Prediction of the pathogens that are the cause of pneumonia by the battlefield hypothesis

Abstract

Commensal organisms are frequent causes of pneumonia. However, the detection of these organisms in the airway does not mean that they are the causative pathogens; they may exist merely as colonizers. In up to 50% cases of pneumonia, the causative pathogens remain unidentified, thereby hampering targeting therapies. In speculating on the role of a commensal organism in pneumonia, we devised the battlefield hypothesis. In the "pneumonia battlefield," the organism-to-human cell number ratio may be an index for the pathogenic role of the organism. Using real-time PCR reactions for sputum samples, we tested whether the hypothesis predicts the results of bacteriological clinical tests for 4 representative commensal organisms: Streptococcus pneumoniae, Haemophilus influenzae, Pseudomonas spp., and Moraxella catarrhalis. The cutoff value for the organism-to-human cell number ratio, above which the pathogenic role of the organism was suspected, was set up for each organism using 224 sputum samples. The validity of the cutoff value was then tested in a prospective study that included 153 samples; the samples were classified into 3 groups, and each group contained 93%, 7%, and 0% of the samples from pneumonia, in which the pathogenic role of Streptococcus pneumoniae was suggested by the clinical tests. The results for Haemophilus influenzae, Pseudomonas spp., and Moraxella catarrhalis were 100%, 0%, and 0%, respectively. The battlefield hypothesis enabled legitimate interpretation of the PCR results and predicted pneumonia in which the pathogenic role of the organism was suggested by the clinical test. The PCR reactions based on the battlefield hypothesis may help to promote targeted therapies for pneumonia. The prospective observatory study described in the current report had been registered to the University Hospital Medical Information Network (UMIN) registry before its initiation, where the UMIN is a registry approved by the International Committee of Medical Journal Editors (ICMJE). The UMIN registry number was UMIN000001118: A prospective study for the investigation of the validity of cutoff values established for the HIRA-TAN system (April 9, 2008).

Figure 1. Battlefield hypothesis.

(A) When pneumonia occurs, the numbers of both the causative pathogen and human inflammatory cells increase at the inflammation site. Meanwhile, the colonizing pathogen lags behind. The ratio of pathogen to human cells may be a good indicator for the differentiation of the causative pathogen from the colonizing pathogen. (B) The cell number ratio is measurable by quantitative PCR. The Ct (threshold cycle) is the PCR cycle at which a statistically significant fluorescent signal is first observed. Ct_pathogen is the Ct for the pathogen-specific gene, Ct_human is the Ct for the human-specific gene, and both are log-proportional to the number of the cells (see Figure 2 ). Accordingly, ΔCt_pathogen =  −(Ct_pathogen−Ct_human) is log-proportional to the ratio of pathogen to human cells. (C) Because ΔCt_pathogen indicates the ratio of pathogen to human cells, we may be able to determine the ΔCt_pathogen cutoff, a ΔCt_pathogen value above which a pathogenic role of the pathogen in pneumonia is strongly suggested.

Figure 2. Relationship between cell number and Ct.

Log-linear relationships between the copy number of pathogen-specific sequence and Ct_pathogen and between the copy number of the human-specific sequence and Ct_human. (A) S. pneumoniae, H. influenzae, Pseudomonas spp., or M. catarrhalis was suspended in sputum. DNA was then purified from the suspension, and the target sequences specific to each organism were amplified by PCR. A log-linear relationship indicates that the sputum does not contain molecules that inhibit isolation of DNA or exponential amplification by PCR. Experiments were done in triplicate. A bar indicates standard deviation. (B) Human genomic DNA isolated from sputum was serially diluted, and a DNA sequence in the human SFTPC gene (arbitrarily selected from human genes, of which sequence is specific to human by BLAST search of GenBank database; Table 2 ) was amplified. A log-linear relationship indicates that the sputum does not contain molecules that inhibit isolation of DNA or exponential amplification by PCR.

Figure 3. Determination of the ΔCt cutoff.

(A) Selection of purulent sputum. Sputum was classified by its gross appearance, with 50 samples studied for each classification. Purulent sputum had a Ct_human <27 (>7×10³ human cells/µL of sputum; Figure 2B ). Samples with M2–P3 appearance as well as a Ct_human <27 (enclosed by a dotted line) were studied further. Classification of the gross appearance of the sputum (M1, M2, P1, P2, and P3) are according to Miller and Jones . (B) Determination of the ΔCt cutoff. ΔCt_pathogen was measured for 4 representative commensal organisms (n = 223). Samples from patients with pneumonia in which a likely causative pathogen was identified using criteria (1)–(4) (see Methods) are shown as blue circles, and samples from patients with pneumonia in which none of criteria (1) – (4) was fulfilled were shown as white circles. The ΔCt_pathogen cutoff (a red line) was defined as the smallest ΔCt_pathogen for the blue circles. Sputum in which the pathogen was not detected and thus ΔCt_pathogen was not assigned is shown at the bottom (labeled as “Not detected”). (C) Reproducibility of ΔCt_pathogen measurements. Duplicate samples were isolated from a single patient in a single day (n = 28), and each of the duplicate samples was independently measured for ΔCt_pathogen. Both of the measurements provided ΔCt_pathogen located on the same side (above or below) of the cutoff. Red line: the cutoff for each organism. (D) Temporal profile of ΔCt_pathogen during antibiotic treatment. A single sample set contains multiple sputum samples isolated from a single patient during antibiotic treatment. A total of 9 consecutive sample sets that included 7 of pneumonia with ΔCt_pathogen for S. pneumoniae > cutoff and 2 of pneumonia with ΔCt_pathogen for H. influenzae > cutoff at day 1 were studied. ΔCt_pathogen decreased to below the cutoff in the course of treatment.

Figure 4. A prospective study.

(A) ΔCt_pathogen for each commensal organism (n = 153). Samples in which real-time PCR failed to detect the organism are shown at the bottom (“Not detected”). The ΔCt_pathogen cutoff demarcated well the samples obtained from the patients in whom the likely causative pathogen was identified by criteria (1) – (4). (B) Interrelationship between the pathogens detected. Samples obtained from the patients in whom the other 3 commensal organisms were identified as a likely causative pathogen or samples in which a non-commensal organism was detected by real-time PCR are colored. Most of the colored circles are located below the cutoff line.