TDP-43 Oligomerization and Phase Separation Properties Are Necessary for Autoregulation

Loss of TDP-43 protein homeostasis and dysfunction, in particular TDP-43 aggregation, are tied to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). TDP-43 is an RNA binding protein tightly controlling its own expression levels through a negative feedback loop, involving TDP-43 recruitment to the 3′ untranslated region of its own transcript. Aberrant TDP-43 expression caused by autoregulation defects are linked to TDP-43 pathology. Therefore, interactions between TDP-43 and its own transcript are crucial to prevent TDP-43 aggregation and loss of function. However, the mechanisms that mediate this interaction remain ill-defined. We find that a central RNA sequence in the 3′ UTR, which mediates TDP-43 autoregulation, increases the liquid properties of TDP-43 phase separation. Furthermore, binding to this RNA sequence induces TDP-43 condensation in human cell lysates, suggesting that this interaction promotes TDP-43 self-assembly into dynamic ribonucleoprotein granules. In agreement with these findings, our experiments show that TDP-43 oligomerization and phase separation, mediated by the amino and carboxy-terminal domains, respectively, are essential for TDP-43 autoregulation. According to our additional observations, CLIP34-associated phase separation and autoregulation may be efficiently controlled by phosphorylation of the N-terminal domain. Importantly, we find that specific ALS-associated TDP-43 mutations, mainly M337V, and a shortened TDP-43 isoform recently tied to motor neuron toxicity in ALS, disrupt the liquid properties of TDP-43-RNA condensates as well as autoregulatory function. In addition, we find that M337V decreases the cellular clearance of TDP-43 and other RNA binding proteins associated with ALS/FTD. These observations suggest that loss of liquid properties in M337V condensates strongly affects protein homeostasis. Together, this work provides evidence for the central role of TDP-43 oligomerization and liquid-liquid phase separation linked to RNA binding in autoregulation. These mechanisms may be impaired by TDP-43 disease variants and controlled by specific cellular signaling.

INTRODUCTION
Aggregation, cellular mislocalization and loss of nuclear TDP-43 (TAR DNA binding protein) are hallmarks of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) (Arai et al., 2006;Neumann et al., 2006) and limbic-predominant age-related TDP-43 encephalopathy (LATE) (Nelson et al., 2019). In addition, TDP-43 inclusions are associated with multisystem proteinopathy (MSP) (Weihl et al., 2009) and other neurodegenerative disorders, including Alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE) (McKee et al., 2010). TDP-43 is an RNA binding protein whose cellular levels are tightly controlled as its overexpression leads to increased cytoplasmic accumulation and aggregation. In addition, even moderate changes in TDP-43 protein expression disrupt the regulation of target genes (Arnold et al., 2013). Abnormal increase in TDP-43 levels results in neurotoxicity as observed in human neurons (Barmada et al., 2010) and in a wide range of animal models, including non-human primates (Tatom et al., 2009;Wils et al., 2010;Xu et al., 2010;Estes et al., 2011;Uchida et al., 2012;Diaper et al., 2013). So far, TDP-43 autoregulation through a negative feedback loop is the only known mechanism controlling TDP-43 expression levels. During this process, TDP-43 binds to its own mRNA 3 UTR and inhibits protein synthesis (Ayala et al., 2011;Polymenidou et al., 2011; Figure 1A). This autoregulatory mechanism, reviewed in Tziortzouda et al. (2021), is conserved among vertebrates and its disruption in mouse models results in widespread splicing changes, neurotoxicity (Xu et al., 2010;Arnold et al., 2013;Sugai et al., 2019) and increased cytoplasmic TDP-43 aggregation (D'Alton et al., 2015;Koyama et al., 2016). The existence of mutations that are causative of ALS in noncoding regions involved in autoregulation (Gitcho et al., 2009;Pesiridis et al., 2009) and the finding that one of these mutations shows increased TDP-43 transcript expression (Gitcho et al., 2009), strongly suggest that defects in self-regulation may result in disease. This is also supported by a knock-in mouse model in which the Q331K ALS mutation exhibits cognitive impairment and disrupts autoregulation (White et al., 2018). Furthermore, accumulation of misfolded TDP-43 aggregates potentially increases protein production in affected cells by triggering a feed-forward mechanism, in which TDP-43 is sequestered and is no longer able to self-regulate, as suggested by recent studies (Sugai et al., 2019). In agreement with this model, ALS-affected motor neurons and FTD neurons that lack nuclear TDP-43 show impaired Tardbp autoregulation (Koyama et al., 2016;Liu et al., 2019). Collectively, these findings indicate that Tardbp may be one of the most critical TDP-43 targets to prevent the loss of protein homeostasis and neurotoxicity. Therefore, improved understanding of the factors controlling TDP-43 autoregulation are necessary to test this model and provide new avenues to maintain TDP-43 proteostasis. However, despite the central importance of this process in TDP-43 function and its link to disease, the mechanisms involved in TDP-43 autoregulation are ill-defined, and the factors controlling autoregulation are even less well understood.
The cellular organization of RNA binding proteins, which in turn impacts protein function, involves condensation into ribonucleoprotein (RNP) granules. This process is mediated by liquid-liquid phase separation (LLPS) into often dynamic, liquidlike complexes (Brangwynne et al., 2009;Wippich et al., 2013;Feric et al., 2016). The high concentration of the components while retaining dynamic properties within the droplets is fundamental for RNP granule function and organization in cells [reviewed in Alberti et al. (2019)]. Formation of RNP granules is mediated by multivalent interactions, including RNA binding and self-assembly through different protein domains, such as low complexity regions and oligomerization domains (Li et al., 2012;Lin et al., 2015;Zhang et al., 2015;Garcia-Jove Navarro et al., 2019). The liquid properties of these assemblies and their multivalent properties enable rapid regulation in response to cellular stimuli [reviewed in Shin and Brangwynne (2017); Wang et al. (2021)]. RNA is a principal component of RNP granules and recent studies, including our own, suggest that RNA binding modulates the LLPS properties of TDP-43 through specific interactions Garcia-Jove Navarro et al., 2019;Grese et al., 2021). However, how LLPS affects RNA processing following recruitment to the transcripts, and whether this is a gene-dependent mechanism is currently not known. Importantly, numerous studies also suggest that defects in LLPS are associated with disease, such as in the case of TDP-43, FUS (Fused in sarcoma) and other RNA binding proteins linked to neurodegeneration (Lin et al., 2015;Molliex et al., 2015;Patel et al., 2015). Specifically, conversion of the condensates into fibrils or complexes with solid-like properties is thought to cause accumulation of protein aggregates associated with pathology. Therefore, further insight on the regulation of TDP-43 LLPS properties and their involvement in controlling the expression of TDP-43 targets will help elucidate important pathogenic factors.
We sought to define the molecular mechanisms in TDP-43 autoregulation and determine the effect disease-associated conditions have in this process. Our results strongly suggest that autoregulation is mediated by TDP-43 self-assembly and LLPS upon RNA binding. In addition, specific TDP-43 binding to RNA sequences that mediate autoregulation promotes liquid properties of TDP-43 condensates or liquid droplets. In addition, we find that TDP-43 posttranslational modifications and diseaseassociated variants may alter autoregulation by modulating TDP-43 condensation. Together, these findings highlight the potential of developing therapies based on controlling pathways linked to TDP-43 autoregulation as well as specific TDP-43-RNA binding interactions.
FIGURE 1 | Binding to the RNA region mediating TDP-43 autoregulation increases the liquid properties of TDP-43 condensates. (A) Tardbp pre-mRNA organization into introns (lines) and exons (boxes), highlighting coding regions (blue boxes). Splicing is denoted by dashed lines and the approximate positions of alternative splicing in the 3 UTR are shown (gray lines). TDP-43 binds to its cognate mRNA transcript in the 3 UTR TDP-43 binding region (TDPBR, gray box), including the 34-nt sequence CLIP34. (B) Lowest free energy secondary structure of CLIP34 predicted by RNAfold. The calculated frequency of this structure in the ensemble is 53%. (C) Condensates formed by purified TDP-43 (4 µM) as seen by brightfield microscopy without RNA (control), in the presence of CLIP34 RNA (4 µM), or the non-specific control RNA A(CA) 18 (4 µM) at 150 mM NaCl, pH 7.5. Representative images of 3 independent experiments from 2 protein preparations. Scale bars, 10 µm. (D) Fluorescence recovery after photobleaching (FRAP) of condensates (white arrow) formed by Oregon green labeled-TDP-43 (10% of total protein) mixed with CLIP34, A(CA) 18 , or in the absence of RNA in the same experimental conditions as (C). Dotted line and arrow define the region of interest. Scale bars, 5 µm. multiple-site mutations. The CR deletion missing a.a. 316-346 was generated from gBlock sequence. pcDNA5 HA-mEGFP-TDP constructs were created by subcloning TDP-43 cDNA into the mEGFP-C1 vector (Addgene) between XhoI and HindIII. HA-mEGFP-TDP-43 was subcloned into pcDNA5 TM /FRT/TO using EcoRV and NotI. Oligonucleotides and gBlock sequence are listed in the Supplementary Table 1.

Expression and Purification of Recombinant TDP-43
Recombinant TDP-43 expression and purification was carried out as previously described (Grese et al., 2021).

Liquid-Liquid Phase Separation, Turbidity Assays, and Fluorescence Recovery After Photobleaching
The protocols developed in our lab for these assays were recently described (Grese et al., 2021). Microscopy images were taken following equilibration of condensates onto glass coverslips, approximately 60 min after the starting point of the reaction. For turbidity assays, data points were taken as the absorbance at 600 nm λ at 25 min. Data points were then normalized using the equation Abs norm = (Abs − Abs blank )/(Abs max − Abs blank ), where Abs max is the condition being normalized to 1. The RNA oligonucleotides used in these experiments are listed in Supplementary Table 3. FRAP was performed as previously described (Grese et al., 2021).

Fluorescence Anisotropy
Purified TDP-43 WT and mutants previously purified were serially diluted in a 1:2 ratio in a final range of 0-2 µM protein into a 300 mM NaCl, 10 mM Tris (pH 8.0), 5% glycerol, 5% sucrose, 0.5 mM TCEP buffer solution. The protein dilution was mixed with CLIP34 (IDT) 3 labeled with FITC (fluorescein isothiocyanate) in a final concentration of 100 nM and added in triplicate in a 384-well black flat bottom plate (Corning) in a total reaction volume of 30 µL protected from light. The anisotropy measurements were performed in a Spectra Max i3 plate reader (Molecular Devices) with excitation and emission wavelengths of 480 and 520 nm, respectively. To assess the binding, the anisotropy data was fitted in a nonlinear fit in 4-parameter logistic model to calculate the apparent IC 50,app . The apparent IC 50 (IC 50,app ) is the protein concentration in which 50% of the maximal anisotropy change is observed. Data analysis were performed using GraphPad Prism 9.
Cell Culture and Stable Cell Line Production HEK293 Flp-In TM T-REX TM cells (Thermo Fisher) were maintained in DMEM (Dulbecco's Modified Eagle's Mediumhigh glucose, Sigma) with 10% FBS (fetal bovine serum) and incubated at 37 • C and 5% CO 2 . Stable cell lines were achieved through co-transfection of pcDNA5 TM /FRT/TO/HA or mEGFP constructs and pOG44 using Lipofectamine 3000 TM (Invitrogen). Cells were selected using 75 µg/mL hygromycin (Sigma).

Cell Collection, Lysis, and Induction of LLPS Using Cell Lysates
This protocol was modified from Freibaum et al. (2021) and described in Grese et al. (2021). RNA oligonucleotides for these assays (Supplementary Total fraction samples were taken after sonication and the samples were then centrifuged at 98,400 g for 30 min at 4 • C. The pellet was then rinsed with RIPA buffer and centrifuged again. The resulting pellet was resuspended in urea buffer (7 M urea, 2 M thiourea, 4% CHAPS, 30 mM Tris pH 8.5). Fractions were quantified by western blot as described above.

RNA Extraction and Quantitative RT-PCR
Trizol Reagent (Thermo Fisher) was used for RNA extraction and was carried out according to manufacturer instructions. M-MLV reverse Transcriptase (Thermo Fisher) was used for cDNA production according to the manufacturer instructions. Each primer mentioned in Supplementary

RESULTS
Specific TDP-43 Binding to an RNA Sequence Linked to Autoregulation Increases the Liquid Properties of TDP-43 Condensates TDP-43 binds to an extended region in the 3 UTR of its own transcript (Tardbp), spanning approximately 500 nucleotides, during autoregulation ( Figure 1A; Ayala et al., 2011;Polymenidou et al., 2011;Tollervey et al., 2011;Bhardwaj et al., 2013). This TDP-43 binding region (TDPBR) is immediately upstream of the proximal alternative polyadenylation site pA 1 and is included in an alternatively spliced intron (in7). The mechanisms proposed to follow TDP-43 recruitment to TDPBR are based on analyses of the endogenous Tardbp transcript and derived gene reporters. These studies support the engagement of different processes during autoregulation: alternative polyadenylation, alternative splicing producing isoforms targeted for degradation via nonsense mediated decay (NMD), and nuclear retention of specific transcripts. Detailed studies by Koyama et al. (2016) suggest that autoregulation results from a combination of these mechanisms, but the extent to which each of these pathways contributes to the control of TDP-43 expression remains unknown (Polymenidou et al., 2011;Bembich et al., 2014;Koyama et al., 2016). A 34-nt. region within TDPBR (CLIP34) is commonly found in crosslinking immunoprecipitation (CLIP) analyses of TDP-43-bound transcripts in human cells and mouse brain (Polymenidou et al., 2011;Tollervey et al., 2011;Figures 1A,B). This isolated sequence is capable of decreasing TDP-43 toxicity in neurons, suggesting that CLIP34 binding prevents TDP-43 aggregation and aberrant phase transitions (Mann et al., 2019). We recently reported that CLIP34 was among the GU-rich RNA sequences capable of modulating TDP-43 phase separation properties (Grese et al., 2021). In the present work, we sought to gain further insight of the mechanisms that mediate TDP-43 LLPS linked to CLIP34 and explore whether LLPS plays a role in TDP-43 autoregulatory function. For this, TDP-43 LLPS was analyzed using purified full-length TDP-43 and we observed a dramatic change in the behavior of TDP-43 condensates in the presence of CLIP34. At 150 mM NaCl in the absence of RNA, TDP-43 forms small condensates that fail to coalesce and cluster into chain-like structures ( Figure 1C). As previously shown, these rapidly obtain fibril-like properties that are more similar to gel or solid complexes instead of behaving as liquid droplets (French et al., 2019). Remarkably, addition of CLIP34 promoted TDP-43 condensate fusion and coalescence increasing droplet size. This was not observed in the presence of an RNA oligonucleotide control sequence of similar length, A(CA) 18 . We measured the size of the condensates in the different conditions to quantify the changes. The condensates mediated by CLIP34 are more than twofold significantly larger than control conditions (Supplementary Figure 1). Addition of A(CA) 18 showed no significant difference relative to control. These observations are in agreement with recently published data from our lab, showing that CLIP34 promotes TDP-43 condensation at higher NaCl concentration (250 mM). Our findings suggest that at physiological salt conditions (150 mM NaCl) TDP-43 binding to CLIP34 specifically increases the liquid and dynamic properties of TDP-43 condensates. Fluorescence recovery after photobleaching (FRAP) of the TDP-43-CLIP34 condensates showed rapid recovery of Oregon green-labeled TDP-43 indicating a dynamic exchange between the light and dense phases. We observed approximately 40% recovery in TDP-43 condensates formed with specific-binding RNA (CLIP34), while condensates without RNA or in the presence of non-binding RNA showed virtually no recovery (Figures 1D,E). This suggests that while a substantial immobile fraction is present in the TDP-43-CLIP34 sample, there is a difference between the dynamics of the specific vs. non-specific RNA conditions. The immobile fraction present in the CLIP34 condition could be explained by the tight binding between TDP-43 and CLIP34 RNA, as the recovery could be partially dependent on exchange of RNA-bound and free labeled TDP-43, and thereby the off-rate of the TDP-43-RNA interaction. TDP-43-CLIP34 binding affinity is in the nanomolar range suggesting that the off-rate may be slow and this could explain the slow fluorescence recovery. In addition, the amount of CLIP34 in our reaction may also affect the degree of recovery. High RNA concentrations in similar experiments causing FRAP values that do not recover to baseline levels have been previously observed . Our results are further supported by videos of condensates that show the dynamic properties of these complexes. Here, we show the marked effect of CLIP34, which increased condensate fusion and coalescence, generating larger complexes compared to control and A(CA) 18 (Supplementary Movies 1-3). Collectively, our findings indicate that TDP-43 phase separation may be modulated by binding to CLIP34 specifically, preventing fibrillization of TDP-43 condensates.
To test whether condensation of CLIP34-bound TDP-43 may be observed in a cellular environment, we adapted a recently developed protocol to observe biomolecular condensates in human cellular lysate (Freibaum et al., 2021). We prepared cellular extract from human embryonic kidney cells (HEK293) cells stably expressing a single copy of monomeric mEGFP-TDP-43 wild-type (WT) (Figure 2A). The lysate was mixed with purified TDP-43 after addition of RNA. At 250 mM NaCl, in the absence of RNA, the mixture appeared homogeneous and lacked visible foci ( Figure 2B). However, addition of CLIP34 readily promoted formation of mEGFP-TDP-43-positive granules. Control conditions in which no CLIP34 was added did not promote mEGFP-TDP-43 condensation. As a control, we tested the effect of A(CA) 18 RNA and observed a marked decrease in phase separation compared to CLIP34. The condensates observed with A(CA) 18 , which is not expected to bind TDP-43 specifically (Buratti and Baralle, 2001), may be due to interactions of cell lysate components with the oligonucleotide and TDP-43 through non-specific binding. Additionally, the higher concentration of TDP-43 and RNA that was required Sidak's multiple comparisons test was used to compare selected groups. *P ≤ 0.05 **P ≤ 0.01, *** P ≤ 0.001, ****P ≤ 0.0001, N.S., no significance. The last column corresponds to blank, buffer only sample.
to generate condensate formation under these conditions could promote liquid-liquid phase separation through less specific interactions. We also found that, at lower salt concentrations (150 mM NaCl), purified TDP-43 and cell lysate resulted in the formation of the small condensates clustering together into fibrillike structures (Supplementary Figure 2). However, addition of CLIP34 generated larger round-shaped condensates, suggesting increased liquid properties consistent with our experiments using purified TDP-43 alone. This was not observed upon addition of A(CA) 18 RNA (Supplementary Figure 2B). To further test the requirement of specific TDP-43 binding to CLIP34, we analyzed RNP granule formation of cellular lysate from HEK293 cells expressing an RNA binding-deficient mutant mEGFP-TDP-43 F4L (Phe147/149/229/231Leu) (Buratti and Baralle, 2001). Addition of CLIP34 to the F4L cellular lysate showed a decrease in condensate formation relative to WT ( Figure 2B). We also observed a dramatic decrease in the in the number and size of granules formed in F4L cell lysates mixed with A(CA) 18 , relative to WT. To further compare and quantify TDP-43 condensation in the various conditions, we measured lysate turbidity, as this often correlates with phase separation (Babinchak and Surewicz, 2020;Grese et al., 2021). Addition of CLIP34 increased the turbidity more than threefold compared to lysate or buffer only controls ( Figure 2C). Lysate turbidity upon mixing with CLIP34 was also significantly higher than A(CA) 18mixed lysate, consistent with our imaging data. Addition of CLIP34 to F4L cellular lysate showed 50% reduction in turbidity compared to WT. As the imaging studies showed, addition of A(CA) 18 to F4L lysate did not significantly increase turbidity compared to control. This data suggests that in the context of cellular lysate, the remaining TDP-43-RNA contacts of F4L are sufficient for condensate formation, albeit with lower efficiency relative to WT. Collectively, these results indicate that CLIP34 binding specifically increases the liquid properties of TDP-43 condensates and promotes phase separation of TDP-43 in celllike conditions.

TDP-43 Autoregulation Is Mediated by Oligomerization and Phase Separation
Based on our results showing modulation of TDP-43 phase separation by CLIP34, we next asked whether LLPS plays a role during TDP-43 autoregulation in human cells. For this, we introduced site directed mutations in different TDP-43 domains that disrupt self-assembly and phase separation ( Figure 3A). We targeted the N-terminal domain (NTD) with specific substitutions that inhibit oligomerization. Residue E17 of each NTD monomer makes multiple contacts upon dimerization, whereby the N-terminal domains are arranged in head-to-tail configuration (Afroz et al., 2017;Wang et al., 2018). Consequently, the E17R mutation greatly impairs NTD oligomerization. We also evaluated the role of S48 in the NTD, which undergoes phosphorylation in human cells (Rigbolt et al., 2011;Hornbeck et al., 2015;Wang et al., 2018). The phosphomimetic substitution S48E disrupts oligomerization and LLPS of full-length TDP-43 (Wang et al., 2018), suggesting that S48 phosphorylation modulates TDP-43 self-assembly. In agreement with these previous results, we observed fewer S48E condensates in the presence or absence of CLIP34 compared to WT or to the phospho-null substitution S48A (Figure 3A). At the same time, S48A showed moderately decreased condensation compared to WT under control and CLIP34 conditions. We found that in stark contrast with WT TDP-43, E17R failed to phase separate and addition of CLIP34 was unable to promote condensation of this mutant ( Figure 3B). As further validation of the role of LLPS in CLIP34-mediated condensates, we deleted an evolutionarily conserved region in the C-terminal domain (a.a. 316-343) ( CR) that forms a partially α-helical structure, which is important for self-assembly and phase separation (Conicella et al., 2016(Conicella et al., , 2020Schmidt and Rohatgi, 2016). As seen with the NTD oligomerization mutants, CR inhibited LLPS in the presence or absence of RNA ( Figure 3B). To better compare the differences in LLPS among the variants, we quantified phase separation in the presence of CLIP34 by turbidity ( Figure 3C). Compared to WT, disruption of NTDmediated oligomerization by E17R and S48E showed greater than 80 and 70% significant reduction in turbidity, respectively. Consistent with the microscopy data, S48A reduced turbidity compared to WT, but not as much as S48E. The CR mutant showed greater than 80% significant reduction in turbidity. We examined whether the defects in CLIP34-driven LLPS were caused by decreased mutant binding to the RNA, quantifying the TDP-43-CLIP34 interactions by fluorescence anisotropy. We recently estimated that more than one TDP-43 molecule may associate with the CLIP34 sequence (Grese et al., 2021). However, further studies are necessary to determine the actual number of TDP-43 molecules binding CLIP34. Due to this limitation, we analyzed the apparent IC 50 (IC 50,app ) for the interaction between WT and mutant TDP-43 and CLIP34, as an estimate of the binding affinity. IC 50,app is the protein concentration in which 50% of the maximal anisotropy change is observed. Our results indicate that NTD mutations and CR do not significantly affect CLIP34 binding (Table 1 and Supplementary Figure 3). As expected, we could not determine the binding of F4L for CLIP34 as these mutations greatly disrupt sequence-specific contacts (Buratti and Baralle, 2001;Lukavsky et al., 2013). Based on our results, we propose that the mutants bind CLIP34 as WT TDP-43 but fail to form condensates due to impaired self-assembly.
To test the role of TDP-43 oligomerization and LLPS on autoregulation, we compared autoregulatory function in human cells expressing each of the LLPS-defective mutants. Stable HEK293 cells were generated expressing a single copy of the tagged TDP-43 transgene upon tetracycline induction, as previously described (Ayala et al., 2011). To determine autoregulatory activity of the mutants we measured protein and mRNA levels of endogenous TDP-43 in these cells at 72 h post transgene induction, which typically results in 70% reduction of endogenous TDP-43 levels in the case of WT (Figures 3D-H). In Figures 3F,H we report autoregulatory activity of the different mutants compared to WT at the protein and RNA levels Values were obtained from binding experiments in Supplementary Figure 3. *Estimated loss (> 1) or gain (< 1) in binding affinity relative to WT.
calculated from the values of endogenous TDP-43 measured in Figures 3E,G. The CR deletion showed a 50% decrease in autoregulatory activity at the protein and transcript level ( Figures 3F,H), suggesting that LLPS is required for this function.
We found a dramatic disruption of autoregulation in E17R cells at the protein and mRNA levels, resulting in >90% loss in activity compared to WT (Figures 3F,H). Similarly, S48E showed reduced autoregulatory function of approximately 50 and 70% compared to WT at protein and RNA levels, respectively. S48A function was not significantly different from WT, indicating that introduction of the negative charge at this site specifically disrupts autoregulation. In addition, these results suggest that the decrease in phase separation observed with S48A (Figures 3B,C) is not sufficient to significantly disrupt autoregulation in the cellular assay. Instead, our findings suggest that TDP-43 phosphorylation at Ser48 may be able to modulate autoregulatory activity and control TDP-43 levels in cells. These results indicate a crucial role of NTD-directed self-assembly in autoregulation, which is particularly highlighted by the degree of functional loss in E17R. This mutation was even more disruptive than the RNA-binding deficient mutant F4L (Ayala et al., 2011), here used as control (Figures 3E-H). Based on these observations, we propose that TDP-43 autoregulation requires TDP-43 selfassembly/oligomerization and condensate formation mediated by both N-and C-terminal domains. It is possible that these domains may also mediate heterotypic protein interactions that are important during autoregulation and this should be further investigated.

TDP-43 Disease-Associated Variants Show Defects in CLIP34 LLPS and Autoregulatory Function
We and others have shown that specific ALS-associated TDP-43 mutations alter the dynamic properties of TDP-43 condensates (Grese et al., 2021). Here, we investigated whether these TDP-43 mutations or variants linked to disease alter CLIP34-driven LLPS and consequently diminish autoregulatory function. We selected mutations positioned in the conserved region of the CTD (Figure 4A; Conicella et al., 2020). Phase separation of purified TDP-43 mutants A321G, Q331K and M337V was analyzed upon mixing with CLIP34 and compared to A(CA) 18 or no RNA control ( Figure 4B). We found that as in the case of WT TDP-43, CLIP34 promoted Q331K condensate liquidity, shown by increased fusion and coalescence into larger droplets. In contrast, A321G and M337V remained in clusters or chainlike structures in the presence of CLIP34, suggesting that these mutations retain their gel/solid properties and do not acquire liquid properties upon binding to this RNA molecule. Addition of A(CA) 18 RNA did not significantly change the LLPS behavior of the mutants compared to control, as seen with WT TDP-43. Previous studies of the isolated CTD showed that these mutations disrupt LLPS through alterations in α-helix structure and helix-helix interactions (Conicella et al., 2016). Q331K and M337V similarly disrupt helix-helix contacts, while A321G shows helix-breaking behavior. However, we find that in the context of the full-length protein and RNA-driven condensation Q331K is distinct from M337V and A321G. The differences in the behavior of the mutants between these studies and the previous report (Conicella et al., 2016) may due to the use of the isolated CTD in previous work compared to the full-length protein in our studies, which specifically analyzed RNA binding-driven LLPS. The specific properties acquired by M337V and A321G, but not Q331K, should be further investigated as these may highlight important disease mechanisms. Next, we sought to determine whether a disease-associated short isoform of , recently characterized by the Barmada group (Weskamp et al., 2020), alters protein condensation associated to autoregulation. Alternative splicing of Tardbp produces sTDP-43, which lacks the CTD and is replaced by a unique 18 amino acid long sequence ( Figure 4A; Wang et al., 2004;D'Alton et al., 2015;Weskamp et al., 2020). This variant is toxic upon overexpression in neurons and is more highly expressed in ALS neurons and glia (Weskamp et al., 2020). We analyzed LLPS properties of sTDP-43 in the presence of CLIP34 and anticipated that loss of the entire CTD would strongly impair LLPS of sTDP-43, as in the case of C (a.a.1-269) which lacks the entire CTD ( Figure 4A) and prevented LLPS regardless of RNA presence, under the conditions tested ( Figure 4B).
In contrast, we found that the sTDP-43 variant spontaneously formed fibril-like structures ( Figure 4B). Addition of CLIP34 did not promote liquid behavior, but increased abundance of the fibril complexes. The presence of A(CA) 18 RNA did not significantly alter properties compared to control. The stark difference between sTDP-43, WT and C suggests that the short peptide at the C terminus dramatically alters the conformation of the rest of the protein by conferring aggregation-prone properties. Alternatively, the short tail, unique to sTDP-43, may drive intermolecular interactions that promote fibrilization. We then investigated whether changes in condensate behavior seen with the ALS mutations affect autoregulation. We created stable HEK293 cell lines expressing a single copy of each mutant transgene upon tetracycline induction as for Figures 3D-H. To compare autoregulatory function between WT and mutants we quantified endogenous TDP-43 protein and mRNA levels in uninduced cells and after 72 h of induction (Figures 5A-F). We observed no significant differences in autoregulation in A321G and Q331K expressing cells relative to WT at protein and transcript levels (Figures 5B-F), suggesting that the mutants were similarly capable of autoregulation as WT TDP-43. Our results regarding the Q331K mutation are in contrast with observations using a knock-in mouse model expressing this mutant which results in altered Tardbp mRNA processing and increased TDP-43 protein and transcript levels (White et al., 2018). However, our observations are supported by similar behavior of Q331K dynamics in cells and autoregulatory activity compared to wild-type seen by others (Hallegger et al., 2021). The observed discrepancies between our cell-based model and the animal model may be caused by species or cell type-specific factors that influence TDP-43 condensation and/or autoregulation. As previously reported by Weskamp et al. (2020), we observed strong defects in sTDP-43 autoregulation using our stable cell line upon quantifying protein and mRNA levels of endogenous TDP-43 (Figures 5B-F). These results are consistent with the important role of the CTD in this function (Ayala et al., 2011).
Because of the dramatic decrease in autoregulation associated with sTDP-43, we measured its binding affinity for CLIP34 RNA, comparing it to WT and C (Table 1 and Supplementary  Figure 3). While C did not significantly change binding relative to WT, sTDP-43 caused a significant twofold increase in IC 50 , suggesting a moderate decrease in binding affinity of sTDP-43. The spontaneous fibrilization of sTDP-43 may account for this reduction in binding and should be further investigated. Nevertheless, based on previous studies, we predict that a decrease of binding affinity in this range is unlikely to alter cellular RNA processing function (Lukavsky et al., 2013). We also found that sTDP-43 was consistently expressed at lower protein levels compared to WT and the other mutants in the stable cell lines (Figure 5B). This may be caused by increased clearance of this isoform because of its propensity to aggregate/misfold, as seen in our assays ( Figure 4B). Importantly, the decreased sTDP-43 protein levels may partly account for the reduction in its autoregulatory activity. Therefore, we propose that the extreme defects in autoregulation in the case of sTDP-43 arise from impaired LLPS, decreased protein expression, and impaired protein-protein interactions in the absence of the CTD. The behavior observed for sTDP-43 may partly explain the association of this isoform with neurotoxicity and TDP-43 pathology in neurons and in patients (Weskamp et al., 2020).
We found that M337V did not affect autoregulatory function when analyzing mRNA transcript levels (Figures 5E,F). These findings suggest that although M337V decreased the liquid properties of the condensates, these defects are not sufficient to significantly alter RNA processing in the case of autoregulatory function. Intriguingly, we found a 40% reduction in autoregulatory function when quantifying endogenous TDP-43 protein levels in M337V cells (Figures 5B-D). This difference derives from significantly greater accumulation of endogenous TDP-43 protein in M337V expressing cells, relative to WT ( Figure 5C). To investigate the mechanism associated with this phenotype, we asked whether M337V increases protein aggregation in cells, as we previously observed using the purified protein (French et al., 2019). The M337V protein was found to be less soluble than the WT counterpart upon cell lysate fractionation into soluble and insoluble fractions (Supplementary Figures 4A-C). These results are in agreement with increased levels of soluble and insoluble TDP-43 in human induced pluripotent stem cells (iPSCs)-derived neurons expressing M337V (Bilican et al., 2012). Next, investigated whether M337V prevents the normal turnover and clearance of endogenous TDP-43 ( Figure 6A). M337V-expressing cells were treated with cycloheximide (CHX), a translation inhibitor, and we measured the levels of induced, exogenous M337V and endogenous TDP-43 protein at different time points posttreatment. Cells expressing WT TDP-43 were similarly treated as control. Quantification of the protein levels for up to 40 h post-CHX treatment showed a stark increase in the half-life of induced M337V protein relative to induced WT protein ( Figure 6B). Furthermore, the half-life of endogenous TDP-43 in M337Vexpressing cells was also drastically increased relative to that measured in WT-expressing cells (Figure 6B). These results strongly suggest that M337V protein homeostasis is impaired and that these defects lead to aberrant accumulation of M337V that affects non-mutated TDP-43 in cells as well. We explored whether these defects may be reflected as differences in TDP-43 cellular localization. However, we did not observe significant changes in the nuclear-cytoplasmic localization of M337V compared to WT, or in the diffuse vs. focal organization of the transgene and endogenous proteins in the nucleus, based on immunofluorescence (Supplementary Figure 4D). Interestingly, we found that the levels of two other RNA binding proteins associated with ALS, FUS and matrin-3, also showed abnormal accumulation post-CHX treatment in M337V, compared to WT-expressing cells (Figure 6B). The stark differences in the proteostasis of M337V may be caused by defects in the loss of liquid properties unique to this mutation as seen by our in vitro condensation assays. These intriguing findings also suggest that the defects caused by M337V alter general pathways of cellular proteostasis, affecting aggregation-prone proteins that are relevant to disease.

DISCUSSION
The autoregulatory activity of TDP-43 is central to its function in RNA processing as even moderate changes in TDP-43 levels may significantly alter gene expression. The importance of autoregulation for TDP-43 metabolism is further highlighted by two lines of evidence. First, in vivo models of TDP-43 pathology and patient-derived tissue show aberrantly increased levels of TDP-43 expression (Gitcho et al., 2009;White et al., 2018;Liu et al., 2019). Second, defects in autoregulation cause TDP-43associated neurotoxicity (Tatom et al., 2009;Barmada et al., 2010;Wils et al., 2010;Xu et al., 2010;Estes et al., 2011;Uchida et al., 2012;Diaper et al., 2013;White et al., 2018). These observations strongly indicate that impaired autoregulation may result in elevated protein levels, increasing the aggregation propensity of TDP-43. Here, we show that this essential TDP-43 function is mediated by TDP-43 condensation into ribonucleoprotein complexes through a mechanism implicating specific RNA binding and protein domain interactions. We show that TDP-43 binding to CLIP34 RNA specifically, whose sequence forms part of the TDP-43 binding region mediating autoregulation, increases the liquid properties of TDP-43 condensates. Importantly, we find that TDP-43 ALS-associated mutations and the short variant isoform sTDP-43 affect different interactions involved in this process. In particular, our studies provide insight into possible pathogenic mechanisms associated with the M337V mutant and the short TDP-43 isoform associated with neurotoxicity in ALS. These findings provide mechanistic insight of an important process regulating TDP-43 homeostasis and may help in the design of new therapeutic strategies to control TDP-43 function and solubility.
Based on our results, TDP-43 autoregulation requires TDP-43-self-assembly and condensate formation. We find that disruption of TDP-43 LLPS activity through targeted mutations strongly impairs autoregulatory activity (Figure 3). These results are supported by studies from the Ule lab published while this manuscript was in preparation (Hallegger et al., 2021).  Hallegger et al. (2021) showed that condensation activity is correlated with autoregulatory function by disrupting the conserved α-helical region in the LCD. Here, we show that in addition to interactions mediated by the LCD, self-assembly through the N-terminal domain of TDP-43 is essential for autoregulation (Figure 3). This mechanism of oligomerization is necessary for TDP-43-mediated splicing regulation of numerous targets and regulation of R-loop metabolism, according to our previous data and others (Afroz et al., 2017;Wang et al., 2018;Wood et al., 2020), suggesting that these processes and autoregulation share common mechanisms. Our results showing that autoregulation-linked condensation requires RNA binding as well as NTD and interactions is consistent with the pivotal role of multivalent interactions in mediating condensate networks. We also note that, at this time, we may not rule out that the N and C-terminal regions are required for oligomerization or interactions with protein partners, in the absence of phase separation. While this possibility needs to be investigated, we provide strong evidence for an important role of TDP-43 condensation during autoregulation. We showed that CLIP34 specifically and potently induces liquid-liquid phase separation of purified TDP-43 as well as in the presence of cellular lysate and promotes liquid properties of TDP-43 droplets.
In addition, our work shows inhibition of autoregulation following the introduction of mutations that inhibit LLPS. Interestingly, our findings suggest that TDP-43 autoregulation may be controlled by phosphorylation at residue S48 in the N-terminal domain, which strongly inhibits self-assembly and phase separation (Figure 3; Wang et al., 2018). The cellular pathway controlling S48 phosphorylation is unknown, yet our data suggests that it may be a powerful modulator of TDP-43 function and proteostasis.
To explore possible links between the condensationautoregulation process and TDP-43-associated disease, we investigated the function of TDP-43 mutations causative of ALS. Among the disease mutations within the CTD conserved region, we found that A321G and M337V were able to form condensates on their own, similar to WT. However, CLIP34 RNA did not confer liquid properties to the condensates formed by these mutants, in contrast to WT and the other mutations tested (Figure 4). These defects were consistent with our recent observations that GU-repeat RNA binding is not capable of increasing the liquid properties to A321G and M337V condensates, in contrast to its effect on WT TDP-43 (Grese et al., 2021). The altered behavior of A321G and M337V suggests less dynamic assemblies compared to WT, which may result in accelerated conversion into fibrils or aggregates. This model is consistent with our previous findings that M337V accelerates aggregate formation and increases aggregate seeding capacity in cells (French et al., 2019). In addition, aberrant M337V condensate behavior is supported by defects in stress granule function observed in a previous M337V mouse model (Gordon et al., 2019). However, despite the observed loss in liquid properties, A321G and M337V mutants did not significantly decrease autoregulatory function at the transcript level, compared to WT (Figure 5). This is in contrast with mutations that greatly decreased or even blocked LLPS entirely, such as CR and NTD mutations (Figure 3). We propose that the ability of A321G and M337V to form condensates, albeit of decreased liquidity, is sufficient for autoregulation in cells where additional protein interactions (e.g., chaperones) may counteract defects in A321G and M337V complexes. It is also possible that additional regulatory factors in cells, such as 3 UTR RNA sequences flanking CLIP34 in the entire TDPBR are able to rescue the defects observed with the purified A321G and M337V proteins.
Our present studies led to intriguing observations of diseaseassociated factors disrupting normal TDP-43 homeostasis. We found significantly increased accumulation of endogenous TDP-43 protein in M337V expressing cells, compared to wild-type (Figures 5B-D). These results are consistent with previous reports of neurons derived from M337V carrier patients, which show decreased survival and higher levels of total TDP-43 compared to control (Bilican et al., 2012). We also find that elevated endogenous TDP-43 protein levels were caused by a dramatic decrease in its clearance upon coexpression of M337V (Figure 6). The M337V protein also shows greatly reduced turnover compared to WT, as was previously reported in a different human cell line (Yin et al., 2021). Of note, the WT and M337V proteins were expressed in isogenic cell lines in our studies, suggesting that M337V homeostasis is intrinsically different from WT. Based on these results, we speculate that structural and functional defects in M337V disrupt the clearance of non-mutated TDP-43 in the affected cells, having the overall effect of increasing TDP-43 levels. Moreover, our observations that FUS and matrin-3 proteins also showed abnormal accumulation in M337V cells suggest strong defects in cellular protein homeostasis. Based on the accelerated maturation of M337V condensates, we speculate that M337V sequesters TDP-43, and perhaps other related proteins (e.g., FUS, matrin-3), into insoluble aggregates. It is also possible that the decreased solubility of M337V (Supplementary Figure 4) reduces the capacity of cellular protein clearance through a yet uninvestigated mechanism. These findings are relevant to patients carrying the M337V mutation as heterozygous, whereby expression of the M337V protein also affects the homeostasis of the WT allele as well as other proteins.
Our findings show that TDP-43 binding to CLIP34, specifically modulates liquid-liquid phase separation properties of TDP-43 (Figure 1). We previously showed evidence that TDP-43 LLPS is upregulated with increasing number of available RNA binding sites. According to band shift analyses, we estimated that 3-4 TDP-43 molecules bind to CLIP34 (Grese et al., 2021). The increased valency of the RNA-bound complex is likely to increase TDP-43 phase separation. Importantly, this sequencespecific RNA binding activity is also demonstrated in a cellular environment using human cell lysate (Figure 2). These results are consistent with our recent findings that interactions with specific RNA sequences promote TDP-43 condensation, and at the same time, increase the liquidity of phase separation (Grese et al., 2021). Additionally, Mann et al. (2019) previously showed that CLIP34 RNA decreases TDP-43-mediated neurotoxicity. Collectively, this evidence indicates that specific TDP-43-RNA interactions are important to prevent TDP-43 aggregation in the condensed state, during the processing of specific targets.

DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

AUTHOR CONTRIBUTIONS
LK, ZG, AB, and YA designed the study. ZG and LM generated the recombinant protein and performed the phase separation analysis. LK carried out the cell biology experiments and analyses. AB measured the RNA binding affinity. TH participated in the design, analysis and interpretation of the RNA binding assays. LM generated the DNA constructs and mutagenesis. YA wrote the manuscript. LK, ZG, AB, LM, and YA reviewed and edited the manuscript. All authors contributed to the article and approved the submitted version.

FUNDING
This work was supported in part by funding from the National Institutes of Health (NIH), National Institute for Neurological Disorders and Stroke (NINDS), and National Institute on Aging (NIA) R01 NS114289 and NINDS R56 NS105806 to YA; and the Department of Defense CDMRP/ALSRP W81XWH-20-1-0241 to YA.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins.

2022.818655/full#supplementary-material
Supplementary Figure 1 | CLIP34 RNA specifically increases the liquid properties of TDP-43 condensates. The size of TDP-43 condensates in the presence and absence of RNA was quantified as an estimation of differences in their liquid properties. The area of condensates composed of purified TDP-43 control, in the presence of CLIP34 or A(CA) 18 RNA shown in Figure 1C was calculated by ImageJ. Mean and SD of > 600 condensates from three biological replicates using two different protein preparations. Analyzed by one-way ANOVA [F(2,1948) = 353.5, P < 0.0001]. Dunnett's multiple comparisons test was used to compare groups to WT. ****P ≤ 0.0001. ns, no significance.


GPX2 predicts recurrence-free survival and triggers the Wnt/β-catenin/EMT pathway in prostate cancer

Objective This study aimed to establish a prognostic model related to prostate cancer (PCa) recurrence-free survival (RFS) and identify biomarkers. Methods The RFS prognostic model and key genes associated with PCa were established using Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression from the Cancer Genome Atlas (TCGA)-PRAD and the Gene Expression Omnibus (GEO) GSE46602 datasets. The weighted gene co-expression network (WGCNA) was used to analyze the obtained key modules and genes, and gene set enrichment analysis (GSEA) was performed. The phenotype and mechanism were verified in vitro. Results A total of 18 genes were obtained by LASSO regression, and an RFS model was established and verified (TCGA, AUC: 0.774; GSE70768, AUC: 0.759). Three key genes were obtained using multivariate Cox regression. WGCNA analysis obtained the blue module closely related to the Gleason score (cor = –0.22, P = 3.3e − 05) and the unique gene glutathione peroxidase 2 (GPX2). Immunohistochemical analysis showed that the expression of GPX2 was significantly higher in patients with PCa than in patients with benign prostatic hyperplasia (P < 0.05), but there was no significant correlation with the Gleason score (GSE46602 and GSE6919 verified), which was also verified in the GSE46602 and GSE6919 datasets. The GSEA results showed that GPX2 expression was mainly related to the epithelial–mesenchymal transition (EMT) and Wnt pathways. Additionally, GPX2 expression significantly correlated with eight kinds of immune cells. In human PCa cell lines LNCaP and 22RV1, si-GPX2 inhibited proliferation and invasion, and induced apoptosis when compared with si-NC. The protein expression of Wnt3a, glycogen synthase kinase 3β (GSK3β), phosphorylated (p)-GSK3β, β-catenin, p-β-catenin, c-myc, cyclin D1, and vimentin decreased; the expression of E-cadherin increased; and the results for over-GPX2 were opposite to those for over-NC. The protein expression of GPX2 decreased, and β-catenin was unchanged in the si-GPX2+ SKL2001 group compared with the si-NC group. Conclusion We successfully constructed the PCa RFS prognostic model, obtained RFS-related biomarker GPX2, and found that GPX2 regulated PCa progression and triggered Wnt/β-catenin/EMT pathway molecular changes.

INTRODUCTION
Prostate cancer (PCa) is one of the most common male malignant tumors in the United States and the second leading cause of cancer-related deaths in men (Kang et al., 2020). More than 80% of PCa cases are diagnosed as local diseases and usually treated by radical prostatectomy. However, about 15% of patients have a biochemical recurrence within 5 years after surgery, and the recurrence rate has been reported to be as high as 40% within 10 years. Local PCa that relapses after treatment can progress to fatal castration-resistant prostate cancer (CRPC) (Li et al., 2017). The causes of PCa recurrence are complex and diverse, and the specific mechanism has not yet been clarified (Siegel, Miller & Jemal, 2019). Therefore, research on the mechanism of PCa recurrence and the application of prognostic biomarkers may be of great significance in improving the survival rate of patients with PCa.
Many studies have shown that the epithelial-mesenchymal transition (EMT) and Wnt/βcatenin signaling pathways play an essential role in the occurrence and development of PCa (Montanari et al., 2017). EMT is necessary for PCa occurrence and distant metastasis, and plays a critical role in PCa metastasis to other organs (He et al., 2020). Epithelial cells attain the biological characteristics of stromal cells (Chaves et al., 2021). Studies have shown that the EMT and Wnt/β-catenin signaling pathways are closely related. Wnt binding to its receptor frizzled protein results in protein phosphorylation, which inhibits GSK-3 β activity. Consequently, β-catenin degradation is blocked and β-catenin accumulates in the cytoplasm, enters the nucleus, interacts with cytokines, activates the transcription of downstream target genes, induces EMT in cells, and promotes tumor growth and metastasis (Hseu et al., 2019;Sun et al., 2020).
Bioinformatics analysis is one of the crucial methods used for gene molecular research based on Big Data (Hutter & Zenklusen, 2018;Botía et al., 2017). In this study, PCa RFSrelated differentially expressed genes (DEGs) were screened by analyzing the data of PCarelated gene expression and clinicopathological characteristics in the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We analyzed the protein-protein interaction (PPI) based on DEGs. Survival, Cox regression, and LASSO regression analyses were used to establish and verify the prognostic model. The DEGs between different Gleason scores of PCa tissues and the key gene glutathione peroxidase 2 (GPX2) were obtained by weighted gene co-expression network analysis (WGCNA). The GSEA of GPX2 and its significance in prognosis and immunity were analyzed. Finally, a series of in vitro experiments were conducted to explore the potential role of GPX2 in PCa, so as to provide new clues for diagnosing and treating PCa.

Data acquisition
The data of gene expression profiles from the TCGA-PRAD dataset were downloaded from the TCGA database and standardized. At the same time, the clinical information of patients, including age, gender, TNM stage, pathological stage, and prognosis, was downloaded. The samples with incomplete clinical information and survival data were excluded. A total of 481 PCa samples and 51 adjacent tissue samples were included in the study. Three datasets of gene expression and clinical profiles of Pca were downloaded from the GEO database (GSE70768, GSE46602, and GSE6919).

Construction and validation of the Pca RFS prognostic model
The data were analyzed using the R software DESeq and Limma package. The volcano and heat maps were drawn using the P value <0.05 and |logfc|>2 as the screening conditions. After taking the intersection, Pca DEGs were obtained. The PPI network of DEGs was constructed using the STRING database, and the setting was adjusted to the interactive score of 0.7. Cytohubba and MCODE modules were used to screen Top30 and topologyrelated genes from Cytoscape 3.7.2. The prognostic model was established using univariate Cox, LASSO, and multivariate Cox regression analyses. Finally, the model was validated in the TCGA-PRAD and GSE70768 datasets.

WGCNA and GPX2 predicted PCa RFS
A total of 2,191 TCGA DEGs were analyzed using WGCNA. The Pearson correlation coefficient between genes was calculated. The scale-free network was constructed and the appropriate threshold was selected for network construction. Using two-step construction, the adjacency matrix was transformed into a topological overlap matrix, the clustering tree was generated through hierarchical clustering, and clustering was combined through a dynamic cut. The significance of gene and module was estimated, and the clinical sample grouping information was obtained. The identity of each gene module was calculated to measure the importance of genes in each module. Setting parameters |gene module|>0.8 and |gene significance|>0.2 as criteria, we screened the hub genes of modules closely related to clinical traits. The blue module was found to be significantly related to the Gleason score.
The key genes and blue modules were crossed, and the single gene GPX2 was obtained. The TCGA-PRAD dataset verified the GPX2-predicted PCa RFS.

GSEA and immunohistochemical (IHC) analysis
GSEA 4.0.1 was used to compare and analyze the DEGs between high-and low-expression groups of GPX2 in the PCa tumor samples of the TCGA-PRAD dataset. Gene set database selection KEGG v7. 4 was used to set the replacement times to 1,000; P < 0.05 and false discovery rate (FDR) <0.25 indicated significantly enriched genes. Between May 2021 and January 2022, the Second Affiliated Hospital of Nanjing University of Chinese Medicine collected tissues from 20 patients with PCa (10 patients with a high Gleason score ≥8 and 10 patients with a low Gleason score ≤7) and 10 patients with benign prostatic hyperplasia. Detailed information is shown in Table S1. All patients signed an informed consent form. This study was approved by the ethics committee of the Second Affiliated Hospital of the Nanjing University of Chinese Medicine (2021SEZ-030-01). The biopsy samples were collected, fixed with 10% formaldehyde, and embedded in paraffin after routine treatment. The prepared wax block was cut into sections with a thickness of 2 µm. Immunohistochemical staining was performed on the treated sections. The processed sections were stained with GPX2 (ab140130; Abcam, Cambridge, UK). Two pathologists used the double-blind method to judge each slice. The sections were observed using a low-power mirror under a microscope to select the best field of vision, and then a high-power lens was used in this range 10× 40. Five visual fields were randomly observed, and the IHC score was defined as the product of the frequency of positive cells and the intensity of staining.

GPX2 expression with immune cells in PCa
In this study, the CIBERSORT algorithm was used to calculate the infiltration proportion of 22 kinds of immune cells in PCa tissue, and 481 PCa samples were analyzed using the R software. The samples with a P value <0.05 were included in the follow-up analysis. Taking the median expression level of GPX2 mRNA as the boundary, the samples were divided into high-and low-expression groups.

Cell culture and qRT-PCR analysis
Human PCa cell lines (PC-3, DU145, LNCaP, and 22RV1) were purchased from Procell (Wuhan, China). The cells were cultured in RPMI-1640 (bl303a;Biosharp, Anhui, China) at 37 • C and in the presence of 5% CO2. The cells adhered to the wall and were passaged every 3 days. The cells in the logarithmic growth phase were used for the experiment. TRIzol reagent (bs259a, Biosharp, China) was used to extract the total RNA of PC-3, LNCaP, 22Rv1, and DU145 cells. A reverse transcription kit (11119es60; Yeasen, Shanghai, China) was used to reverse transcribe RNA into cDNA, and a SYBR Green Kit (11201es50; Yeasen, China) was used for qRT-PCR amplification, with β -actin as an internal control. The 2-CT method was used for calculation. The primers were as follows: GPX2: 5 -GCCTCCTTAAAGTTGCCATA-3 and 5 -GCCCAGAGCTTACCCA-3 ; β -actin: 5 -GAAGAGA-GAGACCCTCACGCTG-3 , and 5 -ACTGTGAGGAGGGGAGATTCAGT-3 . The experiment was repeated three times.

Transfection and grouping
LNCaP and 22RV1 cells in the logarithmic growth phase (n = 200,000) were inoculated into the cell culture plate and transfected according to the Lipofectamine 2000 (11668-027, Invitrogen, Waltham, MA, USA) instructions. They were divided into GPX2 low expression (si-GPX2) and negative control (si-NC) groups, GPX2 overexpression (over-GPX2) and negative control (over-NC) groups, and SKL2001(HY-101085, MCE, USA) +si-GPX2 groups. The transfection effect was verified using qRT-PCR and Western blotting. The experiment was repeated three times.

CCK-8 assay
LNCaP and 22RV1 cells in the logarithmic growth phase (n = 2,000) were inoculated into the cell culture plate. After undergoing corresponding treatment according to experimental grouping, 10 µL of cells were added to each well containing CCK-8 solution (PR645; Dojindo, Kumamoto, Japan). The culture plate was incubated and the absorbance value was determined to be 450 nm using a microplate reader (SpectraMax i3; Molecular Devices, San Jose, CA, USA). Cell proliferation inhibition rate = (control group absorbance valueexperimental group absorbance value)/control group absorbance value ×100%. The experiment was repeated three times.

Flow cytometry assay
The transfected cells were collected and digested with trypsin without EDTA. The adherent cells were collected and centrifuged. The supernatant was discarded and the cell precipitate was washed twice with phosphate-buffered saline (PBS). Annexin V-FITC/PI (556547, BD; Franklin Lakes, NJ, USA) was added. After incubation in the dark at room temperature for 5 min, we detected the apoptosis rate of LNCaP and 22RV1 cells using a flow cytometer (LSRII instrument; BD, Franklin Lakes, NJ, USA). The experiment was repeated three times.

Transwell invasion assay
The transfected cells were collected and the cell concentration was adjusted to 3× 105/mL. The cells were inoculated into the upper layer of the Transwell chamber (3422; Corning, Corning, NY, USA) which contained a serum-free medium, and 100 µL/well of the cell suspension was added. Additionally, 600 µL of the fresh culture medium was added to the lower layer of the chamber. The liquid in the upper chamber was discarded after culturing for 24 h, and the cells were wiped off the upper-chamber membrane with a wet cotton swab. The cells on the lower-chamber membrane were fixed with methanol for 20 min, dyed with crystal violet, rinsed with PBS until the background was clean, dried, and imaged after sealing. ImageJ software was used to count the number of transmembrane cells. The experiment was repeated three times.

Statistical analysis
The Student t -test was used for continuous variables, while the classification variables were analyzed using the χ 2 test. Cox and LASSO regression models were used to analyze the predictors of RFS. The data were expressed as mean ± standard deviation. All data were analyzed with R version 4.1.2, SPSS 24.0 and GraphPad Prism 8.0. A P value <0.05 indicated a significant difference. All tests were repeated three times.

Identified DEGs
The GSE46602 dataset had 211 upregulated genes and 409 downregulated genes. The TCGA-PRAD dataset was comprised of 898 upregulated genes and 1,293 downregulated genes. The volcano and heat maps showed DEGs (Figs. 1A and 1B). After further taking the intersection of the aforementioned datasets, we obtained the common 262 DEGs (94 upregulated genes and 168 downregulated genes) (Table 1 and Fig. 1C). STRING and Cytoscape were used to construct the PPI network of DEGs (Fig. 1D). Cytohubba and MCODE modules were used to screen Top30 and topology-related DEGs (Figs. 1E and 1F).  and low-risk groups, and the RFS-related scatter plot and the heat map of the prognostic model were constructed (Figs. 2C-2E). The ROC curve of the risk score was also generated, with AUC = 0.774 (Fig. 2F). The GSE70768 dataset was used to verify the prognostic model, and the RFS-related scatter plot and the heat map of the prognostic model were constructed (Figs. 2H-2J); the ROC curve of the risk score had AUC = 0.759 (Fig. 2K).

PCa RFS prognosis model
Three key genes obtained by the intersection of the prognostic model and Top30 were GPX2, EZH2, and COL2A1 (Fig. 2L). The multivariate Cox regression showed that the three genes significantly correlated with patient RFS (P = 0.001, 0.023,0.008, Fig. 2M).

WGCNA analysis and GPX2
According to WGCNA analysis and taking the correlation coefficient of 0.85 as the standard, the pickSoft threshold function was used to select the weight parameter of the adjacency matrix (soft threshold); β = 2 was the standard gene module (Figs. 3A-3C). Using the two-step method, the minimum number of genes in each gene module was set to 30, and the height of cutting branches and merging modules was set to 0.25. Finally, nine modules were obtained (Fig. 3D). Of these, we selected the blue module for this study, which was comprised of 450 genes with the correlation (r = -−0.22, P = 3.3e−05) (Fig. 3E). The intersection of blue module and key genes yielded only one gene GPX2 (Fig. 3F), which was used as in follow-up research.

GPX2 expression independently predicted RFS in PCa
To further evaluate the prognostic value of GPX2 for PCa, the prognostic nomogram was constructed by integrating clinical factors and gene expression (Fig. 4D), and the correction curve was drawn to evaluate the predictive ability of the nomogram. The correction curve showed that the risks predicted by the nomogram were highly consistent with the observed RFS for 1, 3, and 5 years (Figs. 4A-4C).

GSEA analysis
The GSEA analysis showed that GPX2 expression was mainly related to EMT and infectious disease biology, including the EMT and Wnt signaling pathways (Figs. 4E and 4F). The

CIBERSORT analysis
A significant difference was found in the degree of immune cell infiltration in 61 samples (20 in the GPX2 low-expression group and 41 in the GPX2 high-expression group) (Figs. 5A and 5B). Eight kinds of immune cells (activated dendritic cells, resting dendritic cells, M0 macrophages, M2 macrophages, monocytes, neutrophils, resting memory CD4 T cells, and CD8 T cells) showed GPX2 expression with significant differences (Fig. 5C).

GPX2 expression in PCa with the Gleason score
The immunohistochemical analysis showed that a GPX2-positive immune reaction was located in the cytoplasm and brownish yellow particles existed in the cytoplasm (Fig. 6A). GPX2 expression in benign prostatic hyperplasia tissue was significantly higher than in PCa tissue, with no significant difference in Gleason score (Fig. 6B). GSE66602 and GSE6919 datasets also confirmed the aforementioned results (Fig. 6C).

Expression of GPX2 in PCa cells and transfection
qRT-PCR and Western blotting were used to detect the highest mRNA level of GPX2 in LNCaP and 22RV1 cells, and GPX2 was used for subsequent experiments (Fig. 6D). Western blotting showed that the expression of GPX2 in the si-GPX2 group was significantly lower than that in the si-NC group. Also, the expression of GPX2 in the over-GPX2 group was significantly higher than that in the over-NC group, indicating that silencing and overexpression were successful and could be used in subsequent experiments (Figs. 6E and 6F).

GPX2 regulates the Wnt/β-catenin/EMT pathway in LNCaP and 22RV1 cells
The protein expression of Wnt3a, GSK3 β, p-GSK3 β, β-catenin, pβ-catenin, c-myc, cyclin D1, and vimentin decreased and that of E-cadherin increased in the si-GPX2 group compared with the si-NC group. The results for over-GPX2 were opposite to those for over-NC (Figs. 8A-8B and 8E-8F). Additionally, the protein expression of β-catenin increased and that of GPX2 decreased in the si-GPX2 + SKL2001 group compared with the si-NC group (Figs. 8C-8D and 8G-8H).

DISCUSSION
Although the incidence rate of PCa in Asia is far lower than that of Europe and North America, the incidence and mortality rate of PCa in China has rapidly increased in recent years (Bray et al., 2018;Gu et al., 2018). The routine clinical application of prostate-specific antigen has produced good results in helping the early diagnosis of PCa (Perera et al., 2021). However, PCa is a clinically heterogeneous cancer with large individual differences, particularly involving the diagnosis and treatment of early tumor diagnosis and later tumor progression, tumor metastasis, and hormone resistance (Ji et al., 2019). Identifying the genes related to the occurrence and development of PCa and clarifying the pathogenesis of cancer can provide a theoretical basis for preventing and treating PCa (Giri et al., 2018;Velho et al., 2018). Therefore, in-depth clinical and basic research involving a larger sample size is necessary in order to explore reliable diagnosis and treatment methods. PCa is a complex disease affected by multiple genes. In this study, we developed a risk score based on 18 genes that was verified using GSE70768 and TCGA-PRAD datasets, with a good prediction performance. WGCNA was used to analyze the TCGA-PRAD dataset, and nine modules associated with the pathological grade, Gleason scores, TNM stage, and clinical characteristics of PCa were obtained. We selected the Gleason score and blue module for analysis and found a significant correlation (Cor = -−0.22, P = 3.3e−05). Then, we predicted the intersection of three parts of the model genes using the blue module, Top30, and key genes. Finally, only the core gene GPX2 was obtained. A nomogram was constructed to predict the recurrence of PCa. The nomogram could predict the possibility of recurrence in PCa patients and was more accurate than clinical indicators.
GPX2, also known as gastrointestinal-specific glutathione peroxidase, is a seleniumcontaining protein. It is mainly expressed in the gastrointestinal system and exerts antiinflammatory and antioxidant effects (Lennicke et al., 2017). In recent years, GPX2 has been found to be highly expressed in a variety of tumors, especially inflammation-induced tumors, and may promote cell proliferation and inhibit apoptosis (Minato et al., 2021;Ji et al., 2021;Tian et al., 2021). GPX2 is also overexpressed in human and mouse CRPC cells and promotes the malignant proliferation of PCa cells. Inhibition of GPX2 expression significantly inhibited the proliferation of PCa cells and made them stagnate in the G2/M phase (Naiki et al., 2014). Inhibiting the expression of GPX2 can also improve the level of reactive oxygen species (Wu et al., 2021). These results showed that GPX2 had a certain correlation with tumor immunity. In this study, the high and low expression of GPX2 could influence eight kinds of immune cells to participate in the immune response of PCa. However, there have been few studies on the relationship between the expression of GPX2 and PCa prognosis and mechanism. The Gleason score system is a PCa pathological grading system that was introduced in 1974 ( Gleason & Mellinger, 1974). It has become the most powerful tool used to predict the prognosis of patients with PCa (Nagpal et al., 2020). It is closely related to the differentiation and invasion of PCa, which is of great significance for clinicians choosing and making treatment plans (Thomsen et al., 2020). IHC staining showed that the expression of GPX2 in PCa tissues had no significant correlation with the Gleason score; two datasets (GSE66602 and GSE6919) were used to verify the same results. Therefore, we speculated that GPX2 played an important role in PCa with no correlation to the Gleason score. We concluded that data mining must be combined with experimental verification. Furthermore, the survival prognosis of patients with high and low GPX2 expression was analyzed according to the public datasets GSE70768 and TCGA-PRAD. The results showed that the RFS time of patients in the GPX2 high-expression group was shorter than that of patients in the GPX2 low-expression group. In addition, this study used TCGA-PRAD data to construct a nomogram to predict the prognosis of patients with PCa, which helped us more intuitively understand the importance of the GPX2 expression levels in predicting PCa prognosis.
We used lentivirus transfection technology to promote the over-expression and low expression of GPX2 in LNCaP and 22RV1 cells in order to determine the role of GPX2 in the occurrence and development of PCa. The corresponding in vitro cell experiment results showed that inhibiting the expression of GPX2 could inhibit the proliferation and invasion of LNCaP and 22RV1 cells and induce apoptosis. Also, promoting the expression of GPX2 could promote proliferation and invasion and prevent the apoptosis of LNCaP and 22RV1 cells. The Wnt/β-catenin and EMT pathways were closely related to the occurrence and development of PCa (Kaplan et al., 2021;Chaves et al., 2021). Nath et al. (2019) found that Abi1 loss promoted the progression of PCa by modulating the Wnt signal and inducing EMT. Zhang & Li (2020) found that long noncoding RNA NORAD contributed to the metastasis of PCa via the Wnt/β-catenin/EMT pathway. However, the modulation of GPX2 on the Wnt/β-catenin/EMT pathway has not been reported. This study was novel in reporting that when the expression level of GPX2 changed, the proteins related to the Wnt/β-catenin/EMT pathways also changed. Therefore, we concluded that the mechanism of GPX2 in influencing the occurrence and prognosis of PCa was related to the Wnt/β -catenin/EMT signaling pathway.
However, despite the clinical significance of our findings, this study had some limitations. First, although the performance and AUC values of the calibration curve were excellent in the validation group, multicenter clinical application is still needed to further evaluate the external utility of the prognostic model. Only 262 genes were defined as genes related to the recurrence of PCa, and the construction of the prognostic model was evaluated. Some important genes might have been excluded before establishing the prognostic model. Second, GPX2 was highly expressed in benign prostatic hyperplasia compared with PCa. However, over-GPX2 promoted PCa cell proliferation and invasion and inhibited apoptosis, indicating that over-GPX2 promoted tumor progression to a certain extent. The underlying mechanism needs to be further examined.
In conclusion, the expression of GPX2 in PCa can be used as a new prognostic biomarker of RFS of PCa. GPX2 might regulate PCa progression via the Wnt/β-catenin/EMT pathway, and is expected to become a potential target for treating PCa.

ADDITIONAL INFORMATION AND DECLARATIONS Funding
This study was funded by The Second Affiliated Hospital of Nanjing University of Chinese Medicine (grant number SEZ202006). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.