Early diagnosis of sepsis is essential for enabling appropriate treatment. PCT and MR-pro ADM have been shown to be independent biomarkers for sepsis and progression to septic shock, and simultaneous analysis seems to be more effective than the single marker approach.
by Dr S. Angeletti, M. De Cesaris, Dr A. Lo Presti, et al.
Introduction
Sepsis is a severe condition that represents the tenth most common cause of death in the USA. In Europe, sepsis occurs in more than 35% of the patients admitted in the intensive care unit. The mortality associated with sepsis is approximately 28% and it rises to 40–60% in cases of septic shock, despite adequate treatment administration. Nearly 9% of patients with sepsis experience severe sepsis and nearly 3% progress to septic shock leading to multi-organ failure. More than 50% of patients affected by septic shock do not survive [1–3]. Consequently, the rapid recognition and treatment of sepsis is mandatory to reduce both the mortality and the hospitalization with related costs [1-3].
Sepsis is commonly defined as the presence of infection in conjunction with the systemic inflammatory response syndrome (SIRS); severe sepsis, as sepsis complicated by organ dysfunction; and septic shock, as sepsis-induced acute circulatory failure characterized by persistent arterial hypotension despite adequate volume resuscitation and not explained by other causes [1, 4]. The diagnosis of sepsis and evaluation of its severity is complicated by the highly variable and non-specific nature of the signs and symptoms of sepsis [5]. However, the early diagnosis and stratification of the severity of sepsis is very important, increasing the possibility of starting timely and specific treatment [4, 6].
The gold standard for detection of bloodstream infections is blood culture. The time required for a positive blood culture result depends on the incubation time required for the culture to turn positive and the subsequent biochemical identification, along with an antibiotic sensitivity test, both of which usually take 48 h [7]. Furthermore, in some cases, blood culture results remain negative owing to empirical broad-spectrum antibiotics that are frequently started in the presence of SIRS and often continued for a prolonged time course despite the absence of clinical and microbiological data supporting a diagnosis of bacterial infection [4, 8]. Several studies have evaluated the diagnostic utility of various biomarkers, including ferritin, haptoglobin, interleukin 6, C-reactive protein (CRP) and procalcitonin (PCT) for suspected sepsis in the ICU patient population [9–11].
It remains difficult to differentiate sepsis from other non-infectious causes of SIRS [12] and there is a continuous search for better biomarkers of sepsis.
PCT is a polypeptide that has demonstrated the highest reliability in the early diagnosis of sepsis, severe sepsis or septic shock compared to other plasma biomarkers or clinical data alone [13]. Moreover, PCT has been advocated also to clarify the bacterial origin of some localized infections [14–15].
The mid-regional pro-adrenomedullin (MR-proADM) has been shown to play a decisive role in both the induction of hyper-dynamic circulation during the early stages of sepsis and the progression to septic shock [16–18], and recently it has been reported that MR-proADM differentiates sepsis from non-infectious SIRS with high specificity. Moreover, simultaneous evaluation of MR-proADM and PCT in septic patients increased the post-test diagnostic probabilities compared to the independent determination of individual markers [19–20]; probably the multimarker approach seems to be the more effective [14, 19].
The aim of the present study was to perform a focused evaluation of the role of the combination of PCT and MR-proADM in patients with severe sepsis and septic shock (SS) to differentiate it from patients with mild sepsis or SIRS for a prompt and specific treatment administration.
Methods
Patient and control characteristics
One hundred and seventeen patients with SS and 100 patients with SIRS, hospitalized at the University Hospital Campus Bio-Medico of Rome between the years 2012 and 2014, were enrolled in the study. The patients’ details are reported in Table 1.
Sepsis was defined by the American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference definition of sepsis [4] based on the presence of a recognized site of infection and evidence of a SIRS occurring when at least two of the following criteria are present: body temperature higher than 38°C or lower than 36°C, heart rate higher than 90 beats per minute, respiratory rate higher than 20 breaths per minute or hyperventilation as indicated by an arterial partial pressure of carbon dioxide (PaCO2) lower than 32 mm Hg and a white blood cell count of higher than 12,000 cells/mm3 or lower than 4,000.
Patients were classified according to clinical signs into SS and SIRS. Acute physiological and chronic health evaluation (APACHE) II and sequential organ failure assessment (SOFA) scores were computed. APACHE II scores in SS and SIRS patients were calculated by Medscape, APACHE II scoring system calculator [21]. The SOFA score was calculated only for SS patients to better define the severity of the sepsis [22–23]. The study was approved by the Ethics Committee of the University Hospital Campus Bio- Medico, Rome, Italy.
Blood culture
Blood samples for blood culture were collected when patients showed the symptoms and signs of SIRS [1, 2, 4]. Blood culture included three sets (time 0, time 30 and time 60 min) of one aerobic and one anaerobic broth bottles (Bactec Plus Aerobic/F, Bactec Plus Anaerobic/F, Beckton Dickinson) per patient drawn during 1-h period of clinically suspected bloodstream infection. Blood culture vials were incubated in the Bactec 9240 automated system (Beckton Dickinson). Blood culture samples that turned positive were immediately processed for Gram staining and cultivated. Bacterial identification was performed by MALDI-TOF, as previously described [24].
PCT and MR-proADM measurement
The plasma concentrations of PCT and MR-proADM were measured by an automated analyser using a time-resolved amplified emission method (Kryptor, Brahms AG), with commercially available assays (Brahms AG) [25].
Statistical analysis
Data was analysed using MedCalc 11.6.1.0 statistical package (MedCalc Software). Plasma levels of PCT and MR-proADM were log-transformed to achieve a normal distribution. The normal distribution of each marker concentration was tested by the Kolmogorov–Smirnov test. PCT and MR-proADM in patients with SIRS and SS were compared using the Mann–Whitney test. Multiple logistic regression analysis (stepwise method) using SS versus PCT and MR-proADM was performed and the odds ratio (OR) computed. For OR calculation variables were retained for P<0.05 and removed for P>0.1.
Receiver operating characteristic (ROC) analysis was performed among independent variables associated with SS to define the cut-off point for plasma PCT and MR-proADM and their diagnostic accuracy to predict SS [26]. Pre-test odds, post-test odds and the consequent post-test probability were computed to investigate whether the combination of PCT and MR-proADM improves post-test probability. Likelihood ratios were used as these tests are not prone to bias due to prevalence rates [27].
Results
Patients with SS and SIRS characteristics
The mean age of the 117 patients with SS (71 men and 46 women) was 69 ± 3 years (Table 1). The principal comorbidities of patients with SS and SIRS and the sources of bacteremia are summarized in Table 1. In patients with SS the average APACHE II score value was 19.8, corresponding to 24% risk of death and the average SOFA score was 6.8 corresponding to a predicted mortality of <33%. In patients with SIRS the APACHE II score was 7, corresponding to 6% risk of death (Table 1).
SS was caused by Gram-negative pathogens in 63/117 (54%) of patients and in Gram-negative sepsis, E. coli (28/63; 44.4%) was the most frequent isolate. Gram-positive SS was present in 24/117 (20.5%) of cases and the most frequent pathogen was S. aureus (14/24; 58.3%), whereas C. albicans was the most frequent isolate in yeast-positive cultures (10/117; 8.5%) and blood cultures were polymicrobial in 20/117 (17%) cases. Bacterial isolates from positive blood culture are reported in Table 2.
PCT and MR-proADM in patients with SS and SIRS
Median values, interquartile ranges (25th percentile and 75th percentile) and Mann–Whitney comparison of PCT and MR-proADM analysed in patients with SS and SIRS are reported in Table 3. PCT and MR-proADM values were significantly higher in patients with SS than SIRS (P<0.0001) (Table 3 and Figure 1).
ROC curve and AUC analysis of PCT and MR-proADM in patients with SS
In SS patients, the area under curve (AUC) values of PCT and MR-proADM are reported in Table 4. Based upon ROC curve analysis and AUC characteristics, PCT and MR-proADM were considered applicable for sepsis diagnosis at the cut-off values of 0.5 ng/mL and 1 nmol/L, respectively (Table 4 and Figure 2).
Multiple logistic regression analysis
Multiple logistic regression analysis using SS as the dependent variable and PCT and MR-proADM as independent variables is reported in Table 5. Patients with MR-proADM >1 nmol/L have ~195 times the probability of being affected by SS than patients with SIRS, and patients with PCT values >0.5 ng/mL have the probability of developing SS 49 times more than SIRS.
Combined PCT and MR-proADM measurement in SS diagnosis: post-test probability calculation
In patients with SS, PCT and MR-proADM used as single markers have a post-test probability of 0.964 and 0.936, respectively. The combination of PCT and MR-proADM resulted in a higher value of post-test probability, 0.996 (Table 4).
Discussion
The early diagnosis and stratification of the severity of sepsis are essential, increasing the possibility of starting timely the specific treatment, especially in patients affected by SS. In this study, the combined measurement of PCT and MR-proADM in patients with SS was evaluated in order to establish the advantage derived from the use of a multimarker rather than a single marker approach.
PCT has been described as a reliable marker in the early diagnosis of sepsis compared to other plasma biomarkers or clinical data alone [13, 14, 19]. MR-proADM has been used as marker of disease severity in different clinical setting and recently its combination with PCT in bacterial infections and sepsis has been evaluated [28–32, 14, 19]. The combination of PCT and MR-proADM could allow the simultaneous evaluation of the presence of a bacterial infection as well as of the severity of this infection, giving to the ward clinicians a first useful indication waiting for blood culture positivity.
Results from this study demonstrated that in patients with SS, PCT and MR-proADM values are significantly higher than patients with SIRS. ROC curve analysis of PCT and MR-proADM demonstrated a high diagnostic accuracy of these two markers in SS diagnosis at the cut-off value of 0.5 ng/mL and 1 nmol/L, respectively. The logistic regression analysis showed higher OR values for both markers indicating a significant increased risk of having SS when these markers are higher than the cut-off values established. Furthermore, the combination of the two markers leads to a very high post-test probability value of about 99.6%.
These data confirmed the important role of the combination of PCT and MR-proADM in the diagnosis and prognosis of patients with sepsis rather than the single marker approach, because it combines the diagnostic ability of PCT with the prognostic value of MR-proADM, as already described in localized bacterial infections and not complicated sepsis [14, 19].
In conclusion, this study further support the advantage derived from the multi-marker approach in sepsis diagnosis and prognosis, especially in critically ill patients.
References
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20. Suberviola B, Castellanos-Ortega A, Ruiz Ruiz A, Lopez-Hoyos M, Santibañez M. Hospital mortality prognostication in sepsis using the new biomarkers suPAR and proADM in a single determination on ICU admission. Intensive Care Med. 2013; 39: 1945–1952.
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The authors
S. Angeletti*1 MD, M. De Cesaris1, A. Lo Presti2 PhD, M. Fioravanti1, F. Antonelli1, R. Ottaviani1, L. Pedicino1, A. Conti1, A. M. Lanotte1, M. Fogolari1 MD, M. Ciccozzi2 PhD, G. Dicuonzo1 MD
1Clinical Pathology and Microbiology Laboratory, University Hospital Campus Bio-Medico of Rome, Italy
2Department of Infectious, Parasitic, and Immune-Mediated Diseases, Epidemiology Unit, Reference Centre on Phylogeny, Molecular Epidemiology, and Microbial Evolution (FEMEM), National Institute of Health, Rome, Italy
*Corresponding author
E-mail: s.angeletti@unicampus.it
Tumours found in the ovaries can be either from primary ovarian tumour processes or metastases (secondary tumours) foremost from colorectal cancer (CRC), appendiceal tumours or stomach cancer. Correctly distinguishing between these tumour subsets using hematoxylin-eosin staining in combination with immunohistochemistry can be problematic [1–3], but is crucial for correct treatment choice. Mutation profiles, generated in a fast and cost-effective way by (targeted) Next Generation Sequencing (NGS), can assist in correctly diagnosing ovarian tumours.
by Stijn Crobach and Prof. Hans Morreau
Background
The ovaries are a preferential location for metastases from, among others, colon, stomach, appendiceal, breast and endometrium carcinomas. The percentage of secondary ovarian tumours (metastases), varies in several reports ranging from 8–30% [4, 5]. Several reasons can be given to explain why the range of percentages is so broad. First, studies are different by design. Some studies are based on autopsy findings, others on prophylactic oophorectomies. Second, differences in incidence of primary tumours can cause a variance in patterns of metastases. For example, stomach cancer has a higher incidence in Japan than in many other countries; therefore, metastases of stomach cancer to the ovaries are expected to be more common in Japan. In general, however, the gastrointestinal tract (GIT) seems to be the main source of ovarian metastases [5].
Macroscopic and histologic approaches
A gross distinction between primary and secondary ovarian tumours can be made taking tumour size and unilaterality versus bilaterality into account [6]. Following the decision tree depicted in Figure 1, it is possible to estimate whether an ovarian tumour is a primary tumour or a metastasis. A unilateral ovarian tumour with a diameter larger than 10 cm is probably a primary tumour. All bilateral and unilateral tumours smaller than 10 cm are much more likely to be metastases.
The histologic characteristics of metastatic GIT ovarian tumours can resemble primary endometrioid and mucinous ovarian tumours, but not serous papillary or clear cell tumours. Thus, based on histology a subset of primary ovarian tumours does not cause diagnostic doubt about the origin of the malignancy. Furthermore, other histologic findings can assist in defining the malignancy. For example, on the one hand, surface involvement by malignant epithelial cells is much more often seen in metastases than in primary ovarian tumours. On the other hand, however, an expansile growth pattern is more often seen in primary ovarian tumours. So, with the help of histopathological findings the characterization of a primary origin or a metastatic process becomes more achievable.
Immunohistochemical approaches
The logical next step in differentiating primary ovarian tumours from metastases is with the use of immunohistochemistry. For example, primary ovarian tumours are classically positive for keratin 7 and negative for keratin 20, whereas colorectal tumours show the opposed staining pattern (keratin 7 negative, keratin 20 positive) [7]. Other markers can also be used, not only to rule out an ovarian origin of the tumour but also to get an idea about the location of the primary tumour. Positivity of intestinal markers [such as carcinoembryonic antigen (CEA) and caudal type homeobox 2 (CDX-2)] can be an argument for an intestinal origin of the tumour cells [8].
Furthermore, when a colon carcinoma is already diagnosed before the ovarian tumour is discovered, the staining profile of the metastasis can be compared with the primary tumour. However, in up to 38% of cases the detection of ovarian metastases precedes the detection of the primary tumours. Also, secondary primary ovarian tumours can occur in patients that anamnestically suffered from another malignancy, complicating the diagnostic procedures. In practice, immunohistochemistry is frequently not fully discriminating. As mentioned, primary ovarian tumours tend to have a Ker7+/Ker20− immunoprofile and colonic metastases a Ker7−/Ker20+ immunoprofile. Nevertheless, keratin 7 positivity can be seen in proximal located GIT tumours, and keratin 20 positivity can also be seen in primary ovarian malignancies. In Figure 2, a guided immunohistochemical decision scheme is shown for complex cases.
Molecular diagnostic approaches
With the combined use of clinical information, histologic features and immunohistochemical staining patterns, differentiating primary tumours from metastases is possible in a substantial subset of cases. With a history of a colorectal tumour and the presentation of a large ovarian mass a few years later showing a similar immunoprofile, it is not difficult to decide that this tumour is a metastasis. Nevertheless, there are cases that are not as clear-cut. In those cases tumour size, unilaterality versus bilaterality and the histologic findings are not discriminating enough to solve the challenge. New approaches using massive parallel DNA sequencing (Next Generation Sequencing; NGS) have emerged in recent years.
Cancer driver genes (oncogenes and tumour suppressor genes) can be screened for DNA mutations in different tumour types. In the Catalogue Of Somatic Mutations In Cancer (COSMIC; http://cancer.sanger.ac.uk/cosmic), literature on these profiles has been compiled [9]. It was hoped that comparing mutational profiles of primary ovarian tumours versus metastases from different organs would reveal specific mutation patterns and/or mutation types in different tumour types.
NGS enables the screening of a large number of genes in a fast and cost-effective way. Previously, Sanger DNA sequencing was used to detect mutations in clinically relevant genes. However, screening complete genes and multiple genes in this way is a time-consuming process. Now, with the introduction of the disruptive NGS technology, it is possible to sequence multiple genes at the same time. NGS will become a standard technique in diagnostics for identifying gene mutations, chromosomal rearrangements and RNA expression/mRNA patterns [10]. One would expect that large scale screening of molecular alterations will results in very specific profiles per tumour type. Each tumour type could be defined by subsets of mutated genes. However, recent studies show that the mutation profiles do not differ so much between tumour types [11]. A few well-known so-called cancer driver genes seem to be important in many malignancies. Other (passenger) mutations, which are also needed in tumorigenesis, seem to be interchangeable. Apparently, there is wide overlap in mutation profiles. Looking at mutations described in the COSMIC database or The Cancer Genome Atlas (TCGA) at the current time, similar mutations can be seen in both primary ovarian tumours and metastases, although with different frequencies. The latter would suggest that the applicability of such tests is limited. However, a more select approach shows that certain genes can be discriminatory.
For example, CTNNB1 mutations are found in primary endometrioid carcinoma of the ovary. CTNNB1 mutations are also found in colon tumours, but only in mismatch repair deficient colon tumours, that do not tend to metastasize to the ovary. This reasoning could also be followed for APC, which is frequently mutated in colon carcinomas but not typically in mucinous and endometrioid primary ovarian carcinomas. However, genes such as these, which show such a ‘black-and-white’ phenomenon, are sparse. Therefore, mutation profiles that are used to guide clinical decision taking will probably be based on combining information from multiple genes. Most of these genes will not provide significant differences on their own, but a combination of odds-ratios will make one diagnosis more probable than the other.
Along with solutions at a mutational level, characterizing the transcriptome, methylation patterns and copy numbers of a tumour could also provide useful information. This field of ‘omics’ has developed rapidly in recent years. In diagnostically challenging cases from unknown primary tumours (UPT) or alternatively named carcinoma of unknown primary (CUP), expression array based assays were developed in order to identify the primary tumours. Genomics will also probably become effective in determining the origin of the tumour. Furthermore, in depth comparison of molecular features of synchronously presenting tumours at different sites might reveal whether the tumours have arisen independently or are clonally related. The readout of these tests can be seen in the context of increased odds-ratios. The use of such tests is still in a premature phase, and not used routinely in clinical practice.
Summary
In conclusion, a combination of the various molecular features will hopefully reveal specific molecular profiles that can be used to correctly identify the origin of malignancies in problematic cases. These techniques are applicable on ovarian tumours, to determine whether tumours are primary ovarian in origin or metastases to the ovaries [12].
References
1. Prat J. Ovarian carcinomas, including secondary tumors: diagnostically challenging areas. Mod Pathol. 2005; 18(Suppl 2): S99–111.
2. Young RH. From Krukenberg to today: the ever present problems posed by metastatic tumors in the ovary. Part II. Adv Anat Pathol. 2007; 14: 149–177.
3. Leen SL, Singh N. Pathology of primary and metastatic mucinous ovarian neoplasms. J Clin Pathol. 2012; 65: 591–595.
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5. de Waal YR, Thomas CM, Oei AL, Sweep FC, Massuger LF. Secondary ovarian malignancies: frequency, origin, and characteristics. Int J Gynecol Cancer 2009; 19: 1160–1165.
6. Yemelyanova AV, Vang R, Judson K, Wu LS, Ronnett BM. Distinction of primary and metastatic mucinous tumors involving the ovary: analysis of size and laterality data by primary site with reevaluation of an algorithm for tumor classification. Am J Surg Pathol. 2008; 32: 128–138.
7. Ji H, Isacson C, Seidman JD, Kurman RJ, Ronnett BM. Cytokeratins 7 and 20, Dpc4, and MUC5AC in the distinction of metastatic mucinous carcinomas in the ovary from primary ovarian mucinous tumors: Dpc4 assists in identifying metastatic pancreatic carcinomas. Int J Gynecol Pathol. 2002; 21: 391–400.
8. Groisman GM, Meir A, Sabo E. The value of Cdx2 immunostaining in differentiating primary ovarian carcinomas from colonic carcinomas metastatic to the ovaries. Int J Gynecol Pathol. 2004; 23: 52–57.
9. Bamford S, Dawson E, Forbes S, Clements J, Pettett R, Dogan A, Flanagan A, Teague J, Futreal PA, Stratton MR, Wooster R. The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website. Br J Cancer 2004; 91: 355–358.
10. Natrajan R, Reis-Filho JS. Next-generation sequencing applied to molecular diagnostics. Expert Rev Mol Diagn. 2011; 11: 425–444.
11. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler KW. Cancer genome landscapes. Science 2013; 339: 1546–1558.
12. Crobach S, Ruano D, van Eijk R, Fleuren GJ, Minderhout I, Snowdowne R, Tops C, van Wezel T, Morreau H. Target-enriched next-generation sequencing reveals differences between primary and secondary ovarian tumors in formalin-fixed, paraffin-embedded tissue. J Mol Diagn 2015; 17: 193–200.
The authors
Stijn Crobach BSc; Hans Morreau MD, PhD
Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
*Corresponding author
E-mail: j.morreau@lumc.nl
Ebola 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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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
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