Mass spectrometry (MS) and proteomics are gaining popularity in bacterial research and applications; notably, bacterial toxin detection and antibiotic resistance. Currently, several MS platforms exist (Fig. 1) and are described below.
by Angela Sloan, Dr Keding Cheng
Mass pattern and spectra comparison using MALDI-TOF-MS
The United States Food and Drug Administration (US FDA)-approved MALDI Biotyper or VITEK MS are both matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF-MS)-based instruments which perform by ionizing molecules extracted from whole cell culture without specific protease treatment. The bacterial culture is normally treated with a strong solvent such as 1% trifluoroacetic acid (TFA) in 50% acetonitrile (ACN) [1] or 70% formic acid (FA) followed by 50% ACN [2] and centrifuged. Extracted molecules are mixed with chemicals (matrices) such as cyano-4-hydroxy-cinnamic acid (CHCA) and loaded onto a MALDI plate for MS detection. Sample spots are shot by laser energy and mass spectra, represented by mass to change ratios (m/z), are then obtained [1–3]. MS spectra are compared against different MS patterns/fingerprints harboured in the spectra library, and the microorganism is identified as the best match. Alternately, the bacterial culture can be smeared directly onto a MALDI plate and covered by the matrix of choice [3]. Each matching spectra result is a potential identification (ID) and given a confidence score. Generally, an ID showing a score equal to or greater than 2 is considered a correct identification [3]. A score below 1.7 is considered unreliable, from 1.7 to 1.9 indicates probable genus identification, from 2.0 to 2.29 indicates confident genus identification, and from 2.3 to 3.0 indicates highly confident species identification [4]. Culture conditions may affect spectra quality and ID [5], with pure cultures producing the most stable and consistent results [6–7]. MALDI-TOF-MS has been used in to test antibiotic resistance by growing cells in media containing normal and isotope-labelled lysine residues with and without antibiotics. The mass shift of many MS peaks, observed using bioinformatics software, demonstrated cell growth in the presence of the antibiotics, hence signifying antibiotic resistance [8].
Mass fingerprinting for molecules of interest using MALDI-TOF-MS or LC-MS
Peptide mass fingerprinting (PMF) is another form of mass fingerprinting of peptides, often obtained after protease treatment. Experimental mass spectra are compared to theoretical mass spectra using protease digestion patterns, which subsequently allows the protein/molecule of interest to be identified [9]. Proteins are typically prepared using an enrichment process such as gel electrophoresis or chromatography, and enzymatically digested either within the gel or in solution. During in-gel digestion, trypsin penetrates dried gel pieces and digests the protein within. The resulting tryptic peptides are then easily extracted from the gel, vacuum-dried, and analysed by MS. When loaded onto a MALDI plate, samples will be covered with a matrix such as CHCA, for downstream MS analysis [10]. Bacterial extracts for routine MALDI-TOF-MS testing can also be digested, fractionated through chromatography, and loaded onto a MALDI plate to reduce sample complexity on each MALDI spot. Further fragmentation of the selected masses can be performed to obtain peptide sequences and subspecies level identification [11].
MALDI-TOF-MS is now able to detect carbapenemase or β-lactamase activities, indicators of antibiotic hydrolysis, by incubating bacteria from positive blood culture with the antibiotic. If the substrate is hydrolysed and shows a mass shift in MS detection, and antibiotic resistance can be inferred [12–13]. Liquid chromatography-mass spectrometry (LC-MS) has also been used for antibiotic susceptibility testing and metabolite profiling. For example, ampicillin (m/z 350 Da) can be hydrolysed into ampicillin-penicilloic acid (m/z 368 Da) and penilloic acid (m/z 324 Da) in ampicillin-resistant cells, resulting in mass changes easily detected by LC-MS [14].
Kalb et al. and Wang et al. used an Endopep-MS (a MALDI-TOF-MS-based method), to analyse the botulinum toxin [15–16], a highly substrate specific endopeptidase. The Endopep-MS method is based on the masses of cleavage products, which will be unique according to which toxin is present. The authors focused on the light chain of the toxin, providing it with a substrate in vitro that mimics the substrate in vivo. The presence/absence of the toxins was detected with 100% accuracy, and the analysis was not disturbed by the complex sample matrices analysed, such as meat and milk.
Targeted LC-MS/MS for protein identification and quantitation
Targeted protein identification and quantitation can be performed by multiple reaction monitoring (MRM) through a quadrupole MS system [17]. Ions (charged peptides) of interest can be selected from one quadrupole field and fragmented in the next. Peptide sequences are obtained and fragmented ions used for quantitation using stable isotope-labelled standard peptides as identification and quantitation references. Ion selection and fragmentation (MRM transition) is very fast and hundreds of targeted proteins can be identified and quantified in a 1-hour LC-MS/MS run. Either protein standards or peptide standards can be synthesized and used [18–19]. The beauty of using protein standards is that they can be spiked into the test sample, and quantitation of the protein performed accurately since the standards go through the sample preparation process [18]. MRM is highly specific, sensitive, accurate and reproducible. Rees et al. used the unique affinity of organisms for their host, such as bacteriophages for certain bacteria, and analysed phage amplification products through sequence-based LC-MS/MRM to deduce antibiotic resistance properties of host cell [20]. MRM-based quantitation can also be multiplexed to quantitate many molecules of interest per sample run, rendering the process desirable for clinical applications [19]. A recent publication by Charretier et al. showed that with Staphylococcus aureus as a model, bacteria identification, antibiotic resistance, virulence and type profiling could all be obtained using one MRM platform [21].
Moura et al. used two methods of liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect the presence of Clostridium difficile toxins in cell culture filtrate: ultra-performance liquid chromatography-tandem mass spec (UPLC-MS/MS) and data independent UPLC-MS/MS [22]. Notably, the label-free data independent method could perform protein identification and quantitation in one MS experiment using alternating high and low energy. UPLC-MS/MS confirmed that digestion with trypsin was efficient and robust with sufficient amino acid coverage to identify the two main C. difficile toxins, TcdA and TcdB. They also showed that the most efficient combination of enzymes for differentiation of the two toxins was trypsin and GluC, providing amino acid coverage of 91% for TcdA and 95% for TcdB. The data independent method quantified toxins at low levels and identified them separately. This is a novel development, as conventional methods typically quantify the total amount of toxin present. The method detected TcdA at 5 ng (1.6 μg/ml) and TcdB at 1.25 ng (0.43 μg/ml). Cell culture filtrate appears to be a novel approach for detection of C. difficile toxins, creating potential for future study.
Staphylococci are Gram-positive bacteria that cause pus-forming infections, food poisoning, and are the major cause of wound infections, nosocomial acquired pneumonia and septicemia [23–26]. Currently different results were obtained for Staphylococci species identification by MS approaches [23–25, 27]. Even so, evidence showed that the emergence of multiple Staphylococcus strains resistant to prescribed antibiotics could be detected by targeted LC-MS/MS by incubating bacteriophages with the bacteria [20]. In addition, Hennekinne et al. used isotope-labelled protein standards spiked into food extracts to identify and quantitate enterotoxins during a S. aureus food-poisoning outbreak using the LC-MS/MS platform. Bacterial toxins were enriched by the immune-affinity method and run on SDS-PAGE. In-gel digestion was performed and the toxin peptides were identified and quantitated based on quantitation standards [26].
Advantages of using MS platforms for bacterial toxin and antibiotic resistance tests
One of the most widely noted benefits of MALDI-TOF-MS is the ability of this platform to produce incredibly fast results, in some cases just a few minutes after loading the sample. MALDI-TOF-MS regularly uses fewer reagents and fewer steps, and requires less information on the organism than methods such as PCR or biochemical testing. Overall analysis is also cheaper since it occupies fewer working hours than traditional methods (the cost per MALDI-TOF-MS sample is reported to be approximately $0.50 to $1.00 [28]. Such rapid analyses would be of great benefit to epidemiological studies and clinical diagnoses where time is of the essence and faster identification will ultimately benefit patients [29].
Conclusion and perspective
An appealing aspect of MS is that any molecule that can be ionized should be detectable by MS with high sensitivity and resolving power. Current studies have confirmed that MS can analyse any cultivatable organism and its related metabolites without much prior knowledge, and it has been shown to be useful in a variety of applications, from fast hospital diagnosis and identification of typical bacteria, to organisms that are difficult to culture. With the gaining popularity of MS instrumentation, growing detectability, and user-friendly hardware and software, MS will certainly play a more substantial role in solving critical problems such as antibiotic resistance and the identification of toxins.
References
1. Santos T, Capelo JL, Santos HM, Oliveira I, Marinho C, Gonçalves A, Araújo JE, Poeta P, Igrejas G. Use of MALDI-TOF mass spectrometry fingerprinting to characterize Enterococcus spp. and Escherichia coli isolates. J Proteomics 2015; 127: 321–331.
2. Malainine SM, Moussaoui W, Prevost G, Scheftel JM, Mimouni R. Rapid identification of Vibrio parahaemolyticus isolated from shellfish, sea water and sediments of the Khnifiss lagoon, Morocco, by MALDI-TOF mass spectrometry. Lett Appl Microbiol. 2013; 56: 379–386.
3. Zautner AE, Masanta WO, Tareen AM, Weig M, Lugert R, Groß U, Bader O. Discrimination of multilocus sequence typing-based Campylobacter jejuni subgroups by MALDI-TOF mass spectrometry. BMC Microbiol. 2013; 13: 247.
4. He Y, Li H, Lu X, Stratton CW, Tang YW. Mass spectrometry biotyper system identifies enteric bacterial pathogens directly from colonies grown on selective stool culture media. J Clin Microbiol. 2010; 48: 3888–3892.
5. Balážová T, Makovcová J, Šedo O, Slaný M, Faldyna M, Zdráhal Z. The influence of culture conditions on the identification of Mycobacterium species by MALDI-TOF MS profiling. FEMS Microbiol Lett. 2014; 353: 77–84.
6. Loff M, Mare L, de Kwaadsteniet M, Khan W. 3M Molecular detection system versus MALDI-TOF mass spectrometry and molecular techniques for the identification of Escherichia coli 0157:H7, Salmonella spp. & Listeria spp. J Microbiol Methods 2014; 101: 33–43.
7. Richter SS, Sercia L, Branda JA, Burnham CA, Bythrow M, Ferraro MJ, Garner OB, Ginocchio CC, Jennemann R, Lewinski MA, et al. Identification of Enterobacteriaceae by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using the VITEK MS system. Eur J Clin Microbiol Infect Dis. 2013; 32: 1571–1578.
8. Sparbier K, Lange C, Jung J, Wieser A, Schubert S, Kostrzewa M. MALDI biotyper-based rapid resistance detection by stable-isotope labeling. J Clin Microbiol. 2013; 51: 3741–3748.
9. Thiede B, Höhenwarter W, Krah A, Mattow J, Schmid M, Schmidt F, Jungblut PR. Peptide mass fingerprinting. Methods 2005; 35: 237–247.
10. Chui H, Chan M, Hernandez D, Chong P, McCorrister S2, Robinson A2, Walker M2, Peterson LA2, Ratnam S3, Haldane DJ, et al. Rapid, sensitive, and specific Escherichia coli H antigen typing by matrix-assisted laser desorption ionization-time of flight-based peptide mass fingerprinting. J Clin Microbiol. 2015; 53: 2480–2485.
11. Gekenidis MT, Studer P, Wuthrich S, Brunisholz R, Drissner D. Beyond the matrix-assisted laser desorption ionization (MALDI) biotyping workflow: in search of microorganism-specific tryptic peptides enabling discrimination of subspecies. Appl Environ Microbiol. 2014; 80: 4234–4241.
12. Jung JS, Popp C, Sparbier K, Lange C, Kostrzewa M, Schubert S. Evaluation of matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid detection of beta-lactam resistance in Enterobacteriaceae derived from blood cultures. J Clin Microbiol. 2014; 52: 924–930.
13. Carvalhaes CG, Cayô R, Visconde MF, Barone T, Frigatto EA, Okamoto D, Assis DM, Juliano L, Machado AM, Gales AC. Detection of carbapenemase activity directly from blood culture vials using MALDI-TOF MS: a quick answer for the right decision. J Antimicrob Chemother. 2014; 69: 2132–2136.
14. Grundt A, Findeisen P, Miethke T, Jäger E, Ahmad-Nejad P, Neumaier M. Rapid detection of ampicillin resistance in Escherichia coli by quantitative mass spectrometry. J Clin Microbiol. 2012; 50: 1727–1729.
15. Kalb SR, Baudys J, Wang D, Barr JR. Recommended mass spectrometry-based strategies to identify botulinum neurotoxin-containing samples. Toxins (Basel) 2015; 7: 1765–1778.
16. Wang D, Krilich J, Baudys J, Barr JR, Kalb SR. Enhanced detection of type C botulinum neurotoxin by the Endopep-MS assay through optimization of peptide substrates. Bioorg Med Chem. 2015; 23: 3667–3673.
17. Parker CE, Domanski D, Percy AJ, Chambers AG, Camenzind AG, Smith DS, Borchers CH. Mass spectrometry in high-throughput clinical biomarker assays: multiple reaction monitoring. Top Curr Chem. 2014; 336: 117–137.
18. Pitt JJ. Principles and applications of liquid chromatography-mass spectrometry in clinical biochemistry. Clin Biochem Rev. 2009; 30: 19–34.
19. Cohen Freue GV, Borchers CH. Multiple reaction monitoring (MRM): principles and application to coronary artery disease. Circ Cardiovasc Genet. 2012; 5: 378.
20. Rees JC, Pierce CL, Schieltz DM, Barr JR. Simultaneous identification and susceptibility determination to multiple antibiotics of Staphylococcus aureus by bacteriophage amplification detection combined with mass spectrometry. Anal Chem. 2015; 87: 6769–6777.
21. Charretier Y, Dauwalder O, Franceschi C, Degout-Charmette E, Zambardi G, Cecchini T, Bardet C, Lacoux X, Dufour P, Veron L, et al. Rapid bacterial identification, resistance, virulence and type profiling using selected reaction monitoring mass spectrometry. Sci Rep. 2015; 5: 13944.
22. Moura H, Terilli RR, Woolfitt AR, Williamson YM, Wagner G, Blake TA, Solano MI, Barr JR. Proteomic analysis and label-free quantification of the large Clostridium difficile toxins. Int J Proteomics 2013; 2013: 293782.
23. Kooken J, Fox K, Fox A, Wunschel D. Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry. Mol Cell Probes 2014; 28: 34–40.
24. Lasch P, Fleige C, Stämmler M, Layer F, Nübel U, Witte W, Werner G. Insufficient discriminatory power of MALDI-TOF mass spectrometry for typing of Enterococcus faecium and Staphylococcus aureus isolates. J Microbiol Methods 2014; 100: 58–69.
25. Kooken J, Fox K, Fox A, Altomare D, Creek K, Wunschel D, Pajares-Merino S, Martínez-Ballesteros I, Garaizar J, Oyarzabal O, Samadpour M. Identification of staphylococcal species based on variations in protein sequences (mass spectrometry) and DNA sequence (sodA microarray). Mol Cell Probes 2014; 28: 41–50.
26. Hennekinne JA, Brun V, De Buyser ML, Dupuis A, Ostyn A, Dragacci S. Innovative application of mass spectrometry for the characterization of staphylococcal enterotoxins involved in food poisoning outbreaks. Appl Environ Microbiol. 2009; 75: 882–884.
27. Kooken J, Fox K, Fox A, Altomare D, Creek K, Wunschel D, Pajares-Merino S, Martínez-Ballesteros I, Garaizar J, Oyarzabal O, Samadpour M. Reprint of “Identification of staphylococcal species based on variations in protein sequences (mass spectrometry) and DNA sequence (sodA microarray)”. Mol Cell Probes 2014; 28: 73–82.
28. Rodríguez-Sánchez B, Marín M, Sánchez-Carrillo C, Cercenado E, Ruiz A, Rodríguez-Créixems M, Bouza E. Improvement of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification of difficult-to-identify bacteria and its impact in the workflow of a clinical microbiology laboratory. Diagn Microbiol Infect Dis. 2014; 79: 1–6.
29. Suarez S, Ferroni A, Lotz A, Jolley KA, Guérin P, Leto J, Dauphin B, Jamet A, Maiden MC, Nassif X, Armengaud J. Ribosomal proteins as biomarkers for bacterial identification by mass spectrometry in the clinical microbiology laboratory. J Microbiol Methods 2013; 94: 390–396.
30. Cheng K, Chui H, Domish L, Hernandez D, Wang G. Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria. Proteomics Clin Appl. 2016; DOI: 10.1002/prca.201500086.
The authors
Angela Sloan*1 MSc, Keding Cheng1,2 MD
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3R2, Canada
2Department of Human Anatomy and Cell Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
*Corresponding author
E-mail: angela.sloan@phac-aspc.gc.ca
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, /in Featured Articles /by 3wmediaDoes Zika virus (ZIKV) cause fetal microcephaly?
, /in Featured Articles /by 3wmediaIn February the WHO declared that the spread of ZIKV infection, which is sweeping through South and Central America resulting in more than a million cases so far, was a global health emergency. Infection with this flavivirus, endemic for decades in areas of Africa and Asia where the vector Aedes species mosquitoes breed, is usually sporadic and either asymptomatic or results in benign disease similar to dengue and chikungunya virus infections. Although ZIKV can, in common with many other viral infections, trigger the rare neurological Guillain-Barré syndrome, it is the recently observed correlation between cases of infection with the virus and infants born with microcephaly that has prompted the WHO’s declaration. So what evidence is there to support the hypothesis that intrauterine infection with ZIKV can result in fetal brain abnormalities?
ZIKV spread to the Pacific Islands nine years ago, and it was during the outbreak in French Polynesia from December 2013 (affecting 11% of the population) that robust laboratory tests including RT-PCR confirmed transmission of ZIKV from two mothers to their neonates. Also, a retrospective investigation of this outbreak documented an increase in infants born with severe cerebral malformations. Brazil notified the WHO of a disease that proved to be ZIKV spreading through the north-eastern states a year ago, and the reporting of a possible link between the virus and microcephaly in neonates resulted in an alert being issued by the Pan American Health Organization and WHO that stressed the need for reliable laboratory detection of the virus. But the strongest evidence for a link so far, published very recently in the NEJM, concerns a pregnant European woman who became ill at the end of her first trimester whilst working as a volunteer in Brazil. On her return to Slovenia an ultrasound at 32 weeks confirmed severe fetal brain disease and microcephaly, the pregnancy was terminated and an autopsy of the fetus, involving electron microscopy as well as RT-PCR, revealed ZIKV RNA confined to the brain. No other pathogens were found.
Since there will be few terminations so late in pregnancy, particularly in the Americas, this is likely to be the most robust evidence obtainable. So what is the immediate need? Surely rapid diagnostic tests, and the provision of reliable contraception and pregnancy termination services – at least until there is widespread immunity in the population at risk.
Mass spectrometry detection of bacterial toxins and antibiotic resistance
, /in Featured Articles /by 3wmediaMass spectrometry (MS) and proteomics are gaining popularity in bacterial research and applications; notably, bacterial toxin detection and antibiotic resistance. Currently, several MS platforms exist (Fig. 1) and are described below.
by Angela Sloan, Dr Keding Cheng
Mass pattern and spectra comparison using MALDI-TOF-MS
The United States Food and Drug Administration (US FDA)-approved MALDI Biotyper or VITEK MS are both matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF-MS)-based instruments which perform by ionizing molecules extracted from whole cell culture without specific protease treatment. The bacterial culture is normally treated with a strong solvent such as 1% trifluoroacetic acid (TFA) in 50% acetonitrile (ACN) [1] or 70% formic acid (FA) followed by 50% ACN [2] and centrifuged. Extracted molecules are mixed with chemicals (matrices) such as cyano-4-hydroxy-cinnamic acid (CHCA) and loaded onto a MALDI plate for MS detection. Sample spots are shot by laser energy and mass spectra, represented by mass to change ratios (m/z), are then obtained [1–3]. MS spectra are compared against different MS patterns/fingerprints harboured in the spectra library, and the microorganism is identified as the best match. Alternately, the bacterial culture can be smeared directly onto a MALDI plate and covered by the matrix of choice [3]. Each matching spectra result is a potential identification (ID) and given a confidence score. Generally, an ID showing a score equal to or greater than 2 is considered a correct identification [3]. A score below 1.7 is considered unreliable, from 1.7 to 1.9 indicates probable genus identification, from 2.0 to 2.29 indicates confident genus identification, and from 2.3 to 3.0 indicates highly confident species identification [4]. Culture conditions may affect spectra quality and ID [5], with pure cultures producing the most stable and consistent results [6–7]. MALDI-TOF-MS has been used in to test antibiotic resistance by growing cells in media containing normal and isotope-labelled lysine residues with and without antibiotics. The mass shift of many MS peaks, observed using bioinformatics software, demonstrated cell growth in the presence of the antibiotics, hence signifying antibiotic resistance [8].
Mass fingerprinting for molecules of interest using MALDI-TOF-MS or LC-MS
Peptide mass fingerprinting (PMF) is another form of mass fingerprinting of peptides, often obtained after protease treatment. Experimental mass spectra are compared to theoretical mass spectra using protease digestion patterns, which subsequently allows the protein/molecule of interest to be identified [9]. Proteins are typically prepared using an enrichment process such as gel electrophoresis or chromatography, and enzymatically digested either within the gel or in solution. During in-gel digestion, trypsin penetrates dried gel pieces and digests the protein within. The resulting tryptic peptides are then easily extracted from the gel, vacuum-dried, and analysed by MS. When loaded onto a MALDI plate, samples will be covered with a matrix such as CHCA, for downstream MS analysis [10]. Bacterial extracts for routine MALDI-TOF-MS testing can also be digested, fractionated through chromatography, and loaded onto a MALDI plate to reduce sample complexity on each MALDI spot. Further fragmentation of the selected masses can be performed to obtain peptide sequences and subspecies level identification [11].
MALDI-TOF-MS is now able to detect carbapenemase or β-lactamase activities, indicators of antibiotic hydrolysis, by incubating bacteria from positive blood culture with the antibiotic. If the substrate is hydrolysed and shows a mass shift in MS detection, and antibiotic resistance can be inferred [12–13]. Liquid chromatography-mass spectrometry (LC-MS) has also been used for antibiotic susceptibility testing and metabolite profiling. For example, ampicillin (m/z 350 Da) can be hydrolysed into ampicillin-penicilloic acid (m/z 368 Da) and penilloic acid (m/z 324 Da) in ampicillin-resistant cells, resulting in mass changes easily detected by LC-MS [14].
Kalb et al. and Wang et al. used an Endopep-MS (a MALDI-TOF-MS-based method), to analyse the botulinum toxin [15–16], a highly substrate specific endopeptidase. The Endopep-MS method is based on the masses of cleavage products, which will be unique according to which toxin is present. The authors focused on the light chain of the toxin, providing it with a substrate in vitro that mimics the substrate in vivo. The presence/absence of the toxins was detected with 100% accuracy, and the analysis was not disturbed by the complex sample matrices analysed, such as meat and milk.
Targeted LC-MS/MS for protein identification and quantitation
Targeted protein identification and quantitation can be performed by multiple reaction monitoring (MRM) through a quadrupole MS system [17]. Ions (charged peptides) of interest can be selected from one quadrupole field and fragmented in the next. Peptide sequences are obtained and fragmented ions used for quantitation using stable isotope-labelled standard peptides as identification and quantitation references. Ion selection and fragmentation (MRM transition) is very fast and hundreds of targeted proteins can be identified and quantified in a 1-hour LC-MS/MS run. Either protein standards or peptide standards can be synthesized and used [18–19]. The beauty of using protein standards is that they can be spiked into the test sample, and quantitation of the protein performed accurately since the standards go through the sample preparation process [18]. MRM is highly specific, sensitive, accurate and reproducible. Rees et al. used the unique affinity of organisms for their host, such as bacteriophages for certain bacteria, and analysed phage amplification products through sequence-based LC-MS/MRM to deduce antibiotic resistance properties of host cell [20]. MRM-based quantitation can also be multiplexed to quantitate many molecules of interest per sample run, rendering the process desirable for clinical applications [19]. A recent publication by Charretier et al. showed that with Staphylococcus aureus as a model, bacteria identification, antibiotic resistance, virulence and type profiling could all be obtained using one MRM platform [21].
Moura et al. used two methods of liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect the presence of Clostridium difficile toxins in cell culture filtrate: ultra-performance liquid chromatography-tandem mass spec (UPLC-MS/MS) and data independent UPLC-MS/MS [22]. Notably, the label-free data independent method could perform protein identification and quantitation in one MS experiment using alternating high and low energy. UPLC-MS/MS confirmed that digestion with trypsin was efficient and robust with sufficient amino acid coverage to identify the two main C. difficile toxins, TcdA and TcdB. They also showed that the most efficient combination of enzymes for differentiation of the two toxins was trypsin and GluC, providing amino acid coverage of 91% for TcdA and 95% for TcdB. The data independent method quantified toxins at low levels and identified them separately. This is a novel development, as conventional methods typically quantify the total amount of toxin present. The method detected TcdA at 5 ng (1.6 μg/ml) and TcdB at 1.25 ng (0.43 μg/ml). Cell culture filtrate appears to be a novel approach for detection of C. difficile toxins, creating potential for future study.
Staphylococci are Gram-positive bacteria that cause pus-forming infections, food poisoning, and are the major cause of wound infections, nosocomial acquired pneumonia and septicemia [23–26]. Currently different results were obtained for Staphylococci species identification by MS approaches [23–25, 27]. Even so, evidence showed that the emergence of multiple Staphylococcus strains resistant to prescribed antibiotics could be detected by targeted LC-MS/MS by incubating bacteriophages with the bacteria [20]. In addition, Hennekinne et al. used isotope-labelled protein standards spiked into food extracts to identify and quantitate enterotoxins during a S. aureus food-poisoning outbreak using the LC-MS/MS platform. Bacterial toxins were enriched by the immune-affinity method and run on SDS-PAGE. In-gel digestion was performed and the toxin peptides were identified and quantitated based on quantitation standards [26].
Advantages of using MS platforms for bacterial toxin and antibiotic resistance tests
One of the most widely noted benefits of MALDI-TOF-MS is the ability of this platform to produce incredibly fast results, in some cases just a few minutes after loading the sample. MALDI-TOF-MS regularly uses fewer reagents and fewer steps, and requires less information on the organism than methods such as PCR or biochemical testing. Overall analysis is also cheaper since it occupies fewer working hours than traditional methods (the cost per MALDI-TOF-MS sample is reported to be approximately $0.50 to $1.00 [28]. Such rapid analyses would be of great benefit to epidemiological studies and clinical diagnoses where time is of the essence and faster identification will ultimately benefit patients [29].
Conclusion and perspective
An appealing aspect of MS is that any molecule that can be ionized should be detectable by MS with high sensitivity and resolving power. Current studies have confirmed that MS can analyse any cultivatable organism and its related metabolites without much prior knowledge, and it has been shown to be useful in a variety of applications, from fast hospital diagnosis and identification of typical bacteria, to organisms that are difficult to culture. With the gaining popularity of MS instrumentation, growing detectability, and user-friendly hardware and software, MS will certainly play a more substantial role in solving critical problems such as antibiotic resistance and the identification of toxins.
References
1. Santos T, Capelo JL, Santos HM, Oliveira I, Marinho C, Gonçalves A, Araújo JE, Poeta P, Igrejas G. Use of MALDI-TOF mass spectrometry fingerprinting to characterize Enterococcus spp. and Escherichia coli isolates. J Proteomics 2015; 127: 321–331.
2. Malainine SM, Moussaoui W, Prevost G, Scheftel JM, Mimouni R. Rapid identification of Vibrio parahaemolyticus isolated from shellfish, sea water and sediments of the Khnifiss lagoon, Morocco, by MALDI-TOF mass spectrometry. Lett Appl Microbiol. 2013; 56: 379–386.
3. Zautner AE, Masanta WO, Tareen AM, Weig M, Lugert R, Groß U, Bader O. Discrimination of multilocus sequence typing-based Campylobacter jejuni subgroups by MALDI-TOF mass spectrometry. BMC Microbiol. 2013; 13: 247.
4. He Y, Li H, Lu X, Stratton CW, Tang YW. Mass spectrometry biotyper system identifies enteric bacterial pathogens directly from colonies grown on selective stool culture media. J Clin Microbiol. 2010; 48: 3888–3892.
5. Balážová T, Makovcová J, Šedo O, Slaný M, Faldyna M, Zdráhal Z. The influence of culture conditions on the identification of Mycobacterium species by MALDI-TOF MS profiling. FEMS Microbiol Lett. 2014; 353: 77–84.
6. Loff M, Mare L, de Kwaadsteniet M, Khan W. 3M Molecular detection system versus MALDI-TOF mass spectrometry and molecular techniques for the identification of Escherichia coli 0157:H7, Salmonella spp. & Listeria spp. J Microbiol Methods 2014; 101: 33–43.
7. Richter SS, Sercia L, Branda JA, Burnham CA, Bythrow M, Ferraro MJ, Garner OB, Ginocchio CC, Jennemann R, Lewinski MA, et al. Identification of Enterobacteriaceae by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using the VITEK MS system. Eur J Clin Microbiol Infect Dis. 2013; 32: 1571–1578.
8. Sparbier K, Lange C, Jung J, Wieser A, Schubert S, Kostrzewa M. MALDI biotyper-based rapid resistance detection by stable-isotope labeling. J Clin Microbiol. 2013; 51: 3741–3748.
9. Thiede B, Höhenwarter W, Krah A, Mattow J, Schmid M, Schmidt F, Jungblut PR. Peptide mass fingerprinting. Methods 2005; 35: 237–247.
10. Chui H, Chan M, Hernandez D, Chong P, McCorrister S2, Robinson A2, Walker M2, Peterson LA2, Ratnam S3, Haldane DJ, et al. Rapid, sensitive, and specific Escherichia coli H antigen typing by matrix-assisted laser desorption ionization-time of flight-based peptide mass fingerprinting. J Clin Microbiol. 2015; 53: 2480–2485.
11. Gekenidis MT, Studer P, Wuthrich S, Brunisholz R, Drissner D. Beyond the matrix-assisted laser desorption ionization (MALDI) biotyping workflow: in search of microorganism-specific tryptic peptides enabling discrimination of subspecies. Appl Environ Microbiol. 2014; 80: 4234–4241.
12. Jung JS, Popp C, Sparbier K, Lange C, Kostrzewa M, Schubert S. Evaluation of matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid detection of beta-lactam resistance in Enterobacteriaceae derived from blood cultures. J Clin Microbiol. 2014; 52: 924–930.
13. Carvalhaes CG, Cayô R, Visconde MF, Barone T, Frigatto EA, Okamoto D, Assis DM, Juliano L, Machado AM, Gales AC. Detection of carbapenemase activity directly from blood culture vials using MALDI-TOF MS: a quick answer for the right decision. J Antimicrob Chemother. 2014; 69: 2132–2136.
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The authors
Angela Sloan*1 MSc, Keding Cheng1,2 MD
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3R2, Canada
2Department of Human Anatomy and Cell Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
*Corresponding author
E-mail: angela.sloan@phac-aspc.gc.ca
Improving the diagnosis of peri-prosthetic joint infections
, /in Featured Articles /by 3wmediaProsthetic joint infections are a devastating complication of arthroplasty. Despite this, current culture techniques lack sensitivity and not standardized. We examined the inoculation of peri-prosthetic tissue specimens into blood culture bottles, demonstrating improved sensitivity compared to conventional methods. These findings influence patient care, allowing accurate diagnosis of infection.
by Dr T. N. Peel, B. L. Dylla, J. G. Hughes, D. T. Lynch, K. E. Greenwood-Quaintance, Prof. A. C. Cheng, Dr J. N. Mandrekar and Prof. R. Patel
Background
It is estimated that over 140 000 patients in the USA underwent revision arthroplasty in 2015 [1]. At the time of revision, it is recommended that biopsies of the tissues surrounding the prosthesis be obtained to diagnose or exclude prosthetic joint infection (PJI), a potential cause of arthroplasty failure [2]. PJIs are associated with significant patient morbidity and substantial healthcare costs [1, 3, 4]. In the setting of an ageing population and increasing demand for arthroplasty, the negative impact of PJIs will continue to compound [1, 4]. Despite the recognized impact of PJIs, diagnosis remains challenging owing to two major issues: (i) the lack of a ‘gold standard’ definition for infection and (ii) current imperfect diagnostic techniques [4].
PJI diagnosis and culture conditions
The isolation of an identical microorganism (or microorganisms) from two or more aseptically obtained peri-prosthetic specimens confirms the diagnosis of PJI [3]. In addition to confirmation of infection, microbiological cultures enable antimicrobial susceptibility testing to ensure institution of appropriate, targeted antimicrobial therapy. There are limited studies examining the optimal media for culturing these peri-prosthetic tissue biopsies [4]. Conventional microbiological techniques frequently include culture on various types of aerobic and anaerobic agar plates, and inoculation into broths such as thioglycollate broth [4]. These conventional techniques, alongside various durations of incubation, are not standardized and may have a low sensitivity, as low as 39% in some published studies, particularly in the setting chronic infection [5–7]. Recent research has focused on strategies that optimize the diagnosis of PJI, including the inoculation of peri-prosthetic tissue biopsies into blood culture bottles (Fig. 1).
Assessment of culture conditions
Previous research
Three previous studies examined inoculation of peri-prosthetic tissue specimens into blood culture bottles for the diagnosis of PJI. Baker and colleagues examined inoculation of synovial fluid aspirates and tissue specimens into blood culture bottles using the Sentinel system (Difco Laboratories) automated blood culture system. There were limitations of this study’s design and methodology, including lack of a control group and lack of comparison with conventional techniques [8]. In the second study, by Hughes and colleagues, four tissue culture techniques were examined – culture on blood and chocolate agars and in Robertson’s cooked meat broth, fastidious anaerobic broth and aerobic and anaerobic blood culture bottles. The aerobic and anaerobic blood culture bottles were incubated on the BACTEC 960 platform for 5 days (BD Diagnostic Systems). The authors defined PJI on the basis of histopathological findings, with 23 subjects meeting this criterion for infection from the 141 subjects included in the cohort [9]. Blood culture bottles were more sensitive compared to direct tissue culture and fastidious anaerobic broth (87% [95% confidence intervals {CI}, 72–100%] versus 39% [95% CI, 18–61%]; P = 0.007 and 57% [95% CI, 35–78%]; P = 0.016, respectively). There was no difference in sensitivity between culture in blood culture bottles and cooked meat broth (83% [95%CI, 66–99%]; P = 0.74) [5]. These previous studies used paired-design methodologies which may lead to the miscalculation of the true sensitivity of tests [10]. In a follow up study, Minassian and colleagues examined the optimal duration of incubation for peri-prosthetic tissue samples in blood culture bottles. The majority of blood culture bottles flagged positive within 3 days of incubation. In contrast, Propionibacterium species was isolated after a median of five days incubation (range 3–13 days). Terminal sub-culture of 1000 blood culture bottles at the end of the 14-day incubation period did not isolate clinically significant microorganisms. The authors concluded that prolonged culture for 14 days was not indicated, suggesting an optimal duration of 4 days incubation based on receiver operator characteristics (ROC) analysis [11].
Current study objectives and design
We undertook a larger, prospective cohort study at the Mayo Clinic, Rochester, MN, USA over a 9-month period (August 2013 – April 2014). The study included 369 consecutive subjects undergoing revision arthroplasty, of which 71 subjects (19%) underwent upper limb revision arthroplasty (49 shoulder joint and 22 elbow joint revisions). Overall, 117 study subjects met Infectious Diseases Society of America (IDSA) criteria for PJI. Applying the definitions proposed by Tsukayama and colleagues, the majority of subjects had late chronic infections (82%), 7% had early post-operative infections and 11% had hematogenous infections [7]. The majority (49%) of infections were caused by staphylococci, including Staphylococcus aureus which was isolated in 24% of culture positive cases. In contrast, Propionibacterium acnes was isolated in 41% of shoulder arthroplasty infections.
The study compared the sensitivity and specificity of inoculation of peri-prosthetic tissue specimens into blood culture bottles with standard agar and thioglycollate broth culture. The performance of the different media was analysed using Nemar’s test of paired proportion. In addition, Bayesian latent class modelling was undertaken; this statistical method overcomes potential limitations of traditional analysis as it assumes that no gold standard exists and that the true disease prevalence is unknown, both germane to PJI [10].
Current study results
Inoculation of tissues into blood culture improved sensitivity by 47% compared to conventional agar and broth cultures applying Bayesian latent class modelling (92.1% [95% credible interval, 84.9–97.0%] versus 62.6% [95% credible interval, 51.7–72.5%], respectively); this magnitude of difference was similar when IDSA criteria were applied (60.7% [95% CI, 51.2–69.6%] versus 44.4% [95% CI, 35.3–53.9%], respectively; P = 0.003). The specificity of culture in blood culture bottles was similar to conventional media, if two or more cultures were required to be positive. In 13 subjects (11%) of the 117 subjects meeting the IDSA criteria for PJI, inoculation of peri-prosthetic tissue samples into blood culture bottles detected microorganisms not found using other culture media. However, inoculation of peri-prosthetic tissue specimens into blood culture bottles failed to identify the pathogen that was detected by conventional methods in five PJI subjects (4%).
Microorganisms were detected earlier using blood culture bottles compared to conventional media; aerobic and anaerobic blood culture bottles flagged positive at a median of 21 and 23 hours (interquartile range [IQR] 14–45 and 16–47 hours, respectively) compared to 41 hours (IQR 21–63) for aerobic agar, 62 hours (IQR 43–144) for anaerobic agar and 65 hours (IQR 43–92) for thioglycollate broth.
Discussion
Culture using blood culture bottles has several advantages: it provides a semi-automated method, with positive results automatically flagging by the instrument, potentially yielding faster time-to-positivity than conventional methods; no technologist intervention is required for negative results except for removal of the bottles at the end of the incubation period; furthermore, the technology is available and used in most microbiology laboratories. Use of blood culture bottles overcomes a current limitation of total laboratory automation, the inability to handle anaerobic cultures.
The timely detection of microorganisms in blood culture bottles compared to conventional methods also has a number of clinical advantages particularly as detection of microorganisms in blood culture bottles may be combined with direct species identification using rapid diagnostics, such as matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) or rapid nucleic acid amplification tests. Given the speed to detection of microorganisms in blood culture bottles, it is theoretically possible that the causative pathogen could be identified with resistance characterization within as few as 24 hours of revision surgery. This would facilitate optimization of antimicrobial therapy and minimize unnecessary antimicrobial use [12].
Conclusion
This study informs clinical care for patients undergoing revision surgery, demonstrating improved sensitivity for diagnosis of PJI with inoculation of peri-prosthetic tissue specimens into blood culture bottles compared to conventional culture techniques. The use of automated blood culture systems also yields faster results with the potential for pathogen identification within the first day of surgery.
References
1. Kurtz SM, Ong KL, Lau E, Bozic KJ. Impact of the economic downturn on total joint replacement demand in the United States: updated projections to 2021. J Bone Joint Surg Am. 2014; 96: 624-30.
2. International Consensus Meeting on Periprosthetic Joint Infection. Musculoskeletal Infection Society; 2013 (http://www.msis-na.org/wp-content/themes/msis-temp/pdf/ism-periprosthetic-joint-information.pdf).
3. Osmon D, Berbari E, Berendt A, Lew D, Zimmerli W, Steckelberg J, Rao N, Hanssen A, Wilson W, Infectious Diseases Society of America. Diagnosis and management of prosthetic joint infection: clinical practice guidelines by the Infectious Diseases Society of America. Clin Infect Dis. 2013; 56:e1–e25.
4. Tande AJ, Patel R. Prosthetic joint infection. Clin Microbiol Rev. 2014; 27: 302–345.
5. Hughes H, Newnham R, Athanasou N, Atkins B, Bejon P, Bowler I. Microbiological diagnosis of prosthetic joint infections: a prospective evaluation of four bacterial culture media in the routine laboratory. Clin Microbiol Infect. 2011; 17: 1528–1530.
6. Font-Vizcarra L, Garcia S, Martinez-Pastor JC, Sierra JM, Soriano A. Blood culture flasks for culturing synovial fluid in prosthetic joint infections. Clin Orthop Relat Res. 2010; 468: 2238–2243.
7. Tsukayama DT, Estrada R, Gustilo RB. Infection after total hip arthroplasty. A study of the treatment of one hundred and six infections. J Bone Joint Surg Am. 1996; 78: 512–523.
8. Baker S, Fraise AP. Use of Sentinel blood culture system for analysis of specimens from potentially infected prosthetic joints. J Clin Pathol. 1994; 47: 475–476.
9. Hughes HC, Newnham R, Athanasou N, Atkins BL, Bejon P, Bowler IC. Microbiological diagnosis of prosthetic joint infections: a prospective evaluation of four bacterial culture media in the routine laboratory. Clin Microbiol Infect. 2011; 17: 1528–1530.
10. Collins J, Huynh M. Estimation of diagnostic test accuracy without full verification: a review of latent class methods. Stat Med. 2014; 33: 4141–4169.
11. Minassian A, Newnham R, Kalimeris E, Bejon P, Atkins B, Bowler I. Use of an automated blood culture system (BD BACTEC) for diagnosis of prosthetic joint infections: easy and fast. BMC Infect Dis.2014; 14: 233.
12. Tamma PD, Tan K, Nussenblatt VR, Turnbull AE, Carroll KC, Cosgrove SE. Can matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF) enhance antimicrobial stewardship efforts in the acute care setting? Infect Control Hosp Epidemiol. 2013; 34: 990–995.
The authors
Trisha N. Peel1,2 MBBS, FRACP, PHD, Brenda L. Dylla1 MT (ASCP), John G. Hughes1 MT (ASCP), David T. Lynch1 MT (ASCP), Kerryl E. Greenwood-Quaintance1 MS, Allen C. Cheng3,4 MSSB, FRACP, MPH, PhD, MBIOSTATs, Jayawant N. Mandrekar5 PhD, Robin Patel*1,6 MD
1Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
2Department of Surgery, St Vincent’s Hospital Melbourne, University of Melbourne, Melbourne, Australia
3Department of Infectious Diseases, Alfred Hospital, Melbourne, Australia
4Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
5Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
6Division of Infectious Diseases, Department of Medicine Mayo Clinic, Rochester, MN, USA
*Corresponding author
E-mail: Patel.robin@mayo.edu
Automating the clinical microbiology lab
, /in Featured Articles /by 3wmediaIn spite of some exceptions, the clinical microbiology lab has been a late starter as far as automation is concerned. It has also traditionally been viewed as ‘low tech’, especially when compared to its cousins in clinical chemistry or pathology. A variety of factors, however, have been converging to reverse such a situation.
Automation hampered by process complexity
One of the most important barriers to the automation of a clinical microbiology lab is process complexity. Unlike hematology or chemistry labs, which have little diversity in specimens and generally use standard collection tubes, microbiology laboratories need to work with a vast range of specimen types in a multitude of transport containers. The complex nature of specimen processing and culturing and the ensuing lack of standardization have been major deterrents to automation.
Nevertheless, growth in the presence of automated technologies in clinical microbiology labs is now expected to accelerate as a result of several factors, above all rising demand. This requires agility and high responsiveness, making automation indispensable.
Ageing populations drive demand
Ageing populations with more-complex diseases and conditions require a growing number of tests – for example, to monitor implants and prosthetic devices for infections. The elderly also need greater care in medicating, since they are more prone to adverse drug events.
In the year 2000, an article by Dr. Thomas T. Yoshikawa of the King-Drew Medical Center in Los Angeles noted that though “the major focus in infectious diseases for the past decade has been on young adults”, in the future “the vast majority of serious infectious diseases will be seen in the elderly population.”
Infectious disease, resistant bacteria
The rise in infectious disease outbreaks in recent decades is another factor driving demand for early detection by clinical microbiology labs, to contain their spread.
On their part, multidrug-resistant pathogens pose their own specific challenges. Delays in obtaining lab results leads to over-treatment of many patients – and increased antibiotic resistance. In 2008, a team from Erasmus University Medical Centre in Rotterdam found that quicker microbiological lab turnaround led to “a significant reduction in antibiotic use” in a study of almost 1,500 patients. This finding assumes considerable significance when one takes account of the fact that 5 years later, another study found that just 3% of community-acquired respiratory infections in the UK were guided by laboratory results.
The role of budgets and cutbacks
In an era of budgetary cutbacks, financial considerations too have reinforced demands for the automation of clinical microbiology labs. There is some irony here. Given the nature of a hospital business, it has been easier for administrators to assess the productivity of their clinical laboratories, determine return on investment (RoI) and justify new outlays – via quantifying and benchmark tests and staff numbers. Such an exercise has, in general, already been conducted for other hospital labs. It is now the clinical microbiology laboratory’s turn.
The above considerations are summed up in an article in the December 2013 issue of the journal ‘Clinical Chemistry’ which quotes Gilbert Greub of the Institute of Microbiology at the University Hospital in Lausanne, Switzerland. He says that the key reasons for the Hospital’s decision to move toward a fully automated laboratory consisted of a shortage of financial resources and the concomitant increase in activity of the Hospital’s clinical diagnostic microbiology laboratory “of about 4% to 12% per year.”
Workflow improvement, staff shortages
Indeed, improvements in workflow and quicker test results are also directly related to growing automation. One of the most important collateral effects of this is the freeing up of staff for other work.
In May 2009, the ‘Wall Street Journal’ warned about “the shrinking ranks of skilled lab workers” in the US, which pose “a potential threat to the safety and quality of health care”. Hospitals, it continued, said that “it can take as much as a year to fill some job openings,” while an American Society for Clinical Pathology (ASCP) survey found average job-vacancy rates topping 50% in some states.
The ASCP survey also illustrated another interesting fact. Laboratories which were affected by new technologies found a decreased need for as large a staff. However, 75% of respondents said they were not affected by new technologies. In other words, not only does automation seem to be an answer to staff shortages. There is also a lot of untapped room for growth.
Europe faces staff shortages too. A report by Belgium’s University Hospital at Leuven highlights the challenges of an ageing workforce, alongside major waves of retirement which have started recently and are expected to continue for several years. The problem is exacerbated by a decline in interest in labs as a career and the presence in the workforce of fewer young recruits. As a result, the paper warns, there is a “trend towards employing less-trained technicians.”
Transferring skills to points of need
The benefit of automation in the face of labour shortages is to utilize the skills of medical laboratory professionals where they are most needed and to automate tasks that are repetitive and do not require the comprehensive skill set of a trained professional.
For example, a laboratory could use an automated system for mundane and repetitive tasks such as “planting and streaking of urine samples and other liquid specimens,” while assigning a lab technician “to perform Gram stain review and processing of more-complex specimens, such as tissue.”
At the other end, boredom can also be a problem. In a non-automated environment, lab staff frequently complain of poor turnaround (TAT), referring to the duration or idling time between inoculation of media and microbial growth. By shifting monotonous tasks to automation, while assigning higher-skill tasks to a technologist, the laboratory reduces boredom and increases productivity.
The May 2009 article by the ‘Wall Street Journal’ quotes Dr. Carol Wells, director of the clinical laboratory sciences programme at the University of Minnesota in Minneapolis: “Many tests are automated, but that doesn’t mean a lab monkey can do them.” The machines, she continues, need careful monitoring. Should they “spit out a result” which does not make sense, only a skilled lab technician can catch a possible discrepancy and determine what is wrong.
Liquid-based microbiology, MALDI-TOF mass spectrometry drive demand
Automation of the clinical microbiology lab is also being driven by supply-side factors.
Among the first is the advent of new technologies, such as liquid-based microbiology and mass spectrometry. Liquid-based microbiology allows specimens of varying viscosities (e.g. stool or sputum) to be homogenized into a liquid phase, in order to enable greater consistency in the inoculation of medium. Specimen elution from recent flocked-style swabs into liquid phase has also resulted in a significant increase in the release of viable organisms from the swab, in other words resulting in greater sensitivity for detection of microorganisms.
The second technology is matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry. This permits the accurate and rapid identification of microorganisms isolated from clinical specimens. MALDI-TOF procedures “are highly amenable to automation because they are relatively simple, do not change based on organism, and are reproducible.” In addition, target plate spotting and extraction of proteins “can be standardized for most organisms, and when combined with automation, automated crude extraction using the on-plate formic acid extraction method can be performed with minimal staffing.”
Specimen processing as entry point
One of the first points of entry by new technology in a clinical microbiology lab consists of front-end instrumentation to automate and standardize initial specimen processing. Automation of the front-end makes it possible for tests to be conducted as soon as specimens arrive, obviating the need for a separate ‘stat’ lab.
Nevertheless, the impact of automation in specimen processing is not necessarily uniform, and depends on the needs of a particular laboratory. One study by researchers at Penn State College of Medicine and Medical College of Wisconsin estimated break-even point of more than 4 years for a barcode-driven, conveyor-connected automated specimen processing system which included plating and streaking, incubation, image acquisition, and digital microbiology.
Full- versus partial automation
As with other types of clinical labs, automation of the clinical microbiology laboratory can be classified into total (or full) laboratory automation or modular automation. Most automation systems have traditionally been designed for the larger, high-volume laboratory with substantial specimen throughput requirements. More recently, automated processing units have been designed for the pre-analytical section of smaller/medium-sized laboratories.
In effect, smaller labs can choose to automate only some of the processing steps. The investment required for automation makes such a choice imperative. The report by the University Hospital at Leuven cited previously notes that its own implementation of ‘full lab automation’ cost €3.2 million with €1.7 million in capital investment and another €1.5 million for refurbishment. Time needs to be also factored in. The Leuven study notes that their automation entailed 1 year in preparatory work and 1 year for adaptation. Against this, the savings achieved were equivalent to 3.8 full time employees (FTE).
Some hospitals begin small and scale up. For example, the University Hospital in Lausanne, Switzerland, started with two stand-alone automated systems for microbial identification. It moved after a few years “to a fully automated laboratory, by adding the missing pieces to the puzzle, i.e., smart incubators, high-quality digital imaging, an automated colony-picking system, and all required transport belts in between.”
A glimpse of the future
Today, state-of-the-art clinical microbiology labs have the potential to automate nearly all areas of testing, including inoculation of primary culture plates, detection of growth on culture media, identification of microorganisms, susceptibility testing, and extraction and detection of nucleic acids in clinical samples. In the future, process standardization is expected to be reinforced by high-resolution digital imaging and robotics, and take automation in the clinical microbiology lab to wholly new frontiers.