Tandem ssDNA in neutrophil extracellular traps binds thrombin and regulates immunothrombosis

Significance

The role of neutrophil extracellular traps (NETs) in promoting thrombosis has been well recognized; however, the precise molecular mechanisms about how NETs function as blood coagulation scaffolds remain underexplored, particularly the contribution of NET-derived DNA. Here, we identified that specific single-stranded DNA sequences, (ATTCC)n repeats, within NETs selectively bind thrombin, a key enzyme in coagulation, thereby enhancing immunothrombosis. This interaction is dependent on both the DNA sequence and its tertiary structure. Targeting this interaction could block the deposition of thrombin in NETs, thus inhibiting NET-promoted thrombosis. These findings expand our understanding of NET-derived DNA functions and suggest therapeutic strategies for managing dysregulated coagulation.

Abstract

Neutrophils release neutrophil extracellular traps (NETs) to neutralize infections, a process that also contributes to immunothrombosis. While beneficial in localized infections, excessive NET formation can lead to widespread coagulopathy and organ failure. While the roles of NET-associated proteins such as histones in immunothrombosis are well characterized, NET-derived DNAs are much less known. To address this issue, we report herein the direct interaction between thrombin and DNA scaffolds and further, the identification of short tandem repeats of single-stranded (ATTCC)_n in NETs that selectively bind thrombin, a crucial enzyme involved in both blood clot formation and immune response. We have also developed a strategy of selective targeting ss(ATTCC)_n using antisense locked nucleic acids (LNAs), effectively disrupting NET–thrombin interactions. This finding reveals an unexplored role of single strand DNA (ssDNA) within NETs and provides a broad avenue for developing targeted therapeutic interventions for immunothrombosis-related disorders.

Inflammation is a crucial physiological response that controls invading pathogens and facilitates tissue repair (1). A major component of this process is neutrophils, which are the predominant type of immune cells and become activated and form neutrophil extracellular traps (NETs) to combat microbial infections. The NETs consist of web-like structures that contain DNA from chromatin and mitochondria, along with granular proteins and they work together to immobilize and neutralize bacteria (2). At the same time, the accumulation of NETs within microvascular vessels can trigger venous thrombosis (3). Such NET-facilitated thrombosis is common in various autoimmune (4), nonimmune disorders (5, 6), and cancer (7–9). This phenomenon, the crosstalk between the activation of neutrophil, NETs, and their interactions with the coagulation system, called immunothrombosis (10), serves as a protective barrier that restricts bacterial dissemination during local infections (11). On the other hand, during systemic infections and the resultant sepsis, dysregulated immunothrombosis can lead to widespread coagulopathy and multiorgan failure due to microvascular blockages that impede blood flow (12). To help clear NET-induced thrombi from circulation, the NETs are degraded by host deoxyribonucleases (DNases), which is a critical regulatory mechanism of immunothrombosis (13). Therefore, administrating external DNase is considered a potential therapy for treating immunothrombosis, as treatment with DNase in vivo effectively prevented thrombus formation (14). However, long-term treatment with DNase dramatically reduced the survival of mice (15). Recognizing the broader roles of NETs in various biological processes, further investigation into the specific mechanisms of how NETs promote thrombosis is imperative.

Recent evidence over the years suggests that NETs facilitate immunothrombosis through multiple pathways (10). Notably, NETs can directly activate several coagulation factors (16–18), particularly factor XII, initiating the intrinsic thrombosis pathway. Additionally, platelets are attracted to and activated by NETs, which further promote the production of thrombin (3). Thrombin is the central enzyme of thrombosis and is responsible for converting fibrinogen to fibrin. Thrombin has been demonstrated to interact with NETs directly. One of the fundamental interactions between NETs and thrombin occurs when the thrombin mediates the proteolytic cleavage of histones and other proteins, leading to alterations in the proteomic composition of NETs (19). Also, NET-generated cell-free DNA (cfDNA) promotes thrombin autolysis and the release of thrombin-derived antibacterial C-terminal peptides (20). Notably, a positive feedback loop exists where NETs stimulate the production of thrombin, which subsequently triggers the release of more NETs by neutrophils (21). Despite these findings, the specific mechanism detailing the interactions between NETs and thrombin is not fully understood. Gaining insight into these interactions holds significant implications for advancing novel treatments for immunothrombosis and coagulation disorders.

The role of NETs in promoting immunothrombosis was considered largely contributed by the proteins of NETs, especially histones. Histones within NETs can activate platelets via TLR2 and TLR4 pathways, enhancing platelet aggregation, and stimulating vascular endothelial cells releasing von Willebrand factor (VWF) and tissue factor (TF), triggering the activation of extrinsic coagulation pathways (22, 23). Beyond histones, other proteins associated with NETs, such as myeloperoxidase (MPO), have also shown significant roles in this process (24). Despite these findings, the roles of proteins alone do not fully explain the mechanisms by which NETs serve as a scaffold for thrombosis, while the contribution of DNA, another major component of NETs, has been overlooked in research. It was reported that either histone proteins or DNA purified from NETs alone could promote blood coagulation in vivo (25). Furthermore, NET-derived DNA modulates the clot structures and stability (26, 27). However, these findings have been challenged by recent reports showing that some methods used to purify NET DNA, including Qiagen kits, shed microscopic silica particles that possess strong procoagulant activity, potentially confounding results (28–30). Given these controversies, a deeper understanding of how NET-derived DNA contributes to thrombosis is needed.

Toward this goal, we herein report the identification of a direct interaction between thrombin and NET-derived short tandem repeats of single-strand ATTCC [termed as ss(ATTCC)_n] using thrombin-mediated chromatin immunoprecipitation sequencing (ChIP-seq) and ssDNA-specific kethoxal-seq (KAS-seq) (31, 32). We verified and measured the binding affinity of ss(ATTCC)_n to thrombin using multiple biochemical and biophysical approaches. The secondary structure of ss(ATTCC)_n, i-motif, was proved crucial in binding. Notably, in the slightly acidic microenvironment, which is related to many diseases, including inflammation and cancer, both ss(ATTCC)_n and NET exhibited heightened thrombin binding affinity. To disrupt this NET–thrombin interactions, we have also developed strategies targeting ss(ATTCC)_n, including ssDNA nuclease cleavage, pH modulation, and antisense locked nucleic acids (LNAs). Collectively, we have identified a molecular mechanism on how NET functions as a coagulation scaffold, facilitated by ss(ATTCC)_n-mediated thrombin interactions, provided evidence that the ss(ATTCC)_n can be a potential therapeutic target for NET-mediated thrombosis.

Results and Conclusion

Thrombin Interacts with the DNA of NET Directly.

To investigate the interactions between thrombin and NET, we used neutrophils isolated from healthy donors and human promyelocytic leukemia cell line HL60. Neutrophils were incubated with a NETosis inducer, Phorbol 12-myristate 13-acetate (PMA), to generate NETs (33), followed by incubating the resulting NETs with biotin-tagged thrombin in the cell culture medium. To visualize the DNAs in NETs and biotinylated thrombin, we added Hoechst and a Cy5-conjugated streptavidin, respectively, and employed confocal microscopy to image them. As shown in Fig. 1A, the red Cy5 signals from the biotinylated thrombin that bound to streptavidin overlay well with the green Hoechst signals from the DNA in the long spread morphology of NET, indicating that the thrombin is colocalized with NET (The Pearson’s correlation coefficient is 0.802 ± 0.140). In contrast, repeating the same procedure without adding the biotinylated thrombin resulted in no red signal from Cy5 (Fig. 1 A and B), confirming that the red signal can be attributed to thrombin. When a general nuclease DNase I or a ssDNA nuclease Mung Bean Nuclease (MBN) were added to the above mixture, no colocalized signal in the NET region was observed anymore (Fig. 1 A and B). The same phenomenon can also be observed from the HL-60-based neutrophil model (SI Appendix, Fig. S1). As shown in Fig. 1 A and B and SI Appendix, Fig. S1, signals from neutrophil-derived NET and thrombin were codistributed and the addition of DNase I and MBN would cause the signal loss of thrombin along with NET. Both results from human neutrophils and HL-60 model showed a nuclease-sensitive interaction between thrombin and NET. This sensitivity to both nucleases (DNase I and MBN) suggests that the DNA scaffold in NETs is crucial for the interaction between thrombin and NET.

Fig. 1.

Thrombin binds NET-derived DNA directly. (A) Confocal images showing the colocalization between thrombin (biotinylated, stained with Cy5-streptavidin, red) and NET (stained with Hoechst, green) with the pretreatment of DNases (DNase1 and Mung Bean Nuclease). (Scale bar: 40 μm.) (B) Quantification of (A) by measuring the mean fluorescent intensity of thrombin within DNA regions in each frame. Statistical significance was determined by unpaired two-tailed Student’s t test with the group without thrombin and enzyme; n.s., no significance, ***P < 0.001. (C) EMSA of DNAzol isolated NET-derived DNA with different concentrations of α-thrombin and γ-thrombin ranging from 0 to 10 µM. (D) Gel blot showing the shift of thrombin (1 µM) as stained by Streptavidin-IRDye 800CW with NET DNA as visualized by SYBR Safe. All experiments were repeated independently three times with similar results.

Encouraged by the above finding of colocalization between thrombin and DNAs in NETs, we used an electrophoretic mobility shift assay (EMSA) to find out whether thrombin can interact with the NET-derived DNA directly (34). The DNAs of NET were isolated as described previously (33), and purified with DNAzol and ethanol precipitation followed by RNase and proteinase treatments. The NET-derived DNAs were then incubated with varying thrombin concentrations at pH 7.2 in Dulbecco’s Phosphate-Buffered Saline (DPBS) buffer containing 1 mM CaCl₂ and 0.5 mM MgCl₂. As shown in Fig. 1C and SI Appendix, Fig. S2A, the addition of α-thrombin at concentrations ranging from 1 to 10 µM resulted in a decrease in the intensity of the DNA bands in the low molecular weight region and an increase in the intensity of a high molecular weight DNA band near the top of each lane. However, the addition of γ-thrombin, which is the autolysis product of α-thrombin lacking cationic exosite I (35, 36), did not result in the observed shift of the DNA bands (Fig. 1C and SI Appendix, Fig. S2A). Also, we did confocal imaging to investigate the interactions between γ-thrombin and NET. As shown in SI Appendix, Fig. S2B, γ-thrombin does not distribute along with the NET fibrin like α-thrombin. These results suggest that the cationic exosites of thrombin may play a role in the DNA–thrombin interactions. To validate the interaction between NET DNAs and thrombin, we incubated NET DNAs with biotinylated thrombin and then performed a gel blot EMSA using streptavidin conjugated to IRDye 800CW dye to monitor the migration of the α-thrombin band. As shown in Fig. 1D, the addition of NET DNA caused the thrombin band in Lane 1 to change its mobility (Lane 3). Pretreatment of NET with DNase I and MBN resulted in an impaired shift of the thrombin band (Lane 5 and 7). DNase I digests both dsDNA and ssDNA thus resulting in empty lanes at Lane 4 and 5, and no thrombin gel mobility changes were observed in Lane 5. Interestingly, the ssDNA nuclease MBN (Lane 6 and 7) can also prevent the NET-induced thrombin mobility change. MBN is able to cut ssDNA loops inside DNA duplex, thus resulting in shorter dsDNA fragments after incubation, as shown by the gel blot using SYBR Safe. MBN-digested DNA did not show slower gel mobilities after thrombin incubation (Lane 7 lower panel) and did not induce thrombin mobility changes (Lane 7 upper panel). Based on this observation of MBN-sensitivity, we hypothesized that the ssDNA may play an important role in NET–thrombin interactions. Collectively, these results demonstrated that α-thrombin interacts with the DNA of NET directly.

Thrombin ChIP-seq Reveals the d(ATTCC/GGAAT)_n Motifs with High Thrombin Binding Affinity.

Having demonstrated that the NET-derived DNAs can bind α-thrombin, we wondered whether such a binding requires specific DNA sequences or motif(s) in NET. To find out an answer to this question, we incubated biotin-tagged α-thrombin with NET in the cell culture and then enriched those bound DNA fragments with streptavidin immobilized magnetic beads before sending the enriched DNAs for next-generation sequencing (NGS) (SI Appendix, Fig. S3). From this thrombin-mediated ChIP-seq, we identified 3571 thrombin-binding DNA peaks on chromosomes from four individual thrombin ChIP-seq replicates (SI Appendix, Fig. S4 A and B). A motif analysis by MEME (37) revealed the presence of tandem repeats of d(ATTCC)_n in those thrombin-enriched peaks (Fig. 2A). When we analyzed the frequency of all possible 5-mer motifs, we observed a prevalence of the d(ATTCC) motif and its reverse complementary counterpart d(GGAAT), both of which are signature motifs of satellite III DNA (38–42). This dominance was evident in the thrombin-enriched DNA fragments (Fig. 2A). Notably, most of the peaks were situated within annotated repetitive regions in the intergenic positions (Fig. 2B and SI Appendix, Fig S4C). To estimate the repeat numbers in each peak, we counted the occurrence of d(ATTCC) or d(GGAAT) motifs in the enriched fragments containing more than 5 d(ATTCC/GGAAT) motifs (Fig. 2C). The median repeat count fell within the range of 16 to 50 counts, revealing a consistent pattern. In comparison, d(ATTCC) or d(GGAAT) motifs were not enriched in nonbiotinylated thrombin-mediated ChIP-seq (SI Appendix, Fig. S4D). Thus, our findings point to the presence of tandem repeats of d(ATTCC/GGAAT)_n as a potential thrombin binding motif in NET.

Fig. 2.

NGS unveils thrombin binding preferences on NET-derived DNA. (A) A representation of the fraction of top 50 5-mer motifs in the thrombin-seq library, insert: The top 5 motifs enriched by thrombin as identified by MEME. (B) The distribution of genomic regions covered by the thrombin-seq library. (C) Distribution of repeat counts of d(ATTCC) or d(GGAAT) in sequencing peaks enriched with thrombin (>5). The peaks show four biological replicates with the exact counts (columns) and fitted curves.

Single-Stranded (ATTCC)n Binds Thrombin.

To further characterize and validate the interactions between the above identified d(ATTCC/GGAAT)_n motif and α-thrombin, we conducted multiple assays. Initially, an EMSA was performed by incubating either ss(ATTCC)₁₈ or ss(GGAAT)₁₈ with α-thrombin or γ-thrombin in the DPBS buffer. As depicted in Fig. 3A, similar to the results shown in Fig. 1 that illustrates interactions between NET DNA and thrombin, synthetic ss(ATTCC)₁₈ caused a shift in the mobility of α-thrombin but not γ-thrombin. In comparison, the complementary ss(GGAAT)₁₈ did not show gel shift with either α-thrombin or γ-thrombin. We also found that more than 12 repeats of ss(ATTCC)_n are required to observe the gel mobility shift in EMSA (SI Appendix, Fig. S5). To further validate and quantify the direct interaction between ss(ATTCC)_n and thrombin, we measured the binding using isothermal titration calorimetry (ITC). As shown in Fig. 3 B and C, ITC indicates that ss(ATTCC)₁₈ binds to α-thrombin with a dissociation constant (K_d) of 1.46 μM in DPBS buffer (pH 7.2), while the complementary strand, ss(GGAAT)₁₈, displayed a flat curve in ITC, suggesting no binding to thrombin. These results suggested that the ss(ATTCC)_n motif, but not the ss(GGAAT)_n motif, strongly binds to thrombin.

Fig. 3.

ss(ATTCC)_n binds thrombin in NET. (A) EMSA depicting the interaction of ss(ATTCC)₁₈ and ss(GGAAT)₁₈ with α- or γ-thrombin. (B) ITC results determining the binding affinities of ss(ATTCC)₁₈ with α-thrombin. (C) ITC results of ss(GGAAT)₁₈ with α-thrombin. (D) Confocal imaging of neutrophils with or without PMA induction, showing NETs (stained by Hoechst DNA stain) and ssDNAs (red, stained by azido-kethoxal and Cy5-streptavidin). (Scale bar: 20 µm.) (E) Quantification of kethoxal-intensities overlapped with DNA in (D). (F) Overlapping peaks in thrombin-enriched sequencing and KAS-seq. (G) The fraction of top 50 5-mer motifs in the overlapped peaks between thrombin-enriched sequencing and KAS-seq. The cell imaging experiments and in vitro assays were repeated three times independently with similar results.

To investigate the presence of the (ATTCC)_n motif in a single strand form within NET, we employed kethoxal-seq (31, 32) within NET. Kethoxal, a DNA binder targeting unpaired guanosine in ssDNA, was used to enrich single-strand fragments for subsequent analysis. Capitalizing on this kethoxal’s property, we introduced azide-conjugated kethoxal to the neutrophils that have been induced with NETosis. Subsequently, we stained the azido-kethoxal with a DBCO-conjugated Cy5 dye, while adding Hoechst to image the DNAs in NET by confocal microscopy. As shown in Fig. 3 D and E, in the absence of PMA, no NET was generated, and only weak kethoxal signals were detected on the cell membrane. In contrast, after PMA induction, the Cy5 signal from kethoxal was colocalized with the blue signal from DNA in NET (Fig. 3D). This colocalization suggests the widespread presence of ssDNAs in NET. To further investigate these ssDNA regions in NET, NETs were collected, and DNAs were fragmented and enriched. We enriched kethoxal-labeled DNA fragments using click chemistry-mediated biotinylation of kethoxal. Subsequent isolation involved magnetic beads with streptavidin on their surface. After NGS of these DNA fragments, we identified >30,000 sequencing peaks. Together, kethoxal-assisted imaging and sequencing revealed a prominent accumulation of ssDNA in NETs.

Interestingly, among the 3571 thrombin-enriched DNA peaks, 68% were also identified in kethoxal-enriched peaks, suggesting their existence in single-stranded conformation in NET (Fig. 3F). Focusing on the 5-mer motifs identified in thrombin-enriched DNA fragments, we observed that the d(GGAAT/ATTCC) motif was highly enriched in the overlapped peaks with kethoxal-seq (Fig. 3G). These results indicate that a proportion of d(GGAAT/ATTCC)_n motif is naturally single-stranded in NET and that the ss(ATTCC)_n in NET has an affinity for thrombin.

ss(ATTCC)_n Binds to Thrombin through Its I-Motif Structure.

It was reported that d(ATTCC)_n is able to form an i-motif structure under acidic to neutral physiological conditions (Fig. 4A adapted from PDB: 1A83) (39, 43, 44). In ss(ATTCC)_n, the i-motif forms where two parallel-stranded duplexes with intercalated C·C(+) base pairs align head-to-tail. This i-motif structure formed by ss(ATTCC)_n is stabilized by a reverse Watson–Crick A·T pair in the loop, base pair stacking, and the intercalated alignment of the strands (Fig. 4A). We explored whether this i-motif structure contributes to the binding between (ATTCC)_n and thrombin. Initially, since the formation and stabilization of the i-motif structures are known to be facilitated at low pH (45), we annealed ss(ATTCC)₁₈ in pH at either 4, 5, 6, 6.5, 7, and 8 using a universal buffer and monitored the secondary structure using circular dichroism (CD) spectroscopy. As shown in Fig. 4A, a positive peak at 287 nm and a negative peak at 254 nm in the CD spectra under pH = 4, 5, and 6 indicated the formation of an i-motif structure under acidic conditions, consistent with previous observations (46–48). When the pH increased to 6.5, 7, and 8, the CD spectrum of (ATTCC)₁₈ changed, with a positive peak near 275 nm and a negative peak near 250 nm, indicating a transition to a flexibly coiled single-strand conformation, distinct from the i-motif structure.

Fig. 4.

ss(ATTCC)_n binds thrombin in a pH- and sequence-dependent manner. (A) CD spectra of ss(ATTCC)₁₈ at different pH (4, 5, 6, 6.5, 7, 8), a pH-dependent shift was observed, the insert shows the i-motif structure formed by ss(ATTCC)n according to PDB: 1A83. (B) ITC measurement of binding affinity of ss(ATTCC)₁₈ with thrombin at physiological acidic pH (Left, pH 7.0) and neutral pH (Right, pH 7.5). (C) ITC measurement of binding affinity of ss(ATTCG)₁₈ with thrombin. (D) MS1 spectrum of 10 μM ss(ATTCC)₁₈ with 10 μM thrombin in native 100 mM NH₄OAc solution (pH 7.0). (E). MS1 spectrum of 10 μM ss(ATTCG)₁₈ with 10 μM thrombin in native 100 mM NH₄OAc solution. All tests were repeated three times independently with similar results.

To find out whether these pH-dependent conformational changes of ss(ATTCC)_n conformation affect its interaction with thrombin, we performed ITC at pH = 7.0 or 7.5 separately. As shown in Fig. 4B, the binding affinity of ss(ATTCC)₁₈ to thrombin at pH 7.0 is much stronger (K_d = 746 nM) than that at pH 7.5 (K_d = 55 µM) and stronger than the affinity at pH 7.2 (K_d = 1.46 μM) (Fig. 3B). Further decreasing of pH could further increase the binding affinity, K_d is 174 nM at pH 6.0 (SI Appendix, Fig. S6). In contrast, further increase of pH to 8.0 would fully abolish the interaction (SI Appendix, Fig. S6B). To confirm that the i-motif structure is responsible for the thrombin binding, we introduced a single-point mutation in ss(ATTCC)₁₈ to create ss(ATTCG)₁₈ disrupting the i-motif formation. CD spectra confirmed the lack of i-motif formation to all investigated pH levels (SI Appendix, Fig. S7A). The ITC did not detect any binding between ss(ATTCG)₁₈ with thrombin (Fig. 4C). To further validate the direct interactions between ss(ATTCC)₁₈ and thrombin and determine their binding ratio, we measured the binding complex molecular weight (MW) through native mass spectrometry (MS) (Fig. 4 D and E and SI Appendix, Fig. S7 B–E). Native MS is a well-established technology that allows the in-depth investigation of protein complexes and protein interactome with high sensitivity over a broad mass range (49). As shown in the native mass spectra in Fig. 4D and SI Appendix, Fig. S7D, in the incubation system containing ss(ATTCC)₁₈ and thrombin, we detected ss(ATTCC)₁₈ (MW: 26.940 kDa), thrombin (MW: 36.040 kDa), and 1:1 ss(ATTCC)₁₈:thrombin complex (MW: 63.100 kDa). These results demonstrated that ss(ATTCC)₁₈ binds directly to thrombin in a 1:1 ratio. In comparison, ss(ATTCG)₁₈, which lacks the capacity to form an i-motif structure, showed no DNA: thrombin complex peak in the native MS spectrum (Fig. 4E and SI Appendix, Fig. S7E). Collectively, these results demonstrated that ss(ATTCC)_n binds to thrombin in a pH- and sequence-dependent manner, likely through an i-motif structure.

To investigate how d(ATTCC)_n interacts with thrombin in its duplex form along with its complementary strand d(GGAAT)_n, which showed no binding to thrombin (Fig. 3 A and B), we annealed d(ATTCC)₁₆ and d(GGAAT)₁₆ with 10-nt flanking sequences at each side to form ds(ATTCC/GGAAT)₁₆ in the DPBS buffer (SI Appendix, Table S1) and incubated it with thrombin, which resulted in a slower mobility in the EMSA of ds(ATTCC/GGAAT)₁₆ (SI Appendix, Fig. S8A) demonstrating a direct interaction between ds(ATTCC/GGAAT)₁₆ and thrombin. To investigate whether environmental pH can also modulate the interaction between ds(ATTCC/GGAAT)n and thrombin, we measured the binding affinity through ITC at acidic and neutral conditions respectively with ITC. As shown in SI Appendix, Fig. S8 B–D, ds(ATTCC/GGAAT)₁₆ exhibited a higher binding affinity at more acidic pHs [K_{d (pH 6.0)}= 1.02 µM, K_{d (pH 7.0)} = 3.51 µM] than neutral [K_{d (pH 7.2)}= 5.98 µM]. These results suggest that the formation of the i-motif structure by ss(ATTCC)n within the duplex, as depicted in SI Appendix, Fig. S8E, likely contributes to the enhanced thrombin binding under acidic conditions.

ss(ATTCC)_n Is a Potential Therapeutic Target for NET-Mediated Thrombosis.

An acidic microenvironment is one of the hallmarks of many diseases including most cancers. Studies have shown that the acidic microenvironment created by the cancer cells can promote thrombosis by activating platelets (50). Since ss(ATTCC)₁₆ showed stronger binding affinity toward thrombin under the acidic condition (Fig. 4B) and ss(ATTCC)₁₆ are a dominant component in NET DNAs that bind thrombin, we wondered whether the DNAs in NET would also show a stronger binding toward thrombin under acidic condition. To answer this question, we modified the pH levels of the NET culture to acidic (pH 7.0), neutral (pH 7.5), and basic (pH 8.0) conditions and monitored their confocal fluorescent images using the same protocol as described in Fig. 1. As shown in Fig. 5 A and B, a significantly higher fluorescence signal was observed at pH 7.0 than those at pH 7.5 and 8.0, indicating that a physiological slightly acidic microenvironment can enhance the binding of thrombin to NET strongly.

Fig. 5.

ss(ATTCC)_n is a potential therapeutic target for NET-mediated thrombosis. (A) Confocal images of thrombin (red) and NET (stained by Hoechst, blue) at physiological acidic (pH 7.0), physiological (pH 7.5), and basic (pH 8.0) conditions. (Scale bar: 20 µm.) (B) Quantification of the mean fluorescence intensity of NET-associated thrombin in (A) [arbitrary units (AU)]. (C) Confocal images of thrombin (red) and NET (stained by Hoechst, blue) with antisense LNA pretreatment. (Scale bar: 10 µm.) (D) Quantification of mean fluorescence intensity (AU) associated with NET per frame. (E) A scheme of plasma recalcification assay with isolated NET and thrombin. (F) Plasma recalcification time quantification with isolated NET, poly T-pretreated NET, and antisense LNA pretreated NET. Data in (B, D, and F) are representative of at least three independent experiments: n = 10 frames (B and D), n = 4 individual measurements (F). Data are shown as mean ± SD. Statistical significance was determined by unpaired two-tailed Student’s t test. ***P < 0.001. (E) is drawn with Biorender.com.

The NET-induced thrombosis is a target for a number of therapies being developed, including the use of anticoagulants (51), platelet inhibitors (52), and coagulation pathway inhibitors (53). Recognizing the broader role of NET in various biological processes, it is essential to develop a more selective approach to block the interaction between NET and thrombin in NET-induced thrombosis disorders. Since this study has identified the ss(ATTCC)_n in NET as a predominant thrombin-binding motif, we hypothesize that it may represent a promising therapeutic target with a higher specificity than using DNase or other reported approaches. To test this hypothesis, we employed an antisense locked nucleic acid (LNA), ss(GGAAT)₄, and applied to NETs at pH 7.0, before adding thrombin. We then measured the NET-bound thrombin intensities through confocal imaging. As shown in Fig. 5 C and D, a dose-dependent inhibition of thrombin signals was observed with the application of the antisense LNA. In contrast, the addition of 10 μM LNA poly T (T₂₀) as a control, which cannot bind ss(ATTCC)_n in NETs, resulted in minimal effects. To further evaluate the impact of antisense LNAs toward ss(ATTCC)_n in NETs in preventing it from binding thrombin, we isolated NET after the above experiments and conducted a human plasma recalcification test. As shown in Fig. 5E, when mixed with human plasma, the NET-bound thrombin promoted plasma recalcification and clots formation. Conversely, pretreatment with the antisense LNA significantly delayed the clotting time after the addition of NET, while pretreatment with the negative control (LNA poly T) showed minor effects (Fig. 5F). Collectively, these results indicate that ss(ATTCC)_n in NET can serve as a potential target for immunothrombosis by inhibiting the interaction between ss(ATTCC)_n and thrombin in a NET-rich condition.

Discussion and Conclusion

This study reveals an unexplored role of the short tandem repeat of ss(ATTCC)_n DNA in NET as a scaffold to bind thrombin during immunothrombosis, particularly under acidic microenvironments. Our investigation began by demonstrating direct interactions between thrombin and NET-derived DNA in the physiological conditions, characterized by its sensitivity to DNase I and ssDNA nuclease MBN. Employing thrombin-mediated ChIP-seq and ssDNA sequencing KAS-seq strategies, we identified ss(ATTCC)_n as a crucial DNA motif with a high affinity for thrombin. Biochemical validations highlighted the significance of the i-motif structure within ss(ATTCC)_n for its binding with thrombin. The acidic microenvironment, often associated with infection (54), inflammation (54), and tumors (55), with pH values dropping of 0.1 to 0.2 is relatively common. This acidic pH changes would significantly enhance the interaction between ss(ATTCC)_n and thrombin. While fibrin, thrombin’s canonical partner, exhibits tighter binding at its high-affinity site (K_d = 204 nM), the ss(ATTCC)_n interaction (K_d(pH7.0) = 746 nM) lies between fibrin’s high- and low-affinity sites (K_d = 3.45 µM) (56). Notably, ATTCC motifs—abundant in satellite DNA III (~2% of the human genome)—enable NETs to act as a secondary thrombin reservoir, synergizing with fibrin to amplify coagulation during early clot formation at inflammatory sites. Furthermore, we demonstrated that antisense locked nucleic acids (LNAs) could disrupt this thrombin–NET interaction, presenting a more targeted approach for therapies of NET-involved thrombotic disorders.

For many years, DNA has been considered primarily as the structural backbone of NETs, immobilizing pathogens during infection and platelets during thrombosis by their physical sizes and electrical properties. However, the active roles of DNA within NETs have been overlooked, even if accumulating evidence has pointed out potential functions of NET-associated DNAs. For example, it was demonstrated that NET-associated DNA has strong bactericidal activities by disrupting bacterial membrane integrities (57). In cancer, the DNAs of NETs were found mediating cancer metastasis via direct interaction with cell surface CCDC25 receptor (58). Despite these observations, the DNA sequences responsible for the functions and their structure and mechanism in carrying out the functions are not understood. The identification of ss(ATTCC)_n as a thrombin-binding motif highlights a direct functional role of NET DNA in coagulation. Targeting ss(ATTCC)_n through approaches like ssDNA nuclease application, pH modulation, LNAs, or i-motif structure resolvers could disrupt NET–thrombin interactions and reduce thrombotic risks in diseases associated with excessive NET formation.

Over the past decades, oligonucleotides with strong thrombin-binding capacity, especially G-quadruplex-forming aptamers, have been extensively studied. Notable examples include thrombin-binding aptamers (TBA, 15-mer and 26-mer) and the HD22 aptamer (59, 60). TBAs and HD22 bind to thrombin through exosite I and II respectively (59, 60). The identification of ss(ATTCC)_n as a natural thrombin-affinity sequence broadens our understanding of DNA–thrombin interactions, revealing mechanisms that extend beyond G-quadruplex structures. Interestingly, while ss(ATTCC)_n forms an i-motif and exhibits strong thrombin-binding affinity, its G-rich complementary strand, ss(GGAAT)_n, showed no detectable thrombin binding (Fig. 3 A and C). This difference is attributed to the distinct secondary structures formed by these sequences. Rather than forming a G-quadruplex, ss(GGAAT)_n adopts a stable stem-loop hairpin structure, which does not interact with thrombin (61). Similar to TBAs, ss(ATTCC)_n binds to α-thrombin but exhibits no affinity for γ-thrombin. This observation suggests that ss(ATTCC)_n binding is dependent on exosite I, which is disrupted in γ-thrombin while exosite II remains intact.

Many studies have highlighted the abundance and transcriptional dynamics of ssDNA regions across the genome, as demonstrated by tools such as KAS-seq (31, 32, 62, 63) and Chromatin Exposed sequencing (64), yet ssDNAs in intergenic regions or extracellular contexts, such as in NETs, remain poorly understood. Emerging evidence has shown that G-quadruplexes in the genome can sequester heme via a DNAzyme-like structure, inducing antioxidation gene expression and protecting cells from heme toxicity (64, 65). Similarly, in NETs, G-quadruplex–heme interactions form DNAzyme-like structures with peroxidase activity, crucial for antibacterial defense (66). Our study extends this understanding by identifying ss(ATTCC)_n in NETs as a natural thrombin-affinity sequence, demonstrating a ssDNA–protein interaction under acidic conditions. These findings suggest that ssDNAs can adopt unique secondary structures and play diverse roles beyond conventional genetic functions, emphasizing the need to explore their broader biological significance.

In summary, we have identified a molecular mechanism in NET-mediated thrombosis through a pH-sensitive ssDNA–thrombin interaction. This finding not only underscores the unexplored potential of ssDNA regions in the genome but also opens a broad avenue for more precisely targeted therapeutic interventions of immunothrombosis-related diseases. The identification of ssDNA as functional units suggests that the ssDNA regions of genomic DNAs could be fertile ground for new therapeutic targets or biomarkers. We believe this research may stimulate others to investigate the active roles of DNA in NETs across various biological processes, such as immune modulation, infectious disease dynamics, cancer progression, and wound healing. Understanding the multifaceted roles of NET-associated DNA will uncover new pathogenic mechanisms and potential therapeutic opportunities, advancing both basic science and clinical applications.

Materials and Methods

Materials.

Sodium chloride, potassium chloride, magnesium chloride, calcium chloride, Tween-20, Ethanol, MOPS, DBCO-Cy5, DBCO-PEG4-Biotin, agarose were purchased from Sigma-Aldrich. 4% PFA solution, Hanks’ Balanced Salt Solution (HBSS, with Ca²⁺ and Mg²⁺), Phosphate Buffered Saline (PBS, 1×), DPBS (10×, with Ca²⁺ and Mg²⁺), native alpha thrombin (RP43100, Invitrogen), alpha thrombin biotin (RP43103, Invitrogen), gamma thrombin (RP43107, Invitrogen), Hoechst 33258, Streptavidin-Cy5, Iscove’s modified Dulbecco’s medium (Corning), FBS, GlutaMAX, MEM-NEAA, DMSO, Dynabeads MyOne Streptavidin C1, SYBR Safe, human plasma were purchased from ThermoFisher. Qiaquick DNA purification column was obtained from Qiagen. Phorbol 12-myristate 13-acetate (PMA) was purchased from Cayman Chemicals. Confocal imaging 35 mm glass bottom dishes were purchased from MatTek. N₃-Kethoxal was a gift from Chuan He at the Department of Chemistry of University of Chicago, Chicago, IL, initially and then purchased from APExBIO (Cat. A8793).

Intercept (PBS) blocking buffer and IRDye 800CW streptavidin were purchased from Li-Cor Biosciences. The 0.45-µm nitrocellulose (NC) membrane was purchased from Cytiva Life Sciences. All the oligonucleotide sequences were purchased from Integrated DNA Technologies and were purified by high-performance liquid chromatography or polyacrylamide gel electrophoresis and confirmed by mass spectrometry. All other reagents and solvents were obtained from the domestic suppliers and were used as received.

Oligonucleotides.

See SI Appendix, Table S1.

Isolation of Human Neutrophils.

Work with neutrophils was approved by the Institutional Review Board at the University of Texas at Austin (Austin, TX) as Protocol No. 2021-00170. All volunteers gave written informed consent.

Human neutrophils from healthy adult volunteer blood donors were isolated following a previously published protocol (67, 68). Whole human blood was freshly drawn into BD Vacutainer Venous Blood collection tubes with ACD solution (Cat. 364816), then mixed with an equal volume of a solution containing 3% dextran (Sigma-Aldrich, ACS Cas. 9004-54-2, Denmark) and 1.8% sodium chloride (Fisher Scientific, ACS Cas. 7647-14-6) and sit for 20 min to aggregate most red blood cells to the bottom of the tube. The supernatant was collected and centrifuged (Eppendorf 5810R, A-4-62 Rotor) for 10 min at 500 × g to separate the remaining blood cells from the plasma. After centrifuge, the supernatant mainly containing plasma, was discarded, and the remaining pellet containing blood cells was suspended in 10 mL Hanks Buffered Salt Solution (HBSS, Gibco Laboratories, Cat. 14175095, Frederick) without calcium or magnesium. This blood cell suspension was then slowly added to the top of 4 mL Ficoll-Paque density gradient (GE Healthcare 17-1440-02, Uppsala, Sweden) and centrifuged for 40 min at 400 × g. The pellet was collected and resuspended in 4 mL of deionized water for 30 s to lyse the residual red blood cells, then stabilized by adding 4 mL of filter-sterilized 1.8% NaCl solution. Following 5 min of centrifugation at 500 × g, a white pellet of neutrophils was resuspended in 800 µL HBSS with calcium and magnesium and 200 µL human serum. Each tube of blood drawn yielded 1 mL of neutrophil-only solution. In experiments where more than one tube of blood was drawn, the resulting neutrophil solutions were thoroughly mixed into one tube by pipette.

Cell Culture and NET Induction.

Isolated primary neutrophils are not culturable, so we used them for experiment immediately after isolation. The human promyelocytic leukemia cell line HL-60 (obtained from Cancer Center at Illinois Urbana-Champaign) was cultured in a growth medium consisting of Iscove’s modified Dulbecco’s medium (Corning) supplemented with 20% FBS, 1× GlutaMAX, 1× MEM NEAA, 100 U mL^–1 penicillin, and 100 U mL^–1 streptomycin. and was cultured at 37 °C in a humidified incubator with 5% CO₂. The cells were differentiated into neutrophil-like cells (dHL-60) with a 5-d treatment of 1.3% DMSO (Sigma) in growth medium, at the cell density around 1 × 10⁶ cells/mL and do not over 2 × 10⁶ cells/mL to ensure the differentiation efficiency.

NETosis was induced by PMA treatment. The dHL60 cells or primary neutrophils were pelleted by centrifuge at 400 rpm for 4 min and then washed twice with PBS (without Mg²⁺ and Ca²⁺). Then the cells were resuspended in serum-free RPMI 1640 medium supplemented with 0.1% Human Serum Albumin (HSA) at the density of 1 × 10⁶ cells/mL. Then the cells were seeded to 35 mm glass bottom imaging dishes, 2 × 10⁶ cells per dish for dHL60 or 0.5 × 10⁶ cells per dish for primary neutrophils. After 30 min incubation at 37 °C, check the cell attachment to the surface, then replace the media with NETosis induction media [serum-free RPMI 1640 supplemented with 500 nM PMA (for dHL60) or 100 nM PMA (for primary neutrophils), 0.1% HSA, 100 U mL^–1 penicillin, and 100 U mL^–1 streptomycin]. Incubate in NETosis induction media for 4 h in the incubator.

Confocal Imaging of NET and Thrombin.

After NETosis, the NETs were washed once with HBSS or DPBS once and then added 1 µM biotinylated alpha thrombin solution diluted in 1% BSA (PBS solution) and incubated for 1 h in the 37 °C incubator. Thereafter, the cells were washed three times with PBS to remove unbound thrombin gently. The cells were then fixed with 4% PFA at room temperature for 15 min. After fixation, the cells were washed with PBS three times and blocked with 3% BSA solution in PBS for 1 h at 37 °C. Without washing, remove the blocking buffer and incubate with streptavidin-Cy5 solution (1:500× dilution in PBS) for 30 min at room temperature. After washing with PBS 3 times, NET was stained by adding Hoechst solution (1:1,000× dilution in PBS) and incubated at room temperature for 15 min. Before imaging, wash three times with PBS and keep the cells in HBSS.

DNase I or Mung Bean Nuclease treatment was performed after NETosis. DNase I (thermofisher) was diluted in 1× DNase I buffer to final concentration of 4U/100 μL and applied to the cells. Mung Bean Nuclease (MBN, NEB) was diluted in 1× Mung Bean Nuclease buffer to a final concentration at 5U/100 μL and applied to the cells. Control groups were incubated in 1× DNase I buffer without enzyme addition. Both DNase I and MBN were treated for 1 h at 37 °C and then washed with PBS for three times and processed to thrombin staining steps as described above.

For pH adjustment of NET experiment in Fig. 5, we induced NETosis first. Then, the NETs were incubated in DPBS buffer at pH 7.0, 7.5, and 8.0 separately at room temperature for 15 min. Then, perform the thrombin imaging steps described above but dilute thrombin in DPBS buffers at different pHs.

For antisense experiment of NET, the antisense locked nucleic acids were stored in nuclease free water at 100 μM. Before experiments, the LNAs were diluted into DPBS (pH 7.0) at 1, 2, 5, or 10 μM, heated to 95 °C for 10 min and then transferred to ice immediately for 2 min. NETs were induced first and then incubated in pH 7.0 for 15 min. After that, antisense strands were added to the dishes, 100 μL per dish, and incubated for 1 h at 37 °C. Afterward, the cells were washed with DPBS three times and processed to thrombin imaging steps described above.

All microscopy images were acquired on a Nikon W1 spinning disk microscope or a Leica SP8 laser scanning microscope. To accomplish the imaging, a ×60 objective was applied, and the fluorophore was excited with a 640-nm laser and Cy5 filter (emission of 672 to 712 nm) for thrombin, with a 405-nm laser and DAPI filter (emission 415 to 510 nm) for Hoechst. The images were taken with monochromatic Andor EMCCD cameras and were processed using ImageJ (Fiji). For the mean-fluorescence quantification in Figs. 1A, 3D, and 5 A and C, regions of interest (ROIs) were defined from the Hoechst channel, and the average Cy5 fluorescence was measured within these ROIs for each frame. When calculating the colocalization Pearson’s value, the raw 8-bit confocal images were first background-subtracted (rolling-ball radius = 40 pixels), split into Hoechst (DNA) and Cy5 (thrombin) channels, and analyzed with the FIJI Coloc 2 plugin. More than 10 frames of each imaging group were processed for further statistical analysis, and more than three biological replicates were performed and validated, showing similar trends. And statistics were performed with GraphPad Prism 10.0 by using the unpaired two-tailed t test.

NET Isolation and DNA Purification.

The NET was isolated following the protocol described previously (30). In brief, the cells were cultured and differentiated as above. When inducing NETosis, pellet and wash dHL60 or primary neutrophils with PBS, and then resuspend the cells in serum-free RPMI 1640 media supplemented with 500 nM PMA (dHL60) or 100 nM PMA (neutrophils) and 0.1% HSA at the cell density 1 × 10^6 cells/mL. Transfer the cells to 100-mm cell culture dishes, 10 mL/dish, incubate for 4 h in the incubator. After the NET induction, remove the media gently, and do not disrupt the layer of NETs and cells which should be adhered at the surface of the dish. Wash the NET layer with PBS once gently. Use 5 mL of cold PBS without Ca and Mg per dish to wash the bottom by pipetting multiple times and collect all the lifted material from the bottom. Then, add another 3 mL of cold PBS and use a cell lifter to collect the remaining NETs on the dish surfaces. Collect these PBS solution together and transfer to 50 mL conical tubes. Centrifuge for 15 min at 300 rpm at 4 °C to remove cells and cell debris. Divide the NET-rich supernatant into 1.5 mL Eppendorf centrifuge tubes and spin for 30 min at 17,500 rpm at 4 °C. This will allow the web-like NET DNA pellet. Discard supernatant and resuspend all pellets obtained together in PBS. To remove the attached proteins of NET, proteinase K was added to the harvest NET at 2 U/μL in total 100 μL per dish and incubated at 37 °C for 1 h. Then the DNA was purified either with Qiaquick columns following the manufactural protocol or purified with the adding of 1 mL DNAzol followed by ethanol precipitation as the manufactural protocol. Elute the NETs in nuclease-free water after Qiagen columns or resuspend the pellet in 8 mM NaOH and then neutralize with 1 M HEPES after DNAzol isolation. The DNA samples were then transferred into −20 °C freezer for storage. NET DNA concentration was measured by Qubit dsDNA BR Kit.

EMSA of NET and Synthetic DNAs.

The interactions between thrombin and NET or synthetic DNAs were analyzed using agarose gel-based EMSAs (69). For the interaction between thrombin and NET, we first dilute the isolated NET (as described above) into 1× DPBS (with Ca²⁺ and Mg²⁺) to 50 ng/μL and incubate at 37 °C for 2 h. The NET-derived DNA was added 500 ng per tube. Then alpha thrombin or gamma thrombin were diluted from their storage stock to 1× DPBS first and then added into each tube to make the desired concentration. The final volume of each tube was 20 μL, DNA amount was 500 ng. Incubate DNA and thrombin in the thermomixer at 37 °C with shaking 1,200 rpm for 30 min before loading to the gel. A 1% agarose gel was prepared with the addition of SYBR Safe nucleic acid staining dye. 6× purple loading dye (no SDS, NEB) was added to each incubation and loaded to the agarose gel immediately. The gel was run in 1× MOPS native gel running buffer (pH 7.0), at the voltage 100 V for 1 h.

The EMSA experiment for validating the interaction between ss(ATTCC)_n, ss(GGAAT)_n, ds(ATTCC)₁₆ and other synthetic nucleic acids were performed with 2% agarose gel supplemented with SYBR Gold nucleic acid stain. For ssDNAs, the DNAs were heated to 90 °C and incubated for 5 min in the desired buffers (DPBS, or universal pH buffers). Then the DNAs were cooling down to room temperature for more than 2 h. Then the DNAs were diluted to 500 nM (GGAAT)_n or 1 μM (ATTCC)_n in 18 μL final volume. Alpha thrombin was diluted to 20 μM and then added 2 μL into each reaction to make the final concentration 2 μM. Incubate DNA and thrombin in the thermomixer at 37 °C for 30 min at 1,200 rpm shaking. 6× purple loading dye (no SDS, NEB) was added to each incubation and loaded to the agarose gel immediately. The gel was run in 1× Native MOPS gel running buffer (pH 7.0), at the voltage 85 V for 1.5 h.

Gels were imaged using a Bio-Rad Gel Imager at the exposure time 1 s. Gels were quantified with ImageLab (Bio-rad).

Gel Blotting of NET–Thrombin Interactions.

The gel shifting assay of alpha thrombin was performed using a biotinylated alpha thrombin (Invitrogen, RP43103). 500 ng NET-derived DNA was incubated with 2 μM biotinylated alpha thrombin in 20 μL DPBS at 37 °C, 1,200 rpm for 30 min. A 0.5% agarose gel was prepared in 1× MOPS gel running buffer. The samples were loaded with the supplement of purple loading dye. Gels were run at 100 V for 45 min at room temperature. Then the gels were stained in 0.5× TBE buffer supplemented 1× SYBR Safe for 30 min at room temperature with agitation 300 rpm. Then the gels were imaged by Bio-rad Gel Imager for the collection of SYBR Safe image. The gels were destained in 0.5× TBE for 30 min with shaking. In parallel, filter papers and nitrocellulose blotting membrane were also balanced with 0.5× TBE buffer for 30 min at room temperature. The DNA–thrombin samples were transferred to a nitrocellulose blotting membrane with Bio-rad semidry electrophorese at 20 V for 30 min at 4 °C. Afterward, the samples were cross-linked to the membrane by using UV cross-linker (Fisher Scientific) for 5 min. The blotting membrane was then blocked with Intercept (PBS) blocking buffer (Li-cor) at room temperature for 45 min and stained with IRDye 800CW streptavidin (10,000× diluted in the blocking buffer) at room temperature for 30 min. The membrane was washed with PBST buffer (PBS and 0.1% Tween-20) for 3 times, each time was 10 min, and then washed once with PBS for 10 min. The membrane was imaged with Bio-rad ChemiDoc, manual exposure for 60 s, with the filter set for IRDye 800CW. Then the results were analyzed with ImageLab software.

Thrombin-Mediated Pull Down and Sequencing.

The protocol for thrombin-seq was modified from a DNA ChIP-seq protocol (70). dHL60 cells were cultured and induced for NETosis in 10 cm dishes at the cell density of 1 × 10^6 cells/ml in serum-free RPMI 1640 medium with 500 nM PMA for 4 h. Then, the cell culture medium was replaced with serum-free RPMI 1640 medium supplemented with 1 μM biotinylated alpha thrombin (ThermoFisher, RP43103), control pull down was carried by using native alpha thrombin (ThermoFisher, RP43100). After another 1 h incubation, the supernatant was carefully removed and washed twice with PBS gently. The NET layer was fixed by cross-linking solution (1% vol/vol formaldehyde in PBS). After 10 min incubation at room temperature, the fixation was stopped by adding glycine to a final concentration of 0.12 M. Gently mix by rotating slowly for 10 min at room temperature. Wash the cells twice with cold PBS and add 10 mL of cold PBS. Lift the NETs with cell lifter and collect them into falcon tube and process the same treatment for NET isolation, which is centrifuge at 300 rpm for 15 min to remove cell bodies and then transfer to 1.5 mL tubes and centrifuge at 17,500 rpm for 30 min at 4 °C. Resuspend the DNA pellet in cold buffer TE and do DNA sonication. DNA was fragmented by using Novaris sonication system under low power mode (intensity at 3, 15 cycles, 30 s on and 60 s off) at 2 to 4 °C. Always keep the DNA on ice.

To enrich thrombin bound DNAs, streptavidin Dynabeads C1 was applied for pull-down experiments. First, save 500 ng DNA as sequencing inputs. Dilute 1 μg DNA into 100 μL 1× PBS. Prepare 50 μL Dynabeads by washing with 500 μL 1× PBS for 3 times and blocked with 1% BSA and 10 μg/mL yeast tRNA (Thermofisher AM7119) in PBS for 30 min at 37 °C in the thermomixer under rotation 1,200 rpm. After blocking, mix 100 μL DNA with 100 μL beads solution and incubate at 37 °C for 30 min with 1,200 rpm shaking. To wash the beads, cold washing buffer (1× PBS and 0.1% Tween-20) was prepared. The beads were washed with 400 μL washing buffer three times 37 °C for 10 min with 1,400 rpm shaking. Then the DNA was eluted from the beads by adding 95 μL buffer TE and 5 μL Proteinase K and incubated under 1,200 rpm shaking for 1 h at 37 °C, then for another 2 h at 65 °C. The DNA was purified with Qiaquick DNA purification columns and eluted in 20 μL nuclease free water. DNA concentration was measured via Qubit. 15 ng DNA from input and pull-down enriched samples were sent to Genomic Sequencing and Analysis Center at UT Austin for library preparation and sequencing.

KAS-seq for ssDNA Identification.

The KAS-seq protocol was optimized from the published KAS-seq methodology (28, 29). N₃-Kethoxal was gifted from Chuan He’s lab and then purchased from APExBIO Inc. Cells were cultured and induced for NETosis as described above. In a well of a six-well plate, after NETosis induction for 4 h, we replaced the cell culture media with serum-free RPMI 1640 supplemented with 5 mM N₃-Kethoxal and incubated for 10 min in the cell culture incubator at 37 °C. After 3 times of gentle washing with PBS, the NET was isolated as described above without proteinase K heat-inactivation to avoid kethoxal dissociation. The DNA pellet was eluted in 130 μL TE buffer and fractionated with Novaris sonication system, 15 cycles, intensity at 3, 30 s on/30 s off in a 4 °C water bath. After sonication, the DNA lengths were checked with agarose gel at 200 to 400 bp. 5 μg fractionated DNA were diluted into 100 μL labeling buffer (1× PBS, 0.5 mM DBCO-PEG4-Biotin, 30 mM Boric acid), and incubated for 2 h in the thermomixer at 37 °C with 1,200 rpm shaking. 5 μL RNase A/T1 was added into the reaction and incubated for another 30 min. Purify the DNA with Qiaquick DNA purification columns and eluted the DNA into 40 μL elution buffer. Dilute the DNA into 100 μL 1× PBS by adding water and 10× PBS. Save 5 μL as the sequencing input sample. Use the rest 95 μL DNA to enrich biotin-tagged ssDNAs.

ssDNA pull down was achieved by using Dynabeads Streptavidin C1 according to the manufacturer’s protocol. 20 μL beads were washed 3 times in PBS in a thermomixer at room temperature for 15 min each time. Then the beads were blocked with PBS supplemented with 1% BSA and 10 μg/mL yeast tRNA (Thermofisher AM7119) for 30 min at 37 °C with shaking. Then, the DNA was mixed with blocked Dynabeads in a final volume 200 μL and incubated for 30 min at room temperature with shaking. The beads were washed three times with 400 μL PBST (PBS supplemented with 0.1% Tween-20). The bound DNA was eluted by heating the beads to 95 °C for 10 min. Then, the DNA was quantified with the Qubit dsDNA HS kit and sent to Genomic Sequencing and Analysis Center at UT Austin for library preparation and sequencing.

Sequencing Data Analysis.

The qualification of the samples is checked by FastQC (v0.11.9) (71). The raw reads are aligned by BWA/MEM (0.7.17-r1188) (72) and the product was transformed into bam file and sorted with samtools (v1.6) (73). Peaks are called according to the KAS-seq protocols (31, 32). In details, duplications of reads are removed by picard (v2.27.4) (74) (http://broadinstitute.github.io/picard) and then the bam file was transformed into bed file with a python script SAMtoBED provided by KAS-seq pipeline. Then the bed file was sorted with bedSort (v377) (75). Peaks were then called using MACS2 (v2.2.7.1) (76) by comparing thrombin pulldown samples to input controls (parameters: -q 0.01 --nomodel). When calling the peaks, the 4 replicates of thrombin-seq pulldown samples were compared to the 4 thrombin-seq input samples respectively, while the KAS-seq pulldown sample was compared to the thrombin-seq input sample 1. To validate thrombin-specific binding, we compared biotinylated thrombin samples to nonbiotinylated thrombin controls to verify the enriched peak is specific in biotinylated thrombin ChIP-seq samples.

For the called peaks of the 4 replicates, the peaks aligned to chromosomes were retained. Overlap of peaks were identified by bedtools (v2.30.0) (77). Motif analysis was done with MEME (37). The annotation rmsk files for repeat sequences in the human genome were downloaded from UCSC (75) (https://hgdownload.soe.ucsc.edu/goldenPath/hg38/database/).

Circular Dichroism Spectroscopy.

CD experiments were carried out using a J-815 CD spectrometer (JASCO) with rectangular quartz cell (JASCO, 1103-0172), 1 mm light path at 37 °C. Each sample was scanned three times for spectrum average from 220 to 320 nm, with 0.5 nm step and 0.5 s time. Before the measurement, the DNA samples were heated to 95 °C for 5 min and cooled down to room temperature slowly for more than 4 h using Bio-rad thermocycler. For each CD measurement, baseline of buffer without DNA was recorded and subtracted for DNA-containing samples.

For ss(ATTCC)n I-motif folding measurement, ss(ATTCC)₁₈ was diluted from 1 mM stock to final concentration of 10 μM in 200 μL universal pH buffers at pH 4, 5, 6, 6.5, 7, and 8, separately. Universal pH buffers were prepared as described previously (78). In brief, a mixture consisting of 0.0286 M citric acid, 0.0286 M monopotassium phosphate, 0.0286 M boric acid, 0.0286 M veronal, and 0.0286 M hydrochloric acid was prepared and then titrated with 0.2 M sodium hydroxide to desired pHs.

ITC.

ITC experiment was performed to measure the binding affinities between DNA oligos with native human alpha thrombin. The DNA oligos were dissolved in the testing buffers and heated to 95 °C for 5 min and slowly cooled to RT for longer than 2 h for annealing: a) in Fig. 3B, ss(ATTCC)₁₈ and ss(GGAAT)₁₈ were diluted to 300 μM and thrombin was diluted to 3.4 μM in 1× DPBS (with Calcium and Magnesium, pH 7.2); b) in Fig. 4B, ss(ATTCC)₁₈ was diluted to 300 μM and thrombin was diluted to 5.2 μM in pH 7.5 universal pH buffer; c) in Fig. 4B, ss(ATTCC) was diluted to 100 μM and thrombin was diluted to 3.4 μM in pH 7.0 DPBS buffer; d) in Fig. 4C, ss(ATTCG)₁₈ was diluted to 100 μM and thrombin was diluted to 6.0 μM in pH 6.0 universal pH buffer; e) in SI Appendix, Fig. S6A, ss(ATTCC)₁₈ was diluted to 10 μM and thrombin was diluted to 6.0 μM in pH 6.0 universal pH buffer; f) in SI Appendix, Fig. S6B, ss(ATTCC)₁₈ was diluted to 300 μM and thrombin was diluted to 3.4 μM in pH 8.0 universal pH buffer. The ITC was performed with Malvern PEAQ-ITC. Thrombin was loaded to the reaction cell and DNAs were loaded to the injection syringe. To measure the ITC, for each measurement, the injection heat was recorded by injecting DNA into buffer without thrombin as blanks. Then, the DNA was added to thrombin-containing solutions following a 14-injection protocol at 25 °C. (0.4 μL for the first injection and 3.0 μL for the rest 13 injections) The data was processed by subtracting the injection heat and then fitting the curves with MicroCal PEAQ-ITC Analysis Software.

Plasma Recalcification Test.

Human plasma (heat inactivated and sterile-filtered) was purchased from Sigma-Aldrich (Cat. H3667) and aliquoted. When doing experiment, human plasma aliquots were equilibrated at RT for 1 h before testing. NETs were induced by PMA for over 4 h and then collected as described previously. In brief, the NETs were collected with cold PBS and centrifuged at 500 g for 5 min to remove cells and debris, and then centrifuged at 17,500 rpm for 30 min at 4 °C to pellet the NET. Resuspend the NET in PBS, 100 μL per 10⁷ cells. Then, add 5 μM LNAs to NET and incubate at 37 °C for 1 h. Removing excessive LNAs by pelleting NET again at 17,500 rpm for 30 min at 4 °C. Resuspend NET and incubate with 1 μM native thrombin at 37 °C for 30 min. Removing excessive thrombin by pelleting NET and washing with PBS once. Pellet NET and resuspend it in 200 μL per 10⁷ cells. Mixing 50 μL human plasma with 50 μL resuspended NET, the plasma solution was monitored for clotting by manually pipetting with RNase/DNase-free low retention filtered tips. Clotting times were recorded at the first sign of fibrin formation at the end of the tip. The test was repeated 4 times for each sample, and biological replicates were performed 3 times for different batches of NETs to get similar biological trends.

Native Mass Spectrometry.

The DNA, ss(ATTCC)₁₈ and ss(ATTCG)₁₈, was desalted by using Amicon Ultra-4 centrifugal filter units (Millipore, Cat. C7719) for 3 times with nuclease-free water. Also, native α-thrombin (Invitrogen, Cat. RP43100) was desalted with Amicon Ultra-4 centrifugal filter units 3 times with 100 mM NH₄OAc solution (pH 6.2). Then, ss(ATTCC)₁₈ or ss(ATTCG)₁₈ was incubated with α-thrombin at 1:1 molar ratio, 10 µM for both in 100 µL final volume. The complexation was performed by incubating DNA and thrombin in a thermomixer at 37 °C, 1,000 rpm for 30 min. Then, the solution was subjected to native MS analysis via nanoelectrospray ionization in positive ion mode. Mass spectra were acquired using a Q Exactive Plus Ultra High Mass Range (UHMR) Orbitrap mass spectrometer (Thermo Fisher Scientific). Electrospray voltage: 0.9 to 1.1 V, in-source trapping voltage: −50 V, resolution: 1 k, scanning mass range: m/z 1,000 to 8,000. The spectra were deconvoluted using Unidec.

Supplementary Material

Appendix 01 (PDF)

Data, Materials, and Software Availability

The thrombin-seq and KAS-seq data generated in this study are available in the NCBI GEO database under the accession GSE253483 (79).