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
MULTISURE HIV The new benchmark for HIV-1/2 screening
, /in Featured Articles /by 3wmediaBioFire launches new meningitis panel for FilmArray
, /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.
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.
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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.
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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.
Trends in infectious diseases and clinical microbiology at ECCMID 2016
, /in Featured Articles /by 3wmediaKeynote sessions on antimicrobial resistance, the microbiome and systems vaccinology as well as presentations on late-breaking research on refugee health and colistin resistance at ECCMID 2016
The annual meeting of the European Society of Clinical Microbiology and Infectious Diseases is taking place this year from April 9 – 12 in Amsterdam. At the world’s largest congress focused on infectious diseases and medical microbiology researchers will present more than 3,000 abstracts with the latest findings and recommendations, which are set to help improve diagnosis, prevention and the clinical care given to patients. Discussions on this vibrant platform not only help translate the research findings into diagnostic tools, guidelines, best practices, and international policies; they also raise awareness of emerging healthcare challenges.
The congress offers more than 150 oral presentations, including keynote lectures, symposia, oral sessions, educational workshops and meet-the-experts session as well as more than 2,000 poster presentations. The event also provides mini-oral e-poster presentations. Posters are presented as printed posters, but also on e-poster viewing stations, where visitors can scroll through abstracts presented as papers.
The main topics are strategies to detect and tackle antimicrobial resistance in various settings, approaches for prevention involving vaccines and infection control as well as descriptions of novel diagnostic technologies. The most popular sessions include lectures by winners of the ESCMID Award for Excellence and the Young Investigator Awards, as well as oral presentations on ground-breaking research approaches and findings, and the late-breaking abstracts.
The keynote speeches include presentations on innovative approaches to vaccines; the microbiome and tuberculosis therapies; lectures on how non-human antibiotics affect public health; and an economic perspective on antimicrobial resistance.
This year, the ECCMID Programme Committee has decided to offer two special tracks for the late-breaking abstract sessions, focused on two topics, requiring a coordinated response from infection specialists across all disciplines.
The first topic is refugee and migrant health. The thousands of people who are currently migrating challenge public health systems in transition and host countries. Clinicians and public health specialists need to develop strategies for the screening, the prevention, and the treatment of infectious diseases some of which were largely eradicated in Europe are now gradually being reintroduced.
The second focus of the late-breaking abstracts is on emerging colistin resistance. Reports about the emergence of plasmid-borne resistance to this last-resort antibiotic have reached us from China, Canada, the UK and most countries in continental Europe.
Hala Audi, head of the UK government review on antimicrobial resistance (AMR review) will examine not only the long-term consequences of increasing antibiotic resistance in terms of healthcare, but also its economic cost. If the present situation fails to improve, the impact could be as high as ten million lives lost every year and €90 trillion in lost productivity by 2050. Hala Audi will present her findings on how we can address this, and describe new financial models, which may be necessary to start developing newer classes of antibiotics.
Another keynote session by Prof. Lance B. Price of George Washington University will address how the use of antibiotics in animal food production is significantly contributing to antimicrobial resistance. Notably, he is pioneering the use of genomic epidemiology to understand how the misuse of antibiotics in animal feed affects public health. Prof. Price found that by analysing the genomes of bacteria – in human and animals – one is able to trace strains of antibiotic-resistant pathogens to industrial livestock productions. In light of this association, it is alarming that many companies are still using antibiotics to prevent infection spread – what is not clear, is how endemic this use is and to what extent antibiotic use can be minimized and avoided in livestock production.
In terms of viral infections, experts at the congress will evaluate HIV and hepatitis C treatments in several sessions. At the same time, researchers will present results on emerging infections including those caused by the Zika virus. The problem with the current outbreak of the Zika virus is that we do not yet have any definitive evidence on how it is affecting their hosts – particularly on its potential link to microcephaly and Guillain-Barré syndrome – or on how this outbreak is different from previous outbreaks, and most crucially of all, on how to prevent transmission. Recent reports from the U.S. have indicated that the virus may be transmitted sexually – yet only a few weeks ago the CDC was stating this as ‘only a theoretical risk’. It is important that infectious disease specialists get together and discuss how to best tackle outbreaks of emerging or re-emerging infectious diseases. ECCMID offers an interdisciplinary platform for these debates.
Amplification-free direct detection of Ebola virus on a hybrid optofluidic platform
, /in Featured Articles /by 3wmediaLow-complexity detection of infectious diseases with high sensitivity and specificity is urgently needed, especially in resource-limited settings. Optofluidic integration combines clinical sample preparation with optical sensing on a single chip-scale system, enabling the direct, amplification-free detection of single RNA from Ebola viruses. The optofluidic system fulfils all key requirements for chip-based clinical analysis, including a low limit of detection, wide dynamic range, and the ability to detect multiple pathogens simultaneously.
by Dr Hong Cai, Prof. Aaron R. Hawkins and Prof. Holger Schmidt
Introduction
The recent Ebola and Zika outbreaks [1, 2] have made it clear that viral infections continue to pose diverse and widespread threats to humanity. Resource-limited settings, in particular, call for diagnostic devices and technologies that are robust and feature relatively low complexity for easy handling by potentially unskilled personnel. At the same time, such instruments need to fulfil all the technical requirements for accurate and reliable diagnosis. These include a limit of detection and dynamic range that are compatible with clinically observed viral loads as well as the ability to carry out multiplexed differential detection by screening simultaneously for several pathogens with similar clinical symptoms.
The ‘gold standard’ test for hemorrhagic fevers as well as other infectious diseases is real-time polymerase chain reaction (RT-PCR) [3]. PCR fulfils the sensitivity and specificity requirement for clinical testing. However, it is not ideal for resource-limited environments and point-of-care applications because of to its complexity. An alternative economic and portable option is antigen-capture enzyme-linked immunosorbent assay (ELISA) testing. However, ELISA requires more highly concentrated samples and thus its clinical application, especially for early disease detection, is restricted.
For the last two decades, the lab-on-chip approach, which features a small footprint and sample volume, has been considered as a promising candidate for the next generation low-complexity medical diagnostics [4]. Among all the approaches, optofluidics, which integrates optics and microfluidics in the same platform, has received increased attention [5, 6]. Microfluidics is ideal for performing biological sample processing on a chip-scale level and leads to miniaturization and simplification of the current diagnostic system. If it can be integrated with an optical sensing/read-out platform that enables high detection sensitivity down to the single pathogen level, an analytic system for which nucleic acid amplification is no longer needed becomes possible.
In order to detect single molecular biomarkers and bioparticles, an in-flow based detection scheme is preferred. In a typical in-flow detection scheme, bioparticles are transported to the sensing region in a stream of gas or liquid where they are detected in transient fashion as they pass an optical interrogation region [7, 8]. Therefore, fast read-out of the optical signal from single bioparticles in sequence can be achieved, and many concerns associated with traditional surface-based sensing schemes such as unwanted nonspecific binding, probe photobleaching, and diffusion-limited transportation are eliminated.
Anti-resonant reflecting optical waveguides (ARROWs) have been proven to be highly efficient in detecting single bioparticles. By properly designing a Fabry–Perot reflector surrounding a hollow channel, light can propagate inside the ARROWs. Therefore, ARROWs confine both liquid and light in the same microfluidic channel, such that light and matter have near-perfect overlap and the sensing capability is maximized [8, 9]. Figure 1(a) shows a cross-section of a liquid-core ARROW using state-of-the-art fabrication technology [9]. Moreover, a two-dimensional photonic sensing platform can be constructed with lithography patterning. Figure 1(b) shows an ARROW platform with solid-core and liquid-core ARROWs crossing orthogonally. Excitation light from an external laser is confined in the solid-core ARROW, producing a few-micron-wide optical mode in the intersecting region. Liquid flow is generated inside the liquid-core ARROW to transport the bioparticles to the excitation volume which is of the order of femtolitres for typical waveguide and channel dimensions of a few micrometers. Optical read-out is extracted orthogonally through the liquid-core ARROW to achieve a low-noise signal, sufficient for reaching single particle fluorescence detection.
Besides the optical sensing aspect, miniaturizing and optimizing sample preparation is equally important in order to achieve a complete bioanalysis detection system. The ARROW-based optofluidic system is particularly well suited for such hybrid integration strategies. The planar optical layout based on intersecting solid-core and target-carrying liquid-core waveguides leaves the third dimension open for vertical integration of other functionalities. A separate microfluidic sample processing layer can be made and optimized and then connected to the ARROW platform (Fig. 1c) [10, 11]. Through this approach, we can perform multiple sample preparation steps, such as mixing, distributing, sorting and pre-concentrating on the microfluidic layer and transfer the sample to the ARROW chip for sensing without compromising each of the layers’ performance [10].
Amplification-free detection of Ebola nucleic acids on an opto-
fluidic system
In our recent work, Zaire Ebola virus RNA detection from clinical samples has been demonstrated in a hybrid optofluidic ARROW system [12]. Through a strain-specific solid-phase extraction method, we extracted and labelled target RNA from Ebola infected Vero cells and put them through the optofluidic chip for detection. The ARROW chip provided a sequence of optical signals when individual fluorescent virus RNAs passed through the small excitation volume. Figure 1(d) shows the recorded digital RNA counts at low concentration levels of from 2.1×102 to ~2.1×104 pfu/mL within one second. We were able to detect six orders of magnitude of the clinical concentration range using the ARROW chip only. The lower concentration limit is determined by the detection time, which was set to be 10 min maximum. As a negative control, we used the same method to test for Sudan Ebola virus and Marburg virus. Our results showed no detectable signals and thus our method is target specific.
In order to incorporate critical sample processing steps and detect RNA at even lower concentrations within 10 min, we adapted a programmable microfluidic chip – an automaton – to handle processing of larger sample volumes (Fig. 1b). The polydimethylsiloxane (PDMS) based automaton chip consists of a two-layer microvalve array. Each valve’s state is controlled individually by the top pneumatic layer through a reprogrammable software program. We used the automaton chip to perform an extra pre-concentration step by processing a large amount of clinical sample. We washed, released and labelled the RNA on the same automaton chip after pre-concentration. Through ~460× concentration, the virus detection limit was improved down to 0.2 pfu/mL, with seven orders of magnitude of concentration range (Fig. 1e). This demonstration exhibits an amplification-free chip-based virus and nucleic acid analysis technique with high sensitivity and wide dynamic range, whose performance is comparable with the gold standard, more complex PCR technique.
Wavelength division multiplexing detection
ARROWs also enable simultaneous detection of multiple pathogens through the wavelength division multiplexing (WDM) technique [13]. WDM is generated using a multi-mode interferometer waveguide (MMI). When an MMI is excited by a single optical mode, all of the modes inside the MMI propagate at different phase velocities. When a constructive interference condition is satisfied, various numbers of self-imaging spots which resemble the excitation mode are formed along the MMI. This allows us to design an MMI section that intersects the fluidic channel, where multiple excitation spots are generated (Fig. 2a). As a fluorescent target flows past this excitation region, multi-peak signals are recorded in the time domain. For a single wavelength excitation, the fixed pattern multi-peak detection enables a signal-to-noise improvement compared to single-mode detection [14].
For a given MMI, the number of the self-imaging spots is wavelength dependent. We can generate various spot patterns at various laser wavelengths. For example, 9, 8 and 7 excitation spots are generated using 488nm, 553nm and 633nm lasers (Fig. 2b). With this approach, multiple targets labelled with different dye can be distinguished by the number and spacing of the peaks in the detected signal. Figure 2(c) shows influenza virus H1N1 and H3N2, which were labelled with different dye, generating 9 and 6 peaks in the time domain, respectively. We also labelled H2N2 virus with a combination of these two dyes which resulted in a superposition of the 9-spot and 6-spot fluorescence signals (Fig. 2c, bottom). A signal-processing algorithm checks for the presence of signals at the two characteristic time delays and can easily identify the mixed-labelled virus particle. This technique was shown to discriminate between three influenza subtypes, again with single virus sensitivity, using only two excitation colours. Thus, the ARROW-based platform has now met all the fundamental requirements for clinical virus detection using single particle sensing.
Conclusion
For the next generation of medical diagnostic devices, low-complexity detection with high sensitivity and specificity is required on the detection side, along with small footprint and multi-functional analyte handling on the sample processing side. In-flow based optofluidic devices in which both analyte handling and optical sensing are carried out on the chip scale are promising candidates. Using our ARROW-based optofluidic system, we demonstrated multi-stage sample processing and detection of clinical Zaire Ebola virus samples using hybrid integration. We also demonstrated wavelength multiplex detection of multiple analytes at the same time. This fulfils all quantitative requirements for clinical virus detection. Therefore, a fully integrated microsystem for front-to-back amplification-free virus analysis is within reach.
References
1. Fact sheet. The top 10 causes of death. World Health Organization 2014. (http://www.who.int/mediacentre/factsheets/fs310/en/).
2. Fact sheet. Zika virus. World Health Organization 2016. (http://www.who.int/mediacentre/factsheets/zika/en/).
3. Kuypers J, Wright N, Morrow R. Evaluation of quantitative and type-specific real-time RT-PCR assays for detection of respiratory syncytial virus in respiratory specimens from children. J Clin Virol. 2004; 31: 123–129.
4. Craighead H. Future lab-on-a-chip technologies for interrogating individual molecules. Nature 2006; 442: 387–393.
5. Fan X, White IM. Optofluidic microsystems for chemical and biological analysis. Nature Photon. 2011; 5: 591–607.
6. Schmidt H, Hawkins AR. The photonic integration of non-solid media using optofluidics. Nature Photon. 2011; 5: 598–604.
7. Zhu H, White IM, Suter JD, Zourob M, Fan X. Opto-fluidic micro-ring resonator for sensitive label-free viral detection. Analyst 2008; 133: 356–360.
8. Bernini R, Campopiano S, Zeni L, Sarro PM. ARROW optical waveguides based sensors. Sensors and Actuators B 2004; 100: 143–146.
9. Yin D, Barber JP, Hawkins AR, Deamer DW, Schmidt H. Integrated optical waveguides with liquid cores. Appl Phys Lett. 2004; 85: 3477–3479.
10. Parks JW, Cai H, Zempoaltecatl L, Yuzvinsky TD, Leake K, Hawkins AR, Schmidt H. Hybrid optofluidic integration. Lab Chip 2013; 13: 4118–4123.
11. Testa G, Persichetti G, Sarro, PM, Bernini R. A hybrid silicon-PDMS optofluidic platform for sensing applications. Biomed Opt Express 2014; 5: 417–426.
12. Cai H, Parks JW, Wall TA, Stott MA, Stambaugh A, Alfson K, Griffiths A, Mathies RA, Carrion R, Patterson JL, Hawkins AR, Schmidt H. Optofluidic analysis system for amplification-free, direct detection of Ebola infection. Scientific Reports 2015; 5: 14494.
13. Ozcelik D, Parks JW, Wall TA, Stott MA, Cai H, Parks JW, Hawkins AR, Schmidt H. Optofluidic wavelength division multiplexing for single-virus detection. Proc Nat Acad Sci U S A 2015; 112: 12933–12937.
14. Ozcelik D, Stott MA, Parks JW, Black JA, Wall TA, Hawkins AR, Schmidt H. Signal-to-noise enhancement in optical detection of single viruses with multi-spot excitation, IEEE J Sel Top Quant Elec. 2016; DOI: 10.1109/JSTQE.2015.2503321.
The authors
Hong Cai1 PhD, Aaron R. Hawkins2 PhD, Holger Schmidt*1 PhD
1School of Engineering, University of California Santa Cruz, Street, Santa Cruz, CA 95064 USA
2ECEn Department, 459 Clyde Building, Brigham Young University, Provo, UT 84602 USA
*Corresponding author
E-mail: hschmidt@soe.ucsc.edu
Visual detection of Ebola virus: targeting the NP gene by RT-LAMP
, /in Featured Articles /by 3wmediaEbola virus (EBOV) can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. More recently, reverse transcription loop-mediated isothermal amplification (RT-LAMP) has become readily available for the diagnosis of EBOV, and is a suitable tool for clinical screening, diagnosis and primary quarantine purposes.
by H. Li, W. Lin, X. Wang, X. Wei, E. Li, P. Li, J. Chen, S. Qi, Y. Ma, L. Cui, X. Hu, Dr X. Zhao, Prof. J. Yuan
The 2014 Ebola virus (EBOV; one of the world’s most virulent viruses) caused an outbreak of human disease with widespread transmission in multiple West African countries and sporadic cases in Europe and North America [1, 2]. The numbers of people infected and deaths were the most severe in history. However, the massive public health response has been limited, in part, by the inability to rapidly detect the presence of EBOV in potential patients living in remote areas [3].
EBOV, (species Zaire ebolavirus from the family Filoviridae), was first identified in Zaire in 1976 and named after the River Ebola in Zaire [4]. However, EBOV could not be detected rapidly in many potential patients living in remote and developing areas. The EBOV genome is approximately 19 kb, and encodes the seven proteins in the following order from the 3’-UTR: nucleoprotein (NP), viral structural protein (VSP)35, VSP40, glycoprotein (GP), VP30, VP24, and RNA-dependent RNA polymerase (L) [5]. As the NP gene is highly conserved among EBOV species, it is, therefore, recommended by the World Health Organization (WHO) for use as a target gene for the reverse transcription (RT)-PCR assay. The initial symptoms of EBOV infection could be confused with those of other febrile illnesses such as endemic malaria [6].
Current approaches for the laboratory diagnosis of EBOV infection include virus isolation, electron microscopy, immunohistochemistry, antigen-capture ELISA testing, IgM ELISA, RT-PCR, and serologic testing for IgM or IgG virus-specific antibodies. In 2015, Baca et al. presented a rapid detection of EBOV with a reagent-free, point-of-care biosensor. In general, the detection of EBOV antigens by antigen-capture ELISA is suitable as a method of laboratory diagnosis when the viral load in the blood reaches a very much higher case fatality rate. Thus, real-time (q)RT-PCR has taken over as a first choice diagnostic technique for detection of EBOV recommended by WHO [3]. However, Taq DNA polymerase in PCR-based techniques can be inactivated by inhibitors present in crude biological samples. Moreover, these methods are relatively complex and require specialized high-cost instruments.
Loop-mediated isothermal amplification (LAMP) is a one-step nucleic acid detection method developed by Notomi et al., which relies on autocycling strand displacement DNA synthesis [7]. This novel method is highly specific and sensitive, takes advantage of four or six specific primers to recognize six or eight different sequences of the target gene, and is performed under isothermal conditions in less than 1 h using Bst DNA polymerase. Kurosaki et al. developed a simple reverse transcription (RT)-LAMP assay for the detection of EBOV, targeting the trailer region of the viral genome. However, this method has yet to be tested in clinical samples [8].
To develop an RT-LAMP for clinical screening and rapid diagnosis of EBOV, we first selected potential target regions based on the NP sequences of the EBOV variant Mayinga (GenBank Accession no. AF086833), which were further analysed with Primer Explorer V4 software (http:/primerexplorer.jp/lamp) and subsequently the sequences were aligned with other species of EBOV. A total of five sets of primers were initially designed to detect artificially synthesized EBOV RNA using a real-time turbidimeter. To compare the sensitivity and specificity of RT-LAMP, normal RT-PCR was performed with the primers.
The RT-LAMP reactions were carried out in a 25-μl reaction mixture with an RNA amplification kit (Eiken Chemical Co. Ltd), in accordance with the manufacturer’s protocol. The reaction mixture contained the following reagents (final concentration): RT-LAMP mixture and 8 U Bst DNA polymerase. The amount of primer needed for one reaction was 80 pmol of forward and backward inner primers (FIP and BIP), 40 pmol of loop primer (LB), and 10 pmol of outer forward primer (F3) and outer backward primer (B3). Finally, an appropriate amount of genomic template DNA was added to the reaction tube. The reaction was carried out in the reaction tube at 61 °C, 60–80 min, in dry bath incubators.
Two different methods were used to detect RT-LAMP products. For direct visual inspection, 1 μl of calcein (fluorescent detection reagent; Eiken Chemical Co. Ltd) was added to 25 μl of LAMP products. For a positive reaction, the colour changed from orange to green, whereas a negative reaction remained orange. The colour change could be observed by the naked eye under natural light or with the aid of UV light at 365 nm. For monitoring turbidity, real-time amplification by the RT-LAMP assay was monitored by spectrophotometry, recording the optical density at 650 nm every 6 s with the help of a Loopamp Realtime Turbidimeter (LA-230; Eiken Chemical Co. Ltd) [9].
Assay validation
1. Optimal primer choice and reaction temperature conditions for the RT-LAMP assay
As shown in Figure 1A, the EBL-2 primer set amplified the NP gene using the shortest time of about 10min; therefore, this was chosen as the optimal primer set for EBOV detection of RT-LAMP (Table 1). To further optimize the amplification, reaction temperatures were compared ranging from 59 °C to 69 °C at 2 °C intervals. Ultimately, 61 °C was chosen as the optimal reaction temperature (Fig. 1B).
2. Specificity of NP detection by RT-LAMP using the artificial in vitro transcribed RNA
Twenty-five other non-EBOV viruses were also tested. As shown in Figure 2, the EBOV RNA was identified positively by a successful RT-LAMP reaction with EBL-2 primer set using both methods of analysis. All non-EBOV strains tested negative, including the blank control, indicating that the RT-LAMP method was specific for EBOV.
3. Sensitivity of NP detection by RT-LAMP
A 10-fold serial dilution of artificial EBOV RNA was tested by real-time turbidity monitoring (Fig. 3A), visual detection method (Fig. 3B), and qRT-PCR (Fig. 3C). The limit of detection by the visual method was 10-fold lower compared with the qRT-PCR assay.
4. Clinical sample detection
The 417 clinical blood or swab samples were analysed by RT-LAMP and qRT-PCR simultaneously. The RT-LAMP and qRT-PCR detections both showed that 307 patients were confirmed cases of EBOV infections and 106 patients tested negative for EBOV.
Summary
Zaire ebolavirus is a key member of the Filoviridae family and causes highly lethal hemorrhagic fever in human beings with extremely high morbidity and mortality. As a typical negative-sense single-stranded RNA (ssRNA) virus, EBOV possesses a nucleoprotein (NP) to facilitate genomic RNA encapsidation to form a viral ribonucleoprotein complex (RNP) together with genome RNA and polymerase, which plays the most essential role in virus proliferation cycle. EBOV is found in Central Africa, but re-emerged in Western Africa in 2014 to cause an outbreak that threatened to spread worldwide. Up until 10 January 2016, 28 601 total cases (including suspected, probable, and confirmed) and 11 300 deaths were reported in Guinea and Sierra Leone (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/case-counts.html). Although several chemical agents, antibodies and vaccines are found to inhibit EBOV in animals or humans, there is no therapeutic with high efficacy that can be provided for clinical usage.
To combat the increasing incidence of EBOV infections, we developed and optimized a novel RT-LAMP assay specific for EBOV diagnosis using primers spanning the 663 bp NP sequence of the viral genome. In the RT-LAMP assay, the reverse transcription reaction and DNA amplification proceed in a single step and with incubation of the reaction mixture at a constant 61°C temperature for a given time period using a temperature-controlled water bath (or other devices that can provide a stable heat are also sufficient). Moreover, LAMP reaction primers specifically recognize five independent regions of the target sequence, compared to PCR primers that recognize two independent regions of the target sequence. The sensitivity of the PCR reaction can be greatly reduced by the presence of exogenous DNA and inhibitors. Therefore, the RT-LAMP method is more suitable for rapid detection of NP in clinical samples.
Conclusion
In conclusion, a specific, sensitive, rapid and cost effective RT-LAMP assay for NP detection in EBOV was established, which is as sensitive as other available technologies, highly specific and extremely rapid in the provision of molecular diagnosis of EBOV infections. The assay can provide accurate results in a short time frame. This makes it potentially useful for clinical diagnosis of EBOV in developing countries.
Acknowledgment
This article is based on one previously published by the authors: Li H, Wang X, Liu W, Wei X, Lin W, Li E, Li P, Dong D, Cui L, Hu X, Li B, Ma Y, Zhao X, Liu C, Yuan J. Survey and Visual detection of Zaire ebolavirus in clinical samples targeting the nucleoprotein gene in Sierra Leone. Frontiers in Microbiology 2015; 6: 1332 [10].
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2. Hampton T. Largest-ever outbreak of Ebola virus disease thrusts experimental therapies, vaccines into spotlight. JAMA 2014; 312(10): 987–989.
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4. MacNeil A, Rollin PE. Ebola and Marburg hemorrhagic fevers: Neglected tropical diseases? PLoS Negl Trop Dis. 2012; 6(6): e1546.
5. Ali MT, Islam MO. A highly conserved GEQYQQLR epitope has been identified in the nucleoprotein of Ebola virus by using an in silico approach. Adv Bioinformatics 2015; 2015: 278197–278203.
6. Grolla A, Lucht A, Dick D, Strong JE, Feldmann H. Laboratory diagnosis of Ebola and Marburg hemorrhagic fever. Bull Soc Pathol Exot. 2005; 98(3):205–209.
7. Notomi T, Okayama H, Masubuchi H, Yonekawa T, Watanabe K, Amino N, Hase T. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res. 2000; 28, E63.
8. Kurosaki Y, Takada A, Ebihara H, Grolla A, Kamo N, Feldmann H, Kawaoka Y, Yasuda J. Rapid and simple detection of Ebola virus by reverse transcription-loop-mediated isothermal amplification. J Virol Methods 2007; 141(1): 78–83.
9. Mori Y, Nagamine K, Tomita N, Notomi T. Detection of loop-mediated isothermal amplification reaction by turbidity derived from magnesium pyrophosphate formation. Biochem Biophys Res Commun. 2001; 289: 150–154.
10. Li H, Wang X, Liu W, Wei X, Lin W, Li E, Li P, Dong D, Cui L, Hu X, Li B, Ma Y, Zhao X, Liu C, Yuan J. Survey and Visual detection of Zaire ebolavirus in clinical samples targeting the nucleoprotein gene in Sierra Leone. Frontiers in Microbiology 2015; 6: 1332.
The authors
Huan Li# MMed, Weishi Lin# MMed, Xuesong Wang MMed, Xiao Wei MMed, Erna Li MMed, Puyuan Li MMed, Jun Chen MMed, Silei Qi MMed, Yanyan Ma MMed, Lifei Cui MMed, Xuan Hu MMed, Xiangna Zhao PhD, Jing Yuan PhD*
Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, PR China
#These authors contributed equally to this work
*Corresponding author
E-mail: yuanjing6216@163.com
Biochemical markers of alcohol intake
, /in Featured Articles /by 3wmediaBiochemical markers of alcohol intake can be separated into two categories: direct markers of ethanol metabolism and indirect markers. The different alcohol markers have varying time windows of detection and are a useful additional tool to detect alcohol intake in alcohol-dependent clients.
by Jane Armer and Rebecca Allcock
Introduction
Alcohol dependence is characterized by craving, tolerance, a preoccupation with alcohol and continued drinking in spite of harmful consequences. The World Health Organization Alcohol Use Disorders Identification Test (AUDIT) is recommended for the identification of individuals that are dependent on alcohol [1]. The prevalence of alcohol use disorders (including dependence and harmful use of alcohol) is 11.1% in the UK compared to 7.5% across Europe [2]. In England, 250 000 people are believed to be moderately or severely dependent and require intensive treatment [3].
Alcohol use is the third leading risk factor contributing to the global burden of disease after high blood pressure and tobacco smoking [4]. In 2012, 3.3 million deaths (5.9% of all global deaths) were attributable to alcohol consumption [2]. It is estimated that the UK National Health Service (NHS) spends £3.5 billion/year in costs related to alcohol and the number of alcohol-related admissions has doubled over the last 15 years [3].
In the UK, one unit equals 10 mL or 8 g of pure alcohol, which is around the amount of alcohol the average adult can process in an hour. The latest UK recommendations are to not regularly drink more than 14 units per week (men and women) and to limit the total amount of alcohol consumed on a single occasion [5].
The most common entry into alcohol treatment services in England is either self-referral or referral by the GP [3]. Services have a limited number of options to determine if an individual in treatment for alcohol dependence is continuing to drink alcohol. They rely on self-report by the individuals in the form of alcohol diaries and breathalyser tests. There is no regular schedule for biochemical markers. If a client is found to be drinking alcohol during the treatment programme, an assessment is done of the amount of alcohol consumed, the pattern of alcohol consumption and how it will impact on their treatment. This is factored into the recovery plan and there is a re-assessment of the support and interventions needed for that client. Possible interventions include cognitive behavioural therapies, pharmacological therapies or in-patient assisted withdrawal. In 2013/14, only 38% of clients in alcohol treatment in England successfully completed their treatment [3].
Monitoring clients in alcohol treatment
Diaries that record alcohol intake are commonly used to monitor the progress of clients. However, this relies on accurate self-reporting of alcohol intake by the client and under reporting is a common problem. Biochemical markers of alcohol intake can provide a more comprehensive assessment of a client’s progress.
Direct markers of alcohol intake
Direct markers of alcohol intake include ethanol, ethyl glucuronide (EtG), ethyl sulphate (EtS), fatty acid ethyl esters (FAEE) and phosphatidylethanol (PEth).
Following the ingestion of ethanol, >95% is metabolized in the liver by alcohol dehydrogenase to acetaldehyde then by aldehyde dehydrogenase to acetic acid [14]. Less than 5% is excreted unchanged in the urine, breath and sweat. A small amount of ethanol is conjugated to form EtG and EtS (Fig. 1). Ethanol is usually only detectable in breath and urine after very recent alcohol consumption and the detection time window depends on the amount of alcohol consumed. In comparison, urine EtG and EtS remain detectable for around 24 hours after moderate alcohol intake and for up to 130 hours in subjects admitted for alcohol detoxification [6, 7]. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods have been developed for EtG and EtS. An immunoassay is also available for EtG [8, 9].
Many studies have demonstrated the benefit of measuring EtG and EtS in clients in alcohol treatment. Continued alcohol consumption can be detected by the measurement of urine EtG and EtS in clients who do not admit to consuming alcohol and provide a negative breathalyser test. This is due to the increased time window of detection for urine EtG and EtS compared to breath ethanol. This demonstrates the unreliability of self-reporting of alcohol intake and the benefit of biochemical markers to detect clients that are continuing to drink alcohol [10].
As with urine testing for drugs of abuse, it is possible for a client to consume a large volume of water to dilute the sample and produce negative EtG and EtS results. Creatinine should always be measured to check for adulteration and it may be beneficial to report EtG and EtS as creatinine ratios to overcome this problem. Further work is required to define cut-offs for EtG and EtS as creatinine ratios.
False negative EtG results can be caused by the presence of Escherichia coli in urine as glucuronidase is present with high activity in most strains. False positive EtG and EtS results have also been reported following use of ethanol based mouthwash or hand gels and after the consumption of non-alcoholic beers (up to 0.5% alcohol). Due to the risk of positive results due to unintentional alcohol exposure, particularly for urine EtG, it is important that clinical cut-offs used are clearly defined and LC-MS/MS methods that measure both EtG and EtS are preferred [11]. In the USA, the Substance Abuse and Mental Health Administration (SAMHSA) have suggested that EtG results >1.0 mg/L are consistent with alcohol intake and that results between 0.1 and 1.0 mg/L should be interpreted with caution. It is accepted that further work is required to clearly define cut-offs for EtG and EtS and that other biomarkers may be useful when interpreting borderline positive results in the range 0.10–0.50 mg/L [12].
Methods for the measurement of EtG and FAEEs in hair have been developed allowing a longer term assessment of alcohol intake. Hair analysis is most suitable for subjects where longer term abstinence needs to be demonstrated such as in patients awaiting liver transplantation. EtG cut-offs have been suggested by the Society of Hair Testing for chronic excessive alcohol consumption (30 pg/mg) and abstinence assessment (7 pg/mg). However, results may be influenced by hair products and this needs to be taken into account when interpreting results.
PEth is formed from ethanol and phosphatidylcholine in cell membranes. The reaction is catalysed by phospholipase D and occurs in the cell membranes of erythrocytes; therefore, PEth is found in the red blood cell fraction of blood rather than in serum or plasma. PEth is a group of phospholipids with varying carbon lengths and LC-MS/MS methods to detect the major forms of PEth in whole blood have been developed. A single dose of ethanol does not produce a measurable amount of PEth and it has been demonstrated that approximately 50 g of ethanol/day (6.25 UK units) is required to provide a positive PEth result. In comparison to serum carbohydrate deficient transferrin (CDT; see ‘Indirect markers of alcohol intake’ below), urine EtG and urine EtS, PEth demonstrated the highest sensitivity for regular alcohol consumption in clients in alcohol treatment and was found to be positive twice as often as CDT [13]. Further work is required to understand how PEth can be used optimally in combination with other alcohol markers in clients in treatment for alcohol dependence [14].
Indirect markers of alcohol intake
The indirect markers include mean corpuscular volume (MCV), gamma glutamyl transferase (GGT) and CDT. These markers increase following significant alcohol intake over a prolonged time period and are not useful for detecting a single alcohol ‘binge’. MCV and GGT are not specific markers of alcohol intake.
CDT refers to altered glycoforms of transferrin as a result of alcohol-induced changes in the carbohydrate composition of transferrin. The main component of serum transferrin is tetrasialotransferrin, which makes up approximately 80% of the total. Normal samples usually contain approximately 15%, 4–5%, 1–1.5% and 1% of pentasialotransferrin, trisialotransferrin, disialotransferrin and hexasialotransferrin, respectively. An alcohol consumption of at least 60 g/day (7.5 UK units) for 2 weeks is required to increase the disialotransferrin [15]. CDT may also be increased if genetic variants are present and in advanced liver disease. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has recently proposed a reference measurement procedure for CDT and more studies assessing the diagnostic performance of CDT to detect alcohol dependence are now needed using methods harmonized to the international reference measurement procedure.
Table 1 summarizes the time window of detection and limitations of the alcohol markers discussed.
Conclusions
Currently, the assessment of clients in alcohol treatment relies largely on self-reporting and limited biochemical testing, which makes assessment of a client’s progress challenging. There are a number of available biochemical markers that could improve the detection of alcohol use in clients with alcohol dependence and ultimately lead to initiation of early intervention and altered treatment strategies. This in turn could improve the numbers successfully completing treatment. A combination of short-term and longer term biochemical markers is likely to be the most useful approach depending on the treatment setting. The advantage of the breathalyser test over biochemical markers that require laboratory analysis is the immediate availability of the result which allows an immediate intervention for a client with a positive result. Laboratory tests need to be available in a timely manner and with appropriate and well-defined cut-offs. The clinical benefit of alcohol markers in improving the number of clients that successfully complete their treatment for alcohol dependency has not yet been demonstrated. Randomized controlled trials comparing outcomes with or without the use of biochemical markers are required.
References
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The authors
Jane Armer*1 BA MSc FRCPath and
Rebecca Allcock2 BSc MSc FRCPath
1Department of Blood Sciences,
East Lancashire Hospitals NHS Trust,
Blackburn, UK
2Department of Clinical Biochemistry,
Lancashire Teaching Hospitals NHS
Foundation Trust, Preston, UK
*Corresponding author
E-mail: jane.armer@elht.nhs.uk