The Association of Serum Heat Shock Protein 72 and Intestinal Permeability with Intestinal Microbiota and Clinical Severity in Patients with Cerebral Infarction

doi:10.21203/rs.3.rs-2603836/v1

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The Association of Serum Heat Shock Protein 72 and Intestinal Permeability with Intestinal Microbiota and Clinical Severity in Patients with Cerebral Infarction

https://doi.org/10.21203/rs.3.rs-2603836/v1

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Purpose

This study aimed to investigate the comparison and relationship between serum heat shock protein 72 (sHSP72) and intestinal permeability in patients with cerebral infarction (CI) and healthy individuals to elucidate the link to gut microbiota alterations and clinical severity of CI.

Methods

Stool samples of 50 CI patients and 46 healthy volunteers were applied to characterize intestinal flora profile through 16S rRNA gene sequencing. Composition difference and taxon evaluation were observed. sHSP72 and zonulin were assayed using enzyme-linked immunoassay (ELISA). Medical comorbidities and dietary habits were acquired using questionnaires and partial biochemical index were recorded. The obtained data were then subjected to comparative and correlative analysis.

Results

We found that the levels of zonulin and sHSP72 were significantly higher in CI group compared to the healthy group. Strikingly, sHSP72 and zonulin levels were positively correlated in CI group. After adjustment for age, gender, medical comorbidities and biochemical index, sHSP72 and zonulin levels correlated positively with clinical severity of CI. In the CI patient group, the abundance of bacteria Eubacterium_fissicatena_group, Eubacterium_eligens_group and Romboutsia manifested remarkably positive correlation with sHSP72. The abundance of bacteria Eubacterium_fissicatena_group and Acetivibrio were significantly positive correlation with zonulin levels. The CI group had a decreased abundance of Eubacterium_fissicatena_group, Eubacterium_eligens_group and Romboutsia, and an increased abundance of Acetivibrio.

Conclusion

Our findings represented that an increase in sHSP72 and zonulin levels were manifested in patients with CI and related to specific gut microbiota alterations and the clinical severity of CI.

Intestinal flora

Cerebral infarction

Serum heat shock protein 72

Intestinal permeability

Zonulin

Stroke, a devastating and lethal disease, is currently among the second leading cause of death and the third contributor to disability in the world. Despite efforts to avoid risk factors, the incidence of stroke continues to increase annually, mainly affecting low-income and middle-income countries and imposing a heavy burden on society [11]. In China, cerebral infarction (CI) is the main type of stroke, approximately accounting for 75% of the total stroke population [36]. Besides the neurological defects caused by the infarct site, the major cause of death is the peripheral tissue damage induced by post-stroke leaky gut. Previous reports have shown that the abundance of opportunistic pathogens was increased significantly and the corresponding product of metabolism changes in CI patients compared with healthy controls [33]. In particular, it is now widely accepted that the hypothesis of microbiota-gut-brain axis [5]has relatively comprehensively illustrated the bidirectionality between gut and brain. Several pathways involved the axis, including immune system, tryptophan metabolism, the vagus nerve and the enteric nervous system, as well as microbial metabolites. CI facilitated the disruption of either of these links, inducing the increase of intestinal mucosal permeability. Indeed, strict regulation of intestinal integrity is essentially related to host antimicrobial immune defense. Regrettably, previous studies on CI and specific alterations of intestinal flora have not been effectively obtained explicit conclusions.

The serum zonulin, a protein produced by the intestine epithelium, is proportional to gut permeability. Vitro studies demonstrated that endogenous human zonulin was responsible for increased permeability in jejunum and ileum [37]. It is now widely accepted that zonulin has high sequential and structural similarity with epidermal growth factor (EGF). In this regard, EGF is essential for actin cytoskeleton modulation, suggesting that zonulin has the potential to disassemble tight junction (TJ) through EGF activation. An overgrowth of intraluminal microorganism and gluten contribute significantly to intestinal zonulin release [29]. Zonulin secretion has been reported to be induced through MyD88-dependent, which is followed by dissociation of the protein ZO-1 from the tight junctional complex, thus generating the leaky gut [7]. And of note, zonulin is the biological door to a vast number of diseases such as autoimmune diseases, neuropsychiatric diseases, and cancer through its intestinal barrier regulation function [6, 1].

Heat shock protein 72 (HSP72), a critical component of inducible HSPs (iHSPs), is a ubiquitous molecule that exerts efficient effects on cellular survivability and tolerance to stressors when confronted with heat stress, hypoxia, inflammation, and injury. Correspondingly, animal experiments showed that up-regulation of iHSP72 in ischemic cerebral tissue has confirmed a crucial protective role in the outcome following stroke [39]. Researches in vitro microglia cell models indicated that overexpression of HSP72 attenuated levels of NF-kB DNA binding and upstream kinase IKK activity, as well as restrained synthesis of the IkBα inhibitor after stroke [27]. Furthermore, HSP72 suppressed c-Jun N-terminal kinase 3 signaling pathway and enhanced the phosphorylation of protein kinase B (Akt), thus exerting a neuroprotective role against ischemia/reperfusion brain injury [24]. Recent evidence indicates that bacterial components and metabolites [19, 26] specifically control the expression of iHSPs. It is proposed that there are two potential mechanisms involved in the release of endogenous extracellular HSP72 (eHSP72). The first is that eHSP72 is released as a result of necrotic or lytic cell death. The second suggests that α-adrenergeric receptor mediates in vivo release of eHSP72 in response to environmental stressors [12]. Intricately, eHSP72 promotes innate immune response to acute pathogenicity under physiological condition. While in pathological states, eHSP72 on the one hand to help the body against pathogen invasion, on the other hand to promote chronic inflammatory diseases such as atherosclerosis and Alzheimer disease. HSP72 can be detected in quite a few of body fluids, such as pleural fluid [34], cerebrospinal [28], synovia [32], bronchoalveolar lavage fluid [38], and serum [22]. Similarly, enterocytes are capable of expressing HSP72, which regulates gut barrier function, initially by exerting efficient effects on the expression of TJ proteins such as occludin [2, 14]. Clinical and experimental studies have confirmed the elevated levels of iHSP in peripheral blood leukocytes and cerebral cells when confronted with stroke [15, 27]. Nevertheless, whether there is a change in serum HSP72 (sHSP72) after CI has not been addressed. Thereafter, how sHSP72 correlates with intestinal dysfunction and CI severity has not been accurately explored.

Accordingly, in this study, we deciphered gut microbiome profiles through 16S rRNA gene sequencing of stool, quantified sHSP72 and serum zonulin via enzyme-linked immunoassay (ELISA), further compared and analyzed the levels of sHSP72 and zonulin in patients with CI and healthy controls and link to alterations in intestinal microbiota and clinical severity of CI.

Study subjects

This cross-sectional study was conducted at Hangzhou First People’s Hospital. We have consecutively enrolled 81 CI patients and 52 healthy individuals respectively from the Department of Neurology and Physical Examination Center. Herein, we rigorously screened out 50 CI patients and 50 healthy controls who satisfied the inclusion criteria and ultimately participated in the study. Case groups were diagnosed within 2 weeks after sudden focal neurological deficits, with the acute infarct area in the corresponding brain region confirmed on the computed tomography (CT) and/or magnetic resonance imaging (MRI). Healthy controls never reported being diagnosed with any of the risk factors associated with CI such as hypertension, diabetes, metabolic syndrome, and atrial fibrillation in their lifetimes. Baseline characteristics such as demographic data including age, gender, dietary habits, medical histories (hypertension, diabetes and atrial fibrillation) and laboratory data were captured. This study was approved by the Clinical Research Ethics Committee of Hangzhou First People’s Hospital.

The inclusion criteria for the study subjects were determined as: (1) aged 40 to 80 years; (2) grew up in southern China and maintained a normal lifestyle, dietary habits and bowel habits; (3) body mass index range from 18 to 24; (4) had available blood and stool samples; (5) signed informed consent before the experiments. Subjects were excluded if they: (1) had a history of intracranial hemorrhage and other neuropsychiatric disorder; (2) was previous diagnosed with respiratory failure, heart failure, uremia, severe liver dysfunction, malignant tumors and autoimmune disease; (3) had inflammatory bowel disease, gastrointestinal bleeding and surgery, as well as other gastrointestinal dysfunction; (4) once received treatment with antibiotics, probiotics, and hormone drugs within 2 months prior to the recruitment.

Sample Collection

To avoid random error, fecal samples inside the middle section were taken with cotton swabs into two 2ml sterile frozen depository tubes of approximately 200mg samples for each tube. Fasting blood samples were collected in the coagulation vessels and centrifuged at 3000r for 10 min at -4℃. Serum was transferred to 1.5ml frozen tubes. Preprocessed stool and serum samples transferred to the laboratory for storage at -80℃ immediately.

Microbial Dna Extraction And Sequencing

The total DNA of fecal specimens was extracted using the E.Z.N.A.®Stool DNA Kit following the manufacturer’s instructions. For the benefit of excluding the possibility of the false positive PCR results as a negative control, ultrapure water was carried out for preparation of the diluent. The V3-V4 region of 16S rDNA was amplified and sequenced through 341F: (5’-CCTACGGGNGGCWGCAG-3’) and 805R: (5’-GACTACHVGGGTATCTAATCC-3’) bar-coded primers. The PCR products were confirmed by 2% agarose gel electrophoresis, purified by AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA), and correspondingly quantified by Qubit(Invitrogen, USA). The size and number of amplicon libraries were assessed on the library quantification kit of the Agilent 2100 Bioanalyzer (Agilent, USA) and Illumina (Kapa Biosciences, Woburn, MA, USA), respectively. In addition, we sorted the libraries on the NovaSeq PE250 platform.

16s Rrna Sequence Data Analysis

Samples were sequenced on the Illumina NovaSeq platform following the manufacturer's recommendations. The paired-end sequences were assigned to the samples according to the unique bar codes of the sample, and the barcode and primer sequences introduced into the library were also removed. Raw reads were quality-filtered under specific filtering conditions in line of fqtrim (v0.94). Chimeric sequences were filtered using the Vsearch software (v2.3.4). DADA2 was used to obtain the feature table and feature sequences. In turn, characteristic abundances were then normalized using the relative abundance of each sample according to the SILVA (release 132) classifier. Complexity of the sample species diversity was characteristic by α diversity within 4 indicators, including Chao1, Goods coverage, Shannon and Simpson, calculated by the QIIME2. The β diversity was calculated by Non-Metric Multi-Dimensional Scaling and plotted by the R package. Composition difference was analyzed by the Wilcoxon rank-sum test and Welch’s t-test, based on which we constructed the heat map at the phyla level.

Quantitative Assay Of Shsp72 And Zonulin By Elisa

A 50uL proof sample was added to the standard well. A 40uL sample diluent and a 10uL sample being-tested were added to the enzymatic coating plate so that samples were eventually diluted to 5-fold. Samples were incubated with 100uL HRP-Conjugate reagent at 37℃ for 60 minutes. Then, each well was filled with wash fluid and discarded for 30 seconds, repeated 5 times and dried. Each well was incubated with chromogenic agent at 37℃ for 15 minutes and then the reaction was terminated by adding 50uL of the stop solution to each well till the blue color turned yellow. Finally, the absorbance of each well was determined within the wavelength of 450nm.

Statistical Analysis

Data were analyzed using SPSS version 26.0 software and R version 3.6.1 statistical software. Continuous variable was denoted by mean ± SD while categorical variables by numbers and percentages. Measurement data meeting normality was indicated by independent sample Student’s t-test or analysis of variance and by wilcoxon's rank sum test if the variable violated the assumption of normality. Categorical variable differences between groups are compared by a χ² test. We used binary logistic regression analysis to explore the relationship between sHSP72 and zonulin levels and the occurrence of CI, after adjustment for age and sex. The area under the receiver operating characteristic (ROC) curve (AUC) was applied to evaluate the model’s diagnostic performance for investigating the ability of sHSP72 and zonulin levels to distinguish between CI patients and controls. Multivariable linear regression models was conducted to examine the association between sHSP72 and zonulin levels and clinical severity. The correlation between intestinal flora and clinical data was assessed by Spearman’s rank correlation analysis. The data correlation conforming to the normal distribution was analyzed with the Pearson test. P-value < 0.05 was defined as statistically significant.

Study Population And Baseline Characteristics

A total of 81 CI patients and 52 healthy individuals were enrolled in this study. 31 patients and 2 control participants failed to defecate on time or unqualified fecal sampling; they were thus excluded from the subsequent analysis. Indeed, 4 healthy samples could not meet the 16S rRNA sequencing requirements due to low fecal volume and unqualified amplification. Ultimately, only 96 subjects (50 CI patients and 46 controls) remained in the next 16S rRNA analysis. Whereas the final inclusion samples carried out ELISA smoothly. The National Institute of Health Stroke Scale (NIHSS) scores was less than 16 in the CI group, for which the patients with severe CI had difficult fecal discharge the early next morning. All participants in the experiment were matched for age (CI, 66.42 ± 6.92; health, 65.15 ± 5.82; p = 0.233) and gender (M/F, case, 26/24; control, 25/21; p = 0.818). The demographic and baseline clinical characteristics of CI patients and controls are shown in Table 1.

Table 1 Comparison of the baseline data between two groups

Clinical parameter	CI (n = 50)	Health (n = 46)	p-value
Sex, male	26 (52%)	25 (54%)	0.818
Age, y	66.42 ± 6.92	65.15 ± 5.82	0.233
NIHSS score	10.88 ± 2.67	/	/
Hypertension (n, %)	36 (72%)	0	＜ 0.01**
Diabetes (n, %)	25 (50%)	0	＜ 0.01**
Atrial fibrillation (n, %)	3 (6%)	0	＜ 0.01**
Smoking history (n, %)	9 (18%)	6 (13%)	0.504
TG (mmol/L)	1.53 ± 0.76	1.21 ± 0.60	0.013*
TC (mmol/L)	4.21 ± 0.97	2.64 ± 0.68	＜ 0.01**
LDL (mmol/L)	2.32 ± 0.84	2.43 ± 0.54	0.203
HCY (umol/L)	16.55 ± 10.90	8.81 ± 3.03	＜ 0.01**
UA (umol/L)	314.28 ± 89.72	350.30 ± 42.75	0.016*
sHSP72 (pg/g)	307.46 ± 42.59	176.61 ± 44.75	＜ 0.01**
zonulin (ng/ml)	135.70 ± 30.74	105.83 ± 24.04	＜ 0.01**

Abbreviation: TG, triglyceride; TC, total cholesterol; LDL, low density lipoprotein; HCY, homocysteine; UA, uric acid; sHSP72, serum heat shock protein 72.

Variables are expressed as mean ± SD or n (%).

*p < 0.05; **p < 0.01.

Comparison of sHSP and zonulin levels between the two groups

The quantification and comparison of sHSP72 and zonulin between the two groups were shown in Table 1 and Fig. 1. The mean sHSP72 level was 307.46 ± 42.59 pg/g in patients with CI, while the mean value being 176.61 ± 44.75 pg/g in controls. In light of this, patients with CI had significantly higher sHSP72 than controls (p < 0.01). Accordingly, the mean zonulin level was 135.70 ± 30.74 ng/ml in patients with CI, while the mean value being 105.83 ± 24.04 ng/ml in controls. Herein, serum zonulin was significantly higher in the CI group than that in healthy patients ( p < 0.01).

We then investigated whether sHSP72 or zonulin distinguished between patients with CI and healthy individuals. Binary logistic regression analysis indicated that higher levels of sHSP72 (OR = 1.10, 95% CI = 1.03-1.11; p < 0.01) and zonulin (OR = 1.04, 95% CI = 1.02-1.07; p < 0.01) have been more likely to associated with CI patients after adjustment for sex and age.

According to binary logistic analysis, ROC curve analysis was performed to predict CI occurrence. Strikingly, the AUC, represented the prediction precision, raised from 0.57 in the basic model (age + gender, p = 0.22) to 0.98 in way that added sHSP72 levels, which discriminated obviously between the CI and health groups in the logistic regression analysis (p < 0.01). The AUC was 0.79 with the addition of serum level of zonulin (p < 0.01), which also discriminated markedly between the CI and health groups in the logistic regression analysis. Furthermore, when brought age, gender, sHSP72 and zonulin into the full model, the AUC reached 0.98 (p < 0.01) (Fig. 2A and Table 2).

Table 2 Receiver Operating Characteristic Association Statistics for forecasting of cerebral infarction

	AUC (95% CI)	p value
Basic (age, sex)	0.57 (0.46 - 0.69)	0.22
Basic + sHSP72	0.98 (0.96 - 1.00)	< 0.01**
Basic + zonulin	0.79 (0.70 - 0.88)	< 0.01**
Full model^a	0.98 (0.95 - 1.00)	< 0.01**

Abbreviations: AUC = area under the receiver operating characteristic curve; CI = confidence interval. ^aFull model represented corresponding independent variables including age, sex, sHSP72 and zonulin. **p < 0.01.

Association of serum HSP72 and zonulin levels and CI Severity

Based on Pearson correlation analysis, we further observed that sHSP72 (ρ = 0.93, p < 0.01) and zonulin (ρ = 0.97, p < 0.01) positively correlated with NIHSS scores (Fig. 2B, 2C). Of note, we found positive correlation between the levels of sHSP72 and zonulin within CI group (ρ = 0.87, p < 0.01) (Fig. 2D). Similarly, after adjustment for age, gender, smoking history, previous related diseases and routine blood test results in bias correlation analysis, sHSP72 (ρ = 0.93, p < 0.01) and zonulin (ρ = 0.97, p < 0.01) levels continuously correlated positively with NIHSS scores in patients with CI. With multivariate linear regression model, we found that sHSP72 (b = 0.06, t = 14.37, p < 0.01) and zonulin (b = 0.02, t = 7.16, p < 0.01) were persistently positively correlate with NIHSS scores. These data demonstrated that higher levels of sHSP72 and zonulin were associated with more severe degree of CI.

Intestinal flora correlate with sHSP72 and zonulin

16s rRNA sequence analysis indicated features of gut microbiome between two groups. Alpha diversity was used to describe the species diversity of individual samples. The Wilcoxon rank-sum test among Chao 1, Good’s coverage, Simpson, Shannon indexes depicted there showed no statistical difference in species richness and evenness between the two groups (Fig. 3A). Beta diversity is an index reflecting the difference in composition and distribution of bacteria between groups. NMDS plots showed significant differences in intestinal microbiota composition between the two groups (Unweighted Unifrac stress = 0.17 and Weighted UniFrac stress = 0.15) (Fig. 3B). We then analyzed the differences in colony abundance at the 67 genus level (Fig. 3C). Accordingly, the CI group was more abundant with 27 Features, while the healthy group was enriched with 40 Features. These data indicated that the microbial abundance in the CI group was much lower than that in the healthy group.

We further performed the Spearman correlation analysis on the differentially abundant bacteria genus with sHSP72 and zonulin, respectively. We found significant correlations between bacteria genus and sHSP72 and zonulin. Among the correlation heatmap for CI participants, the abundance of bacteria Eubacterium_fissicatena_group, Eubacterium_eligens_group and Romboutsia manifested remarkably positive correlation with sHSP72 (ρ = 0.28, p = 0.04; ρ = 0.30, p = 0.03; ρ = 0.28, p = 0.04). The abundance of bacteria Eubacterium_fissicatena_group and Acetivibrio were significantly positive correlation with zonulin levels (ρ = 0.34, p = 0.02; ρ = 0.28, p = 0.04) (Fig. 4). Of note, CI group was characterized by a decreased abundance of Eubacterium_fissicatena_group, Eubacterium_eligens_group and Romboutsia and an increased abundance of Acetivibrio (p < 0.05).

The current study is the first to elucidate both sHSP72 and zonulin levels and interrelating to alterations in intestinal microbiota and CI symptom severity in patients compared with healthy controls. After adjustment for confounders, we subsequently demonstrated that increase in sHSP72 and zonulin associated with the symptom severity of CI and gut microbiota alterations.

Accordingly, in line with previous findings, we demonstrated that higher levels of sHSP72 in patients with CI than healthy controls. Notably, the levels of sHSP72 were positively associated with CI clinical severity. Intra-cellular HSP72 distributes in nearly every cell of the body and provides multiple cell survival functions such as restricting protein aggregation, promoting protein refolding, and acting as protein chaperoning. Current research paid attention to confirming intra-cellular HSP72 expression levels in various diseases. sHSP72 is considered to be involved in a variety of stress response and inflammatory reaction. In this regard, sHSP72 may confer an immunostimulatory effect that on the one hand facilitates innate immune responses against acute pathogenic substances, whereas, on the other hand, sHSP72 accelerates the inflammatory process in people suffering from a variety of disease states such as hypertension and atherosclerosis. As a danger signal, circulation HSP72 is capable of specifically stimulating NO, TNF-α, IL-10, and IL-6 secretion from macrophages and neutrophils [8]. Previous researches confirmed that overexpressing HSP72 facilitated satisfactory prognosis of cerebral ischemia-reperfusion injury, which may attributed to c-Jun N-terminal kinase 3 signaling pathway inhibition and Akt1 activation [23]. George et al. found an association between HSP72 overexpression and reduced reactive astrocytes after stroke, which may contribute to neuroprotection [3]. Consistently, Shailaja et al. suggested that HSP72 knockdown significantly up-regulate apoptosis inducing factor and ROS level in both anoxia / reoxygenation [13]. Recent work by Xu and his colleagues demonstrated that up-regulation of iHSP72 in ischemic cerebral tissue has been confirmed a crucial protective role in the outcome of stroke [13]. Also of note, endogenous HSP72 releases through necrotic or lytic cell death broken and α-adrenergeric receptor activation pathway in response to environmental stressors in ways that can be detected in blood and excreta [12]. We speculated that the elevation of the sHSP72 level after CI mainly resulted from two leading causes. The first is that intracranial ischemic death cells rupture and release HSP72 to peripheral blood circulation. The other is that the sympathetic adrenal axis activated after CI triggers a large amount of HSP72 released from tissue cells and intracranial inflammatory cells to alleviate brain inflammation and oxidative damage. In this connection, theoretically, HSP72 levels are related to the severity of inflammation and stress in organisms. Recent evidence revealed that high levels of sHSP72 were usually associated with enhanced oxidative profiles and ascending rates of mortality among septic patients [31]. Whereas, Zeynep et al. failed to obtain evidences confirming HSP72 was competent as a marker of predicting chronic kidney diseases progression [42]. To this point, our results suggested that HSP72 may play a role in the deterioration of CI.

We observed that patients with CI had higher serum concentrations of zonulin than controls. Zonulin levels correlated with degree of neurological deficit after CI. Our findings support a previous studies that blood levels of zonulin are elevated in neuro-inflammatory diseases, such as stroke, severe traumatic brain injury, neurodegenerative diseases and psychiatric disorders [25]. Produced by small intestine epithelium, blood zonulin levels become a reliable indicators reflecting intestinal permeability and inflammatory response level in vivo. Intriguingly, it is worth mentioning that intestinal epithelium plays an essential role in triggering the pathogenesis of numerous inflammatory diseases and zonulin levels are provoked under acute stress states. Apart from the direct neural pathway connecting the intestine and the brain, it has long been appreciated that post-stroke dysbiosis gives rise to a down-modulate biosynthesis of γδT lymphocytes that directly impairs the immune system stability. The proposed mechanism involves under pathological circumstances, the release of zonulin triggered by intestinal flora imbalance induces antigen influx from intestinal lumen to the lamina propria and further exacerbates immune response causing IFN-γ and TNF-α release [30,17]. It is worth mentioning that gut microbiota dysbiosis not only induces intestinal homeostasis damage but also stimulates the migration of γδT lymphocytes from the intestinal tract to the brain [40]. Additionally, zonulin secretion was regarded as MyD88-dependent followed by protein ZO-1 dissociation from the tight junctional complex which was responsible for both intestinal and extraintestinal inflammation, autoimmunity, and cancer [7,6]. Accordingly, the alterations of zonulin may be attributed to post-stroke dysbiosis and neuro-humoral mechanism.

Besides, we further observed the positive correlation of the levels of sHSP72 and zonulin. A compromise of intestinal mucosa is a result of increased severity and duration of stress and insufficient endogenous protective factors. Previous researches have got an insight into the endogenous protective mechanism of HSP72 within enterocyte. Back in 1999, in vitro cell study conducted by Musch et al. supported that HSP72 played a pivotal role in the integrity of actin cytoskeleton and maintainance of epithelial barrier function under oxidant-induced stress [21]. It remains a mystery whether sHSP72 could be a reliable indicator reflecting intestinal permeability. We speculated that sHSP72 may act on the brain-gut axis accelerating intestinal barrier destruction.

In the present study, the 16s rRNA sequencing results demonstrated that CI was associated with certain transformations in fecal bacteria. Consistent with the findings of previous publications, post-stroke dysbiosis was characterized by reduced diversity, decreased abundance of protective bacteria and harmful bacterial overgrowth. Intestinal dysbiosis is effectively linked to not only quite a number of risk factors for stroke such as diabetes, hypertension, and atherosclerosis, but also stroke outcomes. However, previous studies on CI and specific alterations of intestinal flora failed to obtain unanimous and definite conclusions, which may result from different races, DNA detection methods, and dietary habits among different researches.

Further we discovered that the levels of sHSP72 and zonulin in patients with CI were correlated with the relative abundance of specific differential microbial genera. E. fissicatena group and E. eligens group were positively correlated with sHSP72 and zonulin levels. Indeed, we noted the CI group was associated with a significant decrease in abundance of E. fissicatena group and E. eligens group. The genus Eubacterium, belongs to the bacterial phylum Firmicutes, has been identified to contribute to massive aspects of human health, for the majority of the family produce short-chain fatty acids (SCFAs), especially butyric acid. It is acknowledged accepted that SCFAs act as a special nutrient and energy component of the intestinal epithelium, protect the intestinal mucosal barrier and reduce inflammation levels in the body. Of note, Eubacterium has been shown to detoxify toxic compounds into more benign forms in the intestine. Understandably, it has been reported recently that reduction or absence of Eubacterium is associated with many diseases, such as depression, obesity, inflammatory bowel disease, type 2 diabetes, cardiovascular disease, colorectal cancer and autism [20]. However, functional annotation of E. fissicatena group and E. eligens group still remains poorly understood, partly due to their slightly potentially detectable in previous studies. Although the protective nature of most members of the genus Eubacterium, recent evidence revealed that E. fissicatena group belongs to potentially disease-related bacteria that added the risk of intestinal inflammation and metabolic disorders [44]. Jing et al. reported that the increased abundance of E. fissicatena group had a positive correlation with serum trimethylamine N-oxide (TMAO) levels, which was one of the independent risk factors of acute coronary syndrome [9]. Nevertheless, E. fissicatena group was also regarded as butyrate-producing bacteria and beneficial bacteria suppressing intestinal inflammation [9]. Another associated genus E. eligens group has been widely acknowledged to exhibit its probiotic effects. Using metagenomic analysis to estimate the gut microbiome profile in atherosclerosis patients, Sheng er al. has revealed that the abundance of E. eligens group was positively correlated with propionate and butyrate production but was negatively correlated with inflammatory marker high-sensitivity C-reactive protein and visceral fat area. Similarly, E. eligens group played vital roles in the pathway CDP-diacylglycerol biosynthesis and was also significantly correlated with higher high density lipoprotein-cholesterol levels, which significantly modulate the lipid metabolism [18]. Afterwards, in vitro cell-based assays found that E. eligens group efficiently promoted the production of the anti-inflammatory cytokine IL-10, suggesting the potential to be therapeutic target for inflammatory diseases [4]. In general, it seems reasonable in our results that E. fissicatena and E. eligens group, combined with sHSP72 and zonulin, have the potential to be involved in the post-stroke systemic inflammatory response.

Our research also added to previous reports that CI group has increased abundance of genus Acetivibrio, which manifested positive correlation with zonulin levels. The genus Acetivibrio was equipped with an efficient biological machinery transferring lignocellulose into ethanol and has been known to ferment carbohydrates to produce acetic acid [35]. Yuan et al. provided evidence that A. ethanolgignens group played a pivotal role in facilitating inflammation and lipid metabolism abnormalities as well as interfered with the energy supply process of tricarboxylic acid cycle [41]. Normal peristalsis, digestive and absorption functions of the gut require a series of coordinated operation of intestinal cells. Intestinal flora disorders and systemic inflammation will allow for intestinal barrier disruption and harmful substances invasion into circulation. We speculated that Acetivibrio accelerated increased intestinal permeability through the induction of metabolic disturbance and energy intake difficulty of intestinal cells.

Genus Romboutsia are SCFAs producers and immunomodulators in gut, which act in maintenance of the intestinal barrier integrity. Our results revealed that a significantly increased abundance of Romboutsia genus were observed in health group than CI group, and the higher the abundance of Romboutsia genus, the higher the levels of sHSP72. In earlier studies, Jacoline et al. showed that as a dominant taxa in small intestine of rats, Romboutsia displayed restricted capacity to synthesize amino acids and vitamins, whereas were adept at the utilization of different relatively simple carbohydrates [10]. Intriguingly, Romboutsia has the potential to engage in obesity-related metabolic abnormalities. Previous studies conducted by Zeng et al. presented that Romboutsia were positively associated with body weight, serum lipids and UA [43]. We therefore speculated that the decreased abundance of Romboutsia could be an indicator in post-stroke dysbiosis and the genus Romboutsia may have something to do with sHSP72 levels and post-stroke immunomodulatory effects.

Taken together, our findings proposed that increase in sHSP72 and zonulin were observed in patients with CI. And it has to be emphasized that the levels of sHSP72 and zonulin were related to the clinical severity of CI and specific gut microbiota alterations. Whereas our present study also has some limitations. First, it was a single-center cross-sectional study with inevitable time and place bias. Second, considering timely bowel movements, the NIHSS scores of CI patients enrolled in this study were no more than 15, which made it impossible to assess the relationship between extremely severe CI and the levels of sHSP72 and zonulin. Finally, a considerable part of patients in the CI group were accompanied by different coexisting diseases that may affect the results. In general, our results provided promising research prospects that the levels of sHSP72 and zonulin have the potential to serve as prospective markers for distinguishing CI patients from controls and mirroring disease severity. Further investigation is required to explore the definitive mechanisms of the sHSP72 and zonulin acting on the process of post-stroke systemic inflammatory and intestinal dysbiosis.

Cerebral infarction (CI); serum heat shock protein 72 (sHSP72); enzyme-linked immunoassay (ELISA); National Institute of Health Stroke Scale (NIHSS); epidermal growth factor (EGF); tight junction (TJ); Heat shock protein 72 (HSP72); computed tomography (CT); magnetic resonance imaging (MRI); receiver operating characteristic (ROC); area under the curve (AUC); short-chain fatty acids (SCFAs); trimethylamine N-oxide (TMAO);

Availability of Data and Materials The datasets used and analyzed during our study are available from the corresponding author on reasonable request.

Authors Contributions J.Z. designed and performed the experiments, and drafted the manuscript. J.D. and Y.D. collected and analyzed the data. S.H., B.Y. and X.F. critically revised the experimental design and the manuscript. B.T. and H.Z. helped with the outline and article modification. All authors read and approved the final manuscript.

Funding The work was supported by Zhejiang Provincial Medical and Health Technology Project for Young Backbone Talents (Grant No .2019RC234)

Conflict of Interest The authors declare that they have no conflicts of interest.

Ethics Approval The studies involving human participants were reviewed and approved by the Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine. The patients/participants provided their written informed consent to participate in this study.

Publisher’s Note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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The Association of Serum Heat Shock Protein 72 and Intestinal Permeability with Intestinal Microbiota and Clinical Severity in Patients with Cerebral Infarction

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Introduction

Materials And Methods

Study subjects

Sample Collection

Microbial Dna Extraction And Sequencing

16s Rrna Sequence Data Analysis

Quantitative Assay Of Shsp72 And Zonulin By Elisa

Statistical Analysis

Result

Study Population And Baseline Characteristics

Discussion

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