We recruited 104 AIS patients who underwent thrombectomy, 57.7% (n=60) male and 42.3% (n=44) female. The mean age of the patients was 66.1 years. The median delay time between the onset of ischemic stroke and hospital arrival was 6 hours 58 min (range, 1-23 hours). The general clinical characteristics of LVO stroke patients are shown in Table 1.
Presence of Bacterial DNA and Microbial Features in Thrombus Aspirates
Clot samples were collected from all participants. Notably, 96.2% (n=100) of aspirated thrombi were positive for bacterial DNA in qPCR, while 3.8% (n=4) were bacteria-negative thrombi. All blank control samples obtained from the interventional instruments and interventionalist's gloves were bacteria-negative in qPCR; thus, exogenous contamination (surgical procedures and sample disposal procedures) of bacteria can be ruled out.
To characterize the microbial features of aspirated thrombi, we collected rectal and oral swabs and isolated plasma from all stroke patients within 12 hours after admission (Figure 1A). Rectal swabs were selected to represent the fecal microbiota. As shown in Figure 1B, the average 16S rRNA concentration of clot (15.94 ng/μL) samples was lower than that of oral (186.24 ng/μL) and fecal (40.86 ng/μL) samples but higher than that of plasma (3.91 ng/μL) samples. Except for 9 samples that could not be collected (1 fecal, 6 plasma, 2 oral), 2.9% (n=3) of isolated plasma samples were negative for bacterial DNA in qPCR. Microbiota from 100 clot, 95 plasma, 103 fecal, and 102 oral samples were characterized by 16S rRNA amplicon sequencing.
The OTU data was rarefied to 9500 reads per sample. After rarefaction, there were 3800000 sequences, and these clustered into 7439 OTUs. The rarefaction curves show that the OTU numbers in the clot and plasma groups were similar, but both were lower than those in the fecal and oral groups (Figure 1C). In addition, in the Venn diagram, there were 70 highly abundant OTUs in the thrombus samples that were shared with bacteria from other sites. The number of unique sequences was smallest in the clot (33) group and largest in the oral (140) group (Figure 1D). In terms of alpha diversity, the Shannon index of the clot group differed significantly from that of the fecal and oral groups (all P < 0.001) but was similar to that of the plasma group (P = 0.48) (Figure 1E). Additionally, unconstrained principal coordinate analysis (PCoA) of the Bray-Curtis distance revealed that the microbial composition of clot samples was obviously distinct from that of fecal, oral and plasma samples (Figure 1F, Adonis test, all P < 0.001).
There were 14 phyla, 182 genera and 542 OTUs that had a relative abundance greater than 1% across clot samples. The top 15 relative abundances of genera in thrombi were Acinetobacter (12.8%), Burkholderia (12.5%), Sphingomonas (10.9%), Pedobacter (7.0%), Serratia (5.5%), Stenotrophomonas (5.3%), Brevundimonas (3.8%), Bradyrhizobium (3.1%), Bacillus (2.1%), Elizabethkingia (1.6%), Prevotella (1.6%), Ochrobactrum (1.5%), Ralstonia (1.4%), Herbaspirillum (1.3%) and Chryseobacterium (1.3%). At the phylum level (Figure 1G), most sequences of clot samples were assigned to the phyla Proteobacteria (relative abundance 73.3%), Bacteroidetes (12.9%) and Firmicutes (10.0%) and, to a lesser extent, Actinobacteria (2.0%). At the family level, the top 5 relative abundances of clot bacteria were Moraxellaceae (14.1%), Burkholderiaceae (14.0%), Sphingomonadaceae (11.5%), Enterobacteriaceae (8.0%), and Sphingobacteriaceae (7.0%). In general, the bacterial composition of the thrombus samples was similar to that of the plasma samples but distinct from that of the oral and fecal samples.
Source Tracking of Clot Microbiota and Function Prediction by BugBase
A source tracking method, FEAST, was used to track the origin of the thrombus microbiota based on the OTU data. Contributions from each source were calculated and represented as a percentage. The clot microbial community had approximately 46.69% of the community sourced from plasma, only 2.34% from oral samples, and 2.09% from fecal samples (Figure 1H). Compared with the LAA group, a larger proportion of the thrombosis bacteria in the CE group was derived from plasma (50.69% & 43.74%), but there was no significant difference between the two groups.
To better understand the possible function of the bacteria in the thrombus, BugBase was used to infer and compare organism-level microbiome phenotypes among the different samples. The OTU contributions among the four groups are presented in Figure 2. We observed a significantly higher representation of aerobic bacteria, gram-negative bacteria, potentially pathogenic bacteria, bacteria related to biofilm formation and oxidative stress-tolerant bacteria in the clot and plasma groups (Figure 3).
Signature of Microbiota in the Clot via FISH
To further confirm the presence and visualize the distribution of bacteria in thrombi, we selected the universal bacterial probe EUB338 to label the bacteria in the thrombus (Figure 4A) using FISH and then imaged them with a spectral fluorescence microscope. A total of 58 paraffin-embedded thrombus samples (50% from the CE group) were collected in the study due to an insufficient amount of tissue. As described previously, the main components of thrombi in stroke patients are red blood cells, white blood cells, fibrin, and aggregated platelets. The red blood cells, fibrin, and aggregated platelets were visualized in a purplish red color in FISH slices (Figure 4B), and the blue color represented nucleated cells such as neutrophils and macrophages. In FISH analysis, green dot fluorescence in clot samples was a positive signature of bacteria. Three distribution patterns of microbiota in thrombi were observed: free distribution, intracellular clustering (single green signal dot > 5) and extracellular clustering. Ten visual fields with obvious bacteria-positive signals in each clot sample were randomly selected, and microbial distribution patterns were recorded. The comparison among the three distribution patterns was significantly different between the CE and LAA groups (Table 2). The thrombi in the CE group (Figure 4C-4D) were characterized as a clustered microbial distribution pattern, with mainly intracellular clustering and extracellular clustering, while the LAA group had mainly free microbial distribution (Figure 4E-4F).
Clot Microbial Peculiarity in Different Stroke Pathogeneses
The 16S rRNA concentration of clot samples in the CE group (average, 20.58 ng/μL) were remarkably higher than that in the LAA group (12.43 ng/μL, P = 0.007). Although the pathogenesis of stroke was associated with the distribution pattern of bacteria within the thrombus, no significant difference in bacterial diversity among different pathogeneses was observed based on the number of OTUs (Figure 5A, 5C). The microbial composition of cerebral artery thrombosis with different pathogeneses is probably similar. The relative abundance of the dominant taxa in each clot sample from the CE and LAA groups at the phylum (Figure 5B) and family levels (Figure 5D) is illustrated in the stacked plot. Furthermore, for specific OTUs, 22 OTUs were obviously depleted and 25 were markedly enriched in the CE group compared with the LAA group (Figure 5E). To identify differentially abundant microbiota between the two groups, linear discriminant analysis (LDA) coupled with effect size measurement (LEfSe) was performed. With this approach, we observed that the dominant bacteria in thrombi were different among AIS patients with different pathogeneses (Figure 5F). The CE group featured the Veillonellaceae family in the phylum Firmicutes, while the Chryseobacterium and Lactobacillaceae families were more dominant in the LAA group.
Features of the Clot Microbiome in Poor Clinical Outcomes
A total of 37.5% (n=39) of patients had perioperative adverse events, represented as the With_AE group. The remaining 65 patients were defined as the Without_AE group. The relative abundance of the dominant taxa in the With_AE and Without_AE groups at the family level (Figure 6A) is illustrated in the stacked plot. To further investigate the differences in bacterial species of these two groups, we compared the relative abundances of all OTUs between the groups, as shown by the Manhattan plot in Figure 6B, and found that 47 OTUs were significantly different with a false discovery rate (FDR) < 0.05 (above the dotted line) in the With_AE group. Further LEfSe analysis revealed that Acinetobacter (order Pseudomonadales, family Moraxellaceae) and Enterobacteriaceae were enriched in the thrombi of those patients with adverse events (Figure 6C). During the follow-up period, 17 (16.3%) patients died within 90 days of admission. The stacked plot exhibits the microbial differences in the thrombus samples in the death and survival groups (Figure 6D), and 43 OTUs were markedly different in the death group compared with the survival group (Figure 6E). The LEfSe results suggested that higher abundances of Pseudomonadales and Acinetobacter were closely related to the death outcome (Figure 6F).
Associations between Inflammatory Factors, Specific Microbiota and 90-day Mortality
LVO stroke patients who died within 90 days had higher white blood cell (WBC) levels at admission than those who survived at 90 days, suggesting a possible higher inflammatory response in the body (P = 0.025). To further reveal the level of inflammation in stroke patients, plasma isolated within 12 hours after mechanical thrombectomy was used for the ELISA (Table 3). The results showed that the concentrations of IL 1β (mean, 72.1 pg/mL & 43.2 pg/mL, P=0.004) and IL 6 (mean, 35.4 pg/mL & 26.6 pg/mL, P=0.002) were obviously increased in the plasma of patients with adverse events. Furthermore, increased levels of IL 1β (mean, 147.6 pg/mL & 36.3 pg/mL, P=0.001) and IL 6 (mean, 119.4 pg/mL & 13.1 pg/mL, P=0.001) in stroke patients were also found to be closely associated with 90-day mortality.
A Cox proportional hazards regression model was constructed to examine the associations between the abundances of specific taxa and 90-day mortality after mechanical thrombectomy (Table 4). The results of the univariate model showed that three clinical parameters (WBC, neutrophils (NEU), creatinine) were associated with the 90-day mortality of stroke patients. In addition, the preoperative NIHSS score, adverse events within 48 hours, poststroke infection during hospitalization, and history of atrial fibrillation and stroke were important risk factors for death. Interestingly, we also found that Pseudomonadales, Moraxellaceae and Acinetobacter were associated with 90-day mortality. Moreover, Acinetobacter (HR 2.664, 95% CI 1.384-5.129, P=0.003) remained significantly associated with 90-day mortality in the multivariate Cox regression analysis adjusted for other parameters listed in the table.