Abstract Bacterial and viral infections are often clinically indistinguishable, leading to inappropriate patient management and antibiotic misuse. Bacterial-induced host proteins such as procalcitonin, C-reactive protein (CRP), and Interleukin-6, are routinely used to support diagnosis of infection. However, their performance is negatively affected by inter-patient variability, including time from symptom onset, clinical syndrome, and pathogens. Our aim was to identify novel viral-induced host proteins that can complement bacterial-induced proteins to increase diagnostic accuracy. Initially, we conducted a bioinformatic screen to identify putative circulating host immune response proteins. The resulting 600 candidates were then quantitatively screened for diagnostic potential using blood samples from 1002 prospectively recruited patients with suspected acute infectious disease and controls with no apparent infection. For each patient, three independent physicians assigned a diagnosis based on comprehensive clinical and laboratory investigation including PCR for 21 pathogens yielding 319 bacterial, 334 viral, 112 control and 98 indeterminate diagnoses; 139 patients were excluded based on predetermined criteria. The best performing host-protein was TNF-related apoptosis-inducing ligand (TRAIL) (area under the curve [AUC] of 0.89; 95% confidence interval [CI], 0.86 to 0.91), which was consistently up-regulated in viral infected patients. We further developed a multi-protein signature using logistic-regression on half of the patients and validated it on the remaining half. The signature with the highest precision included both viral- and bacterial-induced proteins: TRAIL, Interferon gamma-induced protein-10, and CRP (AUC of 0.94; 95% CI, 0.92 to 0.96). The signature was superior to any of the individual proteins (P<0.001), as well as routinely used clinical parameters and their combinations (P<0.001). It remained robust across different physiological systems, times from symptom onset, and pathogens (AUCs 0.87-1.0). The accurate differential diagnosis provided by this novel combination of viral- and bacterial-induced proteins has the potential to improve management of patients with acute infections and reduce antibiotic misuse. 
 
 Citation: Oved K, Cohen A, Boico O, Navon R, Friedman T, Etshtein L, et al. (2015) A Novel Host-Proteome Signature for Distinguishing between Acute Bacterial and Viral Infections. PLoS ONE 10(3): e0120012. https://doi.org/10.1371/journal.pone.0120012 Academic Editor: Oliver Schildgen, Kliniken der Stadt Köln gGmbH, GERMANY Received: December 2, 2014; Accepted: February 2, 2015; Published: March 18, 2015 Copyright: © 2015 Oved et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: All relevant data are within the paper and its Supporting Information files. Funding: This study was funded by MeMed. KO, AC, OB, RN, TF, LE, EB and EE are employed by MeMed. YF and OK were previously employed by MeMed. MeMed provided support in the form of salaries for authors KO, AC, OB, RN, TF, LE, EB, EE, YF and OK, and was responsible for protein measurements and multiparametric signature development. Clinical investigators and MeMed affiliated authors collaborated on the study design, data collection and analysis, decision to publish, and preparation of the manuscript as articulated in the ‘author contributions’ section. Galit Denkberg is employed by Applied Immune Technologies. GD contributed to this work in her free time without any compensation from MeMed or Applied Immune Technologies. Applied Immune Technologies did not have a role in the study, design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section. Competing interests: This study was funded by MeMed. KO, AC, OB, RN, TF, LE, EB and EE are employed by MeMed. TF and KO were previously employed by MeMed. Professors PF, IP, and YR report holding equity ownership or stock-options in MeMed. Drs. IC, YD, MG, and AH were part of the clinical expert panel and received hourly fees from MeMed. Prof. RD received consulting fees from MeMed. All MeMed affiliated authors hold stock options. GD is employed by Applied Immune Technologies. Dr. GD contributed to this work in her free time without any compensation from MeMed or Applied Immune Technologies. Drs. EE and KO have two related patents: WO 2011/132086 (Signatures and determinants for distinguishing between a bacterial and viral infection and methods of use thereof) and WO 2013/117746 (Signatures and determinants for diagnosing infections and methods of use thereof). MeMed has the following related products: ImmunoXpert™ and ImmunoPoC™ (in development). This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials. 
 
 Introduction Antibiotic overuse, typically stemming from use of these drugs to treat non-bacterial infections, has severe global health and economic consequences, including the emergence of antibiotic-resistant bacteria [1,2]. Antibiotic underuse due to delayed or missed diagnosis is also common (24%-40% of all bacterial infections) [3–6], and may result in prolonged disease state and medical complications [7–10]. A major cause of antibiotic overuse and underuse is the difficulty of distinguishing between bacterial and non-bacterial (mostly viral) etiologies [3,11]. While routinely used microbiological diagnostic tests such as culture, serology, and more recently nucleic acid based tests (e.g., RT-PCR) can assist the clinician in the etiological determination of the underlying infectious process, several challenges remain. These include: (i) pathogen detection in cases where the infection site is not readily accessible (e.g., pneumonia), or is unknown (e.g., fever without source); (ii) time to microbiological laboratory results may be lengthy (hours or days); (iii) interpreting whether a detected bacteria is the disease causing agent or a mere colonizer [12–14], and (iv) identification of a virus does not preclude the possibility that an undetected bacteria may be the cause of the underlying illness (i.e. a case of mixed infection with both virus and bacteria) [15,16]. An approach that has the potential to address these challenges relies on monitoring the host's immune-response to infection, rather than direct pathogen detection [17]. Recent studies examining host-RNA signatures in response to different infections show promising results [17–21]. However, quantitative and rapid measurements (within minutes) of multiple host-RNAs in the clinical setting remain a technical challenge, especially at the point-of-care where most antibiotics prescriptions are made. Circulating host-proteins are an attractive alternative as they can be rapidly measured at the point of need. Proteins that are routinely used to support diagnosis of infection include procalcitonin, C-reactive protein (CRP), and Interleukin-6 (IL-6) [22]. However, these markers are sensitive to inter-patient variability, including time from symptom onset, clinical syndrome, and pathogen species [22–27]. For example, multiple studies found that procalcitonin is valuable for guiding antimicrobial therapy duration and for predicting disease severity [28–30], however its diagnostic accuracy for detecting bacterial etiology in cases such as sepsis and pneumonia has been challenged [23,31–34]. Elevated CRP levels are suggestive of a bacterial infection [35], but similar levels may be observed in patients with some viral strains (e.g., adenovirus and influenza) [36], and inflammatory diseases. While IL-6 rises quickly in response to a bacterial trigger, its utility is dampened by a limited window of opportunity for measurement due to its rapid decay within approximately 36 hours [37]. To improve the performance of individual host-proteins, combinations of several proteins into a single predictive score have been proposed [11,38–43]. However, to date, in most studies these combinations provided only limited-to-moderate diagnostic improvement over individual proteins. This may be explained by the predominant focus on bacterial-induced proteins (e.g., procalcitonin, IL-6, IL-8, SAA, CRP and sTREM), which share biological pathways, and are thus inherently sensitive to the same factors. Therefore, we reasoned that the combination of unrelated host-proteins participating in different pathways may improve diagnostic accuracy. In particular, the inclusion of new host-proteins that are up-regulated in viral infections may be an innovative complement to bacterially-induced proteins in current clinical use. Accordingly, the aims of the present study were threefold: to perform a large-scale screen of novel and traditional host-proteins; to integrate the findings into a computational signature for accurate diagnosis of acute bacterial (or mixed) versus viral infections; and to validate the signature on an independent cohort of patients. 
 
 Materials and Methods Ethics Statement We prospectively recruited 1002 patients between August 2009 and November 2013 from Hillel-Yaffe and Bnai-Zion Medical Centers, Israel (NCT01917461). The study was approved by the Hillel-Yaffe Medical Center Institutional Review Board (approval ID 0071–10-HYMC), and the Bnai-Zion Medical Center Institutional Review Board (approval ID 0084–12-BNZ). The study was conducted according to the guidelines and recommendations of Good Clinical Practice and the Declaration of Helsinki. Written informed consent was obtained from each participant or legal guardian, as applicable. Study population Pediatric patients (≤18 years) were recruited from pediatric emergency departments, pediatric wards and surgical departments, and adults (>18 years) from emergency departments, internal medicine departments and surgical departments. Inclusion criteria for the infectious disease cohort included: clinical suspicion of an acute infectious disease, peak fever >37.5°C since onset of symptoms, and duration of symptoms ≤12 days. Inclusion criteria for the control group included: clinical impression of a non-infectious disease (e.g., trauma, stroke and myocardial infarction), or healthy subjects. Exclusion criteria included: evidence of acute infection in the two weeks preceding enrollment; congenital immune deficiency; treatment with immunosuppressive or immunomodulatory therapy; active malignancy; and human immunodeficiency virus (HIV)-1, or hepatitis B/C virus infection (Fig. 1A). Importantly, in order to enable broad generalizability, antibiotic treatment was not an exclusion criterion. PPT PowerPoint slide 
 
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 larger image TIFF original image Download: Fig 1. Study workflow. (A) An overview of the study workflow. n Bacterial , n Viral and n Control represent the number of bacterial (including mixed bacterial plus viral co-infections), viral and control (with no apparent infectious disease) cases, respectively. CBC—complete blood count. (B) An overview of protein screening, model construction and validation process. https://doi.org/10.1371/journal.pone.0120012.g001 Enrollment process and data collection For each patient, the following baseline variables were recorded: demographics, medical history, physical examination, complete blood count obtained at enrollment, and chemistry panel. A nasal swab was obtained for microbiological investigation including two multiplex-PCR diagnostic assays (Seeplex RV15 [n = 713; 16 viral strains] and Seeplex PB6 [n = 633; six bacterial strains]), and a blood sample was obtained for host-protein measurements. Additional samples were obtained as deemed appropriate by the physician (e.g., urine [n = 420], stool [n = 66] and blood [n = 420] samples in cases of suspected urinary tract infection [UTI], gastroenteritis [GI] and bacteremia respectively) (S1 Data). Radiological tests were obtained at the discretion of the physician (e.g., chest X-ray for suspected lower respiratory tract infection [LRTI]). Thirty days after enrollment, disease course and response to treatment were recorded. Establishing the reference standard For determining the infectious etiology we created a rigorous expert panel reference standard [44], which follows the broadly accepted recommendations of the Standards for Reporting of Diagnostic Accuracy (STARD)[45], and the NHS Health Technology Assessment (NHS-HTA) for evaluation of diagnostic tests [46]. First, we performed a thorough clinical and microbiological investigation for each patient as described above. This was followed by a review of the data collected throughout the disease course by a panel of three physicians. For adult patients the panel included the attending physician and two infectious disease specialists, while for children it included the attending pediatrician, an infectious disease expert and a senior attending pediatrician. Each panel member assigned one of the following diagnostic labels to each patient: (i) bacterial; (ii) viral; (iii) no apparent infectious disease or healthy (controls); and (iv) indeterminate. Patients diagnosed by the panel as having mixed infections (bacteria and virus) were labeled as bacterial because they are managed similarly. The panel members were blinded to the labeling of their peers to prevent group pressure or influential personality bias as recommended by NHS-HTA [46]. Importantly, they were blinded to the results of the signature. Final diagnosis was determined by panel majority (i.e. at least two of the three panel members assigned the same label) (Fig. 1A). To examine the generalizability of the results it is recommended to examine whether alternative reference standard strategies affect performance [44,46]. Thus, two additional strategies were applied: (i) Unanimous sub-cohort: Patients were assigned the same label by all three panel members; and (ii) Microbiologically confirmed sub-cohort: Bacterial labeled patients were unanimously diagnosed by all three panel members and had one of the following microbiological confirmations: bacteremia (with positive blood culture), bacterial meningitis (with positive CSF culture), lower UTI (with positive urine culture), upper UTI (with positive urine culture and ultrasound demonstration of renal involvement) or peritonsillar abscess (proven by surgical exploration or computerized tomography). Viral labeled patients were unanimously diagnosed by panel members and had at least one laboratory detected virus. Samples, procedures and protein measurements Venous blood samples were stored at 4°C for up to 5 hours, subsequently fractionated into plasma, serum and total leukocytes, and stored at -80°C. Nasal swabs and stool samples were stored at 4°C for up to 72 hours and subsequently transported to a certified service laboratory for multiplex PCRs. In the screening phase, host-proteins were measured using enzyme-linked immunosorbent-assay (ELISA), Luminex, protein-arrays and flow-cytometry. The three proteins used in the final signature were measured as follows: CRP using either Cobas-6000, Cobas-Integra-400/800, or Modular-Analytics-P800 (Roche); TRAIL and IP-10 using commercial ELISA kits (MeMed Diagnostics). Statistical analysis Primary analysis was based on AUC, Sensitivity (TP/P), Specificity (TN/N), Positive likelihood ratio (LR+ = Sensitivity/[1-Specificity]), Negative likelihood ratio (LR− = [1–Sensitivity]/Specificity) and Diagnostic odds ratio (DOR = LR+/LR−), where P, N, TP and TN correspond to positives (bacterial patients), negatives (viral patients), true positives, and true negatives, respectively. Sample size calculations are presented in S2 Data. Half of the patients in the study were randomly assigned to the training-set (used for protein screening and model development), and the remaining half to a mutually exclusive validation-set (used to assess model performance). Importantly, none of the validation-set patients were used to train the algorithms, or to select the proteins (Fig. 1). A multinomial logistic regression model was used to integrate the levels of multiple proteins into a bacterial likelihood score. Patients whose probability of bacterial infection was intermediate, between 0.35 and 0.55, were flagged. We use the term 'equivocal immune response' to describe these patients because their profile borders between bacterial and viral host-responses. Statistical analysis was performed using MATLAB (MathWorks). 
 
 Discussion The host-protein signature presented here addresses several challenges of current microbiological testing. (i) The difficulty of diagnosing patients whose infection site is inaccessible or unknown. The signature accurately diagnosed such cases, including LRTI (AUC 0.95±0.03, n = 153) and fever without source (AUC = 0.97±0.03, n = 123). (ii) Prolonged time to results (hours to days). The signature measures soluble proteins, which can be quantitated using an ELISA format. Moreover, these proteins are readily amenable to rapid measurement (within minutes) using hospital-deployed automated immunoassay machines and point-of-care devices. (iii) Identification of a virus does not exclude the possibility of mixed infection involving an undetected bacteria [15,16]. The signature classifies mixed infections with pure bacterial infections, thus prompting physicians to manage both groups similarly with regard to antibiotic treatment. (iv) A significant drawback of microbiological tests, PCRs in particular, is the detection of potential colonizers in subjects with non-bacterial diseases [12–14]. The signature performance was unaffected by the presence or absence of potential colonizers. The proteins included in the signature are not limited to well-established bacterial biomarkers. Six hundred host-proteins were screened (Fig. 1B), which to the best of our knowledge, is the largest quantitative proteome screening of patients with acute infection to date. Bioinformatics analysis was then used to identify a combination of three proteins with complementary dynamics: (i) We found that TRAIL was induced in response to a wide range of viral infections and surprisingly, also exhibited significantly reduced levels in bacterial infected patients (Fig. 2 and 4). Such opposing dynamics make TRAIL particularly suitable for distinguishing between bacterial and viral infections. The increase in viral patients may be related to TRAIL's role in programed cell death, which is a mechanism of infected cells to inhibit the virus from spreading [47]. The underlying reason for its reduction in bacterial infections warrants further studies. (ii) IP-10 levels were highly elevated in viral patients and less elevated in bacterial patients (Fig. 2 and 4). (iii) CRP levels were highly elevated in bacterial patients and less elevated in viral patients (Fig. 2 and 4). While the utility of increased CRP levels to suggest bacterial infections is well established [49], viral-induced proteins such as TRAIL are not used in clinical practice. The combination of novel viral-induced proteins that complement routinely used bacterial-induced proteins, substantially contributed to the signature’s robustness across a wide range of subgroups. PPT PowerPoint slide 
 
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 larger image TIFF original image Download: Fig 4. TRAIL, IP-10 and CRP participate in different signaling pathways and exhibit complementary dynamics in response to bacterial (B) and viral (V) infections. PAMPs—pathogen-associated molecular patterns; PGN—peptidoglycan; LPS—lipopolysaccharide. https://doi.org/10.1371/journal.pone.0120012.g004 Currently, there is no single perfect reference standard for diagnosing bacterial and viral infections in a large fraction of the patients with symptoms of an acute infection. Several strategies can be applied, each with strengths and limitations [46]. Clinical suspicion confirmed by positive microbiological lab results is often used as a reference standard. However, limitations include false-positives due to technical issues (e.g., culture contamination [50,51] and uncertainty due to viral and bacterial carriage [12–14]). Moreover, these patients may represent the more severely ill, and potentially easier to diagnose cases, leading to overly optimistic performance. The expert panel diagnosis is another widely used approach [44,46]. It has the advantage of capturing a wider spectrum of illness severities including difficult-to-diagnose cases, and is therefore likely to generalize well to clinical practice [44,46]. However, the absence of a microbiological confirmation may lead to higher rates of mislabeling. Since these methods complement each other we applied both. A microbiologically confirmed reference standard was used for proof-of-principle on a sub-cohort of the patients yielding particularly high performance (AUC = 0.96±0.02), and the expert panel reference standard was used to generalize the results to the entire patient cohort (AUC = 0.94±0.02). The latter results are more conservative and likely to represent the performance of the signature in the real clinical setting. A potential limitation of the current study is the heterogeneity of the patient cohort (multiple clinical syndromes, pathogen species, and time from onset of symptoms). We deliberately selected a diverse cohort in order to identify a signature that is insensitive to the inter-patient variability typically encountered in clinical settings. However, this diversity makes it more challenging to control for confounding factors. Although we did not identify significant confounders, follow-up studies on homogenous subgroups are warranted. Finally, the present signature has broader applications beyond the scope of the present study that warrant further investigation. Future studies should seek to replicate our findings with patients of different ethnic populations, particularly in countries with a high prevalence of endemic chronic pathogens (e.g. Mycobacterium tuberculosis, Plasmodium and HIV). Follow-up time course studies that assess whether the signature can predict response to treatment and patient prognosis are also warranted. Despite advances in infectious disease diagnosis, timely identification of bacterial infections remains challenging, leading to antibiotic misuse with its profound health and economic consequences. To address the need for better treatment guidance, we developed and validated a signature that combines novel and traditional host-proteins for differentiating between bacterial and viral infections. Our finding in a large sample size of patients is promising. The translational benefit could have a broad impact on the diagnosis and management of patients with acute infections. 
 
 Acknowledgments We thank Harel Todar and Dr. Mira Peled Kamar for logistic support, Mr. Carlos G. Gonzalez for graphic assistance and Dr. Iris Kulbatski, Dr. Zohar Yakhini and Prof. Itamar Shalit for scientific comments and reviewing the manuscript. 
 
 Author Contributions Conceived and designed the experiments: KO IP YR IS AK EE. Performed the experiments: OB TF LE OK YF RY RW GD YD AH MG IC. Analyzed the data: KO AC OB RN PF MG EE. Wrote the paper: KO AC EB MG IS PF RD IP EE. Interpretation of results: KO AC RN EB RD EE. Critically revised the manuscript: OB RN TF LE OK YF RY RW GD YD AH YR MG IC AK. ||||| Tirat Carmel, Israel - March 19, 2015 - MeMed, Ltd., today announced publication of the results of a large multicenter prospective clinical study that validates the ability of its ImmunoXpert in-vitro diagnostic blood test to determine whether a patient has an acute bacterial or viral infection. The study enrolled more than 1,000 patients and is published in the March 18, 2015 online edition of PLOS ONE. Unlike most infectious disease diagnostics that rely on direct pathogen detection, MeMed's assay decodes the body's immune response to accurately characterize the cause of the infection. 
 
 Bacterial and viral infections are often clinically indistinguishable, leading to antibiotic overuse and contributing to the spread of antibiotic resistance, which the World Health Organization says is approaching crisis proportions. Paradoxically, the inability to rapidly differentiate infections also results in the underuse of antibiotics, estimated to occur in 20-40% of all bacterial infections, putting patients at risk of complications and increasing healthcare costs. MeMed researchers developed the ImmunoXpert test to accurately distinguish between bacterial and viral infections, with the goal of improving patient management by providing physicians with information that enables them to reduce both the overuse and underuse of antibiotics. 
 
 Eran Eden, PhD, CEO of MeMed, noted, "Antibiotic misuse is a pressing public health concern, with devastating healthcare and economic consequences. Rapid, accurate and actionable diagnostic tools are an important part of the solution because they can aid physicians in making better informed treatment decisions. For the past four years, our team has been collaborating with leading clinicians and scientists from around the world to develop and validate our novel approach for distinguishing between bacterial and viral infections. Unlike most traditional diagnostics, this approach builds on an exquisitely informative system crafted by nature - the human immune system. Our scientists have figured out how to decode the actions of the immune system doing what it does best--detecting and responding to the precise cause of infection." 
 
 MeMed's technology leverages the fact that bacteria and viruses trigger different pathways in the immune system. By conducting extensive screening of immune system proteins in patients with acute infections, researchers identified three soluble proteins that are uniquely activated by bacteria or viruses. They then developed proprietary algorithms that integrate these proteins to produce an immune signature that accurately identifies the cause of infection. 
 
 In the PLOS ONE study, the ImmunoXpert immune signature was developed and independently validated on a cohort of 1002 patients with acute infections and yielded highly accurate results, with sensitivity and specificity greater than 90%. The assay was validated in a diverse group of pediatric and adult patients at different time points after the onset of symptoms (from the first day up to 12 days) and across 56 different pathogen species. ImmunoXpert remained robust over all sub-groups studied. The predictive power of the assay's immune signature outperformed routine biomarker and laboratory tests, as well as combinations of these tests. The signature is amenable to rapid measurement using a blood test run on standard hospital and laboratory-deployed automated platforms, or using a point-of-care device now in development. 
 
 "We conducted big data filtering, followed by extensive screening of 600 immune system-related proteins," said Kfir Oved, PhD, MeMed CTO. "A few of the proteins showed distinctly different patterns in bacterial and viral infected patients. In particular, the most informative protein we found, called TRAIL, dramatically increased in the blood of patients infected with a wide range of viruses, but surprisingly, decreased in bacterial infections. Our team developed an algorithm that computationally integrates TRAIL with other immune proteins to diagnose the cause of the infection with high accuracy." 
 
 The ImmunoXpert immune-based approach overcomes inherent limitations of many traditional diagnostics tools. It is accurate and rapid, it can diagnose infections that are not readily accessible such as pneumonia (because immune system components circulate throughout the entire body), and it prevents false alarms due to the benign presence ("carriage") of potentially pathogenic bacteria and viruses that are not causing active disease. 
 
 "This study represents a breakthrough in our efforts to develop more accurate, rapid and actionable diagnostic tools that improve the management of patients with acute infection." said Professor Isaac Srugo, MD, Head of the Pediatric Department and Microbiology Lab at Bnai Zion Medical Center. "The incorporation of novel viral-induced proteins, currently not in clinical use, enables ImmunoXpert to attain high levels of accuracy, which can help physicians make better informed antibiotic treatment decisions. This should result in more bacterial infected patients receiving timely therapy that is actually useful for treating their illness. Additionally, it can lead to fewer prescriptions to viral patients for whom antibiotics do nothing to speed recovery, while causing potential harm to the larger community." 
 
 MeMed's ImmunoXpert test is CE marked and approved for clinical use in the European Union and Israel. It is currently in pilot distribution in these territories, with a broader commercial roll-out planned for later this year. Additional clinical studies are underway and the company is planning to conduct clinical trials in the U.S. using a specially-designed point-of-care platform currently in development. 
 
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 About MeMed 
 
 MeMed is dedicated to improving patient lives through research, development and commercialization of pioneering products that monitor the body's immune state. Its products decode the immune system's distinct responses to different health and disease states. The company focuses on providing rapid, accurate and actionable diagnostic solutions for acute infectious diseases and inflammatory disorders in the hospital and community. Its most advanced product, ImmunoXpertTM, has demonstrated the ability to accurately detect whether a patient has a bacterial or viral infection, with the aim of empowering physicians to make better informed antibiotic treatment decisions. ImmunoXpert is CE marked and approved for clinical use in the EU and Israel, with pilot distribution efforts underway. For additional information, please visit http://www. me-med. com . 
 
 Notes to Editors 
 
 For more information on the public health crisis caused by the spread of antibiotic resistant bacteria, see for example:
– When you're hacking up a lung and it's not getting better, you know you're going to have to visit the doctor. What you (and even the doctor) often don't know is whether that antibiotic Rx you may get is going to work, simply because it's often hard to tell the difference between a viral and bacterial infection. But a study published in PLOS One says that may all change with a blood test that can quickly differentiate between the two, the BBC reports. And if MeMed's ImmunoXpert proves to work as scientists say it does, it could not only get antibiotics more quickly to patients with bacterial infections (the only ones antibiotics work on), but also cut down on patients who don't have bacterial infections from taking them. That's big, because overuse is linked to widespread antibiotic resistance. The study in Israel examined some 1,000 patients, scrutinizing the body's immune response to the sickness and honing in on protein trails that are activated depending on whether an infection is viral or bacterial. In particular, levels in blood of one protein called TRAIL significantly shot up in subjects who had been infected with viruses, while it dropped in patients with bacterial illnesses. The CEO of MeMed says the test works—a post at EurekAlert touts "highly accurate results, with sensitivity and specificity greater than 90%"—and offers results within two hours for most patients, per the BBC. "It is not perfect and it does not replace a physician's judgment, but it is better than many of the routine tests used in practice today," Eran Eden says. (A newly discovered antiobiotic may help fight superbugs.)