diagnostics of infectious bacteria is dependent upon a
TRANSCRIPT
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Diagnostics of Infectious Bacteria is Dependent upon a Reliable and Comprehensive Identification and Taxonomy Framework
protein DNA
genomeproteome
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Mass ( m/ z)
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V o y a g e r S p e c # 1 = > A d v B C ( 3 2 , 0 . 5 , 1 . 0 ) = > N F 0 . 7 [ B P = 4 4 2 3 . 9 , 2 1 1 7 ]
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microbial typing
and identification
20170914; ECCO Annual Meeting 2017; Brno, CZ
E. R. B. Moore et al.
CCUG, Department of Clinical Microbiology, Sahlgrenska University HospitalDepartment of Infectious Disease, Sahlgrenska Academy, University of Gothenburg, Sweden
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Established 1968 (Curator: E. Falsen, 1968 – 2004; E. Moore, 2004 - ?)
Elisabeth Inganäs, BMA (1991), Maria Ohlén, BMA (1992), Susanne Jensie-Markopolous, BMA (2002), Sofia Cardew, BMA (2007)Kent Molin, Chemist (2001), Liselott Svensson-Stadler, Enhetschef (2012)
Created as a unit within the Bacteriological Laboratory of the Dept Clinical Bacteriology, Sahlgrenska University-Hospital (SU)SU is a teaching and research hospital
Associated with Univ Gothenburg through Sahlgrenska Academy
Repository for reference strains (> 40,000) of microorganisms and typing lab for the identification of bacteria from clinical samplesfrom SU and other hospitals and clinics in Scandinavia
1. Typing and identification: phenotyping and genotyping2. Archiving, storing, distributing bacterial strains (some few yeast, fungi)3. Research: systematics / diagnostics / antibiotic resistance
Culture Collection, University of Gothenburg (CCUG)www.ccug.se
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”problematic” strains sent from Routine Lab to CCUG Typing Lab for analyses
Characterization typingIdentification species or sub-species
determinations
SU BaktLab receives approximately 5,000 samples / weekfrom the Hosptial for microbiological processing
? How do we characterise and identify individual stainsin the diversity of prokaryotes, in the diversity of ecosystems ?
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What are the “problematic” organisms?
bacterial strains that are not differentiated from similar and
closely related bacteria.
bacterial strains that are “new”, i.e., they do not fit a
database profile;
in the CCUG, as many as 150 new ’cases’ per year!
Coming from clinical samples!!
need effective, reliable characterisation and identification!!!!!
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Genotypic/Phylogenetic emphasis in bacterial systematics
• The Bergey’s Manuals for Systematic Bacteriology and The Prokaryotesbased on 16S rRNA gene sequence-based phylogenies.
• 16S rRNA gene sequence determination and analysis the only singletest required for the description of all new bacterial species.
• Genomic DNA-DNA similarities have been the genotypic criterion for defining bacterial species
"Gold Standard ” ?
1 Wayne et al. 1987, Report of the ad-hoc committee on reconcilliationof approaches to bacterial systematics, Int J Syst Bacteriol 37: 463-464
1 “... the complete deoxyribonucleic acid (DNA) sequence would be the reference standard to determine phylogeny and ... phylogeny shoulddetermine taxonomy.”
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phylogenetic coherence
16S 23S rRNA
Functional genes (MLSA)
Genomic analyses
70-50%70%
genotypic coherence
Reasociation DNA-DNA
G+C, PFGE, AFLP, MLSA
Genomic comparisons
(ANI; AAI)
100%
60%
70%
80%
50%phenotypic coherence
metabolism
chemotaxonomy
proteomics
(MALDI-TOF; LC-MS/MS)
Species descriptions: the examination should be as exhaustive as possible
from R Rosselló-Móra, IMEDEA, ES
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At recent ICSP Meeting in Valencia, July 2017, this ’proposal’ was discussed
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serotyping (monoclonal and polyclonal antisera)
Raman spectroscopy
protein SDS-PAGE (whole-cell or cell envelope)
pyrolysis mass spectrometry
Fourier-Transformation Infra-Red (FTIR) spectroscopy
MALDI-TOF mass spectrometry
cellular fatty acid fingerprinting (FAME)
chemotaxonomy (polyamine, polar lipid, quinone, etc., analysis)
phenotyping (growth, morphology, Api, BIOLOG, etc.)
restriction analysis of amplified fragments (PCR-RFLP)
low-frequency restriction fragment analysis (PFGE)
PCR-amplfication analysis (REP-, BOX-, ERIC-PCR, RAPD)
selective amplification of restriction fragments (AFLP)
Multi-Locus Variable-number tandem-repeat Analysis (MLVA)
Ribotyping
Mulit-Locus Sequence Typing (MLST)
Multi-Locus Sequence Analysis (MLSA)
Amplified Ribosomal DNA Restriction Analysis (ARDRA)
rRNA gene sequence analysis
DNA-DNA Hybridisation (DDH)
Genomic DNA mol % G+C
whole genome sequence analysis
Methodology
Bacterial Characterisation and Identification
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CCUG: since 2013, focussed on developing proteomic-genomic methods for:
strain identification
strain sub-typing
strain characterisation
diagnostics of infectious disease in clinical samples without cultivation
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Characterisation of infectious or clinically-relevant bacteria
Virulence – a measure of the degree of pathogenicity
virulence factors – effectively enable:- colonization in the host (attachment) - evasion of host defense mechanisms- potential to cause disease
bacterial toxins, cell surface proteins, hydrolytic enzymes, …
Antibiotic resistance – inherent and acquired resistanceWHO – ”… one of the biggest threats to global health, food security, and development today. …we are heading for a ‘post-antibiotic era’, in which common infections and minor injuries can once again kill.”
resistance factors - enable:- survival in competitive environments
- pathogenic bacteria to adapt to antimicrobial therapies
gene activation/repression, binding proteins, porins,
efflux pumps, …
Virulence Factor Database: www.mgc.ac.cn/VFs/main.htm
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Target/Acceleration
Time-of-Flight Molecular MassDesorption/Ionisation
DetectorDrift Region
m/z
a.i.
Mass
Spectra
Laser
MALDI-TOF MS
Modified from M Erhard, Anagnostec, GmbH
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Streptococcus pneumoniae: identfying mass signals
mass signals matching to ribosomal proteins are marked in red
~50% of peaks represent ribosomal proteins
protein masses obtained from the Swiss-Prot/TrEMBL sequence database
m/z
% I
nte
ns
ity
95
17
6865
L32
79
85 L
29
66
38
839
4
58
72
52
63
L34
62
65
L30
65
05
44
19
L36
90
71
S18
80
61
77
03
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51
67
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L28
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08
9 L
27
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8 S
19
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40
3 S
15
4757
12
31
0 L
7/L
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935
7 L
31
728
6
1101
9 S
6
3000 5000 7000 9000 11000 13000
88
06
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1 S
10
56
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3 L
23
modified from M Welker, Anagnostec, GmbH
”-omics” relevant for identification of proteins
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Can tandem Mass Spectrometry and proteomics – ’Proteotyping’, be applied for the direct analyses of clinical samples för rapid and reliable diagnostics of infectious bacteria?
What would be the advantages over traditional diagnostic methodsor NGS-based methods?
1) Respiratory infections: detection and identification, virulence and antibiotic resistance
S. pneumoniae, S. aureus, P. aeruginosa, K. pneumoniae, S. pyogenes, H. influenzae, M. catarrhalis, M. pneumoniae
2) Urinary-tract infections: detection and identification, virulence and antibiotic resistance
E. coli, K. pneumoniae, Enterobacteriaceae
3) Septicemia and Sepsis: detection and identification, virulence andantibiotic resistance
E. coli, S. aureus, S. pyogenes
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Optimisation of MS-proteomics
Different protein targets in different cell compartments.
* optimised fractionation of Gram-positive and Gram-negative cells.
Bacterial Cell Structure
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Clinical sample (nasal swabs)
Bacterial culture
Sample preparation protocols
Digestion of proteins into peptides
LC-MS/MS analysis of peptides
Biomarkers of species, strain, antibiotic resistance and virulence
direct sample processing
pre-culturing
NGS analyses of
genome sequences
LC-MS/MS ’bottom-up’ Proteomics-basedbacterial identification and diagnostics
Q-Exactive Hybrid Quadrupole-Orbitrap MS (ThermoFisher)
from R Karlsson, EU TAILORED-Treatment project
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Bacterial culture
Clinical sample
Intact cells - Surface shaving
Surface proteins = hotspots for genetic variation!
Virulence factors – Host-pathogen interactions
Wash cells
Soluble
Bead beating
and centrifugation
Fractions
Membrane and soluble fractions
Highly abundant conserved proteins = species markers!
Antibiotic resistance markers and virulence factors
Membrane
LC-MS/MS-based Proteomics
from R Karlsson, EU TAILORED-Treatment project
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Peptide generation by LPI FlowCell analysis
Step 1. Microbial cells or cell fractions are immobilized in the Hexalane Flow-Cell.
Step 2. Trypsin (digestive enzyme) is added and allowed to digest exposed proteins
Step 3. Peptides are eluted from the Flow-Cell and analyzed, using LC-MS/MS
Trypsin digestion: carboxyl-side of lysine or arginine, except if followed by proline
from R Karlsson, EU TAILORED-Treatment project
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Peptide fragmentsLIEVDSQGNR
TVFFEDGNQPISK
LLEDVGSNGAR
ILEVNEEER
LLDIDQEER
AGVGEAAGRGAGVGGR
Proteome profile
Sensitive matching•Genome-wide alignment in all six reading-frames•Average size of matched fragment: 16 AA (down to 6 AA)•Database
• well-annotated genomes• >5000 resistance factors (E Kristiansson, Chalmers Univ. Technology)• Virulence Factor Database: www.mgc.ac.cn/VFs/main.htm
Shotgun ‘bottom-up’ proteomics – data processing
Genomes Resistance factors
Virulence factors
Sample statistics on strain level
Peptide biomarkers
from R Karlsson, EU TAILORED-Treatment project
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20
Analysis of the H. pylori strain 26695 sample. The distribution of peptide-to-strain counts for different
H. pylori strains available in databases is shown.
Proteotyping: Helicobacter pylori – ranking species matching
Karlsson et al., 2012. J Proteome Res.
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Proteotyping: Staphylococcus aureus – ranking species matching
0
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Proteotyping: Streptococcus spp. – ranking species matching
from R Karlsson, EU TAILORED-Treatment project
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modified from M Kilian, 2016
94.58
Streptococcus Mitis-Group: core-genome sequence clustering
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Accuracy in correct species identifications in the Mitis-Group
92%
1%
7%
S. pneumoniae Type strain
S. pneumoniae
S. suis
Others54%
13%
8%
8%
1%
1%
15%
S. mitis Type strain
S. mitis
S. pneumoniae
S. pseudopneumoniae
S. oralis
S. oligofermentans
S. gordonii
Others
- Only 1 WGS of S. pseudopneumoniae and S. mitis available in the database- S. mitis Type strain was not available – the B6 strain genome clustered far away from the Typestrain
from R Karlsson, EU TAILORED-Treatment project
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How can we know if a genome is correctly classified ?
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Genome sequence 1
Genome sequence 2VS
Similarity value
Fragments of the genome sequences are aligned and compared
ANI: Average Nucleotide Identity
F Salvà Serra, CCUG
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< 93% 93 - 96% ≥ 96%
Streptococcus pneumoniae 323 0 0 323
Streptococcus mitis 40 18 22 0
Streptococcus australis 0 0 0 0
Streptococcus cristatus 2 0 1 1
Streptococcus infantis 4 3 1 0
Streptococcus oligofermentans 7 7 0 0
Streptococcus oralis 11 7 4 0
Streptococcus parasanguinis 9 1 6 2
Streptococcus peroris 0 0 0 0
Streptococcus pseudopneumoniae 6 0 0 6
Streptococcus sanguinis 23 2 16 5
Streptococcus sinensis 0 0 0 0
Streptococcus tigurinus 3 0 3 0
Total 428 38 53 337
100% 8.88% 12.38% 78.74%
Total number of
genome sequences
ANIb
Organism < 93% 93 - 96% ≥ 96%
Streptococcus pneumoniae
Streptococcus mitis 40 18 22 0
Streptococcus australis 0 0 0 0
Streptococcus cristatus 2 0 1 1
Streptococcus infantis 4 3 1 0
Streptococcus oligofermentans 7 7 0 0
Streptococcus oralis 11 7 4 0
Streptococcus parasanguinis 9 1 6 2
Streptococcus peroris 0 0 0 0
Streptococcus pseudopneumoniae 6 0 0 6
Streptococcus sanguinis 23 2 16 5
Streptococcus sinensis 0 0 0 0
Streptococcus tigurinus 3 0 3 0
Total 105 38 53 14
100% 36.19% 50.48% 13.33%
Organism
Total number of
genome sequences
ANIb
F Salvà Serra, CCUG
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Peptides
Genomes
DB
Non-unique
Unique =
biomarkers
All complete
genomes from
RefSeq DB
Additional
genomes from
GenBank DB
Genomes of
CCUG strains
We need more genomes!!
Tenaillon et al. 2010
Proteomic-Genomic analysesDevelopment
F. Salvà Serra, CCUG
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CCUG Genomics
• Started genome sequencing, January 2015
• To-date: approx 200 draft whole-genome sequences
Illumina(SU Genomics
Core)
Ion-Torrent(SU ClinMicroiol)
PacBio(NGI – Uppsala)
F Salvà Serra, CCUG
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Introduction of Oxford Nanopore MinION to CCUG
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Organism 2015-02-10 2016-12-31
Streptococcus australis 0 1
Streptococcus cristatus 0 1
Streptococcus gordonii 1 3
Streptococcus infantis 0 1
Streptococcus mitis 1 33
Streptococcus oligofermentans 1 1
Streptococcus oralis 1 13
Streptococcus parasanguinis 2 3
Streptococcus peroris 0 1
Streptococcus pneumoniae 27 28
Streptococcus pseudopneumoniae 1 9
Streptococcus sanguinis 1 6
Streptococcus sinensis 0 1
Streptococcus tigurinus 0 4
35 105
Addition of Streptococcus spp. genomes to the database
from F Salvà-Serra, EU TAILORED-Treatment project
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Accuracy in finding the correct species in the S. Mitis-Group
54%
13%
8%
8%
1%
1%15%
S. mitis
S. pneumoniae
BEFOREWGS databaseupdate
94%
1%1%1%
3%Streptococcus mitis
Streptococcuspneumoniae
Streptococcus suis
Streptococcus oralis
Others
AFTERWGS databaseupdate
Streptococcus mitis Type strain
from R Karlsson, EU TAILORED-Treatment project
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Proteotyping of Sahlgrenska Hospital clinical samples (nasopharyngeal)Positive samples
77%
(34
unique
peptid…
7% (3
unique
peptides
)
16%Moraxella
catarrhalis
Staphylococc
us aureus
Sample positive forMoraxella catarrhalis
93%
(26
unique
pepti…
7% (2
unique
peptide
s)Staphyloc
occus
aureus
Sample positive forStaphylococcus aureus
Results of MS-Proteomics peptide identification and matching
Example 1 Example 2
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Samples from Utrecht
Proteomic results
Bacteria (152)
Firmicutes (148)
Bacilli (144)
Lactobacillales (49)
Lactobacillus reuteri 100-23 (1)
Streptococcus (48)
Streptococcus pneumoniae (42)
Streptococcus pseudopneumoniae (2)
Streptococcus sanguinis (4)
Staphylococcus (95)
Staphylococcus aureus (91)
Staphylococcus hominis subsp. hominis C80 (1)
Staphylococcus simiae CCM 7213 (2)
Staphylococcus sp. M0480 (1)
Clostridiales (3)
Lachnospiraceae (2)
Lachnospiraceae bacterium 8_1_57FAA (1)
Ruminococcus torques ATCC 27756 (1)
Syntrophomonas wolfei subsp. wolfei (strain DSM 2245B / Goettingen)
(1)
Mitsuokella sp. oral taxon 131 str. W9106 (1)
Mycobacterium vanbaalenii (strain DSM 7251 / PYR-1) (1)
Mycoplasma sp. CAG:472 (1)
Proteobacteria (2)
Pseudomonas fulva (strain 12-X) (1)
Rhodopseudomonas palustris (strain BisB5) (1)
Eukaryota (309)
UM 6044
High number of bacteria
qPCR positive for S. pneumoniae S. aureus
Taxonomy view from UniprotNumber of protein hits
EU516 Clinical sampleFrom Utrecht Pediatrics
Clinic
Direct MS-proteomics analysis of clinical sampleBiomarker inclusion list for S. pneumoniae
from R Karlsson, EU TAILORED-Treatment project
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Discriminatory proteins
S. pneumoniae S. oralis S. mitis S. pseudopneumoniae
S. pyogenes
Number of proteins
649 564 678 622 407
Number of peptides
3556 2495 3722 2141 1197
Number of discriminative peptides
417 282 237 313 308
S. pneumoniae discriminatory proteins found by proteotyping workflow
• general stress protein 24
• surface protein PspA
• rpsP 30S ribosomal protein S16
• strH beta-N-acetylhexosaminidase
• cbpA choline binding protein A
• acpP acyl carrier protein
• ugd UDP-glucose 6-dehydrogenase
• prsA foldase PrsA
• lytB endo-beta-N-acetylglucosaminidase
• SURFACE-ASSOCIATED VIRULENCE FACTORS
All strains analysed in triplicateGood reproducibilityIdentified peptides and proteinsIdentified discriminatory peptides
Proteotyping of S. mitis complex
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S. pneumoniae virulence factors
S. pne S. pse S. mit
PspA Pneumococcal surface protein A +++ N NLytA Autolysin A ++ N NBac Bacteriocin ++ ++ NStrH B-N-acetylglucosaminidase +++ ? ?BgaA B-galactosidase ++ ? ?CpbA Choline binding protein A +++ N NEno Enolase ++ + +Hyl Hyaluronate lyase N N NIgA IgA1 protease ++ N NNan Neuraminidase ++ N NChoP Phosphorylcholine ? ? ?PavA Pneumococcal adhesion/virulence A ++ N NPlaA Pneumococcal iron acquisition A ? N NPiuA Pneumococcal iron uptake A ? N NPsaA Pneumococcal surface antigen A ++ N NPly Pneumolysin N ? ?
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Biomarker inclusion list S. pneumoniae
Selection of potential biomarker peptides
Diluted cell cultures
Analysis with inclusion lists to set retention time window
Targeted MSMS of diluted cell cultures
Analysis of negative clinical samples spiked with cell culture
Analysis of positive clinical samples
Workflow
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Biomarker inclusion list for S. pneumoniae
7 strains – including Type strain
All strains run in triplicate = 21 MS runs
Strain 1 CCUG 28588
Strain 2 CCUG 33774
Strain 3 CCUG 1350
Strain 4 CCUG 11780
Strain 5 CCUG 35272
Strain 6 CCUG 7206
Strain 7 CCUG 33180
from R Karlsson, EU TAILORED-Treatment project
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Biomarker inclusion list for S. pneumoniae
Dilutions of cells (#/ml)1 milj
100000 10000 1000 100
Sequence 100 1000 100000 1 milj 100 1000 100000 1 milj
VSDVAESTGEFTSEQFEK High High High High High HighDAELLFAGIVGDTGR Low HighYTLLAGETPAVAAAIR High High High HighIDTFGTGTVAESQLEK High High High High HighNGNYETAEGSEETSSEVK High High High High HighAHIYFINSEEPSQLNDLQAFR High High High HighANYGVSADK High High HighAVSAILGELNGNEGK High High High HighLMDVAQPELAIVFGR High High
Inclusion list Normal non-targeted
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Analysis of positive clinical samples – respiratory tract samplesSputum from CVID patients
Clinical samples
EU sample BACT LAB IDENTIFICATION TCUP - open Targeted
1257 Negative S. mitisS. pneumoniaeM. catarrhalis
1258 Negative - - CORRECT
1259 Negative - M. catarrhalis??1260 Negative - - CORRECT
1261 Negative S. mitisS. pneumoniaeM. catarrhalis
1262 Negative - - CORRECT
1263H. influenzae- isolate analyzed as 1266 - -
1264
H. influenzae- isolate analyzed as 1268 S. pneumoniae- isolate analyzed as 1267
H. influenzae S. pneumoniae
H. influenzaeS. pneumoniae
CORRECT
1264
H. influenzae- isolate analyzed as 1268 S. pneumoniae- isolate analyzed as 1267
H. influenzae S. pneumoniae
H. influenzaeS. pneumoniae
CORRECT
1265 Negative - M. catarrhalis
Isolates from clinical samples
1266 H. influenzae - H. influenzae CORRECT1267 S. pneumoniae S. pneumoniae S. pneumoniae CORRECT1268 H. influenzae H. influenzae H. influenzae CORRECT
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• WGS of urinary tract infectious bacteria• Type strains• Model strains• Multiresistant strains (CCUG, Sahlgrenska, Rotger)
• Inclusions lists• Pan-genome analyses
Proteotyping - Detection of anti-microbial resistance (AMR)
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ESBL-E. coli without antibiotics ESBL-E. coli with antibiotics
Sample preparation through bead beating
Digestion of proteins using trypsin
Analysis using LC-MS/MS
Database search against known resistance genes
Detection of anti-microbial resistance (AMR)
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• The number of peptides detected thatmatch to CTX-M β-lactamase aresignificantly higher with exposure toantibiotic than without.
• These data were compared with thosefrom analyses of a non-ESBL-E. coliReference strain.
• All analyses were done in triplicate.
Relative abundance of peptides matched to ESBL- E. Coli CCUG 62462 CTX-M β-lactamase
4
With antibiotics
Without antibiotics
Reference strain
Detection of anti-microbial resistance (AMR)
Experiments: Resistance factors detectedIn WGS
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Conclusions
- Proteotyping provides high-resolution characterisation of bacteria;
- Proteotyping is able to detect virulence factors;
- Proteotyping is able to detect AMR factors;
- Proteotyping is applicable to clinical samples, without cultivation;
- Proteotyping requires comprehensive and accurate wgs database;
- Proteotyping requires a stable taxonomy;
- Bacteria do not cooperate with microbial systematists;
- There is more interesting work to be done
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Acknowledgements
Elisabeth Inganäs, BMA CCUG LabMaria Ohlén, BMA CCUG LabSusanne Jensie Markopoulos, BMA CCUG LabSofia Cardew, BMA CCUG LabKent Molin, Chemist CCUG Lab
Roger Karlsson CCUG - ProteomicsFrancisco Salvà-Serra CCUG - GenomicsHedvig Jakobsson CCUG - GenomicsDaniel Jáen-Luchoro CCUG - GenomicsLucia Gonzales-Siles CCUG - MicrobiologyNahid Karami SU - Microbiology / AMRShora Yazdanshenas SU – Microbiology (RA)Bea Piñeiro-Iglesias SU - Microbiology (RA)Eri (k Kristiansson Chalmers Univ – BioinformaticsFredrik Boulund Chalmers Univ – BioinformaticsElisabeth Carlsohn GU Proteomics Core Facility
ALF-Medel / Regionala FoU
EU – TAILORED-Treatment Project (www.tailored-treatment.eu)