJE
CB
T8
K2
6R
34
−3
22
5R
34
−3
22
6R
34
−3
10
23
03
65
6Z
PN
7P
OZ
J9
FR
34
−3
17
3R
34
−3
12
11
87
40
6R
34
−3
14
9R
34
−3
17
0H
3Q
9M
10
27
20
R3
4−
30
52
R3
4−
30
81
KY
DZ
M0
74
12
43
86
32
9R
34
−3
14
7R
34
−3
15
5R
34
−3
07
1R
34
−3
20
3R
34
−3
20
82
8I7
HF
1O
DP
F1
G5
RE
4N
SI
45
97
47
QH
XZ
ZR
34
−3
21
4T
14
BF
R3
4−
30
54
RA
V8
56
CO
3C
8G
3X
E8
AH
8E
33
55
74
J1
LX
6D
FS
2Q
R5
2D
J3
YFA
42
63
13
7 FP
9D
MX
CJ9
72
42
58
8H
WJV
HR
34
−3
09
53
89
10
96
ZC
AZ
R3
4−
31
56
9A
BK
RR
Q6
NH
R3
4−
32
28
R3
4−
30
80
F7
IXH
5J9
7G
K9
N0
O3
42
67
2C
XQ
2T
R3
4−
32
01
06
54
35
17
97
43
10
84
80
05
17
15
44
86
43
R3
4−
31
71
R3
4−
31
68
AI3
GZ
2R
LC
4R
34
−3
17
64
30
77
23
41
36
5R
34
−3
23
1R
34
−3
23
02
68
66
03
06
43
51
42
53
4R
34
−3
01
2R
34
−3
09
0R
34
−3
08
2R
34
−3
18
7F
JZ
ZW
38
53
85
FB
PN
SR
WZ
JE
16
32
86
12
05
81
R3
4−
31
67
DQ
KY
E0
35
10
0Q
3H
1U
12
0T
71
53
40
8R
34
−3
01
7R
34
−3
14
3R
34
−3
09
1I0
UZ
QR
34
−3
18
9Z
XP
KH
R3
4−
31
77
CJIS
L9
4O
RH
Y0
16
09
T4
2W
R3
4−
30
51
R3
4−
30
57
2A
HB
EO
N3
8S
TE
F7
SR
34
−3
05
0D
P0
7V
R3
4−
30
76
46
29
56
02
53
10
20
36
92
23
94
34
R3
4−
30
29
FO
R9
5T
7IZ
1 8A
4V
RQ
RP
PW
R3
4−
30
13
15
16
84
42
79
37
R3
4−
31
81
C3
W4
1R
34
−3
02
27
LL
CL
BD
GW
M0
4W
B3
LF
B1
5W
CU
LS
DY
JG
LR
34
−3
19
5R
34
−3
11
4R
34
−3
16
92
48
73
4R
34
−3
01
9R
34
−3
02
03
MB
4Z
WY
MQ
IL
IT4
QJ9
GM
MR
34
−3
12
7R
34
−3
05
5R
34
−3
17
4R
34
−3
06
7Y
HP
D0
27
64
30
36
55
02
04
94
70
35
45
57
15
43
89 5Z
S1
X4
03
79
0R
34
−3
08
82
55
21
0W
VC
E6
R3
4−
30
32
R3
4−
30
39
R3
4−
30
15
68
G2
D4
62
74
65
08
90
7E
KR
1O
P0
N8
KR
34
−3
14
6K
81
21
J2
9X
81
44
37
0R
34
−3
04
61
47
58
7R
34
−3
06
5H
U4
AA
8P
NF
12
W7
ME
M6
6V
OX
70
3J
SH
TP
BR
D7
KX
BA
5T
C2
Y1
CQ
R3
4−
30
62
00
19
96
R3
4−
31
66
33
68
50
06
20
31
R3
4−
30
75
47
26
99
08
98
48
04
23
97
CV
6JA
13
56
31
38
37
39
R3
4−
32
22
R3
4−
30
18
R3
4−
30
35
44
63
76
11
80
39
R3
4−
32
20
29
98
01
PK
MM
42
79
38
8N
6I9
80
01
33
4R
34
−3
02
4R
34
−3
02
1R
34
−3
15
7G
2Z
0B
N5
O6
85
Z5
2R
R3
4−
31
84
RN
3X
8R
34
−3
18
2R
34
−3
11
1R
UJ9
02
9O
RI
Q7
F2
6U
VV
WA
BL
0S
N7
C7
G1
R3
4−
31
91
R3
4−
32
13
4H
UA
7B
50
V6
NIP
QY
R3
4−
31
18
12
75
30
R3
4−
32
16
47
39
37 0C
NY
CR
34
−3
17
84
D0
HZ
R3
4−
31
12
R3
4−
31
20
MF
II0
X7
1H
5 Y6
BS
G6
U8
ZJ
3U
TO
8F
RIZ
4 26
IET
3G
WV
1R
34
−3
05
90
40
24
1R
34
−3
19
67
NA
98
33
37
93 YS
OF
PR
34
−3
03
3N
8Y
A4
E0
ZK
KV
OD
W3
11
95
71
NB
8E
4R
34
−3
07
2P
HY
03
QD
0Z
V8
CR
CE
V5
VF
12
91
88
06
PU
39
R3
4−
30
89
R3
4−
30
92
3JK
7Y
R3
4−
31
25
05
7G
3R
34
−3
04
1Q
U2
WM
LY2
88
OD
NW
T4
XIL
AQ
QK
9Y
NK
LJL
09
32
09
R3
4−
30
60
R3
4−
30
53
SE
OT
TP
WG
X0
ST
PD
EN
J4
1D
3F
BX
JR
34
−3
10
95
MZ
1D
R3
4−
30
93
F8
P2
5R
34
−3
21
5X
QR
0B
VP
PX
V2
34
32
33
12
94
2R
34
−3
04
54
22
26
4R
34
−3
01
65
W9
08
04
28
61
R3
4−
31
80
10
10
58
R3
4−
31
00
CM
91
7F
U8
OL
R3
4−
30
27
16
66
37
R3
4−
30
99
42
08
81
R3
4−
32
11
R3
4−
32
10
01
54
45
0T
N5
HR
34
−3
09
6R
34
−3
15
13
59
37
01
81
27
21
60
98
64
36
15
40
18
04
43
88
48
3R
34
−3
03
83
02
64
93
23
48
51
73
01
52
18
22
93
34
84
74
36
91
5G
J6
MQ
9L
UM
5R
34
−3
18
3R
34
−3
21
2R
34
−3
16
04
83
39
10
72
78
2R
34
−3
19
22
17
47
5D
H8
X5
−2
XZ
HZ
PR
34
−3
03
1R
34
−3
14
0W
Q9
GV
R3
4−
31
59
FQ
PL
SP
XB
8V
R3
4−
32
06
R3
4−
32
05
36
24
12
37
22
97
14
60
66
R3
4−
31
44
R3
4−
30
14
EH
2W
NR
34
−3
01
1Q
LC
SW
IZC
EG
LJ6
JL
WW
C1
TR
34
−3
15
3M
6A
JV
5Q
BR
PR
34
−3
15
4R
34
−3
03
0
100 200 300 400 500 600
−4
−2
02
4
Isolate
log
2 T
ET
_M
IC
PG 8 PG 16 PG 7 PG 16 PG 15 PG 16 PG 11 PG 16 PG 6 PG 16 PG 3 PG 16 PG 2 PG 14 PG 16 PG 4 PG 9 PG 12 PG 16 PG 1 PG 16 PG 10 PG 5 PG 13 PG 16 PG 8
non−susc.
susceptible
inferred non−susc.
inferred susc.
R3
4−
30
63
36
51
52
R3
4−
31
88
R3
4−
30
34
PC
KM
OIM
AP
Y5
09
36
5E
SB
KM
PN
3IH
8P
Y5
X4
92
70
6K
51
SW
TG
9A
8A
YF
PY
IRE
4I
P4
GIC
R3
4−
31
75
09
53
44
YQ
UA
QR
34
−3
07
9R
34
−3
12
4F
UO
YQ
08
01
04
2E
AK
R3
66
29
3W
LTN
82
10
16
21
48
05
6D
PG
ZI
31
20
34
R3
4−
31
03
05
71
44
RC
BG
R0
OH
1I
AT
BL
M6
EO
69
RM
EO
XR
L3
6E
6U
UP
J6
JS
Y8
R3
4−
30
68
RE
QG
JV
QC
7K
RZ
PN
F1
35
77
11
60
44
91
V4
ME
R3
4−
31
16
Z6
0Y
PL
OO
XY
R3
4−
31
85
WN
YE
LK
MM
CT
R3
4−
32
18
21
81
86
R3
4−
30
73
26
60
35
R3
4−
31
97
BH
CQ
B6
FX
SQ
R3
4−
30
49
R3
4−
31
10
R3
4−
30
61
IZQ
WI
LIW
28
10
34
53
R3
4−
31
22
R3
4−
32
23
R3
4−
30
23
11
00
93
W9
G4
K2
VB
TK
R3
4−
31
08
R3
4−
31
13
QIK
YS
Q0
41
3T
JR
UQ
DA
LR
80
27
99
9R
34
−3
04
3R
34
−3
07
04
39
69
9S
QA
DW
27
73
94
R3
4−
31
93
R3
4−
32
24
R3
4−
31
37
R3
4−
30
28
20
94
64
28
49
68
R3
4−
31
98
GW
TK
7R
34
−3
05
6E
3G
XY
3X
UC
4R
34
−3
16
3B
4R
32
D8
RP
Y5
5N
O4
R3
4−
32
19
UF
G1
AY
89
K0
7R
CF
03
BD
EM
RJB
FJ
30
47
93
F5
UY
4R
34
−3
08
4R
34
−3
21
7R
34
−3
10
10
72
51
1R
34
−3
20
2P
21
3M
06
56
45
R3
4−
31
90
LD
D8
7R
34
−3
07
83
69
82
06
GU
7V
R3
4−
31
41
R3
4−
31
42
R3
4−
30
85
41
61
85
50
35
74
9S
KO
TC
HP
0M
LA
BT
O0
6U
RQ
NF
PT
SD
H8
X5
−1
1Q
JA
PO
QT
RJ
R3
4−
32
21
R3
4−
32
07
10
55
42
R3
4−
30
94
R3
4−
32
00
R3
4−
30
98
40
44
63
20
88
66
20
99
30
R3
4−
30
58
WM
K3
TR
34
−3
02
60
44
74
4R
34
−3
03
70
67
09
4R
34
−3
02
54
K4
C9
R3
4−
30
97
81
LM
XO
0R
HB
O6
1U
70
U6
4I
B1
KM
B1
VD
X8
68
93
ZR
34
−3
22
9C
CV
1H
LS
3O
B4
PY
M0
0N
WX
9R
34
−3
08
7R
34
−3
08
3U
TE
DZ
R3
4−
31
64
R3
4−
31
39
AF
VC
5F
77
ZH
QW
SZ
TR
34
−3
13
1R
34
−3
20
4W
AM
FH
R3
4−
32
27
BZ
2I7
R3
4−
31
72
P1
NM
2R
34
−3
07
4T
8Z
8O
O8
I1E
00
76
49
R3
4−
31
65
W9
GK
OJB
YF
YR
34
−3
04
4R
EA
OU
37
96
78
R3
4−
31
19
R3
4−
30
69
RS
9D
29
D2
5H
W8
IHX
34
YL
EW
G6
0C
R3
4−
30
48
43
81
80
R3
4−
31
15
NA
03
LD
R1
PD
6JT
2I
R3
4−
30
86
14
YE
51
32
57
1U
3E
O1
R3
4−
31
36
17
47
02
R3
4−
31
94
48
16
43
1T
R6
C1
53
43
8U
B6
XH
R3
4−
31
86
48
78
27
22
38
32
01
ZW
MB
JF
60
HR
2T
30
FQ
8K
H8
YK
WA
12
WS
R3
4−
30
47
R3
4−
32
09
0G
B6
KR
34
−3
12
32
8P
CJ
O3
45
21
LQ
KE
5X
CD
5U
NU
OJ
DN
B9
0O
SE
Y6
TV
66
E3
97
07
91
8F
DW
8Q
TW
4X
VM
DP
Z4
95
2R
34
−3
17
9H
B7
S5
R3
4−
31
99
CS
I7H
R3
4−
30
40
R3
4−
31
50
R3
4−
30
36
IB8
MW
R3
4−
30
77
XC
B6
6S
LX
Y1
R3
4−
31
26
R3
4−
31
30
R3
4−
31
58
R3
4−
30
64
R3
4−
31
38
KR
HY
AW
5H
GR
UJE
CB
T8
K2
6R
34
−3
22
5R
34
−3
22
6R
34
−3
10
23
03
65
6Z
PN
7P
OZ
J9
FR
34
−3
17
3R
34
−3
12
11
87
40
6R
34
−3
14
9R
34
−3
17
0H
3Q
9M
10
27
20
R3
4−
30
52
R3
4−
30
81
KY
DZ
M0
74
12
43
86
32
9R
34
−3
14
7R
34
−3
15
5R
34
−3
07
1R
34
−3
20
3R
34
−3
20
82
8I7
HF
1O
DP
F1
G5
RE
4N
SI
45
97
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0
Supplementary Figure 3: MIC intervals for individual isolates in the RASE database. The plot illustrates MIC
intervals and point values extracted from. Each panel corresponds to a single antibiotic, while vertical lines and points
correspond to individual isolates. Their colors correspond to the resistance category after applying a breakpoint
(horizontal lines). When a resistance category could not be assigned directly (i.e., in case of an interval crossing the
breakpoint line), then it was inferred using ancestral state reconstruction.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
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O0RHB
O61U7
0U64I
B1KMB
1VDX8
6893Z
R34-3229
CCV1H
LS3OB
4PYM0
0NWX9
R34-3087
R34-3083
UTEDZ
R34-3164
R34-3139
AFVC5
F77ZH
QWSZT
R34-3131
R34-3204
WAMFH
R34-3227
BZ2I7
R34-3172
P1NM2
R34-3074
T8Z8O
O8I1E
007649
R34-3165
W9GKO
JBYFY
R34-3044
REAOU
379678
R34-3119
R34-3069
RS9D2
9D25H
W8IHX
34YLE
WG60C
R34-3048
438180
R34-3115
NA03L
DR1PD
6JT2I
R34-3086
14YE5
132571
U3EO1
R34-3136
174702
R34-3194
481643
1TR6C
153438
UB6XH
R34-3186
487827
223832
01ZWM
BJF60
HR2T3
0FQ8K
H8YKW
A12WS
R34-3047
R34-3209
0GB6K
R34-3123
28PCJ
O3452
1LQKE
5XCD5
UNUOJ
DNB90
OSEY6
TV66E
397079
18FDW
8QTW4
XVMDP
Z4952
R34-3179
HB7S5
R34-3199
CSI7H
R34-3040
R34-3150
R34-3036
IB8MW
R34-3077
XCB66
SLXY1
R34-3126
R34-3130
R34-3158
R34-3064
R34-3138
KRHYA
W5HGR
UJECB
T8K26
R34-3225
R34-3226
R34-3102
303656
ZPN7P
OZJ9F
R34-3173
R34-3121
187406
R34-3149
R34-3170
H3Q9M
102720
R34-3052
R34-3081
KYDZM
074124
386329
R34-3147
R34-3155
R34-3071
R34-3203
R34-3208
28I7H
F1ODP
F1G5R
E4NSI
459747
QHXZZ
R34-3214
T14BF
R34-3054
RAV85
6CO3C
8G3XE
8AH8E
335574
J1LX6
DFS2Q
R52DJ
3YFA4
263137
FP9DM
XCJ97
242588
HWJVH
R34-3095
389109
6ZCAZ
R34-3156
9ABKR
RQ6NH
R34-3228
R34-3080
F7IXH
5J97G
K9N0O
342672
CXQ2T
R34-3201
065435
179743
108480
051715
448643
R34-3171
R34-3168
AI3GZ
2RLC4
R34-3176
430772
341365
R34-3231
R34-3230
268660
306435
142534
R34-3012
R34-3090
R34-3082
R34-3187
FJZZW
385385
FBPNS
RWZJE
163286
120581
R34-3167
DQKYE
035100
Q3H1U
120T7
153408
R34-3017
R34-3143
R34-3091
I0UZQ
R34-3189
ZXPKH
R34-3177
CJISL
94ORH
Y0160
9T42W
R34-3051
R34-3057
2AHBE
ON38S
TEF7S
R34-3050
DP07V
R34-3076
462956
025310
203692
239434
R34-3029
FOR95
T7IZ1
8A4VR
QRPPW
R34-3013
151684
427937
R34-3181
C3W41
R34-3022
7LLCL
BDGWM
04WB3
LFB15
WCULS
DYJGL
R34-3195
R34-3114
R34-3169
248734
R34-3019
R34-3020
3MB4Z
WYMQI
LIT4Q
J9GMM
R34-3127
R34-3055
R34-3174
R34-3067
YHPD0
276430
365502
049470
354557
154389
5ZS1X
403790
R34-3088
255210
WVCE6
R34-3032
R34-3039
R34-3015
68G2D
462746
508907
EKR1O
P0N8K
R34-3146
K8121
J29X8
144370
R34-3046
147587
R34-3065
HU4AA
8PNF1
2W7ME
M66VO
X703J
SHTPB
RD7KX
BA5TC
2Y1CQ
R34-3062
001996
R34-3166
336850
062031
R34-3075
472699
089848
042397
CV6JA
135631
383739
R34-3222
R34-3018
R34-3035
446376
118039
R34-3220
299801
PKMM4
279388
N6I98
001334
R34-3024
R34-3021
R34-3157
G2Z0B
N5O68
5Z52R
R34-3184
RN3X8
R34-3182
R34-3111
RUJ90
29ORI
Q7F26
UVVWA
BL0SN
7C7G1
R34-3191
R34-3213
4HUA7
B50V6
NIPQY
R34-3118
127530
R34-3216
473937
0CNYC
R34-3178
4D0HZ
R34-3112
R34-3120
MFII0
X71H5
Y6BSG
6U8ZJ
3UTO8
FRIZ4
26IET
3GWV1
R34-3059
040241
R34-3196
7NA98
333793
YSOFP
R34-3033
N8YA4
E0ZKK
VODW3
119571
NB8E4
R34-3072
PHY03
QD0ZV
8CRCE
V5VF1
291880
6PU39
R34-3089
R34-3092
3JK7Y
R34-3125
057G3
R34-3041
QU2WM
LY288
ODNWT
4XILA
QQK9Y
NKLJL
093209
R34-3060
R34-3053
SEOTT
PWGX0
STPDE
NJ41D
3FBXJ
R34-3109
5MZ1D
R34-3093
F8P25
R34-3215
XQR0B
VPPXV
234323
312942
R34-3045
422264
R34-3016
5W908
042861
R34-3180
101058
R34-3100
CM917
FU8OL
R34-3027
166637
R34-3099
420881
R34-3211
R34-3210
015445
0TN5H
R34-3096
R34-3151
359370
181272
160986
436154
018044
388483
R34-3038
302649
323485
173015
218229
334847
436915
GJ6MQ
9LUM5
R34-3183
R34-3212
R34-3160
483391
072782
R34-3192
217475
DH8X5-2
XZHZP
R34-3031
R34-3140
WQ9GV
R34-3159
FQPLS
PXB8V
R34-3206
R34-3205
362412
372297
146066
R34-3144
R34-3014
EH2WN
R34-3011
QLCSW
IZCEG
LJ6JL
WWC1T
R34-3153
M6AJV
5QBRP
R34-3154
R34-3030
CRO
0.125585
R34-3063
365152
R34-3188
R34-3034
PCKMO
IMAPY
509365
ESBKM
PN3IH
8PY5X
492706
K51SW
TG9A8
AYFPY
IRE4I
P4GIC
R34-3175
095344
YQUAQ
R34-3079
R34-3124
FUOYQ
080104
2EAKR
366293
WLTN8
210162
148056
DPGZI
312034
R34-3103
057144
RCBGR
0OH1I
ATBLM
6EO69
RMEOX
RL36E
6UUPJ
6JSY8
R34-3068
REQGJ
VQC7K
RZPNF
135771
160449
1V4ME
R34-3116
Z60YP
LOOXY
R34-3185
WNYEL
KMMCT
R34-3218
218186
R34-3073
266035
R34-3197
BHCQB
6FXSQ
R34-3049
R34-3110
R34-3061
IZQWI
LIW28
103453
R34-3122
R34-3223
R34-3023
110093
W9G4K
2VBTK
R34-3108
R34-3113
QIKYS
Q0413
TJRUQ
DALR8
027999
R34-3043
R34-3070
439699
SQADW
277394
R34-3193
R34-3224
R34-3137
R34-3028
209464
284968
R34-3198
GWTK7
R34-3056
E3GXY
3XUC4
R34-3163
B4R32
D8RPY
55NO4
R34-3219
UFG1A
Y89K0
7RCF0
3BDEM
RJBFJ
304793
F5UY4
R34-3084
R34-3217
R34-3101
072511
R34-3202
P213M
065645
R34-3190
LDD87
R34-3078
369820
6GU7V
R34-3141
R34-3142
R34-3085
416185
503574
9SKOT
CHP0M
LABTO
06URQ
NFPTS
DH8X5-1
1QJAP
OQTRJ
R34-3221
R34-3207
105542
R34-3094
R34-3200
R34-3098
404463
208866
209930
R34-3058
WMK3T
R34-3026
044744
R34-3037
067094
R34-3025
4K4C9
R34-3097
81LMX
O0RHB
O61U7
0U64I
B1KMB
1VDX8
6893Z
R34-3229
CCV1H
LS3OB
4PYM0
0NWX9
R34-3087
R34-3083
UTEDZ
R34-3164
R34-3139
AFVC5
F77ZH
QWSZT
R34-3131
R34-3204
WAMFH
R34-3227
BZ2I7
R34-3172
P1NM2
R34-3074
T8Z8O
O8I1E
007649
R34-3165
W9GKO
JBYFY
R34-3044
REAOU
379678
R34-3119
R34-3069
RS9D2
9D25H
W8IHX
34YLE
WG60C
R34-3048
438180
R34-3115
NA03L
DR1PD
6JT2I
R34-3086
14YE5
132571
U3EO1
R34-3136
174702
R34-3194
481643
1TR6C
153438
UB6XH
R34-3186
487827
223832
01ZWM
BJF60
HR2T3
0FQ8K
H8YKW
A12WS
R34-3047
R34-3209
0GB6K
R34-3123
28PCJ
O3452
1LQKE
5XCD5
UNUOJ
DNB90
OSEY6
TV66E
397079
18FDW
8QTW4
XVMDP
Z4952
R34-3179
HB7S5
R34-3199
CSI7H
R34-3040
R34-3150
R34-3036
IB8MW
R34-3077
XCB66
SLXY1
R34-3126
R34-3130
R34-3158
R34-3064
R34-3138
KRHYA
W5HGR
UJECB
T8K26
R34-3225
R34-3226
R34-3102
303656
ZPN7P
OZJ9F
R34-3173
R34-3121
187406
R34-3149
R34-3170
H3Q9M
102720
R34-3052
R34-3081
KYDZM
074124
386329
R34-3147
R34-3155
R34-3071
R34-3203
R34-3208
28I7H
F1ODP
F1G5R
E4NSI
459747
QHXZZ
R34-3214
T14BF
R34-3054
RAV85
6CO3C
8G3XE
8AH8E
335574
J1LX6
DFS2Q
R52DJ
3YFA4
263137
FP9DM
XCJ97
242588
HWJVH
R34-3095
389109
6ZCAZ
R34-3156
9ABKR
RQ6NH
R34-3228
R34-3080
F7IXH
5J97G
K9N0O
342672
CXQ2T
R34-3201
065435
179743
108480
051715
448643
R34-3171
R34-3168
AI3GZ
2RLC4
R34-3176
430772
341365
R34-3231
R34-3230
268660
306435
142534
R34-3012
R34-3090
R34-3082
R34-3187
FJZZW
385385
FBPNS
RWZJE
163286
120581
R34-3167
DQKYE
035100
Q3H1U
120T7
153408
R34-3017
R34-3143
R34-3091
I0UZQ
R34-3189
ZXPKH
R34-3177
CJISL
94ORH
Y0160
9T42W
R34-3051
R34-3057
2AHBE
ON38S
TEF7S
R34-3050
DP07V
R34-3076
462956
025310
203692
239434
R34-3029
FOR95
T7IZ1
8A4VR
QRPPW
R34-3013
151684
427937
R34-3181
C3W41
R34-3022
7LLCL
BDGWM
04WB3
LFB15
WCULS
DYJGL
R34-3195
R34-3114
R34-3169
248734
R34-3019
R34-3020
3MB4Z
WYMQI
LIT4Q
J9GMM
R34-3127
R34-3055
R34-3174
R34-3067
YHPD0
276430
365502
049470
354557
154389
5ZS1X
403790
R34-3088
255210
WVCE6
R34-3032
R34-3039
R34-3015
68G2D
462746
508907
EKR1O
P0N8K
R34-3146
K8121
J29X8
144370
R34-3046
147587
R34-3065
HU4AA
8PNF1
2W7ME
M66VO
X703J
SHTPB
RD7KX
BA5TC
2Y1CQ
R34-3062
001996
R34-3166
336850
062031
R34-3075
472699
089848
042397
CV6JA
135631
383739
R34-3222
R34-3018
R34-3035
446376
118039
R34-3220
299801
PKMM4
279388
N6I98
001334
R34-3024
R34-3021
R34-3157
G2Z0B
N5O68
5Z52R
R34-3184
RN3X8
R34-3182
R34-3111
RUJ90
29ORI
Q7F26
UVVWA
BL0SN
7C7G1
R34-3191
R34-3213
4HUA7
B50V6
NIPQY
R34-3118
127530
R34-3216
473937
0CNYC
R34-3178
4D0HZ
R34-3112
R34-3120
MFII0
X71H5
Y6BSG
6U8ZJ
3UTO8
FRIZ4
26IET
3GWV1
R34-3059
040241
R34-3196
7NA98
333793
YSOFP
R34-3033
N8YA4
E0ZKK
VODW3
119571
NB8E4
R34-3072
PHY03
QD0ZV
8CRCE
V5VF1
291880
6PU39
R34-3089
R34-3092
3JK7Y
R34-3125
057G3
R34-3041
QU2WM
LY288
ODNWT
4XILA
QQK9Y
NKLJL
093209
R34-3060
R34-3053
SEOTT
PWGX0
STPDE
NJ41D
3FBXJ
R34-3109
5MZ1D
R34-3093
F8P25
R34-3215
XQR0B
VPPXV
234323
312942
R34-3045
422264
R34-3016
5W908
042861
R34-3180
101058
R34-3100
CM917
FU8OL
R34-3027
166637
R34-3099
420881
R34-3211
R34-3210
015445
0TN5H
R34-3096
R34-3151
359370
181272
160986
436154
018044
388483
R34-3038
302649
323485
173015
218229
334847
436915
GJ6MQ
9LUM5
R34-3183
R34-3212
R34-3160
483391
072782
R34-3192
217475
DH8X5-2
XZHZP
R34-3031
R34-3140
WQ9GV
R34-3159
FQPLS
PXB8V
R34-3206
R34-3205
362412
372297
146066
R34-3144
R34-3014
EH2WN
R34-3011
QLCSW
IZCEG
LJ6JL
WWC1T
R34-3153
M6AJV
5QBRP
R34-3154
R34-3030
TMP
0.125585
R34-3063
365152
R34-3188
R34-3034
PCKMO
IMAPY
509365
ESBKM
PN3IH
8PY5X
492706
K51SW
TG9A8
AYFPY
IRE4I
P4GIC
R34-3175
095344
YQUAQ
R34-3079
R34-3124
FUOYQ
080104
2EAKR
366293
WLTN8
210162
148056
DPGZI
312034
R34-3103
057144
RCBGR
0OH1I
ATBLM
6EO69
RMEOX
RL36E
6UUPJ
6JSY8
R34-3068
REQGJ
VQC7K
RZPNF
135771
160449
1V4ME
R34-3116
Z60YP
LOOXY
R34-3185
WNYEL
KMMCT
R34-3218
218186
R34-3073
266035
R34-3197
BHCQB
6FXSQ
R34-3049
R34-3110
R34-3061
IZQWI
LIW28
103453
R34-3122
R34-3223
R34-3023
110093
W9G4K
2VBTK
R34-3108
R34-3113
QIKYS
Q0413
TJRUQ
DALR8
027999
R34-3043
R34-3070
439699
SQADW
277394
R34-3193
R34-3224
R34-3137
R34-3028
209464
284968
R34-3198
GWTK7
R34-3056
E3GXY
3XUC4
R34-3163
B4R32
D8RPY
55NO4
R34-3219
UFG1A
Y89K0
7RCF0
3BDEM
RJBFJ
304793
F5UY4
R34-3084
R34-3217
R34-3101
072511
R34-3202
P213M
065645
R34-3190
LDD87
R34-3078
369820
6GU7V
R34-3141
R34-3142
R34-3085
416185
503574
9SKOT
CHP0M
LABTO
06URQ
NFPTS
DH8X5-1
1QJAP
OQTRJ
R34-3221
R34-3207
105542
R34-3094
R34-3200
R34-3098
404463
208866
209930
R34-3058
WMK3T
R34-3026
044744
R34-3037
067094
R34-3025
4K4C9
R34-3097
81LMX
O0RHB
O61U7
0U64I
B1KMB
1VDX8
6893Z
R34-3229
CCV1H
LS3OB
4PYM0
0NWX9
R34-3087
R34-3083
UTEDZ
R34-3164
R34-3139
AFVC5
F77ZH
QWSZT
R34-3131
R34-3204
WAMFH
R34-3227
BZ2I7
R34-3172
P1NM2
R34-3074
T8Z8O
O8I1E
007649
R34-3165
W9GKO
JBYFY
R34-3044
REAOU
379678
R34-3119
R34-3069
RS9D2
9D25H
W8IHX
34YLE
WG60C
R34-3048
438180
R34-3115
NA03L
DR1PD
6JT2I
R34-3086
14YE5
132571
U3EO1
R34-3136
174702
R34-3194
481643
1TR6C
153438
UB6XH
R34-3186
487827
223832
01ZWM
BJF60
HR2T3
0FQ8K
H8YKW
A12WS
R34-3047
R34-3209
0GB6K
R34-3123
28PCJ
O3452
1LQKE
5XCD5
UNUOJ
DNB90
OSEY6
TV66E
397079
18FDW
8QTW4
XVMDP
Z4952
R34-3179
HB7S5
R34-3199
CSI7H
R34-3040
R34-3150
R34-3036
IB8MW
R34-3077
XCB66
SLXY1
R34-3126
R34-3130
R34-3158
R34-3064
R34-3138
KRHYA
W5HGR
UJECB
T8K26
R34-3225
R34-3226
R34-3102
303656
ZPN7P
OZJ9F
R34-3173
R34-3121
187406
R34-3149
R34-3170
H3Q9M
102720
R34-3052
R34-3081
KYDZM
074124
386329
R34-3147
R34-3155
R34-3071
R34-3203
R34-3208
28I7H
F1ODP
F1G5R
E4NSI
459747
QHXZZ
R34-3214
T14BF
R34-3054
RAV85
6CO3C
8G3XE
8AH8E
335574
J1LX6
DFS2Q
R52DJ
3YFA4
263137
FP9DM
XCJ97
242588
HWJVH
R34-3095
389109
6ZCAZ
R34-3156
9ABKR
RQ6NH
R34-3228
R34-3080
F7IXH
5J97G
K9N0O
342672
CXQ2T
R34-3201
065435
179743
108480
051715
448643
R34-3171
R34-3168
AI3GZ
2RLC4
R34-3176
430772
341365
R34-3231
R34-3230
268660
306435
142534
R34-3012
R34-3090
R34-3082
R34-3187
FJZZW
385385
FBPNS
RWZJE
163286
120581
R34-3167
DQKYE
035100
Q3H1U
120T7
153408
R34-3017
R34-3143
R34-3091
I0UZQ
R34-3189
ZXPKH
R34-3177
CJISL
94ORH
Y0160
9T42W
R34-3051
R34-3057
2AHBE
ON38S
TEF7S
R34-3050
DP07V
R34-3076
462956
025310
203692
239434
R34-3029
FOR95
T7IZ1
8A4VR
QRPPW
R34-3013
151684
427937
R34-3181
C3W41
R34-3022
7LLCL
BDGWM
04WB3
LFB15
WCULS
DYJGL
R34-3195
R34-3114
R34-3169
248734
R34-3019
R34-3020
3MB4Z
WYMQI
LIT4Q
J9GMM
R34-3127
R34-3055
R34-3174
R34-3067
YHPD0
276430
365502
049470
354557
154389
5ZS1X
403790
R34-3088
255210
WVCE6
R34-3032
R34-3039
R34-3015
68G2D
462746
508907
EKR1O
P0N8K
R34-3146
K8121
J29X8
144370
R34-3046
147587
R34-3065
HU4AA
8PNF1
2W7ME
M66VO
X703J
SHTPB
RD7KX
BA5TC
2Y1CQ
R34-3062
001996
R34-3166
336850
062031
R34-3075
472699
089848
042397
CV6JA
135631
383739
R34-3222
R34-3018
R34-3035
446376
118039
R34-3220
299801
PKMM4
279388
N6I98
001334
R34-3024
R34-3021
R34-3157
G2Z0B
N5O68
5Z52R
R34-3184
RN3X8
R34-3182
R34-3111
RUJ90
29ORI
Q7F26
UVVWA
BL0SN
7C7G1
R34-3191
R34-3213
4HUA7
B50V6
NIPQY
R34-3118
127530
R34-3216
473937
0CNYC
R34-3178
4D0HZ
R34-3112
R34-3120
MFII0
X71H5
Y6BSG
6U8ZJ
3UTO8
FRIZ4
26IET
3GWV1
R34-3059
040241
R34-3196
7NA98
333793
YSOFP
R34-3033
N8YA4
E0ZKK
VODW3
119571
NB8E4
R34-3072
PHY03
QD0ZV
8CRCE
V5VF1
291880
6PU39
R34-3089
R34-3092
3JK7Y
R34-3125
057G3
R34-3041
QU2WM
LY288
ODNWT
4XILA
QQK9Y
NKLJL
093209
R34-3060
R34-3053
SEOTT
PWGX0
STPDE
NJ41D
3FBXJ
R34-3109
5MZ1D
R34-3093
F8P25
R34-3215
XQR0B
VPPXV
234323
312942
R34-3045
422264
R34-3016
5W908
042861
R34-3180
101058
R34-3100
CM917
FU8OL
R34-3027
166637
R34-3099
420881
R34-3211
R34-3210
015445
0TN5H
R34-3096
R34-3151
359370
181272
160986
436154
018044
388483
R34-3038
302649
323485
173015
218229
334847
436915
GJ6MQ
9LUM5
R34-3183
R34-3212
R34-3160
483391
072782
R34-3192
217475
DH8X5-2
XZHZP
R34-3031
R34-3140
WQ9GV
R34-3159
FQPLS
PXB8V
R34-3206
R34-3205
362412
372297
146066
R34-3144
R34-3014
EH2WN
R34-3011
QLCSW
IZCEG
LJ6JL
WWC1T
R34-3153
M6AJV
5QBRP
R34-3154
R34-3030
ERY
0.125585
R34-3063
365152
R34-3188
R34-3034
PCKMO
IMAPY
509365
ESBKM
PN3IH
8PY5X
492706
K51SW
TG9A8
AYFPY
IRE4I
P4GIC
R34-3175
095344
YQUAQ
R34-3079
R34-3124
FUOYQ
080104
2EAKR
366293
WLTN8
210162
148056
DPGZI
312034
R34-3103
057144
RCBGR
0OH1I
ATBLM
6EO69
RMEOX
RL36E
6UUPJ
6JSY8
R34-3068
REQGJ
VQC7K
RZPNF
135771
160449
1V4ME
R34-3116
Z60YP
LOOXY
R34-3185
WNYEL
KMMCT
R34-3218
218186
R34-3073
266035
R34-3197
BHCQB
6FXSQ
R34-3049
R34-3110
R34-3061
IZQWI
LIW28
103453
R34-3122
R34-3223
R34-3023
110093
W9G4K
2VBTK
R34-3108
R34-3113
QIKYS
Q0413
TJRUQ
DALR8
027999
R34-3043
R34-3070
439699
SQADW
277394
R34-3193
R34-3224
R34-3137
R34-3028
209464
284968
R34-3198
GWTK7
R34-3056
E3GXY
3XUC4
R34-3163
B4R32
D8RPY
55NO4
R34-3219
UFG1A
Y89K0
7RCF0
3BDEM
RJBFJ
304793
F5UY4
R34-3084
R34-3217
R34-3101
072511
R34-3202
P213M
065645
R34-3190
LDD87
R34-3078
369820
6GU7V
R34-3141
R34-3142
R34-3085
416185
503574
9SKOT
CHP0M
LABTO
06URQ
NFPTS
DH8X5-1
1QJAP
OQTRJ
R34-3221
R34-3207
105542
R34-3094
R34-3200
R34-3098
404463
208866
209930
R34-3058
WMK3T
R34-3026
044744
R34-3037
067094
R34-3025
4K4C9
R34-3097
81LMX
O0RHB
O61U7
0U64I
B1KMB
1VDX8
6893Z
R34-3229
CCV1H
LS3OB
4PYM0
0NWX9
R34-3087
R34-3083
UTEDZ
R34-3164
R34-3139
AFVC5
F77ZH
QWSZT
R34-3131
R34-3204
WAMFH
R34-3227
BZ2I7
R34-3172
P1NM2
R34-3074
T8Z8O
O8I1E
007649
R34-3165
W9GKO
JBYFY
R34-3044
REAOU
379678
R34-3119
R34-3069
RS9D2
9D25H
W8IHX
34YLE
WG60C
R34-3048
438180
R34-3115
NA03L
DR1PD
6JT2I
R34-3086
14YE5
132571
U3EO1
R34-3136
174702
R34-3194
481643
1TR6C
153438
UB6XH
R34-3186
487827
223832
01ZWM
BJF60
HR2T3
0FQ8K
H8YKW
A12WS
R34-3047
R34-3209
0GB6K
R34-3123
28PCJ
O3452
1LQKE
5XCD5
UNUOJ
DNB90
OSEY6
TV66E
397079
18FDW
8QTW4
XVMDP
Z4952
R34-3179
HB7S5
R34-3199
CSI7H
R34-3040
R34-3150
R34-3036
IB8MW
R34-3077
XCB66
SLXY1
R34-3126
R34-3130
R34-3158
R34-3064
R34-3138
KRHYA
W5HGR
UJECB
T8K26
R34-3225
R34-3226
R34-3102
303656
ZPN7P
OZJ9F
R34-3173
R34-3121
187406
R34-3149
R34-3170
H3Q9M
102720
R34-3052
R34-3081
KYDZM
074124
386329
R34-3147
R34-3155
R34-3071
R34-3203
R34-3208
28I7H
F1ODP
F1G5R
E4NSI
459747
QHXZZ
R34-3214
T14BF
R34-3054
RAV85
6CO3C
8G3XE
8AH8E
335574
J1LX6
DFS2Q
R52DJ
3YFA4
263137
FP9DM
XCJ97
242588
HWJVH
R34-3095
389109
6ZCAZ
R34-3156
9ABKR
RQ6NH
R34-3228
R34-3080
F7IXH
5J97G
K9N0O
342672
CXQ2T
R34-3201
065435
179743
108480
051715
448643
R34-3171
R34-3168
AI3GZ
2RLC4
R34-3176
430772
341365
R34-3231
R34-3230
268660
306435
142534
R34-3012
R34-3090
R34-3082
R34-3187
FJZZW
385385
FBPNS
RWZJE
163286
120581
R34-3167
DQKYE
035100
Q3H1U
120T7
153408
R34-3017
R34-3143
R34-3091
I0UZQ
R34-3189
ZXPKH
R34-3177
CJISL
94ORH
Y0160
9T42W
R34-3051
R34-3057
2AHBE
ON38S
TEF7S
R34-3050
DP07V
R34-3076
462956
025310
203692
239434
R34-3029
FOR95
T7IZ1
8A4VR
QRPPW
R34-3013
151684
427937
R34-3181
C3W41
R34-3022
7LLCL
BDGWM
04WB3
LFB15
WCULS
DYJGL
R34-3195
R34-3114
R34-3169
248734
R34-3019
R34-3020
3MB4Z
WYMQI
LIT4Q
J9GMM
R34-3127
R34-3055
R34-3174
R34-3067
YHPD0
276430
365502
049470
354557
154389
5ZS1X
403790
R34-3088
255210
WVCE6
R34-3032
R34-3039
R34-3015
68G2D
462746
508907
EKR1O
P0N8K
R34-3146
K8121
J29X8
144370
R34-3046
147587
R34-3065
HU4AA
8PNF1
2W7ME
M66VO
X703J
SHTPB
RD7KX
BA5TC
2Y1CQ
R34-3062
001996
R34-3166
336850
062031
R34-3075
472699
089848
042397
CV6JA
135631
383739
R34-3222
R34-3018
R34-3035
446376
118039
R34-3220
299801
PKMM4
279388
N6I98
001334
R34-3024
R34-3021
R34-3157
G2Z0B
N5O68
5Z52R
R34-3184
RN3X8
R34-3182
R34-3111
RUJ90
29ORI
Q7F26
UVVWA
BL0SN
7C7G1
R34-3191
R34-3213
4HUA7
B50V6
NIPQY
R34-3118
127530
R34-3216
473937
0CNYC
R34-3178
4D0HZ
R34-3112
R34-3120
MFII0
X71H5
Y6BSG
6U8ZJ
3UTO8
FRIZ4
26IET
3GWV1
R34-3059
040241
R34-3196
7NA98
333793
YSOFP
R34-3033
N8YA4
E0ZKK
VODW3
119571
NB8E4
R34-3072
PHY03
QD0ZV
8CRCE
V5VF1
291880
6PU39
R34-3089
R34-3092
3JK7Y
R34-3125
057G3
R34-3041
QU2WM
LY288
ODNWT
4XILA
QQK9Y
NKLJL
093209
R34-3060
R34-3053
SEOTT
PWGX0
STPDE
NJ41D
3FBXJ
R34-3109
5MZ1D
R34-3093
F8P25
R34-3215
XQR0B
VPPXV
234323
312942
R34-3045
422264
R34-3016
5W908
042861
R34-3180
101058
R34-3100
CM917
FU8OL
R34-3027
166637
R34-3099
420881
R34-3211
R34-3210
015445
0TN5H
R34-3096
R34-3151
359370
181272
160986
436154
018044
388483
R34-3038
302649
323485
173015
218229
334847
436915
GJ6MQ
9LUM5
R34-3183
R34-3212
R34-3160
483391
072782
R34-3192
217475
DH8X5-2
XZHZP
R34-3031
R34-3140
WQ9GV
R34-3159
FQPLS
PXB8V
R34-3206
R34-3205
362412
372297
146066
R34-3144
R34-3014
EH2WN
R34-3011
QLCSW
IZCEG
LJ6JL
WWC1T
R34-3153
M6AJV
5QBRP
R34-3154
R34-3030
TET
0.125585
Supplementary Figure 4: Ancestral state reconstruction of resistance categories in the RASE database.
Each panel corresponds to a single antibiotic and displays the database phylogenetic tree, colored according to the
reconstructed resistance categories for the antibiotic (blue, green, red, violet correspond to ‘susceptible’, ‘unknown
– inferred susceptible’, ‘non-susceptible’, ‘unknown – inferred non-susceptible’, respectively).
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
10 15 20 25 30 35 40
050
010
0015
0020
0025
00
k
#k−
mer
s (x
1000
)
k
Subword complexity function of S. pneumoniae
S.pneumoniaeRandom DNAAsymptote
Supplementary Figure 5: Subword complexity of pneumococcus. The plot depicts the number of canonical
k-mers as a function of k for S.pneumoniae ATCC 700669 (NC_011900.1) and for a random DNA text containing all
possible k-mers. For k<10, the pneumococcus k-mer composition is similar to the one of random text. For k > 14,
the k-mer sets are almost saturated and the complexity grows very slowly. Since the genome has a finite length
and is circular, the function has an asymptote, which would be attained for k equal to the length of the genome
(2,221,315). The highlighted region corresponds to the range of k values, which are suitable for use in RASE. Note
that k-mers longer than 32 are not currently supported by ProPhyle.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
20 25 30
020
4060
Index
NA
PG
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
● SP01SP02SP03SP04SP05SP06SP07SP08SP09
20 25 30
020
4060
Index
NA
PG
2
●● ●
●
●
●●
●●
●● ●
●● ● ● ●
20 25 30
020
4060
NA
Isol
ate
●
●● ● ● ● ● ● ● ● ● ● ●
● ● ● ●
Supplementary Figure 6: Delays in prediction based on the k-mer length. The plot displays delays in prediction
as a function of the used k-mer length, for all experiments and all possible k-mer lengths. Each horizontal panel
displays times required for stabilization of one of the three predictions: phylogroup (PG), alternative phylogroup
(PG2), and closest isolate (Isolate). Every column within a panel corresponds to a single k-mer length. When
the required time exceeded 1 hour, the point is displayed at the top. Experiments where phylogroup could not be
identified are plotted in red. The highlighted column corresponds to the k-mer length used for constructing RASE.
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint
Supplementary Table 1: Prevalence of resistance phenotypes across phylogroups. For all sequencing ex-
periments, the table displays the best matching isolates, the strain MIC and all measurements of database MICs
(the original reported values or categories inferred using ancestral state reconstruction when not available, retested
values, and the resulting resistance categories).
Supplementary Table 2: Metadata for all isolates included in the RASE database. Each record contains the
strain’s taxid, phylogroup, serotype, sequence type (ST), order in the phylogenetic tree, and three fields related to
resistance for every antibiotics: the ‘_mic’, ‘_int’, ‘_cat’ fields contain the original published MIC information (possibly
corrected after retesting), the extracted MIC interval, and the resulting category after ancestral state reconstruction
(S = susceptible, R = non-susceptible, s = unknown but reconstructed susceptible, r = unknown but reconstructed
non-susceptible), respectively.
Supplementary Table 3: Additional MIC measurements for selected strains. The table contains results from
strain retesting. Each record contains date when the retesting was done, the antibiotic, the measured MIC, and the
corresponding resistance category according the RASE breakpoints.
Supplementary Table 4: Overview of performed resistance tests. For all sequencing experiments, the table
displays the best matching isolates, the strain MIC and all measurements of database MICs (the original reported
values or categories inferred using ancestral state reconstruction when not available, retested values, and the re-
sulting resistance categories).
.CC-BY-NC 4.0 International licenseacertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under
The copyright holder for this preprint (which was notthis version posted August 29, 2018. ; https://doi.org/10.1101/403204doi: bioRxiv preprint