extfieldsofstudy: Medicine Biology

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Lif1 SUMOylation and its role in non-homologous end-joining

Non-homologous end-joining (NHEJ) repairs DNA double-strand breaks by tethering and ligating the two DNA ends. The mechanisms regulating NHEJ efficiency and interplay between its components are not fully understood. Here, we identify and characterize the SUMOylation of budding yeast Lif1 protein, which is required for the ligation step in NHEJ. We show that Lif1 SUMOylation occurs throughout the cell cycle and requires the Siz SUMO ligases. Single-strand DNA, but not double-strand DNA or the Lif1 binding partner Nej1, is inhibitory to Lif1 SUMOylation. We identify lysine 301 as the major conjugation site and demonstrate that its replacement with arginine completely abolishes Lif1 SUMOylation in vivo and in vitro. The lif1-K301R mutant cells exhibit increased levels of NHEJ repair compared with wild-type cells throughout the cell cycle. This is likely due to the inhibitory effect of Lif1 SUMOylation on both its self-association and newly observed single-strand DNA binding activity. Taken together, these findings suggest that SUMOylation of Lif1 represents a new regulatory mechanism that downregulates NHEJ in a cell cycle phase-independent manner.

INTRODUCTION
DNA double-strand breaks (DSBs) are highly toxic lesions that challenge genomic integrity. DSBs arise both endogenously and from exogenous sources. Two distinct repair pathways, non-homologous end-joining (NHEJ) and homologous recombination (HR), have evolved to repair DSBs. Although NHEJ ligates the ends with little or no requirement for homology, HR uses a homologous sequence to copy the lost information (1,2). The pathway used depends on the organism, the type of break and the cell cycle phase. In the yeast Saccharomyces cerevisiae, NHEJ is used throughout the cell cycle, whereas HR operates predominantly in S and G2 phases when it is the preferred over NHEJ. In mammals, NHEJ is a dominant pathway in DSB repair and is critical for processing breaks that occur in the immune system during V(D)J recombination (3). Defects in the human NHEJ pathway lead to cancers, immunodeficiences and neurodegeneration, emphasizing the importance of this pathway to human health (4,5). As the core factors of NHEJ are evolutionarily conserved, budding yeast has been used as a model organism for NHEJ studies (5)(6)(7). Three protein complexes are fundamentally required for efficient NHEJ in S. cerevisiae [reviewed in (6,7)]. The Ku complex, consisting of the Ku70 and Ku80 subunits, binds specifically to DNA ends in a sequence-independent manner (8,9). Besides promoting NHEJ, Ku binding to DSB ends also protects it from nucleolytic degradation (9)(10)(11)(12). The second complex, Mre11/Rad50/Xrs2 (MRX), which binds early at DSB sites, can either bridge the broken ends for NHEJ repair or initiate resection to commence HR (13,14). Both Ku and MRX recruit the DNA ligase IV complex (Dnl4/ Lif1/Nej1) to DNA ends, where it performs the end-joining reaction as the final step of NHEJ. Lif1 serves several roles in this step. It preferentially binds longer DNA substrates to form oligomeric complexes (5,15,16). This correlates with its recruitment of Dnl4 to chromosomal DSBs and stimulation of Dnl4 ligase activity (16,17).
How the choice between HR and NHEJ is made and how NHEJ components collaborate remains largely unaddressed questions. CDK and Mec1-checkpoint-mediated phosphorylation have been shown to contribute to repair pathway choice. More recently, SUMOylation has been implicated in DSB repair and the DNA damage response (22). SUMOylation entails the covalent attachment of Small Ubiquitin-like Modifier (SUMO) to target proteins in a three-step process requiring E1 (Aos1/Uba2), E2 (Ubc9) and often E3 ligase enzymes [reviewed in (23)]. In budding yeast, three mitotic E3 ligases, Siz1, Siz2 and Mms21, have been identified (24)(25)(26). Although SUMOylation has been shown to be critical for DNA replication and repair, the consequences of SUMO attachment to many target proteins are not known (27)(28)(29).
Here, we report that Lif1 is subjected to SUMO modification in vivo. We show that Siz1 and Siz2 stimulate this modification, whereas double-strand DNA (dsDNA) or Lif1-interacting partners do not have any effect. We identify K301 as the main SUMOylation site and show that K301R increases Lif1 self-interaction without affecting binding to dsDNA or other NHEJ factors. This correlates with an increased capacity for NHEJ repair in lif1-K301R cells. Our results suggest that SUMOylation of Lif1 is involved in downregulation of NHEJ.

Plasmids and yeast strains
Plasmids for expression of Lif1 and Nej1-Lif1 complex were generous gifts from Dr. Murray Junop (McMaster University, Canada) (5). The construct containing fulllength Nej1 was kindly provided by Dr. Stefan Å stro¨m (Stockholm University, Sweden). The two-hybrid vectors were generous gifts from Dr. Thomas E. Wilson (University of Michigan, USA) (15). Construction of plasmids pGADT7-XRS2 and pGADT7-DNL4 was previously described elsewhere (30). The Lif1-K301R mutant was generated by substituting the lysine codon at position 301 with arginine using site-directed mutagenesis. Primer sequences are available on request.

Recombinant protein expression and purification
Purification of Lif1 and Lif1-K301R The (His) 6 -Lif1 protein was expressed in Rosetta-gami (DE3) pLysS using pMJ4102 plasmid (kindly provided by Dr. Murray Junop). An overnight culture (150 ml) was used to inoculate 12 l of 2xTY supplemented with 100 mg/ml ampicillin and 25mg/ml chloramphenicol. Cultures were grown at 37 C with vigorous shaking to an OD 600 of 0.5 and induced for 3 h at 37 C in the presence of 1 mM Isopropylthio-b-galactoside (IPTG). Cells were harvested by centrifugation, frozen in liquid nitrogen and stored at À80 C. Extract from 10 g of cell paste was prepared by sonication in 40 ml of Cell Breakage Buffer (CBB) buffer [50 mM Tris-HCl (pH 7.5), 10% sucrose, 2 mM ethylenediaminetetraacetic acid] containing 600 mM KCl, 0.01% NP40, 1 mM b-mercaptoethanol and protease inhibitor cocktail (pepstatin, leupeptin, aprotinin, chymostatin, benzamidine and phenylmethylsulfonyl fluoride). The lysate was clarified by ultracentrifugation, and the resulting supernatant was loaded on SP-sepharose column (7 ml, GE Healthcare). The SP-column was then eluted with a 70 ml gradient of 150-1000 mM KCl in buffer K (20 mM K 2 HPO 4 , 10% glycerol, 0.5 mM EDTA). The Lif1-containing fractions were pooled and mixed with 1 ml of Ni-NTA agarose (Qiagen). The beads were washed with 10 ml of buffer K containing 500 mM KCl, followed by 10 ml of buffer K containing 500 mM KCl and 10 mM imidazole. The bound proteins were eluted with buffer K supplemented with 500 mM KCl and containing 50, 150, 300 or 500 mM imidazole. The fractions with Lif1 protein eluting from 50 to 300 mM imidazole were pooled and loaded onto a 1-ml Heparin column (GE Healthcare). The column was washed and eluted with a 10 ml gradient of 150-1000 mM KCl in buffer K. The peak fractions were pooled and concentrated in a Centricon-30 (Sartorius Stedim) to 10 mg/ml and stored in small aliquots at À80 C. The same procedure was used to purify the (His) 6 -Lif1-K301R mutant protein.

Expression and purification of Nej1
Recombinant MBP-tagged Nej1 protein was expressed in Rosetta-gami (DE3) pLysS containing pSTEF446 plasmid (gift from Dr. Stefan Å stro¨m). A saturated 150 ml of overnight culture was used to inoculate 12 l of 2xTY containing 100 mg/ml ampicillin and 25 mg/ml chloramphenicol. Cultures were grown at 37 C with vigorous shaking to an OD 600 of 0.5 and induced for 12 h at 16 C in the presence of 0.1 mM IPTG. Cells were harvested by centrifugation, frozen in liquid nitrogen and stored at À80 C. Extract from 10 g of cell paste was prepared by sonication in 40 ml of CBB containing 600 mM KCl, 0.01% NP40, 1 mM b-mercaptoethanol and protease inhibitor cocktail. The lysate was clarified by ultracentrifugation, and the resulting supernatant was loaded on SP-sepharose column (7 ml). The SP-column was then eluted with a 70 ml gradient of 150-1000 mM KCl in buffer K. The Nej1-containing fractions were pooled and mixed with 1 ml of amylose agarose (New England Biolabs). The beads were washed with 10 ml of buffer K containing 200 mM KCl.
The bound proteins were eluted with buffer K containing 1, 5 or 10 mM maltose and 200 mM KCl. The fractions with Nej1 protein eluting from 1 to 10 mM maltose were pooled and loaded onto a 1-ml Heparin column and eluted with a 10 ml gradient of 150-1000 mM KCl in buffer K. The peak fractions were pooled, concentrated in a Centricon-30 to 10 mg/ml and stored in small aliquots at À80 C.

LC-MS/MS analysis of gel bands
Gel bands were washed and proteins were reduced with dithiothreitol, alkylated by incubation with iodoacetamide and subsequently digested by addition of trypsin (recombinant, proteomics grade, Roche) over night at 37 C. Peptides were analysed on an UltiMate 3000 reversed phase-HPLC system (Thermo Fisher Scientific) connected to an LTQ-Orbitrap Velos mass spectrometer (Thermo Fisher Scientific) via a nanoelectrospray ionization source (Proxeon, Thermo Fisher Scientific). Peptides were separated applying a 60-min linear gradient from 2.5% up to 40% acetonitrile. The voltage of the ion source was set to 1500 V. The mass spectrometer was operated in the data-dependent mode: 1 full scan in the orbitrap (m/z: 400-1800, resolution 60 000) with lock mass (m/z 445.120 025) enabled was followed by maximal 20 MS/ MS scans. Monoisotopic precursors were selected, and singly charged signals were excluded from fragmentation. The collision energy was set at 35%, Q-value at 0.25 and the activation time at 10 msec. Fragmented ions were excluded from further selection for 90 s.
Peptide identification was performed by the SEQUEST algorithm in the Proteome Discoverer 1.3.0.339 software package (Thermo Fisher Scientific). Spectra were searched against a small database containing the protein sequences of the SUMOylation assay plus proteases, contaminants and a short list of unrelated proteins. To increase the identification rate of the SUMOylated peptides, the proteins of interest were digested in silico with trypsin, and the resulting peptides were extended at the N-terminus with amino acids EQIGG and added to the database (35). EQIGG is the part of SUMO that remains attached to the target sequence after tryptic digest.
Search parameters were as follows: tryptic specificity with max. 3 missed cleavages, peptide tolerance of 2 ppm, fragment ions tolerance of 0.8 Da.
Carbamidomethylation of Cys was set as static modifications, oxidation of Met and SUMOylation residue (484.2282 Da) at Lys as variable modifications. Modified peptides were checked manually.

Detection of Lif1 SUMOylation in vivo
Protein extracts and immunoprecipitates were prepared as described previously (28). In brief, cells were disrupted by bead beating under denaturing conditions, and diluted protein extracts were immunoprecipitated using immunoglobulin G-Sepharose to pull down TAP-tagged Lif1. Immunoprecipitated proteins were then washed and eluted with loading dye before separating by SDS-PAGE and immunoblotting with anti-SUMO or PAP antibodies. As only 5-10% of Lif1 is SUMOylated, this modified form is not detected by the PAP antibody without long exposures but is preferrentially detected by anti-Smt3, which also recognizes ProA on the TAP tag (28). For the analysis of SUMOylation during cell cycle, Lif1-TAP strains were arrested in G1 phase with 5 ug/ml a-mating factor or in G2/M phase with 15 ug/ml nocodazole, then released into the cell cycle. Samples were collected every 15 min for analysis by protein immunoprecipitation and western blotting. Samples from these time points were also examined by fluorescenceactivated cell sorting (FACS) analysis. Induction of Lif1 SUMOylation by treatment with methyl methane sulphonate (MMS) was achieved by subjecting logarithmically growing cells to 0.3% MMS for 2 h before harvesting samples.

Pull-down assay
Amylose resin was incubated with (His) 6 -Lif1 and (His) 6 -Lif1-K301R proteins or in vitro SUMOylated (His) 6 -Lif1 together with MBP-Nej1. After extensive washing (100 ml) with immunoprecipitation buffer IP (20 mM K 2 HPO 4 , 10% glycerol, 0.5 mM EDTA) containing 50 mM KCl, the bound proteins were eluted from the affinity resin by boiling with 30 ml of SDS sample buffer. The samples were resolved on a 10% SDS-PAGE gel and transferred to a Polyvinylidene difluoride (PVDF) membrane. The blot was subjected to analysis with anti-His antibodies (Sigma Aldrich).

Two-hybrid analysis
The analysis was performed as described elsewhere (36). The indicated recombinant vectors were co-transformed into haploid yeast cells and tested for expression of the reporter gene by growth on synthetic complete media lacking histidine, tryptophan and leucine (SD/ÀHis/ ÀTrp/ÀLeu) for 4 days at 30 C.

Plasmid-based rejoining assay
The assay was carried out as described previously (37,38). Briefly, plasmid pRS425 containing the LEU2 gene was digested with the indicated restriction enzymes to completion. Yeast cultures were grown to log phase and transformed with 500 ng of corresponding linearized plasmid using the lithium acetate method (39). Parallel transformation was always performed with an equivalent amount of undigested plasmid to enable normalization for differences in transformation efficiencies between strains and individual experiments. Serial dilutions were plated on selective media, and colonies were counted after 5 days of incubation.

HO-induced DSB repair assay
In contrast to plasmid-based rejoining assay, HO-induced DSB repair assay measures DSB rejoining in chromatinized chromosomal DNA (40,41). Parental JKM139 strain contains no HML and HMR loci (see genotype above), two silent copies of the MAT locus. Therefore, HO-induced DSB at the MAT locus can be repaired only by NHEJ in this strain. The HO-encoding gene is placed under the control of a galactose-inducible promoter. In persistent DSB induction experiment (40), yeast cultures grown overnight in media containing 3% glycerol were pelleted, washed with distilled water and directly plated in serial dilutions on glucose-and galactose-containing media in parallel. The efficiency of rejoining of HO-induced DSBs was calculated as the number of colonies on galactose plates normalized to that on glucose. Transient DSB induction experiment as well as persistent DSB induction experiment in G1-, S-and G2/M-arrested cells were perfomed as described previously with asynchronous cells being treated similarly except the addition of arresting agent (42).

Sensitivity to DNA damage-inducing agents
For the purpose of DNA damage sensitivity assays, a spot test was used. Serial 10-fold dilutions of cell suspensions were spotted onto Yeast Peptone Dextrose (YPD) plates containing indicated concentrations of hydroxyurea, MMS or bleomycin. Images were taken 4 days after incubation at 30 C.

Lif1 is a target for SUMOylation and requires both Siz1 and Siz2 SUMO ligases
A previous study has shown that Lif1 is SUMOylated in vivo (28). To define requirements for SUMOylation of Lif1, we took advantage of our in vitro SUMOylation reaction (27). The reaction was assembled with SUMO (Smt3), E1 (Aos1/Uba2 complex), E2 (Ubc9) and ATP. We directly tested the SUMO ligase required for Lif1 SUMOylation. As shown in Figure 1A, Lif1 SUMOylation was stimulated by Siz1 (lane 3) or Siz2 (lane 4) proteins, indicating that both E3 ligases SUMOylate Lif1 in vitro. The modification was also confirmed using anti-Lif1 and anti-Smt3 antibodies (Supplementary Figure S1). To test the role of these E3 ligases in vivo, we analysed SUMOylation of endogenous Lif1 protein in siz1D, siz2D and siz1D siz2D cells. Although siz1D and siz2D did not show a significant effect, the siz1D siz2D double mutant abolished Lif1 SUMOylation ( Figure 1B), indicating that both Siz1 and Siz2 are required but are redundant for Lif1 SUMOylation. Quantification revealed that up to 10% of Lif1 was SUMOylated when cells were treated with MMS, although basal level of SUMOylation without DNA damage was also detected (Figures 1B and 6A).
As Lif1 binds to dsDNA (16), we asked whether DNA affects Lif1 SUMOylation. As shown in Figure 1A, addition of neither ssDNA nor dsDNA had any effect on the level of Lif1 SUMOylation in the absence of an E3 ligase. In the presence of Siz1 or Siz2 ligase, although dsDNA had no effect, ssDNA resulted in up to 50% reduction in Lif1 SUMOylation level ( Figure 1C). This result was surprising, as Lif1 has not previously been shown to bind to ssDNA. To understand the effects of ssDNA, we tested whether Lif1 is capable of binding to ssDNA. Using electrophoretic mobility shift assay, we found that Lif1 can interact with ssDNA, and direct comparison as well as competition with dsDNA revealed similar albeit weaker, affinity compared with dsDNA ( Figure 1D). Thus, ssDNA binding may underlie the reduction in Lif1 SUMOylation in Figure 1C. The fact that Lif1 and Nej1 form a tight complex in vitro and in vivo (18,20,21) prompted us to test the effect of Nej1 on Lif1 SUMOylation. We found that Nej1 did not have any impact on Lif1 SUMOylation ( Figure 1E). Taken together, these data indicate that neither binding to Nej1 nor to dsDNA affects Lif1 SUMOylation, but ssDNA binding is likely inhibitory to its SUMOylation.

Lysine 301 is the main SUMO-conjugation site in Lif1
To determine the SUMOylation sites in Lif1, we analysed the SUMOylated protein using mass spectrometry (MS). This analysis identified lysine at position 301 (K301) as a major conjugation site (Supplementary Figure S2).   Therefore, we introduced the K301R substitution into the LIF1 sequence and purified the mutant protein (Lif1-K301R). As shown in Figure 1A (lanes 8-11), the mutant protein failed to be SUMOylated in vitro. This indicates that K301 is essential for this post-translational modification.
To address whether K301 is also targeted for SUMOylation in vivo, we fused Lif1 and Lif1-K301R with the TAP tag at the chromosomal locus in yeast. Lysates from these strains were subjected to immunoprecipitation and immunodetection using an antibody recognizing the TAP tag on Lif1 protein and another recognizing SUMO. This analysis revealed stronger SUMOylation of Lif1 under DNA damaging conditions, as seen previously (28). Similarly to in vitro conditions, Lif1-K301R failed to be SUMOylated, indicating that K301 is essential for Lif1 modification in vivo ( Figure 1F).

DNA binding of Lif1-K301R and SUMOylated Lif1 proteins
We asked whether SUMOylation of Lif1 affects its DNA binding activity by electrophoretic mobility shift assay analysis. First, we tested the DNA binding activity of Lif1 wild-type and K301R mutant proteins. No differences in DNA binding were observed, indicating that the K301R substitution does not affect the dsDNA binding properties of the protein (Figure 2A).
Next, we compared DNA binding properties of unmodified and SUMOylated Lif1 proteins. SUMOylated Lif1 protein ($90%, Supplementary Figure S3) did not show any decrease in the ability to bind to dsDNA compared with wild-type. However, although the unmodified protein formed a discrete band with DNA, SUMOylated Lif1 showed a diffused signal, suggesting   differences in the formation of higher order complexes ( Figure 2B). Strikingly, SUMOylated Lif1 exhibited a decrease in ssDNA binding ( Figure 2C), again suggesting that the DNA binding properties of Lif1 change after SUMOylation.
Lif1 SUMOylation and the K301R mutation do not affect interaction with Nej1, Xrs2 and Dnl4 Lif1 has been reported to interact with several proteins functioning in the NHEJ pathway, including Nej1, Xrs2 and Dnl4 (15,16,(18)(19)(20)(21)43). We tested whether SUMOylation of Lif1 impinges on these functions by checking whether SUMOylation at lysine 301 or the K301R substitution in Lif1 alters its ability to interact with Nej1. To ensure that the reaction conditions, as well as the amounts of proteins in the pull-down reactions, are the same, we took equivalent fractions from the SUMOylation reactions performed in the presence or absence of ATP. As is evident from pull-down experiments, the Lif1-Nej1 interaction was unaffected by SUMOylation status and by the K301R substitution ( Figure 3A and B). The ability of the Lif1-K301R mutant to interact with Nej1 was also confirmed using two-hybrid analysis, where Nej1 was fused to the activation domain of Gal4, whereas Lif1 (wild-type or K301R) was fused to the DNA binding domain ( Figure 3C). Similarly to the Nej1-Lif1 two-hybrid interaction, neither the Xrs2-Lif1 nor the Dnl4-Lif1 combinations showed any noticeable differences between wild-type and K301R mutant protein ( Figure 3C). Taken together, SUMOylation status and the K301R substitution do not affect Lif1's interactions with Nej1, Dnl4 or Xrs2.

SUMOylation of Lif1 inhibits its self-interaction
As Lif1, as well as its human counterpart, has been shown to self-associate (15,(44)(45)(46)(47)(48), we asked whether SUMOylation of Lif1 affects this interaction using two-hybrid assays. Interestingly, we detected stronger self-interaction for Lif1-K301R compared with wildtype, indicating that SUMOylation of Lif1 at lysine 301 negatively regulates its self-association ( Figure 4A). To further demonstrate the inhibitory effect of SUMOylation on Lif1 self-association, we generated two-hybrid reporter strains lacking Siz1, Siz2 or both. In agreement with the aforementioned results, downregulation of Lif1 SUMOylation by deleting the E3 ligases resulted in an enhancement in Lif1 self-association compared with the wild-type two-hybrid strain ( Figure 4B).

Lif1 SUMOylation inhibits NHEJ repair
To determine the functional effect of the non-SUMOylatable lif1-K301R allele, we replaced wild-type LIF1 with this mutation in yeast and tested sensitivity to various DNA damaging agents. Similarly to lif1D cells, the lif1-K301R mutant did not show significant sensitivity to any type of DNA damaging agent (Supplementary Figure  S4) (7). Next, we used a plasmid-based rejoining assay to test whether Lif1 SUMOylation affects DSB repair. In line with previous findings (17), we observed a severe defect of lif1D cells in rejoining plasmid-based DSBs, regardless of polarity, complementarity, length or sequence content of the cleavage site (Supplementary Figure S5). An exception is the repair of blunt ends that is also markedly reduced in wild-type cells. The lif1-K301R cells consistently showed higher efficiency of NHEJ repair for all combinations of linearized plasmids tested compared with wild-type cells, although these were not statistically significant, probably owing to the large margins in the plasmid assays (Supplementary Figure S5).
To further test the effect of Lif1 SUMOylation, we assayed donor-less HO-induced chromosomal rejoining that is strictly dependent on NHEJ (40,41). Under persistent DSB induction, lif1-K301R cells exhibited nearly 2-fold increase in rejoining HO-induced breaks compared with wild-type cells ( Figure 5, p = 4.5 Â 10 À5 ). Analysis of transient DSB induction shows a similar trend; however, the increase was not statistically significant (Supplementary Figure S6). Together, these results suggest that Lif1 SUMOylation is inhibitory to NHEJ repair, particularly under persistent DSB-induction conditions.
As the choice of NHEJ versus HR is regulated differently during the cell cycle, we asked whether Lif1 SUMOylation also varies during cell cycle progression. When cells synchronized in either G1 or G2/M were released, we observed that Lif1 SUMOylation does not show cell cycle phase dependence ( Figure 6A and Supplementary Figure  S7), suggesting that Lif1 is SUMOylated constantly. This is consistent with the finding that lif1-K301R resulted in increased NHEJ repair in G1, S, G2/M arrested or asynchronized cells in the donor-less HO-induced chromosomal rejoining assay ( Figure 6B).

DISCUSSION
HR and NHEJ are two major repair pathways for DSBs and are important for genomic stability. How the pathway choice is made and how protein interactions within each pathway are regulated remains unclear. Several types of reversible modifications of proteins can dynamically modulate protein functions, providing possible mechanisms for this regulation (49). Besides CDK and Mec1checkpoint-mediated phosphorylation, modification by SUMO has emerged as an important regulator in DSB repair. A number of DNA repair proteins have been shown to undergo SUMOylation, primarily after DNA damage (22,(50)(51)(52)(53). Nevertheless, little is known about the precise role of SUMOylation in regulating each of these substrates and how that contributes to different repair mechanisms.

SUMOylation of Lif1 involves lysine 301 and is influenced by ssDNA binding
Here, we examined SUMOylation of the NHEJ protein Lif1. We identified lysine 301 as the major target site for SUMOylation, and its substitution with arginine abolished this modification both in vitro and in vivo. We showed that the Siz1 or Siz2 SUMO E3 ligase was required for Lif1 SUMOylation in vitro. This is further supported by the in vivo analysis that demonstrated redundancy of Siz1 and Siz2 in Lif1 modification. Redundancy of Siz proteins has been observed for several other substrates (29,52). Whether they can differently affect their substrates is unclear in most cases and will need to be addressed in the future.
Although Nej1 and dsDNA had no impact on Lif1 SUMOylation, ssDNA exerted an inhibitory effect. We further uncovered that Lif1 binds ssDNA with a similar, albeit weaker, affinity than dsDNA. It is tempting to speculate that this newly discovered ssDNA binding activity of Lif1 might be important in joining DNA ends containing ssDNA regions, such as in microhomology-mediated end-joining. This activity may add to its known interaction and stimulation of Fen1 endonuclease (54) and interaction and coordination of Pol4 (55) to promote certain types of end joining. How ssDNA binding inhibits Lif1 SUMOylation requires further study, but we surmise that ssDNA binding may induce conformational changes in Lif1 that either prevent its interaction with SUMOylation enzymes or disfavour proper alignment of K301 with these enzymes. The inhibitory effect of ssDNA on Lif1 SUMOylation is in contrast to Rad52 whose SUMOylation is stimulated by ssDNA binding (27), highlighting an interesting difference of ssDNA effect on NHEJ versus HR protein SUMOylation.
Lif1 SUMOylation decreases self-association and ssDNA binding without affecting binding to other proteins or dsDNA Unlike ubiquitination, SUMOylation does not target proteins for degradation, but instead can alter proteinprotein interactions or biochemical properties of the proteins (22,52,56). Using in vitro pull-down and yeast two-hybrid assays, we determined that SUMOylation of Lif1 does not affect its interaction with Nej1, Xrs2 or Dnl4, indicating that these interactions are not regulated by this modification. Binding of the Lif1-K301R mutant or SUMOylated Lif1 to dsDNA was also indistinguishable from that of wild-type or unmodified protein. On the contrary, ssDNA binding was reduced on Lif1 SUMOylation. Although the biological significance of this reduction is unclear, several possibilities can be envisioned. For example, this may help prevent joining of ssDNA-containing ends or interference with HR steps such as resection and consequent loading of RPA or Rad51 proteins onto ssDNA.
An interesting effect of Lif1 SUMOylation is its influence on self-association of the protein. We observed increased association of the Lif1-K301R mutant compared with wild-type protein in yeast two-hybrid. In addition, deletion of SIZ1 or SIZ2 resulted in increased Lif1 self-interaction, and siz1D siz2D led to interaction

Abolition of Lif1 SUMOylation promotes NHEJ repair
To elucidate the role of Lif1 SUMOylation in vivo, we took advantage of two NHEJ-dependent DSB repair assays. First, using a plasmid-based rejoining assay, we observed slightly increased (though not statistical significant) recircularization efficiency for all combinations of linearized plasmids in lif1-K301R cells compared with wild-type. Second, we assayed repair of DSBs induced by HO endonuclease at the MAT locus on chromosome III in a strain that lacks the donor sequences and thus solely uses NHEJ for repair (41). Here, lif1-K301R cells rejoined DSBs more efficiently (statistically significant) than the wild-type cells on persistent HO induction. When HO was induced transiently, lif1-K301R cells still repaired HO-induced DSB efficiently than the wild-type cells, but the difference was not statistically significant. As Lif1 is phosphorylated by cyclin-dependent kinase in S and G2 phases, but not G1 (42), we asked whether SUMOylation of Lif1 is also differently regulated during the cell cycle or is involved in the cell cycle regulation of NHEJ. We observed a constant level of Lif1 SUMOylation throughout the cell cycle. Additionally, lif1-K301R increases NHEJ in G1, S, and G2/M phases of the cell cycle. These results suggest that SUMOylation of Lif1 serves as a cell cycle-independent negative regulator of NHEJ. This level of regulation may safeguard the genome by ensuring that NHEJ levels remain low during normal growth. Lif1 SUMOylation is induced by MMS; the meaning of this increase is unclear, though we provide several possibilities. As lif1D cells are not MMS sensitive, Lif1 modification may prevent its interference with other repair pathways. For example, SUMOylation of Lif1 results in decreased binding to ssDNA, thus possibly alleviating competition with other ssDNA binding proteins. On the other hand, the lack of sensitivity to MMS and other DNA damaging agents by lif1D or lif1-K301R may be due to the presence of redundant pathways. For example, SUMOylation of Ku, MRX or other NHEJ proteins could compensate for loss of Lif1 SUMOylation (28,(57)(58)(59). Further studies combining various SUMOdeficient alleles will be able to address this possibility.
Moreover, the effect of Lif1 SUMOylation on its selfinteraction could represent a similar mechanism of regulation as is observed for human XRCC4 where binding of the BRCT domain or DNA-PK phoshorylation alters XRCC4 tetramerization (48,60,61). Inhibition of NHEJ could be an efficient strategy in the fight against cancers, particularly those with mutations in HR genes (BRCA1 and BRCA2), because repression of the alternative DSB repair pathway of NHEJ in these cells could lead to a substantial decrease in cancer cell survival. Understanding the molecular mechanisms of NHEJ and its regulation will aid the development of novel therapeutic strategies, such as blocking XRCC4 self-association, that may be used along with DNA-damaging agents in the treatment of HR-deficient cancers.


s2fieldsofstudy: Biology Medicine

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Significant Association of Glutathione S-Transferase T1 Null Genotype with Prostate Cancer Risk: A Meta-Analysis of 26,393 Subjects

Background Recent studies on the association between Glutathione S-transferase T1 (GSTT1) polymorphism and risk of prostate cancer showed inconclusive results. To clarify this possible association, we conducted a meta-analysis of published studies. Methods Data were collected from the following electronic databases: Pubmed, Embase, and Chinese Biomedical Database (CBM). The odds ratio (OR) and its 95% confidence interval (95%CI) was used to assess the strength of the association. We summarized the data on the association between GSTT1 null genotype and risk of prostate cancer in the overall population, and performed subgroup analyses by ethnicity, adjusted ORs, and types of controls. Results Ultimately, a total of 43 studies with a total of 26,393 subjects (9,934 cases and 16,459 controls) were eligible for meta-analysis. Overall, there was a significant association between GSTT1 null genotype and increased risk of prostate cancer (OR = 1.14, 95%CI 1.01–1.29, P = 0.034). Meta-analysis of adjusted ORs also showed a significant association between GSTT1 null genotype and increased risk of prostate cancer (OR = 1.34, 95%CI 1.09–1.64, P = 0.006). Similar results were found in the subgroup analyses by ethnicity and types of controls. Conclusion This meta-analysis demonstrates that GSTT1 null genotype is associated with prostate cancer susceptibility, and GSTT1 null genotype contributes to increased risk of prostate cancer.

Introduction
Prostate cancer is a common cause of cancer mortality and one of the most frequently diagnosed malignancies in men [1,2]. Identifying risk factors for prostate cancer is critically important to develop potential interventions and to expand our understanding of the biology of this disease [2,3]. Endogenous products and environmental factors could result in the production of reactive oxygen species (ROS) and nitrogen metabolites causing cell injury and genetic instability, and further result in the carcinogenesis in prostate [2]. Glutathione S-transferases (GSTs) play an active role in the detoxification of a variety of endogenous or exogenous carcinogens by glutathione (GSH) conjugation [4,5]. These enzymes also play a crucial role in protection of DNA from oxidative damage by ROS [4,5]. In humans, GST super family consists of many cytosolic, mitochondrial, and microsomal proteins, and the cytosolic family has eight distinct classes alpha, kappa, mu, omega, pi, sigma, theta, and zeta [6]. The theta class of GSTs is encoded by the Glutathione S-transferase T1 (GSTT1) gene located on the long arm of chromosome 22 (22q11.23), and the homozygous deletion (null genotype) of GSTT1 gene causes complete absence of GST enzymes activity [7,8]. In 2009, a meta-analysis on the association between GSTT1 null genotype and prostate risk was reported. This meta-analysis including 22 studies (3,837 cases and 4,552 controls) concluded that there was no association between GSTT1 null genotype and prostate risk [9]. Nevertheless, this meta-analysis included relatively small sample size, and many new studies recently have examined the association between GSTT1 null genotype and prostate risk [10][11][12][13][14][15][16][17][18][19][20], but the results remain inconclusive and inconsistent. Hence, to clarify this possible association, we conducted an updated meta-analysis of published studies, which may provide an evidence for the association of GSTT1 null genotype and prostate risk.

Identification and Eligibility of Relevant Studies
Data were collected from the following electronic databases: Pubmed, Embase, and and Chinese Biomedical Database (CBM). Relevant publications were identified through a literature search using the following search strategy: (''Glutathione S-transferase T1'' or ''GSTT1'' or ''GSTT'') and (''prostate cancer'' or ''prostate carcinoma''). Additional literature was collected from crossreferences within both original and review articles. No language

Data Extraction
Information was carefully extracted from all the eligible publications independently by two of the authors according to the inclusion criteria listed above. Disagreement was resolved by discussion among all authors. Data extracted from the selected studies included author, year of publication, country, ethnicity, definition of cases, characteristics of controls, total numbers of cases and controls, the genotype frequency of GSTT1 polymorphism, and adjusted odds ratio (OR) and its 95% confidence interval (95%CI). Different descents were categorized as Caucasians, East Asians, Africans, Indians, and Others. If original genotype frequency data were unavailable in relevant articles, a request was sent to the corresponding author for additional data. In deed, only two requests were sent, but no replies were obtained.

Statistical methods
The strength of the association between GSTT1 null genotype and prostate cancer risk was assessed by calculating the pooled OR with its 95%CI. The pooled ORs were obtained using either the fixed-effects (Mantel-Haenszel's method) [21] or random-effects (DerSimonian and Laird method) models [22], and the significance of the pooled OR was determined by the Z-test. Heterogeneity assumption was checked by the Chi-square test based Q-statistic [23] and the I 2 statistic [24]. A significant Q statistic (P,0.10) or I 2 statistic (I 2 .50%) indicated obvious heterogeneity across studies, and the random effect model was selected to pool the ORs. Otherwise, the fixed effect model was selected to pool the ORs. Subgroup analyses were performed by ethnicity, adjusted ORs, and types of controls. Subgroup analyses were firstly performed by adjusted ORs including subgroup analysis of adjusted ORs and subgroup analysis of unadjusted ORs. Subgroup analyses were then performed ethnicity, and ethnicities were categorized as Caucasians, East Asians, Africans, Indians, and Others. Finally, Subgroup analyses were performed by the types of controls. Publication bias was investigated with the funnel plot. The funnel plot should be asymmetric when there is a publication bias, and the funnel plot asymmetry was further assessed by the method of Egger's linear regression test [25]. Analyses were performed using the software Stata version 11 (StataCorp LP, College Station, TX). A P value less than 0.05 was considered statistically significant, and all the P values were two sided.

Meta-Analysis
The summary of meta-analysis for GSTT1 null genotype with prostate cancer risk was shown in Table 2.
In the subgroup analyses were firstly performed by ethnicity (Caucasians, East Asians, Africans, and Indians). There was an obvious association between GSTT1 null genotype and increased risk of prostate cancer in Caucasians (OR = 1.17, 95%CI 1.01- In the subgroup analysis of BPH controls, there was no obvious association between GSTT1 null genotype and increased risk of prostate cancer (OR = 1.15, 95%CI 0.73-1.80, P = 0.549). In the subgroup analysis of controls without BPH, there was an obvious  association between GSTT1 null genotype and increased risk of prostate cancer (OR = 1.41, 95%CI 1.06-1.88, P = 0.020).

Evaluation of Publication Bias
Both funnel plot and Egger's test were performed to assess the publication bias of the studies. The shape of the funnel plots did not reveal any evidence of obvious asymmetry for any genetic model in the overall and subgroup meta-analysis ( Figure 3). Next, Egger's test was used to provide statistical evidence of the funnel plot symmetry. The results still did not suggest any obvious evidence of publication bias for any genetic model (P Egger's test = 0.117). Thus, there was no obvious risk of bias in this metaanalysis.

Discussion
Genetic susceptibility to cancer has been a research focus and many genetic association meta-analyses have been published to find some possible susceptibility polymorphisms [3,[10][11][12][13][14][15][16][17][18][19][20]. Previous studies assessing the association between GSTT1 null genotype and prostate cancer risk reported inconclusive and inconsistent findings. Therefore, to get a reliable conclusion for the association of GSTT1 null genotype and prostate risk, we conducted the present meta-analysis of 43 independent studies including a total of 26, 393 subjects (9, 934 cases and 16, 459 controls). Overall, there was a significant association between GSTT1 null genotype and increased risk of prostate cancer ( Table 2). Meta-analysis of adjusted ORs also showed a significant association between GSTT1 null genotype and increased risk of prostate cancer (Table 2). Similar association was also found in the subgroup analyses by ethnicity and types of controls (Table 2). Therefore, our meta-analysis demonstrates that GSTT1 null genotype is associated with prostate cancer susceptibility, and GSTT1 null genotype contributes to increased risk of prostate cancer.
Previous literature didn't provide a comprehensive assessment on the association between GSTT1 null genotype and prostate cancer risk, but a trend for potential genetic effects was suggested in early data for the association between GSTT1 null genotype and prostate cancer risk. Postulated genetic associations for prostate cancer need to be carefully validated, because early and small genetic association studies may come up with spurious findings. Two previous meta-analyses were published to assess the association between GSTT1 null genotype and prostate cancer risk, but both failed to find a significant association [9,62] ( Figure 4). Compared with those two meta-analyses, our metaanalysis provides several new findings. Our meta-analysis includes much larger participants and more new studies (43 studies, 9, 934 cases and 16, 459 controls) and is the largest meta-analysis of the association between GSTT1 null genotype and prostate cancer risk. The present meta-analysis has much greater power to detect the real association, and draw a more precise and reliable conclusion. The pooled results in our meta-analysis suggests a significant association between GSTT1 null genotype and increased risk of prostate cancer, which provides a comprehensive evidence and reliable conclusion for the association above ( Figure 4).
In our meta-analysis, the cases and controls have been recruited through different sources. The control subjects in our metaanalysis are defined as cancer-free, and the BPH patients are also enrolled in many included studies in the meta-analysis. Though there is no obvious association between BPH and prostate cancer, there is also a significant association between GSTT1 polymorphism and BPH and the GSTT1 null genotype frequency is higher in the BPH patients than that in the healthy controls [10]. Our meta-analysis suggest there is no obvious association between GSTT1 null genotype and prostate cancer risk in the subgroup analysis of studies with BPH controls, but there is an obvious association between GSTT1 null genotype and increased risk of prostate cancer in the subgroup analysis of studies with non-BPH controls (Table 2), which indicates this discrepancy in the GSTT1 null genotype frequency between BPH patients and healthy controls may affect the association between GSTT1 null genotype and risk of prostate cancer. Since there is also an obvious association between GSTT1 null genotype and increased risk of BPH, the frequency of GSTT1 null genotype is much higher in the BPH patients than that in the healthy controls [10]. When one case-control study selects the BPH patients as the controls to assess the association between GSTT1 null genotype and prostate cancer risk, the higher frequency of GSTT1 null genotype in the BPH patients may become a major confounding factor and could bias the real estimation of the association between GSTT1 null genotype and prostate cancer risk [10].
GSTs are the most important family of phase II isoenzymes which are known to detoxify a variety of electrophilic compounds including carcinogens, chemotherapeutic drugs, environmental toxins, and DNA products generated by reactive oxygen species damage to intracellular molecules [4,6]. GSTs also play a major role in cellular antimutagen and antioxidant defense mechanisms, and these enzymes may regulate pathways that prevent damage from several carcinogens [4,6]. The null genotype of GSTT1 gene causes complete absence of GST enzymes activity, decreases the ability of detoxifying electrophilic compounds, and may increase the susceptibility to various cancers [7]. Thus, there is obvious biochemical evidence for the relationship of GSTT1 null genotype with prostate cancer risk. Besides, GSTT1 null genotype has also been studied extensively in terms of susceptibility for other malignancies. Previous meta-analyses have yielded significant associations of GSTT1 null genotype with colorectal cancer [63], breast cancer [64], lung cancer [65] and hepatocellular carcinoma [66], which further suggest GSTT1 null genotype plays an important role the carcinogenesis and can affect the host susceptibility to common malignancies.
Some limitations of this study should be acknowledged. Firstly, significant between-study heterogeneity was detected in overall analysis, and subgroup analyses in Caucasians and Africans. There are several aspects could explain the significant heterogeneity: the different proportion of BPH patients in the controls, different definition of control group and ethnicity. In addition, it is known that a shorter androgen signaling pathway exist in these individuals from African population, which contributes to prostate cancer risk and may bias the real estimate of the gene-cancer associations in Africans [67]. Therefore, more studies with estimates adjusting for those known risk factors are needed. Secondly, meta-analysis remains retrospective research that is subject to the methodological deficiencies of the included studies. We minimized the likelihood of bias by developing a detailed protocol before initiating the study, by performing a meticulous search for published studies, and by using explicit methods for study selection, data extraction, and data analysis. Thirdly, some misclassification bias is possible. Most studies could not exclude latent prostate cancer cases in the control group. Finally, we could not address gene-gene and gene-environmental interactions. The latter may be important for genes that code proteins with detoxifying function, but would require detailed information on exposures to various potential carcinogens and individual-level data and would be most meaningful only for common exposures that are found to be strong risk factors for the disease.
In conclusion, this study is, to the best our knowledge, the largest meta-analysis of the association between GSTT1 null genotype and prostate cancer risk. This meta-analysis demonstrates that GSTT1 null genotype is associated with prostate cancer susceptibility, and GSTT1 null genotype contributes to increased risk of prostate cancer.


Post-cancer Treatment with Condurango 30C Shows Amelioration of Benzo[a]pyrene-induced Lung Cancer in Rats Through the Molecular Pathway of Caspa- se-3-mediated Apoptosis Induction

Objectives: The present investigation aimed at examining if post-cancer treatment with a potentized homeopathic drug, Condurango 30C, which is generally used to treat oesophageal cancer, could also show an ameliorating effect through apoptosis induction on lung cancer induced by benzo[a]pyrene (BaP) in white rats (Rattus norvegicus). Methods: Lung cancer was induced after four months by chronic feeding of BaP to rats through gavage at a dose of 50 mg/kg body weight for one month. After four months, the lung-cancer-bearing rats were treated with Condurango 30C for the next one (5th), two (5th-6th) and three (5th-7th) months, respectively, and were sacrificed at the corresponding time- points. The ameliorating effect, if any, after Condurango 30C treatment for the various periods was evaluated by using protocols such as histology, scanning electron microscopy (SEM), annexinV-FITC/PI assay, flow cytometry of the apoptosis marker, DNA fragmentation, reverse transcriptase-polymerase chain reaction (RT-PCR), immunohistochemistry, and western blot analyses of lung tissue samples. Results: Striking recovery of lung tissue to a near normal status was noticed after post-cancerous drug treatment, as evidenced by SEM and histology, especially after one and two months of drug treatment. Data from the annexinV-FITC/PI and DNA fragmentation assays revealed that Condurango 30C could induce apoptosis in cancer cells after post-cancer treatment. A critical analysis of signalling cascade, evidenced through a RT-PCR study, demonstrated up-regulation and down-regulation of different pro- and anti-apoptotic genes, respectively, related to a caspase-3-mediated apoptotic pathway, which was especially discernible after one-month and two- month drug treatments. Correspondingly, Western blot and immunohistochemistry studies confirmed the ameliorative potential of Condurango 30C by its ability to down-regulate the elevated epidermal growth factor receptor (EGFR) expression, a hallmark of lung cancer. Conclusion: The overall result validated a positive effect of Condurango 30C in ameliorating lung cancer through caspase-3-mediated apoptosis induction and EGFR down-regulation.

Introduction
Lung cancer is a leading cause of death worldwide. Among different types of lung cancers, non-small-cell lung cancer (NSCLC) is the most common type (85%) [1]. Cigarette smoking is the primary cause of lung cancer. Benzo[a]pyrene (BaP) is a prototype of the polycyclic aromatic hydrocarbons (PAHs) found in cigarette smoke; it induces lung tumors [2]. BaP can increase cell proliferation and DNA adduct formation to induce lung cancer [3]. Surgical resection is the only treatment for patients with stage I or II NSCLC whereas patients with later stages are treated with combinations of surgery, chemotherapy, and radiation therapy, all of which have significant side effects [4]. Apart from conventional therapies, complementary and alternative medicines (CAMs) are now being used to combat cancer because of their lesser toxic side effects [5]. Homeopathic medicines are being used as major alternatives for various ailments, including cancer. Earlier we reported the anti-cancer potentials of different potentized homeopathic drugs like Chelidonium 30C and Lycopodium 30C in ameliorating hepato-carcinogenesis in mice [6,7] and of Lycopodium 5C and 15C against HeLa cells in vitro [8]. Most anti-cancer therapeutic agents exert their effect by inducing apoptosis, necrosis, and/or autophagy in cancer cells [9]. Apoptosis is characterized by several cellular changes, including formation of plasma membrane blebbing, chromatin condensation and DNA fragmentation. The members of the Bcl-2 family are central regulators of the intrinsic apoptotic pathway that governs mitochondrial outer membrane permeabilization, the release of cytochrome-c, and the activations of apaf-1, caspase-9, -3, and poly (ADP-ribose) polymerase (PARP) [10]. The homeopathic drug Marsdenia condurango (commonly called Condurango) is generally used against esophageal cancer [11]. Dried bark is the main source for Condurango ethanolic extracts. Condurango was first introduced to treat stomach cancer and syphilis in the United States in 1871 [12], but no detailed reports on the efficacy of the homeopathic drug Condurango and its potentized forms for treating neoplastic lung cancer exist. Hence, the present study was undertaken to examine if the potentized form of Condurango, Condurango 30C, could induce apoptotic cell death in BaP-induced lung cancer in rats in vivo.

Experimental animals
Inbred healthy white Wistar rats (Rattus norvegicus) weighing between 80 g and 90 g were reared in the animal house of the Department of Zoology, Kalyani University, West Bengal, India, under proper hygienic condition in polypropylene cages (temperature: 24 ± 2℃; humidity: 55 ± 5%; 12-h light/dark cycles) and were allowed free drinking water and basal diet ad libitum. Ethical clearance was obtained from the Institutional Ethical Committee, University of Kalyani.

Study design
A randomized set of 42 rats was used for each time-point. Each set of rats was sub-divided into 7 different groups consisting of 6 rats in each group: Group 1, Normal: animals received food and water ad libitum without any supplementation, Group 2, olive-oil fed: animals received normal food and water supplemented with olive oil (solvent of BaP), Group 3, placebo fed: normal animals received a drug vehicle (30% ethyl alcohol as a placebo) orally once daily for 1, 2 and 3 months, respectively, after cancer development in BaP-fed rats, Group 4, only drug-treated: normal animals received Condurango 30C orally once daily for 1, 2 and 3 months, respectively, after four months of cancer development, Group 5, Carcinogen (BaP)-treated: animals received BaP orally 2 days (Tuesday and Friday) a week for 1 month and then a normal diet and water, Group 6, BaP+placebo-treated: animals received a placebo orally once daily for 1, 2 and 3 months, respectively, after development of lung cancer, Group 7, BaP+Condurango 30C-treated: animals received Condurango 30C orally once daily for 1, 2 and 3 months, respectively, after development of lung cancer. The experimental data were collected after 1 (5 th ), 2 (6 th ) and 3 (7 th ) months to investigate the possible efficacy of Condurango 30C. At the ends of the experimental periods, the animals were sacrificed humanely by cervical dislocation.

Preparations and administrations of BaP and Con-
durango 30C BaP (dissolved in olive oil) at a dose of 50 mg/kg body weight was fed to each rat through gavage [4]. Condurango 30C was supplied by Boiron Laboratory, Lyon, France.
One ml of Condurango 30C was diluted with 20 ml of double-distilled water to make the stock solution, and each rat was fed 0.06 ml orally from the stock at a time with the aid of a fine pipette [13].
2.4. Scanning electron microscopy (SEM) and histology of lung Lung samples were fixed with 2.5% glutaraldehyde, dehydrated with graded acetone (50%-100%) and observed by using an S530-Hitachi SEM instrument (Department of University Science Instrumentation Centre, Burdwan University) after gold coating [14]. Formalin-fixed lung sections (5µm) from each group were stained with hematoxylin-eosin double staining [15] and were evaluated by using a light microscope.
2.5. Lung cell perfusion, annexinV-FITC/PI, DNA fragmentation, and caspase-3 activation assays The lung tissues were minced within 2% Roswell Park Memorial Institute-1640 media (Himedia, India), and the lung epithelial cells were flushed gently using a hypodermic syringe. The media-containing cells were spun down at 1,000 G, and the supernatant-containing lung epithelial cells were used for further study [14].
The rate of apoptosis of the perfused cells (3 x 10 7 cells/ well) was assessed by using AnnexinV-fluorescein isothiocyanate/propidium iodide (FITC/PI) through flow cytometry (FACS Callibur, BD Bioscience, USA) [16]. DNA was extracted by using the conventional phenol-chloroform method, was separated in 2% agarose gel and was visualized under an UV transilluminator. Perfused lung cells were incubated with caspase-3 primary and FITC-tagged secondary antibodies (Santa Cruz Biotechnology, USA). Caspase-3 (Cas-3) activity was analyzed by using flow cytometry (Callibur, BD Bioscience, USA).

Preparation of lung and liver tissue homogenates
and semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) Lung and liver tissues were homogenized, and homogenates were collected after centrifugation [16]. Total RNA was extracted from each lung by using trizol (Himedia, India), and expressions of different apoptotic genes were analyzed by using semi-quantitative RT-PCR [17]. The primer sequences are presented in Table 1. The band intensities were analyzed densitometrically by using Image J software (Germany).  Rev 5'-GCCAGTAGAGGCAGGGATGATGTTC-3' 2.7. Localization of protein distribution by immunohistochemistry and analysis of protein expression by using a Western blot An immunohistochemical study was performed [18] with caspase-3 and epidermal growth factor receptor (EGFR) primary antibodies and HRP-conjugated secondary antibodies (Santa Cruz Biotechnology, USA). Haematoxylin was used to counterstain for observation under a light microscope (Leica, Germany). The expressions of EGFR and PARP1 were analyzed by using Western blots [16]. The band intensities were analyzed densitometrically by using Image J software (Germany).

Statistical analysis
Data were analyzed, and the significance of the differences between the mean values was determined by using the one-way analysis of variance (ANOVA) with Fisher's least significant difference (LSD) post-hoc tests with the SPSS 14 software (SPSS Inc, Chicago, IL, USA). Statistical significance was considered at *P < 0.05.

SEM and histology of lung
The typical tissue arrangement was observed in the normal lung, but architectural distortion of the pulmonary microvasculature with narrow alveolar spaces was observed in a cancerous lung, which gradually increased with time. Noticeably, alveolar spaces gradually became broader, specifically at the 5 th and the 6 th month fixation intervals of drug treatment, thus indicating the tissue damage-repair activity of Condurango 30C (Figs. 1A, B, C).

AnnexinV-FITC/PI assay
Apoptotic cell death is accompanied by surface exposure of phosphatidylserine (PS) in the plasma membrane, which can be detected by using AnnexinV. Fig. 2A-1 reveals a time-dependent increase of apoptosis, especially at the 5 th and the 6th month fixation intervals. Percentages of cells are shown in Fig. 2A-2 table. Standard deviations ( Fig.  2A-3) of early and late apoptosis clearly demonstrate the percentages of cells that undergo apoptosis.
3.3. DNA fragmentation DNA-smearing was found in cancerous lung samples at the three-month time point. However, a gradual increase in DNA fragmentation was observed in drug-treated groups, especially at the 5 th and the 6 th month intervals, indicating the cells' journey towards apoptosis (Fig. 2B). Fig. 3A shows an increased level of caspase-3 after post-cancerous-drug treatment, specifically at the 5 th and the 6 th month intervals, which may suggest that a timebound action of the drug to increase the caspase-3 activation in cancerous lungs remains maximal, at least, in the first two-month interval, to trigger apoptosis. The standard deviation of the caspase-3 activation (Fig. 3B) supports the conclusion stated above.

Caspase-3 activation
3.5. Semi-quantitative RT-PCR and localization of protein distribution by immunohistochemistry RT-PCR results confirmed a significant difference in the expressions of different pro-and anti-apoptotic genes between normal and cancerous and between cancerous and drug-treated groups, especially at the 5 th and the 6 th month time points. (Figs. 4A, B, C). Appearance of caspase-3, indicated by black spots in drug treated sections, demonstrated caspase-3-mediated apoptosis induction, especially at the 5 th and the 6 th month intervals (Fig. 5A). EGFR is normally over-expressed in 80% NSCLC [19]. Figure 5B clearly shows a decreased level of EGFR expression after drug treatment, especially at the 5 th and the 6 th months, but a dramatic increase at the 7 th month, indicating that the drug did not ameliorate cancerous progression during the last month interval, possibly due to excessive growth of lung tumors.

Protein expression by-Western blot
We found a more decreased expression of EGFR in drug-treated lung proteins than in cancerous samples, especially at the 5 th and the 6 th month fixation intervals, which supported the immunohistochemical data. Thus, Condurango 30C further proved to have anti-EGFR activity in NSCLC by inhibiting uncontrolled cell growth (Figs. 6A, B, C). The increased expression of PARP1 is indicative of cells undergoing apoptosis (Figs. 6A, B, C). At the 6 th month interval of drug treatment, although the PARP1 expression was slightly low, formation of PARP1 cleavage further supported the apoptosis-inducing activity of the drug in vivo.

Discussion
The ultra-highly-diluted remedies, particularly those exceeding Avogadro's limit, have been claimed [20] to have beneficial and curative effects against disease/disease symptoms. Therefore, the positive effects against cancer found in this study are very important. Further, the remedy demonstrates sufficient efficacy when administered after the complete development of cancer in an animal model. The hallmark of most anti-cancer drugs is the induction   Figure 2 (A-1) Flow cytometric analysis of perfused lung cells by using annexin V-FITC/PI. (i) normal, (ii)-(iv) BaP-induced lung cancer at 5 th , 6 th and 7 th month intervals (Cancer1, Cancer2, Cancer3) and (v)-(vii) BaP + Condurango 30C treated groups at 5 th , 6 th and 7 th month intervals (30_1, 30_2, 30_3), respectively. Live cells are denoted as 'Live' , early apoptosis is denoted by 'Early' , late apoptosis is signified by 'Late' and PI positive cells (dead cells) is denoted by Q1. FL1H-filter of annexin V -FITC and FL2H-filter of PI. Table (2A-2) and graphical representation (2A-3) below give the apoptosis percentages. (B) DNA fragmentation of rat lung DNA of different groups. (i) Fragmented DNA (L3) occurred after Condurango-30C treatment at 5 th month interval, whereas cancerous DNA sample (L2) became slightly smeared. (ii) Representation of the increase in the DNA fragmentation (L5) after Condurango-30C treatment at the 6 th month interval, whereas the cancerous DNA (L4) showed increased smearing. (iii) A slight decrease in the DNA fragmentation (L7) after Condurango-30C treatment with increased smearing of cancerous DNA (L6) at the 7 th month interval. L1-is normal DNA. Immunohistochemical studies of (A) caspase-3 and (B) EGFR: (A) (i) normal lung section, (ii)-(iv) BaP-induced lung sections at 5 th , 6 th and 7 th month intervals, respectively, where caspase-3 expression was not found, (v)-(vii) Condurango-30C-treated lung sections at 5 th , 6 th and 7 th month intervals, respectively, where the caspase-3 localization was found, especially at 5 th and 6 th month intervals, indicated by black spots with arrows; (B) (i) normal lung section, (ii)-(iv) BaP induced lung sections at 5 th , 6 th and 7 th month intervals, respectively, where EGFR over-expression was clearly visible (denoted by black spots with arrows), and (v)-(vii) Condurango-30C-treated lung sections at 5 th , 6 th and 7 th month intervals, respectively, where the downregulation of EGFR was found, especially at 5 th and 6 th month time-points. (C) L6-cancer and L7-Condurango-30C-treated (after 7 th month). The relative band intensities shown in the histograms are averages ± SDs; n = 6. Significance *P < 0.05 normal vs. cancer (5 th (A), 6 th (B) & 7 th (C) month intervals) and normal vs. Condurango-30C treatment (5 th , 6 th & 7 th month intervals); † P < 0.05 cancer (5 th , 6 th & 7 th month intervals) vs. Condurango-30C treatment (5 th , 6 th & 7 th month intervals).
A B C of apoptosis in cancer cells, which are otherwise immortal and ever-growing in nature. However, most anti-cancer drugs used in orthodox therapy are highly toxic and have undesirable side effects, largely precluding their use in all cancer patients. Therefore, any drug that can be used in a low and tolerable dose without any side-effects is highly sought in cancer therapy because it can also be used as a supportive therapy if needed. Herein lies the novelty of this ultra-highly-diluted remedy that also demonstrated an unquestionable ability to induce apoptosis in cancer cells with positive recovery of cancerous lungs back to their near normal states in rats, particularly at the 5 th and the 6 th month intervals. The present study seems to be the first one that convincingly demonstrates the anticancer potentials of Condurango 30C in BaP-induced lung cancer in rats through a multitude of scientific protocols. The recovery due to post-treatment with Condurango 30C in this study was quite remarkable.
One of the hallmarks of apoptosis is internucleosomal DNA breakdown or fragmentation. Formation of DNA laddering suggested the ability of Condurango 30C to induce apoptosis, which was further supported by An-nexinV-FITC/PI dual staining data, especially at the 5 th and the 6 th month fixation intervals. Multiple apoptotic stimuli trigger caspase-3 activation, which initiates and executes apoptosis. Our experimental data support the activation of caspase-3 based on flow cytometry, RT-PCR and immunohistochemical analysis after post-cancerous drug treatment, and represent a positive signal towards caspase-3-mediated apoptosis. The key events involved in caspase-3-mediated apoptosis are up-regulation of Bax and down-regulation of Bcl2 [21]. Increased and decreased expressions of Bax and Bcl2, respectively, lead to loss of mitochondrial membrane potential (MMP), which induces apoptosis via cytochrome-c release. RT-PCR analysis indicates decreased Bcl2 and increased Bax levels after treatment with Condurango 30C, especially at the 5 th and the 6 th month intervals. Furthermore, Condurango 30C treatment leads to the activation of cytochrome-c, caspase-3, caspase-9, apaf-1 and PARP1, especially at the 5 th and the 6 th month intervals. PARP1 is important to trigger apoptosis in the caspase-3-mediated pathway. Increased levels of PARP1 were found at the 5 th and the 6 th month fixation intervals, especially the formation of PARP1 cleavage at the 6 th month, depicting further that the cells were undergoing apoptosis. EGFR expression was found to be elevated in cells undergoing proliferative activities, particularly during development of a lung tumor [19]. However, in this study, Condurango 30C inhibited EGFR expression at the 5 th and the 6 th month of post-cancerous treatment, further lending support to its anti-proliferative activity.

Conclusion
Thus, Condurango 30C activated a caspase-3-dependent apoptotic pathway in BaP-induced lung cancer in rats, validating the hypothesis of Khuda-Bukhsh [22-23] that potentized homeopathic drugs could act at the molecular level of gene expression as a very probable means to remove disease symptoms.


extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Chemistry

text:
Holographic Quantitative Structure-Activity Relationships of Tryptamine Derivatives at NMDA, 5HT1A and 5HT2A Receptors

Tryptamine derivatives (Ts) were found to inhibit the binding of [3H]MK-801, [3H]ketanserin and [3H]8-OH-DPAT to rat brain membranes. [3H]MK-801 labels the NMDA (N-methyl-D-aspartate) receptor, a ionotropic glutamate receptor which controls synaptic plasticity and memory function in the brain, whereas [3H]ketanserin and [3H]8-OH-DPAT label 5HT2A and 5HT1A receptors, respectively. The inhibitory potencies of 64 Ts (as given by IC50 values) were correlated with their structural properties by using the Holographic QSAR procedure (HQSAR). This method uses structural fragments and connectivities as descriptors which were encoded in a hologram thus avoiding the usual problems with conformation and alignment of the structures. Four correlation equations with high predictive ability and appropriate statistical test values could be established. The results are visualized by generation of maps reflecting the contribution of individual structural parts to the biological activities.

Introduction
Ionotropic glutamate receptors are responsible for glutamate-mediated excitatory transmission in mammalian brain [1,2]. 5HT 2A and 5HT 1A receptors are probably the most prominent subtypes of the OPEN ACCESS exuberant family of serotonin receptors. Several modeling studies have dealt with these two targets [3][4][5][6][7][8][9][10], most of them based on SAR considerations by using solely synthetic drugs as ligands. Until now structural variants of the natural ligand 5-OH-tryptamine were not investigated in great detail. In this work, potencies of tryptamine derivatives (Ts) as inhibitors of [ 3 H]MK-801 [11] binding (in the absence or presence of a stimulating spermine concentration) and as inhibitors of [ 3 H]ketanserin [12], and [ 3 H]8-OH-DPAT [13] binding to rat brain membranes were used to generate and evaluate holographic quantitative structure activity relationship (HQSAR) models.
The fragment-based HQSAR turned out to be a promising tool for establishing a relationship between the structure of a compound and its biological activities. It is a modern QSAR technique that requires no explicit 3D information for the ligands (e.g., structure, physicochemical descriptors, conformation and molecular alignment) [14]. As it is done with 3D-QSAR techniques, such as CoMFA and CoMSIA, HQSAR as well could easily and rapidly generate QSAR models with high predictive value for both small and large data sets [15].

Results and Discussion
Basically, this analysis involves three main steps: (1) generation of structural fragments for each T; (2) the encoding of these fragments into a molecular hologram; (3) the statistical generation of PLS QSAR models [16]. In our studies, the influence of the fragment distinction parameters on the statistical values of our models was investigated. Thus, several combinations of fragment parameters were considered during the QSAR modeling runs.

HQSAR of Ts as Inhibitors of [ 3 H]MK-801 Binding
A set of 64 Ts were used to establish a HQSAR model for the inhibition of [ 3 H]MK-801 binding. The optimum number of components was selected for each fragment parameter combination. We have calculated 63 parameter combinations. Only a set of six combinations is given in Table 1 (the others show less significant results).
The donor & acceptor parameter (model 6) seems to play a certain role for inhibitory activity, while hydrogen atoms (model 4) and chirality (model 5) show a small q 2 . By adding more fragment parameters to the model, continuously further improvements were observed (models 15, 28, 50, 58, 63). Model 63, based on a combination of all fragments gave the best result (q 2 = 0.632 and r 2 = 0.855). This model was derived using six fragment distinctions, with six being the optimum number of PLS components. The plot of pIC 50 values of all molecules predicted by model 63 versus experimental values is shown in Figure 1A. As can be seen, the predicted values are in good agreement with experimental values thus entailing a model with good correlative and predictive abilities.
The HQSAR-based fragmentation of a molecule into atoms allows to evaluate which of them are correlated with the biological activity of the molecule. HQSAR models can be graphically represented in the form of contribution maps where the color of each molecular fragment reflects the contribution of an atom or a small number of atoms to the activity of the molecule under study. The colors at the red end of the spectrum (i.e., red, red-orange, and orange) reflect unfavorable (negative) contributions, while colors at the blue end (i.e., yellow, green-blue and blue) indicate favorable (positive) contributions. Atoms with intermediate contributions are colored in white. The common backbones are colored cyan.   Table 2).
A red color code at position 5 was returned for compounds without substituent at this position: thus, there is an obvious demand for an appropriate substitution at this particular carbon (compound 1). Methyl groups at positions 6, 7, α or N, respectively, are strongly disfavored. Several 2-Me-Ts with different alkyl substituents at position 5 (compounds 19-22) contribute favorably to activity as indicated by the green and yellow color (compound 20 being the most potent, Figure 2A). Halogen substituents as well, especially fluorine (compound 47), are positively contributing to the activity. On the other hand, hydroxy-or methoxy-substituents exert a weak to strong negative contribution. For instance, compound 40, the least active compound of the series, carries a hydroxyl group at position 5 and a methyl group at position α, a highly unfavorable substituent pattern ( Figure 2C).  Figure 2B) are positively contributing to activity. These results imply that electronegative substituents at position 5 and 7 enhance activity. Compound 43, being one of the least active compounds, carries methyl groups at positions 2, 4 and 7. The decisive negative influence comes from the methyl group at position 7 ( Figure 2D).

HQSAR of [ 3 H]MK-801 Binding in the Presence of Spermine
As reported previously [17] the polyamine spermine reduces the potency of most Ts as inhibitors of [ 3 H]MK-801 binding. This effect may involve the recently described GluN1/GluN2B interface mediating polyamine stimulation of the NMDA receptor [18]. We have calculated 63 parameter combinations. Only a set of 6 combinations is given in Table 2 (the others show less significant results).
In an effort to obtain the best model, combinations of different fragments were considered. The parameter hydrogen atoms (model 4) and chirality (model 5)   The fragment contribution pattern in the presence of spermine is similar to that in its absence. The same model 63 proved as the best one. While it was remarkable that in the presence of spermine substituents in position 5 were less advantageous than without spermine (especially in the case of substituents larger than methyl, see compounds 14, 16, 20, 22, 23, 25, 29), all these attenuated IC 50 values were above 10 µM, more than 2/3 even above 100 µM. Therefore, it may not be justified to elaborate on these results in any more detail.

HQSAR of Ts as Inhibitors of [ 3 H]ketanserin Binding
We have calculated 63 parameter combinations for the 64 Ts as inhibitors of [ 3 H]ketanserin binding. Only a set of seven combinations is given in Table 3 (the others show less significant results).  Figure 3A.   Table 4).
A fragment contribution pattern including substituents in positions 1, 4 or 5 was favorable for high activity. A methyl substitution at the positions 6 and 7 was less advantageous, resulting in red and orange color coding (e.g., compound 42, Figure 4D). However, combined substitution at positions 4, 5, 6 or 7 with methyl and halogen is tolerated. Substituents like CN, OH, OMe and CONH 2 at position 5 are strongly disfavored (compound 29, Figure 4C), while a halogen substituent at this position (i.e., compound 14, Figure 4A) moderately contributed to activity. As we mentioned previously, also in this case the lack of coloring in A (Figure 4) it due to a slight advantage compared to compound 2 (orange in position 2 and 7). Combined with a 2-methyl substituent, halogens at positions 4, 5, 6 and 7 improve the inhibitory activity. Moreover, combined with 2-Me-substituted Ts alkyl groups can be at positioned at carbon 5 but not at carbon 7. The fragment contributions to the activity of molecule 53 (the most potent at this target) is displayed in Figure 4B.

HQSAR of Ts as Inhibitors of [ 3 H]8-OH-DPAT Binding
We have calculated 63 parameter combinations for 47 Ts as inhibitors of [ 3 H]8-OH-DPAT binding. Only a set of six combinations is given in Table 4 Figure 3B. Mono-alkylation (each position possible) has not much influence on activity. Two-and three-fold methyl-substituted derivatives, however (compound 19 and 45, Figure 5C,D) exhibit reduced activity.

Data Set
Several Ts inhibit at micromolar concentration the four binding sites (5-HT 2A site, 5-HT 1A site, NMDA channel and polyamine-modulated NMDA channel). The affinities of 64 Ts (from sources as described [19]) at the NMDA channel were obtained from the inhibition of specific binding of the radioligand [ 3 H]MK-801 (5 nM) to membranes prepared from hippocampal and parietal cortex of male Wistar rats. As reported previously [17], the potency of most Ts as inhibitors of [ 3 H]MK-801 binding was reduced by the polyamine spermine (10 mM Tris acetate buffer pH 7.0, 30 µM spermine). The affinities at 5-HT 2A receptors were obtained from the inhibition of specific binding of [ 3 H]ketanserin (1 nM) to rat prefrontal cortex membranes. In addition, 47 Ts were tested at 5-HT 1A receptors, as inhibitors of [ 3 H]8-OH-DPAT binding (1 nM) to rat hippocampal membranes. Chemical structures together with experimental inhibition potencies are listed in Table A (see appendix).
At the chosen neutral pH, all Ts were in the protonated form. Concentrations of Ts providing 50% inhibition (IC 50 values) were transferred to the corresponding pIC 50 (-log IC 50 ) values and used as dependent variables in the HQSAR analysis. In our previous work [19], we published an extended description of the data set together with the discussion of detailed pharmacological investigations.

HQSAR Analysis
The HQSAR modeling analyses, calculations and visualizations were performed using the SYBYL-X 1.0 package (Tripos Inc., St. Louis, MO, USA). HQSAR is a technique which employs fragment fingerprints as predictive variables of biological activity. These molecular fingerprints are broken into strings at fixed intervals as specified by the hologram length. The generation of the molecular fragments was carried out using several combinations of the following fragment distinction parameters: atoms (A), bonds (B), connections (C), hydrogen atoms (H), chirality (CH), and donor & acceptor (DA). Several combinations of these parameters were considered using fragment size of default 4-7. Each unique fragment in the data set is assigned a large positive integer by means of a cyclic redundancy check (CRC) algorithm. Each integer corresponds to a bin in an integer array of fixed length L (usually within 12 default hologram lengths of 53, 59, 61, 71, 83, 97, 151, 199, 257, 307, 353, and 401 bins). Thus, all generated fragments are hashed into array bins in the range of 1 to L. This array now constitutes a molecular hologram, the bin occupancies being the descriptor values. The following standard PLS analysis identifies a set of explanatory variables [20][21][22].

Conclusions
By using the holographic QSAR method, four correlation equations with high statistical quality and predictive value could be established. The visualization of the results by contribution maps with special color codings reflects, which combinations of molecular fragments are essentially contributing to the recognition of the NMDA and two 5-HT receptors by Ts.