Essay: Salmonellosis – Salmonella

ABSTRACT
Salmonella is a genus of Gram-negative bacteria that causes a range of diseases generally referred as salmonellosis. Although not all strains of Salmonella infect humans and most common Salmonella infections are mild, it can also cause a life-threatening syndrome called enteric fever. Conventional methods of identifying and discriminating between strains of Salmonella are based on phenotypic or genotypic traits of the bacteria and are often time consuming and expensive. The recent introduction of matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI-TOF MS) has enabled genus and species level characterisation of Salmonella. This project sought to evaluate the suitability of MALDI-TOF MS to discriminate between five Salmonella enterica subspecies enterica serovars consisting of Hvittingfoss, Enteritidis, Herston and two Typhimurium serovars belonging to different page types through the analysis of intracellular bacterial proteins in addition to surface proteins analysed in intact cell MALDI-TOF MS techniques. Thymol treatment and formic acid extraction method were used for bacterial protein extraction prior to MALDI-TOF analysis and the reflectron mode was used to provide increased peak resolution in generated MALDI-TOF spectra in order to discriminate between the serovars. Protein extraction improved the quality of MALDI spectra obtained but failed to provide a significant difference between the serovars both in the linear and reflectron modes even with the incorporation of Zip Tip, a technique for concentrating proteins.
INTRODUCTION
Salmonellosis infections are caused by Salmonella, a Gram-negative bacterium. Salmonellosis results, when ingested Salmonella, from contaminated food or through the oral-fecal route, escapes digestion by gastric enzymes in the stomach. They proliferate in the intestine and invade the lining of the intestine (intestinal lumen) resulting in stomach cramps suffered by salmonellosis patients. Salmonella can also proliferate inside macrophages of the reticuloendothelial system and spread throughout the body via the blood stream. Clinically Salmonella infection broadly called salmonellosis can be grouped into four syndromes with each having different symptoms and requiring different methods for a cure and common syndromes includes;(1) Gastroenteritis commonly caused by S. typhimurium and clinical symptoms often include abdominal pain, nausea, and vomiting. (2) Enteric fever, a life-threatening infection commonly caused by S. typhi and S. paratyphi-A. (3) Bacteraemia; the existence of Salmonella in the blood. (4) Symptomless carriers; infected individual present no obvious symptoms but are able to propagate the pathogen to another host. Any serotype of Salmonella is capable of causing any of the four syndromes outlined but the clinical expression may differ with serovars(Goldberg & Rubin, 1988). Unlike gastroenteritis that has mild clinical effects, enteric fever could be life threatening and needs to be treated in a timely fashion. Knowing the specific Salmonella serovar is, therefore, critical for antibiotic administration.
In 2009, Salmonellosis recorded the second most common food poisoning bacteria in the European Union after campylobacter based on reported zoonotic disease that infect humans, with 108 614 registered cases (Alvarez-Ordonez et al., 2011). The genus Salmonella is made up of two species; Salmonella enterica and Salmonella bongori (Dieckmann & Malorny, 2011). Not very much is known about the genetic makeup Salmonella bongori or their diversity but they have been known to be mostly related to cold-blooded animals although they can also infect humans (Fookes et al., 2011). Salmonella enterica is the most well studied and common species of Salmonella and the infections they cause constitutes significantly to the disease burden suffered by humans worldwide (Gal-Mor et al., 2014). Using differences in biochemical properties and DNA-DNA hybridization results, the species S. enterica species has been divided into six subspecies; enterica, salamae, arizonae, diarizonae, houtenae, and indica (Dieckmann et al., 2008)(figure1).
Figure 1 Classification of Salmonella
Gastrointestinal diseases are mainly caused by Salmonella enterica subspecies enterica. Each subspecies is in turn composed of serovars discriminated based on their antigenic presentations and in total, more than 2,600 distinct serovars have been characterised and are named based on their host preference (Gal-Mor et al., 2014), syndromes they were believed to cause (which could vary from symptomless carriers to severe systemic infections) (Feasey et al., 2012, Gal-Mor et al., 2014) and the origin of their discovery (e.g., Salmonella enterica var Panama) (Feasey et al., 2012). The majority of the Salmonella enterica serovars that infect humans are members of subspecies I including; typhoidal and non-typhoidal Salmonella (NTS) serovars (Gal-Mor et al., 2014). Typhoidal Salmonella serovars include; Typhi, Sendai, and Paratyphi A, B, or C and they have a high selectivity for humans and cause enteric fever, which is also referred to as typhoid or paratyphoid fever if the causative salmonella serovar is Typhi or Paratyphi respectively (Gal-Mor et al., 2014).
Enteric fever is a fatal systemic disease and it has been estimated that in the year 2000 alone there were at least 2.6 million cases of typhoid fever recorded globally resulting in the death of more than 200, 000 people, and Paratyphi alone was responsible for more than 5 million of these cases (Crump et al., 2004). In the 19th Century, typhoid fever was recorded to one of the most important causes of morbidity and mortality in Europe and the United states (Osler W, 1912) but it has been suggested that the supply of good drinking water and improvements in sewage management is responsible for the drastic reduction in the incidence of typhoid fever in these areas (Kothari et al., 2008). Enteric fever is still endemic in Sub-Saharan Africa and in most cases they are wrongly diagnosed as malaria, as both diseases have similar clinical symptoms, typically febrile illness (Kuhns et al., 2012) and are thought to be triggered by the HIV epidemic(Reddy et al., 2010). Blood stream infections (BSI) caused by Salmonella serovars, Staphylococcus, and Escherichia coli are primarily responsible for most febrile illnesses. It is also an important cause of mortality and in cases where septic shock occurs; mortality rate can be up to 60% (Brun-Buisson et al., 1995). It is well-known
that the time difference between reported hypotension and administration of appropriate antimicrobials in hospitals is crucial to the survival of patients suffering from septic shock (Kumar et al., 2006). Nevertheless, in Africa lack of infrastructure, poor budget and a limited number of health workers are common challenges suffered in providing an effective health care system. As a result, diagnosis of febrile illness is often based on syndrome presentations due to unavailability of microbial approach most times (Petti et al., 2006, Perkins et al., 1997). Consequently, fever in Africa is commonly treated step wisely; anti-malaria drugs are administered first and if symptoms persist antibiotics are given, risking development of antimicrobial resistance and low clinical outcomes (Shears, 2001). Typhoid fever caused by Salmonella enterica serovar Typhi and non-typhoid Salmonella are common in these regions (figure 2) (Reddy et al., 2010) but typhoid fever presents the highest death rate with the yearly admission of approximately 21.6 million cases with more than 216 deaths(Kothari et al., 2008). The increasing perseverance of multi-drug resistant strains of Salmonella(Kuhns et al., 2012) with a lack of clean water and proper sanitation(Gal-Mor et al., 2014) have been believed to fuel the spread of Salmonella through the oral-fecal route.
Unlike Enteric fever that is now endemic in developing countries, NTS is a global disease (Gal-Mor et al., 2014). About 93.8 million cases are estimated each year globally for gastroenteritis (an NTS) with 155,000 deaths most of which were suspected to be foodborne(Majowicz et al., 2010).
Figure 2 The distribution of Salmonellosis in Africa (Reddy et al., 2010).
A common approach used in detecting Salmonella in the laboratory involves the use of selective media(Cooke et al., 1999). Almost all strains of Salmonella can secrete hydrogen sulphide except for serovar Paratyphi A and a few serovar Typhi strains and are commonly discerned from the other genera of bacteria under the family of Enterobacteriaceae (Perkins et al., 1997). A major drawback with this method of bacterial typing is that some species like Citrobacter freundii can also secrete hydrogen sulphide but other chromogenic media have been exploited to differentiate between these bacteria(Browne et al., 2010).
Below the subspecies level serotyping based on White-Kauffmann-Le Minor is globally accepted as a benchmark for the differentiation of Salmonella (Grimont & Weill, 2007). This classification is based on biochemical reactions and serotyping of Salmonella based on their surface antigens namely; the capsular Vi, somatic O and the flagellar H antigens(Dieckmann & Malorny, 2011). A major drawback in the use of this method, however, is that the serotyping is carried out by slide agglutination which is expensive, labour and time demanding and necessitating in excess of 250 antisera (Dieckmann & Malorny, 2011). Also, in common use is the 16S rRNA gene sequencing for subspecies discrimination but this method is expensive to perform routinely and time-consuming(Singhal et al., 2015). There is, therefore, a need for an easy, inexpensive and reproducible method for biotyping bacteria below the species level in other to determine what type of salmonellosis a patient has and the appropriate treatment required.
MALDI-TOF MS is a faster alternative to serotyping of bacteria based on phenotypic traits(Patel, 2013). It is a proteomic technique that is based on matching specific bacterial proteins, mostly ribosomal proteins of bacteria to a reference database and detected respectively(Gekenidis et al., 2014). Although there are limitations to the use of MALDI-TOF MS in discriminating some species of bacteria like Acinetobacter baumannii (Sousa et al., 2015) various bacteria can be accurately identified. MALDI-TOF MS is believed to provide a rapid, cheap and easy protocol for identifying bacteria at the species level (Gekenidis et al., 2014, Dieckmann & Malorny, 2011). It provides a procedure for accurately identifying and distinguishing bacteria, cyanobacteria, and fungi within minutes(Murray, 2012) and as such has useful applications in health and safety especially in the treatment of infection, biodefense and food safety (Alves et al., 2016). Routine MALDI-TOF MS consists of the irradiation of a pulse of a laser source on in tacked bacteria spotted on an MALDI sample target plate (figure 3). A matrix solution is usually overlaid on the bacterial sample prior to analysis to aid the ionization of bacterial proteins (typically ribosomal proteins, as they are the most abundant on the bacterial cell wall) into charged molecules. The clouds of ionized proteins are then electrostatically attracted into a mass analyser, the flight tube. In the flight tube, the ionised proteins are separated based on their charge-to-mass ratio (m/z) as they approach the detector. The detector records the time of flight of each ion and their abundance and converts the data into a spectrum representing a distribution of all detectable ions formed from the bacterial sample. The obtained spectrum can then be matched with those contained in a reference database. Commercial database and interpretive algorithms for discriminating various microbes of biological relevance are now obtainable(Murray, 2012).
Figure 3 The MALDI-TOF MS workflow. Analysis of microorganism produces unique spectrum specific to the analysed sample and could be used to identify it by comparing the spectra against a reference database (Croxatto et al., 2012).
Furthermore, certain factors tend to limit the use of MALDI in bacteria biotyping. The reproducibility of MALDI spectrum and hence the identification of microbes ranges from 79.9%-93.6% at the species level of classification to 94.5%-97.2% at the genus level (Gekenidis et al., 2014). It is interesting to point out that some research groups have described various biomarkers that could aid the discrimination of Salmonella subspecies and serovars. Dieckmann et al., in 2008 investigated 126 strains of Salmonella representing all 6 subspecies Salmonella under enterica species and bongori species (figure 1) by analysing variations in the mass spectra profiles of several housekeeping proteins through whole-cell MALDI-TOF MS and uncovered over 200 biomarkers signals corresponding to large and fundamental nucleic acid binding proteins and ribosomal proteins. Two of these peaks were verified in a later report by Gekenidis et al., in 2014to represent; ribosomal protein L17 and glutaredoxin-1, both of which are specific for the identification of Salmonella enterica subspecies enterica. Later in 2011 Dieckmann & Malorny, in order to identify serovar specific biomarkers screened 913 strains of Salmonella enterica subspecies enterica using whole-cell MALDI-TOF and reported that the ribosomal protein L17 was present in over 89 serovars in Salmonella enterica subspecies enterica but not present in bongori and other Salmonella enterica subspecies.
PROJECT AIM
This project was aimed at assessing the suitability of MALDI-TOF for rapid serovar discrimination of Salmonella enterica subspecies serovars consisting of Hvittingfoss (serovar 1), Herston (serovar 2), Enteritidis (serovar 3), and two Typhimurium serovars of different phage types (serovars 4 and 5). Salmonella subspecies 1 (enterica) is the most clinically relevant Salmonella subspecies with 2,300 characterised serovars and responsible for most Salmonella infections of warm-blooded animals (Porwollik et al., 2004). Salmonella enterica serovars tend to have different propensity to cause diseases and these differences are associated with the presence, absence or varied expression levels of some biomarkers (Andino & Hanning, 2015). Some researchers have demonstrated that treating bacteria with thymol suspension or formic acid prior to MALD analysis lysis the bacterial cell and exposes bacterial intracellular proteins for analysis subsequently resulting increased MALDI spectral quality (Holland et al., 2014, Gekenidis et al., 2014). Both protein extraction methods were investigated in both linear and reflectron modes in search for serovar specific biomarkers that could enable discrimination of Salmonella at serovar level. Zip Tip was also used to concentrate extracted proteins to enhance biomarker identification through improvements in the reflectron mode.
MATERIALS AND METHOD
Bacteria culture: The five Salmonella serovars (serovars 1-5) were collected from Singleton hospital, Swansea.
Routine MS bacterial identification: The classical protocol of bacterial identification at the species level was performed using a Voyager mass spectrometry instrument as described by Holland et al., in 2014 by spotting small colonies of each Salmonella serovars on respective wells on the MALDI target plate using sterile toothpicks and immediately overlaid with a 1μl saturated matrix solution (matrix A). Matrix A was made by dissolving 10mg of α-hydroxy-4-cinnaminic acid (HCCA) in 1ml of a solvent containing acetonitrile (ACN), water and trifluoric acid (TFA) in the ratio 50:47.5:2.5 (vol/vol/vol). The bacteria-matrix mixture was allowed crystallised by air drying prior to MALDI analysis.
Protein extraction using thymol suspension: Protein extraction was performed as describe by Holland et al., in 2014. Prior to MALDI analysis, a loop full of each Salmonella serovar was suspended in 100μl of thymol solution containing 30mg or 60mg of thymol dissolved in a solution of 70% ethanol and 30% of 0.1% TFA. Two concentrations of thymol (30mg and 60mg of thymol per ml of solution) were used for bacterial protein extraction in parallel to investigate the effect of increased thymol concentration on the quality of MALDI spectra generated. The bacteria suspension was then vortexed to increase the rate of the protein extraction and homogenise the suspension prior to centrifugation. A centrifugation step of the homogenized suspension separated the protein extract (supernatant) from the cell debris (pellet). The supernatant was then mixed with matrix A in a 9:1 matrix to protein extract ratio. Finally, the resulting protein extract/matrix mixture was then vortexed to ensure homogenous mixture and 1μl was spotted on the MALDI target plate, allowed to air dry before MALDI-TOF analysis. In parallel, a second matrix solution (matrix B), made from 10mg of HCCA dissolved in 1ml of solvent containing 50% acetonitrile (ACN) and 50% of 0.1% of trifluoric acid (TFA) was also used to investigate the effect of changing matrix solvent on the quality of the MALDI spectra generated.
Protein extraction using formic acid: Protein extraction was performed as described by Gekenidis et al., 2014. The formic acid method was used as a second approach to extract intracellular proteins from the same five Salmonella serovars described above. Each serovar was treated with 70% ethanol solution in duplicates, vortexed and centrifuged; the supernatant contained most of the 70% ethanol while the pellet retained the bacteria killed by the ethanol. The ethanol layer (supernatant) was pipetted off and discarded. The remaining ethanol that could not be removed by pipetting was then left to dry off in air. To the resulting pellet, 50μ of ACN was added followed by 50μl of formic acid. The resulting solution was then vortexed to homogenise the solution and centrifuge to separate the extracted proteins (contained in the supernatant) from the cell debris (contained in the pellet). A 1μl aliquot of the supernatant was then spotted on the MALDI plate and overlaid with matrix A and allowed to crystallise in air prior to MALDI analysis.
Zip Tip protein extract concentration: Zip tip was used to concentrate the extracted proteins obtained via the thymol extraction and formic acid extraction protocol. The Zip Tip is a 10 µL pipette tip containing a bed of chromatography media (0.6 µL) fixed to its end and devoid of dead volumes. Only serovar 3 and 5 were used as test samples to evaluate sensitivity improvement in the reflectron mode that could enable biomarker detection. The protein extracts (20µ) for both serovar 3 and 5 obtained via the thymol treatment method were dried using a speed vac concentrator prior while same volume of protein extract obtained from the formic acid method frozen in liquid nitrogen followed by drying in a freeze dryer. To the dried proteins form both extraction methods, 20µl of water was added and thoroughly vortexed to keep the extracted proteins in suspension. Vortexing was followed by the Zip Tip procedure including; wetting the chromatography media with 2 runs of ACN, running a 50% ACN and 50%TFA solution through the chromatography media 2 times and equilibrating the media 3 times with a 0.1% TFA solution. This was followed by pipetting and releasing the20µl of the protein extract made up with water and releasing for at list 5 times to ensure enough proteins have been bound to the chromatography media. This was immediately followed by a washing step to remove unbound proteins from the chromatography media using 3 runs of 0.1% TFA. The final step involved eluting the chromatography bound proteins into 10µl of matrix A. 1µl of the protein matrix mixture was then spotted on the MALDI plate, air dried and analysed using MALDI-TOF.
Data collection. MALDI spectra were generated using an Ultraflexextreme MALDI-TOF MS supplied with a Smartbeam Nd:YAG laser source and run in the linear positive mode at 100Hz, 100ns delay, 25KV volt, and 1-20KDa molecular weight using the flexControl software. An average of 2,000 laser shots was taken at 60% laser power and accumulated to for each spectrum produced because the minimum laser power required for ionisation was 60%. Spectra were transferred from flexControl to flexAnalysis to make adjustments such Gaussian smoothing and baseline correction. Additionally, the reflectron positive mode was also performed in parallel for 1500 to 8KDa molecular weight of proteins.
RESULTS
Direct smear method
The direct smear protocol was aimed at demonstrating that all 5 bacterial samples were from the same species (Salmonella) and to check for the possible difference between them in terms of the distribution of signals on the spectra and the relative intensities of the signals. The use of mass spectrometry in microbiology laboratories for biotyping of bacterial samples is done via the direct smear method. Initial MALDI spectra obtained with a Voyager biotyper in the linear mode were inputted on a user-supplemented database to confirm that all five serovars belonged to the same genus (Salmonella) and since the serovars were obtained from warm-blooded host they are all most likely of the species enterica. This provided no information on the subspecies level discrimination of Salmonella.
Since there was no comprehensive database containing unique MALDI spectra information that would allow differentiation of the five different serovars of Salmonella, visual comparison of the obtained spectra was anticipated to provide a useful method of data comparison. Since each serovar may produce slightly different peaks to signify composition of different biomarkers owing to the fact that the proteome of two subspecies is not exactly the same. A comparison of MALDI spectra obtained for the five serovars used (figure 4) in the linear mode demonstrated that there are no visually evident differences between the serovars based on the distribution of their constituent biomarkers. Most intense signals, for example, the peak at m/z value of 4,364Da, 5379Da, 6,254Da, and 7,158KDa were found in all serovars (figure 4). No significant differences could also be discerned between the five serovars based on the MALDI spectra generated via the reflectron mode but the resolution of the peaks seem to improve.
The effect of changing the matrix solvent on the quality of the spectra generated from MALDI was tested. The effect of using matrix A was compared to the effect of using matrix B containing 10mg of HCCA per ml of a solvent solution containing 50% of ACN and 50% of 0.1% TFA. The resulting MALDI spectra showed no improvement in the quality of the spectra (figure 5). Therefore, matrix A was consistently used in all experiments carried out.
Intracellular Protein Extraction
In order to increase the number of biomarkers available for analysis two extraction protocols were carried out; thymol suspension and formic acid extraction. The thymol extraction protocol appears to contribute to the quality of the spectra obtained; more peaks were detected in the spectra obtained when the bacteria were suspended in thymol suspension prior to MALDI analysis compared to those obtained through the routine direct smear approach without protein extraction (figure 6). The improvement of spectra quality seems to be common across most replicated analyses with minimal exceptions. The formic acid extraction procedure also produced spectra of similar quality in the linear mode as those obtained via the thymol suspension extraction (figure 7). However, none of the data obtained from both extraction methods enabled significant visual differentiations between the spectra obtained for all five serovars of Salmonella. The effect of increasing the concentration of thymol in the thymol suspension was also carried out by using 30mg and 60mg of thymol per ml of suspension volume. The resulting spectra demonstrated that increasing the concentration of thymol to 60mg of thymol increased the number of peaks and the quality of the spectra. However, a serial dilution of the concentration of thymol in the thymol suspension is needed to determine the most effective concentration of thymol that would produce the best quality peak.
In the reflectron mode, MALDI spectra generated from both extraction methods failed to show enough signals to enable discrimination of the serovars (figure 8). The loss of sensitivity in the reflectron mode compared to the linear mode was thought to be caused by the presence of very little or no detectable biomarker.
Furthermore, the address the loss of sensitivity in the reflectron mode the Zip Tip protocol was incorporated to increase the purification of biomarkers and enable detection. The MALDI spectra obtained for serovars 3 and 5 in duplicates for both protein extract from the thymol suspension and the formic acid extraction showed increased number of peaks compared to spectra obtained with Zip Tip incorporation (figure 9). The number of detectable increased from (2 in serovar 3 to 5 upon Zip Tip application). Unfortunately, the intensity of the baseline peaks in the reflectron mode did not increase and the available scanty peaks are not enough to discern any differences between the Salmonella serovars.
Figure 4 Linear mode: Comparison of MALDI spectra for all 5 serovars
Representative MALDI spectra of all five Salmonella serovars showed common peak distribution with the exception of serovar 5 that appears to have a unique set of unresolved peaks around 6,300Da in serovars 5 (circled in red). The resolution in the linear mode is not enough to resolve the signals identified and as such no significant differences between serovars could be discerned.
Figure 5 Linear: Spectra produced from matrices A and B. Matrix A produced more informative spectra compared to matrix B with an increased number of signals and overall spectra quality.
Figure 6 Linear: Effect of thymol protein extraction on serovar 5. Thymol seems to increase both the quality of the spectra and the number of peaks.
Figure 7 Comparison of linear spectra for serovar 5 with protein extraction via thymol extraction and formic acid extraction. Both methods increase the spectral quality in a similar magnitude.
Figure 8 Reflectron: MALDI spectra for Serovars 3 and 5. Few peaks were detected with low intensities in all serovars as represented with serovars 3 and 5. The low numbers of peaks detected have low intensity with maximum intensity around 115 a.u. This could indicate low levels of extracted bacterial proteins prior to MALDI analysis.
Figure 9 Reflectron: Effect of Zip tip on thymol extracted proteins for serovar 5
Figure 10 Effects of Zip Tip on protein extracts from formic acid and thymol suspension method. Thymol extraction prior to Zip Tip addition provided more informative spectra than (formic acid) with increased number of peaks but the resolution and peak intensities still need to be improved to enable discernment of serovar
DISCUSSION
This project sought to evaluate the suitability of MALDI-TOF MS for rapid serovar level discrimination of Salmonella enterica sub-species. Salmonella subspecies 1 (enterica) is the most clinically relevant Salmonella subspecies consisting of 2,300 out of the 2,600 known Salmonella serovars and is responsible for most Salmonella infections of warm-blooded animals (Porwollik et al., 2004). Salmonella enterica serovars tend to have different propensity to cause diseases and these differences are associated with the presence, absence or varied expression levels of some virulence genes(Andino & Hanning, 2015).
The importance of Salmonella subspecies identification: Salmonella serovars have varied host specificity and severity of infections. Two serovars used in this study (Typhimurium and Enteritis) are described as ubiquitous because of their ability to infect a wide range of host and both serovars commonly cause a mild enteric disease but in some hosts like mice, severe systemic infections could occur (Uzzau et al., 2001). This host specificity is in contrast with Salmonella serovars Abortusovis and Typhi that are restricted to sheep and humans respectively (Dougan & Baker, 2014, Goldberg & Rubin, 1988). Furthermore, antibiotic resistance for common drugs is constantly on the increase and non-targeted antibiotic administration is a major contributing factor. In other to administer the correct antibiotics to patients suffering from Salmonellosis, a quick and efficient protocol for the discrimination of different serovars of Salmonella is essential. Perez et al., in 2014 demonstrated that reducing the time it takes for diagnosis and administration of targeted antibiotics could reduce mortality rate up to 21%. It is, therefore, advantageous to find alternative methods to conventional serotyping that is easy to perform and produces results faster.
MALDI-TOF success: MALDI-TOF is used routinely for identification and classification of various bacteria ranging from Gram-negative bacteria such as Salmonella, Aeromonas, Campylobacter and Helicobacter as well as Gram-positive bacteria such as Listeria, Streptococcus, and Staphylococcus for diagnosis and is also applicable in the quick biotyping of bioterrorism agents such as Bacillus anthracis, and Francisella tularensis (Murray, 2012). Identification of bacteria using MALDI-TOF is more reliable with Gram-negative bacteria compared to Gram-positive bacteria. Gram-positive bacteria are identified in 96.6% of cases using MALDI-TOF with a score >1.7 (a score of 2 indicates a 100% prediction of unknown bacteria) while Gram-negative bacteria are identified in only 64.8% of cases at the genus level(Ferreira et al., 2011).
MALDI analysis of intact bacteria and fungi has demonstrated significant discrimination at the species level of classification (Dieckmann et al., 2008). In principle, the MALDI spectra generated in the positive linear mode serves as a fingerprint that enables identification of bacteria and fungi species when compared with data contained on a user-supplemented database. However, there are few misidentifications associated with MALDI-TOF bacterial biotyping. A notable example is the inability of MALDI-TOF to discriminate between closely related bacterial species like Escherichia coli and Shigella flexneri even when using a user-supplemented database containing spectra information for both species(Kuhns et al., 2012). It is not yet clear why these discrepancies occur but the most common reason for misidentification at the species level occurs when the database used for a post MALDI-TOF search lacks the specific MALDI spectra that would enable the identification of a bacteria species(Schmitt et al., 2013). The use of MALDI-TOF for bacteria biotyping is therefore limited by the microorganism content of the database used. The use of MALDI-TOF for bacterial biotyping is applicable to both isolates obtained from Sub-Saharan Africa and the developed countries(Kuhns et al., 2012).
TOF analysers: Linear and Reflectron modes. The linear mode gives high sensitivity but low resolution. The use of a reflector, which is an electrostatic reflector normally consisting of grids ring electrodes and a series of grids increases the mass resolution with the loss of sensitivity and confers a mass range limitation. This is done by forming a field that functions as an ion mirror by deflecting the charged biomolecules and returning them back via the flight tube. The reflectron corrects the energy variation of the ions emanating from the ion source with equal m/z values; biomolecules with higher kinetic energy will go through the reflectron more and would linger more in the reflectron. Consequently, the biomolecules will get to the detector with the same time as ions with less kinetic energy but equal m/z values. The time, t0 required to penetrate the reflectron at a distance of x is defined by equation the equation t0= 2Ek/qEVx where E represents the field in the reflectron, q represents the charge of an ion penetrating the reflectron at a depth of x with a kinetic energy of Ek and a velocity of Vix (Hoffmann & Stroobant, 2001).
Application of MALDI-TOF for bacterial discrimination at the serovar level: Classification of bacteria down the phylogenetic tree (figure 1) requires more precision than those higher up because of their closely related genome. Discrimination of bacteria at the species level using intact cells (direct smear method) may have been possible because of the large differences in proteome between different bacterial species, but beyond the species classification, the difference is more subtle and is much more difficult to detect.
Unlike the discrimination of bacteria at the species level where spectra data of unknown bacteria can be matched against a reference database, at present, there is no comprehensive reference database for bacterial biotyping below the species level. To this end, the differentiation ability at the subspecies level was investigated by comparing MALDI spectra generated from the five Salmonella serovars used. Peaks on the MALDI spectra represent specific proteins contained on the bacteria (both surface and intracellular proteins) and the height of the peaks represents their relative abundance of the respective proteins normalised to the abundance of the base peak; the peak with the highest intensity in the spectra designated with an intensity of 100%.
Initial routine MALDI-TOF analysis carried out through the direct smear method and the user of a user-supplemented database confirmed that all five bacterial serovars belonged to the same species (enterica) but no significant information on serovar differentiation was obtained. This may be due to reduced sample space of protein analysis. By increasing the number of proteins screened the likelihood of detecting significant differences in the MALDI spectra from the five serovars could increase. The routine direct smear methods screen only bacterial surface proteins, therefore, increasing the number of proteins analysed was aimed at increasing the chances of serovar discrimination. A comparison of the linear MALDI spectra generated from each serovar (figure 4) showed a common signal distribution pattern among all five serovars without significant differences. The only observed difference was seen in the MALDI spectra for serovar 5 with the formation of a unique set of poorly resolved peaks around 6,300Da but the poor resolution of the peaks could not allow a detailed signal comparison between the spectra to detect any significant differences between them. The use of a different composition of matrix solution (matrix B) did not seem to improve the quality of the obtained MALDI spectra significantly (figure 5) and as such it was discontinued.
Furthermore, the extraction of bacterial intracellular proteins prior to MALDI-TOF analysis seems to have improved the quality of the spectra generated compared to the direct smear method (figure 6). This was evidenced by the increased number of peaks and the relative reduction signal to noise ratio as shown in the MALDI spectra and could have resulted from the increase in bacteria intracellular protein analysis. In order to discern any possible differences between the serovars, a comparison of spectra from each serovar is expected to demonstrate a significant number of well-resolved signals with high intensity. A comparison of the linear spectra obtained with protein extraction via both the formic acid extraction and thymol suspension extracted demonstrated a similar degree of improvement compared to the direct smear method (figure 7). The explanation for this similarity in spectral improvement could be explained in that regardless of the method of protein extraction, the extracted proteins remain the same.
Despite improvements in the quality of the linear spectra, no significant difference between the serovars could be noted due to low resolution and an insufficient number of peaks. The reflectron mode MALDI-TOF analysis was done to improve the peak resolution but obtained results showed very few peaks with a 10-fold decrease in the base peak intensity compared to the linear spectra (figure 8) making serovar discrimination almost impossible. The drastic loss of sensitivity in the reflectron mode was thought of as resulting from contamination of the extracted proteins by the pellet of cell debris formed after protein extraction. This is coherent with the fact that pure sample produces better MALDI spectra than impure samples. Incorporation of the Zip Tip technique was aimed at purifying the extracted proteins but this resulted in only a slight improvement in the number of peaks detected with very small increase in the base peak intensity (from 70 a.u to 400 a.u) (figure 9). However, the increase in a number of peaks was not enough to provide enough comparable signals that could enable discernment between the five serovars. Also, the intensity of the peaks needs to increase reasonably in order for serovar level discrimination to be feasible. It is noteworthy to state that a possible explanation for the inability of the present study to discriminate between the five serovars used could be linked to the fact that they are all of the same subspecies and as such are very similar in their protein profiles and the solution to discriminating between these serovars could depend on incorporating techniques that would not only increase the number of MALDI peaks but also the intensity and resolution of the detected peaks.
In addition to bacteria biotyping, MALDI-TOF has been reported to be applicable as a cheap and time-saving tool for the identification and discrimination of viruses compared to traditional serotyping methods such cell culture, nucleic acid detection, and electron microscopy(Calderaro et al., 2014). There have not been so many studies on the application of MALDI-TOF in fungi identification, strain discrimination or antibiotics susceptibility determination but these are potential areas of investigation that holds promising results (Murray, 2012).
FUTURE RESEARCH
The application of MALDI-TOF in microbe identification has gained considerable interest over the last few years due to its advantages. Gekenidis et al., 2014 reported that integrating tryptic digestion of the acid/organic solvent extracted and resolubilised proteins and nano-liquid chromatography followed by detection of the peptides using MALDI-tandem TOF mass spectrometry improved the differentiation of bacteria down to the subspecies level. Three subspecies of Salmonella (Salmonella enterica subspecies enterica, Salmonella enterica subspecies houtenae and Salmonella enterica subspecies arizonae) were investigated and a 10 fold increase in proteins was detected (51 to 59 inclusive of ribosomal proteins within a mass range of 3 to 14KDa) relative to values obtained via routine MALDI-TOF MS method. This method could be fine-tuned to enable serovar level discrimination. More so, peptide profiling as done by (Alves et al., 2016) could be improved for serovar level identification and discrimination of Salmonella.
CONCLUSION
It is difficult to establish difference at serovar level because of the relative similarities in their protein composition. MALDI-TOF can be used for genus and species classification of Salmonella but while promising results have been reported for serovar level discrimination a wider scope of investigation needs to be carried out to fully appreciate the use of MALDI-TOF in microorganism biotyping. In order to achieve this, most promising extraction method, matrix solution and time conserving and reproducible methods would be tried. While studies are ongoing to find serovar specific biomarkers and a standard MALDI-TOF procedure that would enable rapid serovar level differentiation, It can be used as a prescreening tool for genus and species classification of bacteria prior to subspecies discrimination using traditional serotyping techniques.