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Sequence diversity on four ORFs of citrus tristeza virus correlates with pathogenicity

The molecular characterization of isolates of citrus tristeza virus (CTV) from eight locations in Mexico was undertaken by analyzing five regions located at the opposite ends of the virus genome. Two regions have been previously used to study CTV variability (coat protein and p23), while the other three correspond to other genomic segments (p349-B, p349-C and p13). Our comparative nucleotide analyses included CTV sequences from different geographical origins already deposited in the GenBank databases. The largest nucleotide differences were located in two fragments located at the 5' end of the genome (p349-B and p349-C). Phylogenetic analyses on those five regions showed that the degree of nucleotide divergence among strains tended to correlate with their pathogenicity. Two main groups were defined: mild, with almost no noticeable effects on the indicator plants and severe, with drastic symptoms. Mild isolates clustered together in every analyzed ORF sharing a genetic distance below 0.022, in contrast with the severe isolates, which showed a more disperse distribution and a genetic distance of 0.276. Analyses of the p349-B and p349-C regions evidenced two lineages within the severe group: severe common subgroup (most of severe isolates) and severe divergent subgroup (T36-like isolates). This study represents the first attempt to analyze the genetic variability of CTV in Mexico by constructing phylogenetic trees based on new genomic regions that use group-specific nucleotide and amino acid sequences. These results may be useful to implement specific assays for strain discrimination. Moreover, it would be an excellent reference for the CTV situation in México to face the recent arrival of brown citrus aphid.

Background
Citrus tristeza virus (CTV) is a destructive pathogen that causes the most important disease of citrus. CTV is phloem-limited and naturally transmitted by several species of aphids in a semipersistent mode and by the use of infected propagative budwood [1].
CTV infects almost all citrus species, including hybrids and relatives, causing different range of symptoms depending on the host and virus strain. The most common symptoms are: quick decline (QD) or death of most citrus species propagated on the sour orange (Citrus aurantium L.) rootstock; stem pitting (SP) of the scion that reduces the yield and fruit quality of some citrus varieties regardless of the rootstock; and seedling yellows which is seen on sour orange, lemon (Citrus lemon (L.) Burn. f.) and grapefruit (Citrus paradisi Macf.). Strains that not elicit symptoms on commercial citrus hosts have been named as mild isolates [2].
Citriculture represents a very important activity in Mexico where 517,000 has. are grown in several agroecological regions yielding 7.1 million tons of fruit [3]. CTV was first detected in the Mexican State of Tamaulipas in 1983. Extensive survey in the major citrus growing regions indicated (up to 2006) that CTV incidence was low (< 1%) in other 17 States of Mexico. Because of the random pattern of the infected trees, CTV infection was probably propagated in Mexico by the use of infected budwood, rather than by aphid vectors [4]. In general, the trees remain asymptomatic, without declining suggesting a possible prevalence of mild strains. However, Mexican citrus industry is now facing a real and immediate threat due to: i) the recent introduction to Mexico of the most efficient vector of CTV, commonly called brown citrus aphid (BCA), Toxoptera citricida and ii) the predominance of sour orange as rootstock (the most susceptible to CTV) in almost the totality of the citrus groves. Despite the importance of CTV, there is a lack of knowledge about the genetic diversity of CTV in Mexico. Therefore, the objective of this study was to determine the molecular variability of CTV isolates collected in eight of the major citrus growing areas in Mexico, before the spreading of the BCA.

Biological characterization of the CTV isolates
Symptoms of CTV isolates varied in their severity and ranged from a severe SP observed in the isolates Mx-Tam and Mx-BC (Mexican lime on C. macrophylla) to those as Mx-Yuc and Mx-QR, which showed a mild vein clearing in Mexican lime. Incipient SP and vein clearing were observed for Mx-Mich, Mx-NL, Mx-Col, Mx-Ver and Mx-QR. When sour orange was used as rootstock, a gradual declining occurred for the Mx-Tam isolate associated to pinholing or honeycombing below the bud union.

Phylogeny and genetic variability in CTV isolates
The nucleotide sequences of five regions of the CTV genome were determined. They are situated at the oppo-site ends covering around the 20% of the CTV genome. These DNA fragments include two fragments of the p349 ORF located at the 5'end of the genome: p349-B (nucleotides 1460 to 2350) and p349-C (nucleotides 6870 to 7900) and the ORFs CP, p23 and p13 (located at the 3' end).
Alignments of these genomic regions indicated that variations at nucleotide level were simple nucleotide changes. Overall similarities for the five regions among CTV Mexican isolates ranged from 71.2 to 100% at the nucleotide level; however, the sequences of these strains clustered into two groups that were highly homologous (92.1-100% identical nucleotides and 92.9-100% identical amino acid) such as Mx-Mich, Mx-Ver, Mx-QR, Mx-NL, Mx-Yuc and Mx-Col and less homologous sequences (71.2-96.7% identical nucleotides and 71.6-96.4% identical amino acid) such as Mx-Tam and Mx-BC (data not shown).
The neighbour-joined method of Clustal × program was used to generate phylogenetic trees for each ORF including the following full length CTV sequences: T36 [5] and T30 from Florida [6], VT from Israel [7], T385 from Spain [8], SY568 from California [9] and NUagA from Japan [10]. In order to compare our five amplified regions as individual ORFs, sequences from regions p349-B and p349-C were combined and named as p349-B/C. The phylogenetic trees were topologically similar for all the ORFs. A very consistent and defined cluster was observed with a bootstrapping over 990, which included the highly homologous Mexican isolates (Mex-QR, Mex-Mich, Mex-NL, Mex-Col, Mex-Ver and Mex-Yuc) as well as isolates T30 and T385 (figure 1). Despite the distant geographical origin of the isolates, they all induced mild symptoms on indicator plants and only mild stem pitting on the Mexican lime.
On the other hand, CTV Isolates Mex-Tam, Mex-BC, NUagA, VT, SY568 and T36, which induced severe symptoms, showed a more disperse phylogenetic distribution (figure 1). The comparative analysis revealed that both severe Mexican isolates Mx-Tam and Mx-BC, tended to be clustered away from the group formed by NUagA, VT and SY568, although not enough to be considered a separate cluster. Similar clustering was obtained using the predicted amino acid sequences (data not shown).
The calculated sequence diversity for the mild cluster was almost the same for the five analyzed regions ranging from 0.002 to 0.022. On the contrary, the severe cluster showed an increased diversity especially toward the 5'end of the genome (CP < p23 < p13 < p349-B < p349-C) (table  1).  Interestingly, two observations could be emphasized for the p349 gene. First, the genomic regions p349-B and p349-C showed the greatest diversity (0.143 and 0.169, respectively), twice as much as the one for CP, p13 and p23. Second, the T36 isolate remained separated in the phylogenetic tree for p349-B/C region. When the genetic distances were calculated for the severe group excluding the T36 isolate, it showed little variation for CP, p13 and p23, but it diminished two-fold p349-B (0.233 to 0.143) and for p349-C (0.276 to 0.120) (data not shown). The marked increase in the genetic diversity given by the T36 isolate suggests the presence of two lineages within the severe group.
To further analyze this possibility, a 280-nucleotide fragment from p349-B region (nucleotides 3333 to 4000) was compared for 44 CTV isolates which nucleotide sequences and biological behaviors had been previously reported [11]. Topology of the phylogenetic trees constructed from sequences alignments (for nucleotide as well as for amino acid residues) was similar to those observed for the p349-B/C. In this case, the T36 isolate considerably diverged forming an additional cluster with other two severe CTV isolates (T734 and T346) (data not shown). Another phylogenetic tree confirmed the divergence of the selected CTV isolates into three groups according to the severity level: one contained the 30 isolates (mild group), a second contained the previously reported five severe isolates and other ten more (severe common group), and a third one contained severe isolates which were located in the same branch along with T36 isolate (severe divergent group). Within-and between-groups nucleotide diversity analyses indicated that all mild isolates had a very low average intra-group genetic diversity (0.013) while the severe groups showed values up to seven times higher than the mild isolates. The inter-group distances were always higher than within groups. The highest variability (0.633 and 0.584) was observed among the severe divergent group and the other two groups (mild and severe common) respectively, thus confirming that the severe divergent group represents a different CTV genotype (table 2).
Additionally, clones obtained from five Mexican isolates belonged to more than one group: mild and severe common groups. This was the case of severe isolates Mx-BC for p349-B and Mx-Tam for p349-C, and mild isolates Mx-Col, Mx-Mich and Mx-NL, illustrating the presence of different sequence variants in their gRNA populations. However, several rounds of amplification, cloning and sequencing were repeated for these isolates and only the consensus nucleotide sequences of the major variants were considered in the analyses.
Similarly, the CP and p23 sequences from 24 and 28 CTV isolates from the GenBank databases were compared, respectively. As a result, the spatial distributions in the phylogenetic trees for CP and p23 were very similar to the observed with only 14 isolates shown in the figure 1. The mild isolates were grouped in a single branch with a high intra-group homology greater than 98% while for the severe isolates this rank was smaller, between 80-85% (data not shown).

Nucleotide and amino acid substitutions of the CTV variants
A further visual examination of the sequences alignments for all the isolates revealed group-specific features that can be used to classify isolates. Group-specific nucleotides could be identified for each ORF and many of them were located on regions p349-C (37.3%), p349-B (32.0%), followed by p23 (20.0%), CP (13.3%) and p13 (10.7%) (table 3). The majority of the sequence polymorphisms corresponded to single changes, and only three putative stretches of nucleotides were observed for the regions p349-C (positions 310-311 and 355-357) and p23 (positions 86-87).
Sequence alignments revealed that 85% of differential nucleotides could be classified in severe isolates (including T36 isolate) and the mild isolates. On the other hand, the 25% of the remainder polymorphisms distinguished the isolate T36 from the others, whether severe common or mild isolates. Most of these T36 typical changes were observed throughout the p349-B and p349-C genomic regions and only two of these types of changes were   (table 3). Finally, there were three nucleotide insertions at positions 153, 369 and 792 in the sequence of T36 for p349-C region (data not shown). Many of these nucleotide substitutions yielding amino acid changes were conserved within each group. From the 34 group-specific amino acid substitutions that were identified, 14 were located in the p349-B (table 4).

Discussion
The genetic diversity of different regions on the genomic RNA of CTV isolates from Mexico was analyzed for the first time. The phylogenetic relationships of CTV have been analized utilizing genomic regions such as CP, p20, p23, p27, p349 (genomic regions A and F), 5'and 3' UTR.
To better understand the diversity among different CTV isolates from Mexico, genes CP, p23, p13, p349-B and p349-C were sequenced. This approach allowed the comparison of the Mexican isolates with those previously reported and also look for additional regions that may be useful to further characterize CTV strains. The regions analyzed here are located at opposite sides of the CTV genome.
To achieve homogeneity in the sequence alignments, the Mexican isolates were compared with six geographical and biologically distinct isolates and whose complete genome sequences are known: a severe quick decline isolate T36 from Florida-USA (Karasev et al., 1995), grapefruit stem pitting and a decline isolate VT from Israel Our results showed that clustering of isolates highly correlates with their symptom severity. The overall branching pattern of the phylogenetic trees based on all regions were highly similar for all the mild isolates, including six of our Mexican isolates, forming a single cluster. The genetic distance analyses based on these segments indicated that the mild isolates were almost identical with a very low genetic diversity intra-group (lower than 0.022) independently from any analyzed ORFs. Such high similarity may be sur-prising since their considerable differences in geographical origin and time of sampling. This high similarity was observed for the first time dissecting the complete consensus sequences of the mild isolates T30 from Florida and T385 from Spain, which were geographically isolated for at least 24 years [12]. However, a different situation was observed for the severe isolates, where the genetic distance had a large range of variation (from to 0.066 to 0.276) and a unique branch could not be identified for them. In this way, the severe isolates were located more dispersed in the trees for all ORFs as opposed to the mild isolates.
The diversity among the severe isolates obtained was not random and the ORF p349, located in the 5'region of the viral genome was twice more variable than those located in the 3' end. The analyses of other two areas located into the ORF p349, region A (nucleotide 2021 to 2548) and region F (nucleotide 3561 to 3998), for 30 CTV isolates from Spain and California, showed appreciable differences because the former showed the greatest diversity (0.136). The values of genetic distance determined by us for the other two regions of p349:p349-B (nucleotides 1460 to 2350) and p349-C (nucleotides 6870 to 7900) were 0.143 and 0.169 respectively and coincide with those reported for the region A [11].
These observations were confirmed by comparing a sequence that covers the final 300 nucleotides of the p349-B region from 44 additional CTV isolates. This nucleotide stretch of DNA was found to be highly conserved in isolates from the same group (mean of 0.076), but highly variable among isolates of different groups (mean of 0.451), which supported the differentiation of CTV isolates for this region into three major genotypes here designed as: mild, severe common (all severe isolates excluding T36 group) and severe divergent isolates (T36like isolates).
Sequences obtained from five Mexican isolates belonged to more than one group. It is possible that when a mixture of mild and severe clones are present in the host at different ratios, disease development can be restricted by a large excess of mild viral genome, even though the diseasecausing variant remains at low levels in the viral populations. Previous reports have extensively demonstrated that most CTV isolates are composed by a population of genetically related variants (haplotypes) that could have origi- a Nucleotide (nuc.) differences in five CTV genomic region among mild isolates (M), severe common isolates (SC) and T36 isolate. Nucleotide positions which resulted in amino acid residue changes are underlined. Only differences between T36 and SC are indicated for T36. S: C or G; M: A or C; B: C or G or T; W: A or T; K: G or T; R: A or G; V: A or C or G; Y: C or T. nated from mixed infection of two or more CTV isolates with diverged sequence variants [13]. Also, the presence of mixed infection should be expected in woody plants that may live many years and are exposed to multiple aphid inoculations [14].
We observed that the nucleotide and amino acid variation were higher for 5' termini than for 3' termini indicating that the former target appears to be better suited to molecular clarification of relationship among CTV strains. In turn, the conserved 3' terminal nucleotide sequences would be insufficient to establish possible sub-groups inside of severe isolates to which the virus belongs.
Our results are in agreement with several reports that suggest a considerable degree of sequence variation in the CTV isolates mostly toward 5' termini of the genome. The sequencing of the 5' untranslated genomic region from eight CTV isolates from Spain and Japan, allowed their classification into three groups, I (severe-like T36), II (severe-like VT) and III (mild) represented by sequences of T36, VT and T317-8 (similar to T385), respectively, with a very low intergroup nucleotide identity ranged between 44 and 66%. This grouping was confirmed by sequencing an additional 15 virus isolates from several countries since all sequences could be assigned to one of the three types previously established [15].
Another report compared the predominant sequence variants of p23 gene from 18 CTV isolates of different geographic origin and pathogenicity . As a result of the phylogenetic analyses, the CTV isolates were separated in three groups: first including the mild isolates, second including the most of severe isolates and third, an atypical group which showed variable pathogenicity. This last group was loosely related and included asymptomatic as well as seedling yellows isolates, maybe as result of recombination events . In that report the intra-group genetic diversity for mild and severe isolates were similar of what we found, confirming that p23 is more heterogeneous that some others ORFs located toward 3' termini as p13 and CP. When we compared the eight Mexican isolates with those 18 reported for p23 [13], the divergence among the CTV isolates was supported for only two clearly distinct groups: mild and severe.
Similar mild genotypes have been found in several countries and led to speculate that this group is well adapted to its host and could have evolved from the same original sequence. As hypothesized, the divergences of the CTV strains could initiated in four possible different progenitors species in South East Asia prior to citrus cultivation [12]. According with this rationale, they spread to different citrus growing areas via infected budwood within the last 200 years. Then, mild strains could be distributed by growers due to the absence of symptoms on the commercial varieties and to the lack of certification programs.
In contrast, severe isolates induce stem-pitting, which affect the plant physiology and therefore reduce vigor and yield and cause eventually the death of the tree [2]. So, the visibly affected trees had been continuously eliminated or not propagated. Probably, like other viruses, the flow and evolution could have been interrupted several times creating successive bottlenecks leading to variability.

Conclusion
This study represents the first attempt to analyze the genetic variability of CTV strains in Mexico. The analysis of eight CTV isolates, originally obtained from Mexican citrus fields, confirms that the CTV has been present in many citrus-producing of Mexico as a mixture of variants with different biological and genetic properties for long time. The divergence found between the isolates Mx-Tam and Mx-BC and also among these two severe isolates and the other six mild isolates plus the relative distant geographical separation of isolates, may suggest that it is unlikely that one strain evolved from the other after arriving to Mexico. It is likely, that the introduction of CTV to Mexico was under independent events an in several occasions to different citrus areas occurred via the use of infected propagative budwood sources.
Taking into account in the recent arrival of the aphid T. citricida to Mexico, the most important vector of CTV, and the predominance of sour orange as a rootstock in almost all the country, this fact should be of great concern for the future of the Mexican citrus industry.
The group-specific genome features identified here would provide a valuable tool for the generation of diagnostic tools for an early discrimination of virus strains based in at least five viral genome regions. Thus, the success of the citrus management strategies could depend in part, of the elucidation of the diversity and evolutionary relationships of the CTV isolates present in the different citrus areas of Mexico.

Virus isolates
Samples from CTV-infected plants were collected by technicians of the Dirección General de Sanidad Vegetal (DGSV), in eight citrus-growing areas of Mexico between 1983 and 2000. CTV isolates were graft-propagated and maintained in insect-proof greenhouses at DGSV headquarters at Mexico City. These isolates were biologically characterized on graft-inoculated indicator plants using different scion/rootstock combinations. Scions included Mexican lime, grapefruit, and sweet orange, whereas Citrus macrophylla and sour orange were used as rootstocks.
Geographic origin and symptoms induced by these CTV isolates are summarized in table 5.

RNA isolation, reverse transcription and polymerase chain reaction (RT-PCR)
Total RNA was extracted using fresh bark tissue from healthy/CTV-infected plants in the presence of Trizol (Invitrogen, Carlsbad, CA) following the manufacturer's protocol. The final RNA preparation was dissolved in 30 μl of RNase-free distilled water.
For the reverse transcription (RT), 300 ng of total RNA and the reverse primer were incubated at 70°C for 5 min and chilled immediately on ice for 3 min. The mixture was added to provide a final concentration of 50 mM Tris-HCl, pH 8.3, 75 mM KCl, 10 mM DTT, 2.5 mM MgCl 2 , 500 μM of each dNTPs, 25 pmol of antisense primer, 20 U RNasin and 200 U MLV-RT (Promega, Madison, WI). Five different sets of primers were designed in our lab to direct the amplification of several genomic regions (table  6). These regions were selected as conserved regions after aligning the published CTV sequences from different geographical regions [8,12].

Cloning and nucleotide sequencing
The reaction mixture was fractioned by agarose gel electrophoresis and the PCR products were purified using the GeneClean glass bead method (Bio101, Vista, CA) and ligated into pGEM-T Easy Vector System II (Promega, Madison, WI). The ligation mixture was used to transform Escherichia coli DH5α cells. Plasmids containing the expected sizes were chosen for sequencing. At least, three clones of each isolates were sequenced in both directions to obtain a consensus sequences by the Dye Cycle Sequencing kit (Applied Biosystem, Foster City, CA) in an ABI PRISM 377 sequencer

Sequence alignment and phylogenetic analyses
Multiple sequences of different CTV isolates were aligned using the software MegAlign 4.0 of the Lasergene package (DNASTAR Inc. Madison). The unrooted and neighbourjoined phylogenetic trees were prepared using Clustal × [16] and drawn with TreeView 1.5 (Page, 1996). The robustness of individual internal phylogenetic tree nodes was estimated using 1,000 bootstrap reiterations. Clustal W algorithm was used for the estimation of genetic distance by the Kimura two-parameter method [17]. A genetic distance was also calculated using MEGA 2.1 with the output used to calculate both individual pairwise diversity and mean pairwise diversity using the Kimura-2parameter approach.
The nucleotide sequences of the Mexican isolates obtained in this study were deposited in the GenBank database under the accession numbers: AF342890 to AF342895, AY649491 to AY649492, and AF652892 to AF652923.
JCOS collected viral samples and organized information and material data. RRB and JPMS conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.


extfieldsofstudy: Biology Medicine

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Puromycin-based vectors promote a ROS-dependent recruitment of PML to nuclear inclusions enriched with HSP70 and Proteasomes

Background Promyelocytic Leukemia (PML) protein can interact with a multitude of cellular factors and has been implicated in the regulation of various processes, including protein sequestration, cell cycle regulation and DNA damage responses. Previous studies reported that misfolded proteins or proteins containing polyglutamine tracts form aggregates with PML, chaperones, and components of the proteasome, supporting a role for PML in misfolded protein degradation. Results In the current study, we have identified a reactive oxygen species (ROS) dependent aggregation of PML, small ubiquitin-like modifier 1 (SUMO-1), heat shock protein 70 (HSP70) and 20S proteasomes in human cell lines that have been transiently transfected with vectors expressing the puromycin resistance gene, puromycin n-acetyl transferase (pac). Immunofluorescent studies demonstrated that PML, SUMO-1, HSP70 and 20S proteasomes aggregated to form nuclear inclusions in multiple cell lines transfected with vectors expressing puromycin (puro) resistance in regions distinct from nucleoli. This effect does not occur in cells transfected with identical vectors expressing other antibiotic resistance genes or with vectors from which the pac sequence has been deleted. Furthermore, ROS scavengers were shown to ablate the effect of puro vectors on protein aggregation in transfected cells demonstrating a dependency of this effect on the redox state of transfected cells. Conclusion Taken together we propose that puromycin vectors may elicit an unexpected misfolded protein response, associated with the formation of nuclear aggresome like structures in human cell lines. This effect has broad implications for cellular behavior and experimental design.

Background
The human promyelocytic leukemia PML gene was initially identified as the fusion partner of the retinoic acid receptor α gene in the T(15;17) chromosomal translocation in acute promyelocytic leukemia [1]. The PML protein localizes to punctate nuclear structures called PML nuclear bodies (NBs) which are discrete foci (0.1-0.2 μm diameter) that are present in most mammalian cells. PML is essential for the formation of PML NBs, however the bodies themselves are composed of many other proteins such as SUMO, SP100, CBP and Daxx. SUMO-1 (Small Ubiquitin like Modifier 1) belongs to a family of ubiquitin like proteins that may be covalently attached to protein substrates and are typically associated with protein localization. SUMO modification of PML is required for NB formation [1,2]. Thus far over 50 proteins have been identified to reside, either permanently or more typically transiently, in PML NBs. Typically the size, localization and number of PML NBs is well conserved in most cells, however they are dynamic structures that change size, position and number in response to stress such as heat shock, DNA damage and heavy metal exposure [2]. PML NBs have been implicated in the regulation of many cellular functions including DNA repair, antiviral responses, apoptosis, proteasomal degradation, senescence and gene regulation. It is still unclear how PML carries out its functions but it is recognized that the localization of proteins to NBs is important [3]. It has been suggested that PML NBs may operate as storage sites for nuclear proteins and/ or act as catalytic surfaces where proteins accumulate to be post translationally modified [4,5]. It has also been suggested that PML NBs may act as active sites for specific nuclear functions such as chromatin regulation and transcription [6,7]. PML is nonessential and PML knockout mice are viable, but the protein has been linked to many pathological states [8]. In particular, PML has been characterized as a tumor suppressor due to its functions in apoptosis, genomic stability and senescence [3]. PML NBs also play a role in neurodegenerative diseases however its participation is not very well defined. Nevertheless, PML NBs are often localized in the nuclear inclusions formed by protein/polyglutamine aggregates in diseases such as spinocerebrellar ataxia and Huntington's disease [9,10].
Newly synthesized proteins must fold correctly to become functional molecules. Many events including errors in transcription, mRNA processing and translation lead to failure in achieving correct protein conformation [11]. Furthermore, environmental factors such as oxidative, thermal or osmotic stress can interfere with folding of nascent polypeptides and can damage correctly folded proteins or intermediates [12,13]. Misfolded proteins expose hydrophobic residues that are normally buried in the protein's interior leading to protein aggregation. Cells have evolved 'quality control' systems to minimize protein misfolding and prevent protein aggregation. Molecular chaperones such as the Heat Shock Proteins (HSP) bind to and stabilize exposed hydrophobic residues thereby reducing the likelihood of protein aggregation [14]. Chaperones such as HSP70 are also believed to assist in refolding misfolded proteins. In addition, misfolded proteins are generally targeted for degradation by the ubiquitin proteasome system [13]. Proteasomes are multi subunit complexes that are abundant in the nucleus and cytosol in all eukaryotic cells that function to degrade unwanted or damaged proteins. Typically proteins are covalently modified with one or more ubiquitin molecules that act as a tag for recognition by the proteasomal complex. Failure of these quality control systems leads to protein aggregates which are difficult to unfold and/or degrade and are associated with the etiologies of many degenerative diseases such as amyloidoses, Alzheimer's disease and Parkinson's disease [14,15].
In the current study we have identified a reactive oxygen species (ROS) dependent aggregation of proteins (including PML), proteasomes and chaperones into nuclear inclusions in cells lines that have been transfected with vectors expressing the puromycin resistance gene. This response is strikingly similar to previously described misfolded protein responses and has broad implications for cellular behavior and experimental design.

Results
During the course of our studies we observed an apparent relocalization of PML nuclear bodies (NBs) in cell lines transfected with shRNA vectors targeting specific E3 ligases (MDM2 and CHIP). Surprisingly, we also observed this effect in cells transfected with control vectors expressing non targeting shRNA sequences and those without DNA inserts (empty vectors). To examine this further, U2OS cells were transiently transfected with empty vectors using Fugene transfection reagent and immunostained for PML 24 h and 48 h after transfection. PML localized to discrete foci (11 ± 5 foci per cell) dispersed throughout the nuclei of non transfected and mock transfected cells (Fig 1A). These foci had the typical size and appearance of PML NBs [3]. Transfection with pcDNA3.1 Neo or pCMV Neo empty vectors had no apparent effect on PML localization ( Fig 1A). However, cells transfected with pBABE Puro, pSIREN Puro and pLKO.1 Puro empty vectors displayed aggregation of PML at multiple nuclear sites. This aggregation appeared as clustering and/or clumping of PML, and was apparent 24 h and 48 h after transfection. To test the generality of this effect, we transfected MCF7 and HeLa cells with these empty vectors. pCMV Neo and pcDNA3.1 empty vectors had no effect on PML localization in these cells (data not shown). However, transfection with pBABE Puro, pSIREN Puro and pLKO.1 Puro (Fig 1B) resulted in aggregation of PML in the nuclei of both MCF7 and HeLa cells.
We next aimed to quantify the percentage of transfected cells in which PML aggregation occurred. To this end, pEGFP Neo empty vector was cotransfected with pBABE Puro into U2OS cells, and the cells immunostained for PML 48 h after transfection. Transfected cells were identified by EGFP expression. PML localization was not altered in cells transfected with pEGFP Neo alone ( Fig. 2A). In contrast, pBABE Puro (Fig 2A) empty vectors caused PML aggregation in EGFP co-expressing cells. Transfection of pBABE Puro caused PML NB aggregation in 21 ± 6% of EGFP expressing cells (Fig 2B).
PML aggregates similar to that observed in Figs 1 and 2 have been described previously in association with mis-folded proteins that accumulate in response to proteasome inhibition, viral protein expression, and in polyglutamine diseases such as Huntington's and spinocerebrellar ataxias [9,10,16,17]. PML was found coaggregated in these nuclear inclusions with SUMO-1, HSP chaperones, and proteasomes. We examined SUMO-1, HSP70, and proteasome localization in cells transfected with the empty, puromycin-resistance vectors. U2OS cells were transiently transfected with pBABE Puro or pCMV Neo (control) empty vectors and immunostained 48 h later for PML and either HSP70, SUMO-1 or 20S proteasomes. HSP70 was detected diffusely in both the nucleus and cytoplasm of non-transfected and control U2OS cells ( Fig 3A). In pBABE Puro transfected cells, HSP70 was dramatically relocalized to both nuclear and cytoplasmic aggregates. Large nuclear aggregates of HSP70 colocalized with PML clusters in all cells examined. Smaller, speckled HSP70 aggregates were also observed throughout the nuclei of many transfected cells but these usually did not colocalize with PML aggregates (Fig 3A, lower panel/magnified nuclei). SUMO-1 was detected in distinct nuclear foci that colocalized with PML in non-transfected and control cells (Fig 3B). In pBABE Puro transfected cells SUMO-1 relocalized to regions of PML aggregation, either colocalized with aggregated PML or in the area immedi-ately surrounding PML aggregates. Immunostaining using antibodies against 20S proteasomes demonstrated diffuse nuclear and cytoplasmic localization in non transfected and control cells (Fig 3C). In pBABE Puro transfected cells, 20S proteasomes were relocalized to large cytoplasmic and nuclear aggregates which colocalized with nuclear PML aggregates ( Fig 3C) and HSP70 aggregates in both the nucleus and cytoplasm (data not shown). Relocalization of HSP70, SUMO-1, and 20S proteasomes was also observed in pLKO.1 Puro and pSUPER Puro transfected U2OS cells (data not shown). In addition, these vectors caused a similar relocalization of HSP70, SUMO-1, and 20S proteasomes in MCF-7 and HELA cells (data not shown). Nucleolar localization of PML has been described during proteasomal inhibition and thermal stress [17]. To examine the sub-nuclear localization of PML, we immunostained pBABE Puro transfected cells for both PML and Fibrillarin as a nucleolar marker. PML did not colocalize with Fibrillarin stained regions (nucleoli) in non transfected or control cells (Fig 3D), and PML aggregates also did not colocalize with Fibrillarin in pBABE Puro transfected cells. This indicates the PML aggregates are not localized in nucleolar regions. In summary, transfection of pBABE Puro, pSUPER Puro and pLKO.1 Puro caused aggregation of PML, HSP70, SUMO-1 and 20S Proteasomes in nuclear regions distinct from nucleoli.
Next, we wished to address why this effect was specific to certain vectors but not others. The empty vectors that caused PML, HSP70, SUMO-1, and 20S proteasome aggregation (pBABE Puro, pLKO.1 Puro and pSUPER Puro) are retroviral vectors that express the puromycin resistance gene. The vectors that did not cause this effect (pcDNA3.1 Neo, CMV Neo and pEGFP Neo) are non-retroviral vectors that express the neomycin resistance gene. We questioned whether this effect could be related to either retroviral genetic sequences or expression of the puromycin resistance gene, puromycin n-acetyl transferase (pac). In order to investigate this, we used multiple pBABE vectors which differed only in the selection marker expressed (Puro, Hygro, Neo, GFP, HcRed). U2OS cells were transfected with these pBABE vectors and immunostained 48 h later for HSP70 and PML. While pBABE Puro caused PML and HSP70 coaggregation in transfected cells (as shown in Figs 1, 2, 3), none of the other pBABE vectors had this effect ( Fig 4A). This suggested that the puromycin resistance gene was responsible for PML and HSP70 aggregation. Next, we deleted the pac gene sequence from the pBABE Puro vector and transfected the resultant vector (named pBABE Puro del) into U2OS cells. Immunostaining for PML and HSP70 demonstrated that neither PML nor HSP70 were aggregated in cells transfected with pBABE Puro del ( Fig 4B). Collectively, this data demon-Transfection with pSIREN Puro, pBABE Puro or pLKO.1 Puro vectors causes PML aggregation in multiple cell types Figure 1 Transfection with pSIREN Puro, pBABE Puro or pLKO.1 Puro vectors causes PML aggregation in multiple cell types. (A) U2OS cells on glass coverslips were transiently transfected with empty vectors using Fugene transfection reagent and immunostained for PML (red) 48 h after transfection. PML antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG. Cell nuclei were counterstained with DAPI (blue). Images were captured at 100× magnification. (B) MCF-7 and HELA cells on glass coverslips were transiently transfected with pCMV Neo or pLKO.1 PURO empty vector using Fugene transfection reagent and immunostained for PML (red) 48 h after transfection. PML antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG. Cell nuclei were counterstained with DAPI (blue). Images were captured at 100× magnification.
strates the pac gene is required for PML and HSP70 coaggregation.
In the course of these experiments, we observed that highpassage U2OS cells were prone to PML aggregation following transfection with Puro-based vectors. However, when these experiments were repeated in low passage U2OS cells (<10 passages) we did not detect any aggregation (n = 3 separate experiments). Cell lines are often maintained in culture over long periods and are subjected to frequent passaging and multiple freeze-thaw cycles. Notably, ROS levels have been reported to increase in cells maintained in culture for prolonged periods, and multiple studies have linked elevated ROS levels with protein aggregation and misfolding [13,18,19]. We hypothesized that oxidative stress/ROS generation in cells maintained in culture over long periods might influence PML aggregation in transfected cells. To investigate this, we first compared the level of ROS in high passage and low passage U2OS cells using a flow cytometry approach based on H2DCFDA, a cell-permeant indicator for reactive oxygen species that fluoresces in a quantifiable manner in response to oxidation levels within the cell. Flow analysis to detect fluorescent H2DCFDA demonstrated that high passage U2OS cells contain 2.7 ± 0.69 (n = 3 separate experiments) fold higher levels of ROS compared to low passage cells (Fig 5A). Next we investigated whether these higher levels of ROS may be responsible for the protein aggregation observed in high passage cells. To this end, aggregation-prone (high passage) U2OS cells were transfected with pBABE Puro or pEGFP Neo. ROS scavengers, N-acetyl cysteine (NAC) or catalase, were then added to the media of transfected cells (15 h later), and the cells immunostained 48 h after transfection for PML and HSP70. EGFP expressing cells were quantified as a measure of tranfection efficiency under each condition. Cells displaying aggregation of PML/HSP70 were quantified and values corrected for transfection efficiency. PML/ HSP70 aggregation in NAC and catalase treated cells was reduced by 80% ( Fig 5B). This data suggests that ROS levels enhance PML and HSP70 aggregation in these cells.
Finally, we examined whether transfected cells maintain protein aggregation after undergoing puromycin selection. For this, U2OS cells were transfected with pBABE puro or left non-transfected. Four days later, cells were placed in media containing puromycin (0-15 μg/mL). Non-transfected cells were killed at all doses of puromcyin 2 days after treatment. Transfected cells were grown for two weeks in puromycin in order to select for stable, puroresistant cells. Stable cells were seeded on coverslips in the presence or absence of puromycin and stained 3 days later for PML and HSP70. Analysis of transfected cells grown in the absence of puromycin demonstrated these cells do not display PML and/or HSP70 aggregation (Fig 5C). Similarly, stable resistant cells grown in the presence or absence of puromycin (3 days), no longer display aggregation of PML and/or HSP70.

Discussion
In the current study, we have described a ROS sensitive aggregation of PML, HSP70, SUMO-1 and 20S proteasomes into nuclear inclusions in cells transfected with vectors expressing the selection marker gene, puromycin nacetyl transferase (pac). Moreover, aggregation of HSP70 and proteasomes was also observed in the cytoplasm of transfected cells. Cytoplasmic inclusions containing HSP70 and proteasomes have been previously described and are associated with aggregates of misfolded proteins [20][21][22]. Misfolded proteins generated by either protein over-expression, mutation, or cellular stress expose hydro- (green) and PML (red). PML and HSP70 antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG and Alexa 488 goat anti rabbit IgG respectively. Lower panel displays magnified nuclei (2×) from pBABE Puro transfected cells (panel above) in order to display speckled nuclear staining pattern of HSP70 in transfected cells. (B) Representative images of cells immunostained for SUMO-1 (green) and PML (red). PML and SUMO-1 antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG and Alexa 488 goat anti rabbit IgG respectively. (C) Representative images of cells immunostained for 20S Proteasomes (red) and PML (green). 20S Proteasomes and PML antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG and Alexa 488 goat anti rabbit IgG respectively. (D) Representative images of cells immunostained for Fibrillarin (green) and PML (red). PML and HSP70 antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG and Alexa 488 goat anti rabbit IgG respectively. phobic residues leading to non productive cellular aggregates throughout the cell [11]. In the cytoplasm it has been proposed that these aggregates are transported to the microtubule organizing center (MTOC) in a microtubule dependent manner where they coalesce to form aggresomes [11,22]. Aggresomes are typically enriched with chaperones such as HSP70 and proteasomes, and are thought to be sites of misfolded protein degradation. Similarly, nuclear inclusions enriched for chaperones and proteasomes have been described in cells expressing proteins that contain expanded polyglutamine (polyQ) repeats [20,23]. In neurodegenerative disorders, such as Huntington's disease and spinocerebellar ataxias, mutant proteins (huntingtin and ataxins respectively) containing expanded polyQ repeats form nuclear inclusions associated with proteasomes and HSP70 in neuronal cells [9,20,23]. Notably, many reports have described the presence of PML and SUMO-1 in these neurodegenerative nuclear inclusions [9,10,24]. Moreover, nuclear inclusions containing HSP70, proteasomes and PML have been well characterized in cells overexpressing non-PolyQ aggregation prone proteins, viral proteins and in cells treated with proteasomal inhibitors [16,17,[25][26][27]. Collectively, these studies suggest that PML bodies can represent nuclear aggresomes and potential sites of nuclear misfolded protein degradation. Based on these previous studies, we propose that a protein aggregation/misfolded protein response may account for nuclear aggregation of PML, HSP70, SUMO1 and proteasomes into nuclear inclusions in this study. We observe nuclear and cytoplasmic aggregates in cells transfected with puro vectors which are strikingly similar to cellular aggresomes. Previous studies have shown aggregation of transiently overexpressed proteins, however this has not been previously described in cells transfected with empty vectors [22,25]. Cells transfected with a puro vector and then selected in puromycin did not display PML/HSP70/proteasome/ SUMO aggregates. This suggests cells with aggregates may either die, or clear/resolve the aggregates through autophagy or other mechansisms [27,28].

PML aggregation occurs specifically in transfected cells
Our results demonstrate that protein aggregation in cells transfected with empty puro vectors depends on the presence of the puromycin-resistance (pac) gene. It is presently unclear why this effect is specific to pac and why similar aggregation does not occur upon transfection with vectors expressing other selection markers. One possible reason could be that puromycin n-acetyl transferase protein (PAC) is more aggregation prone than other antibiotic resistance proteins. We propose that PAC protein may colocalize with both nuclear and cytosolic aggregates and that the presence of proteasomes and chaperones may represent the cells response to aggregated PAC protein. However, in the absence of commercially available antibodies specific to PAC, we were unable to confirm this hypothesis. The composition and the primary structure of a polypeptide determine to a large extent its propensity to aggregate. We have used two recently developed bioinformatics software programs as a preliminary approach to compare the protein sequences of neomycin, puromycin and hygromycin resistance gene products for aggregation propensity (data not shown). The software Aggrescan predicts aggregation hotspots in protein sequences [29]. Using this software we did not detect any apparent differences in aggregation propensity based on protein sequence/amino acid content. However, using a second piece of software, PONDR VL-XT (Molecular Kinetics, Inc., IN) we have detected that a greater percentage of the puromycin resistance protein (38%) is naturally disordered compared to hygromycin (25%) and neomycin (22%) resistance proteins [30]. Disordered regions (DRs) are entire proteins or regions of proteins which lack a fixed tertiary structure, essentially being partially or fully unfolded which have been linked to aggregation propensity [31]. It is tempting to speculate that the percentage of disorder in PAC may lead to its aggregation; however, it is presently unclear whether this could contribute to the observed phenotype. Other potential reasons for aggregation may include possibly higher expression levels, a greater sensitivity to ROS damage and/or a higher rate of degradation for PAC which have been shown to contribute to aggregation propensity in other studies [19,32]. It also cannot be ruled out that PAC activity or its interaction with other native proteins may contribute to protein aggregation in transfected cells. The specificity of this effect to pac is of great interest and warrants further study.
During the course of this study, we observed the effect of puro vectors on protein aggregation in multiple cell types but not in low passage/newer cells (<10 passages). Many studies have described the generation of reactive oxygen species (ROS) in cultured cells and higher levels of ROS are associated with protein aggregation [13,18,19,33]. We proposed that older cells may contain higher levels of ROS which could account for aggregation being limited to higher passage cells. Initially we identified that high passage cells have a higher level of intracellular ROS. To investigate this hypothesis further, we used two scavengers that reduce ROS through different mechanisms. Catalase functions to catalyze the decomposition of H 2 O 2 , the major cellular source of ROS, to water and oxygen. H 2 O 2 readily passes through cell membranes allowing extracellular catalase (in cell medium) to drain H 2 O 2 from cells thereby protecting against extracellular and intracellular H 2 O 2 [18]. N-acetyl cysteine functions to stimulate expression of endogenous intracellular ROS scavengers, such as glutathione peroxidase [34]. Both ROS scavengers blocked protein aggregation in aggregation prone U2OS cells in this study. Since these scavengers use different mechanisms to decrease ROS, we consider this strong evi-dence that ROS contributes to aggregation. ROS are typically generated as the byproduct of cellular metabolic processes and are carefully controlled by cellular antioxidants or scavengers. However, oxidative stress ensues when an imbalance occurs between ROS generation and antioxidant defenses in favor of the former. Excessive ROS leads to oxidation of cellular proteins rendering them less active, less thermostable and more hydrophobic [13]. It is possible that overexpressed PAC protein is directly dam-aged by ROS in these cells, leading to increased hydrophobicity and aggregation. Most oxidative damage cannot be reversed and oxidized proteins are generally removed by proteasomal degradation. Proteasomal activity is also impaired by ROS and such inhibition of proteasomes may also contribute to aggregation in our model [35,36]. Many aspects of cell culture could account for excessive ROS generation in these cells. Cell culture media tends to be pro-oxidant due to components such as ascorbate, flavonoids and thiols which undergo rapid oxidation to generate H 2 O 2 and other ROS [37][38][39]. Cell media is also often deficient in many antioxidants and antioxidant precursors [40,41]. Furthermore, cultured cells are grown at high oxygen tension levels (15-100 times greater than in vivo) which can lead to enhanced ROS generation by increased leakage of electrons from electron transport chains [18]. Finally, an association between ROS generation and the frequency of freeze-thaw cycles of cells has been identified [42]. We suggest that continuous culture of cell lines may render cells more susceptible to oxidative stress and that this may alter cell behavior.

Conclusion
This study has broad implications for cell experimentation. Many studies are based on malignant cell lines that are often maintained in culture and/or frozen over long periods. Cell lines are generally considered to be more robust than primary cells which often undergo stress during cell culture; however, our study shows that cell lines can also be susceptible to oxidative stress during prolonged culture. Our study clearly shows an alteration in cell phenotype/behavior in a ROS dependent manner. The aggregation of critical multifunctional proteins and complexes such as HSP70, PML and proteasomes into nuclear inclusions clearly may affect multiple cellular processes and may lead to inaccurate conclusions in experimental studies. Cell transfection itself is a critical component of cell biology studies. Typically DNA vectors are used without consideration for the effects of resistance proteins in transfected cells. It is surprising that the puromycin resistance gene can cause these effects in cells however it is worth noting that this gene expresses a foreign protein in mammalian cells. We suggest caution when using puromycin-based DNA vectors, as these vectors may elicit an unexpected misfolded-protein response that includes PML, HSP70, SUMO-1, and proteasome coaggregation, and that could alter the outcome or interpretation of experiments.

Cells, Reagents and Plasmids
HeLa, MCF-7 and U2OS cells were obtained from ATCC and were grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum PML/HSP70 co-aggregation is dependent upon the presence of the pac resistance gene sequence in puromycin vectors Figure 4 PML/HSP70 co-aggregation is dependent upon the presence of the pac resistance gene sequence in puromycin vectors. U2OS cells on glass coverslips were transiently transfected with empty vectors and immunostained for HSP70 (green) and PML (red) 48 h after transfection. PML antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG or Cy5 goat anti mouse IgG/ pseudocolored red (pBABE hcRed transfected cells only). HSP70 antibodies were detected using Alexa 488 goat anti rabbit IgG or Cy5 goat anti rabbit IgG/pseudocolored green (pBABE GFP transfected cells only). Cell nuclei were counterstained with DAPI (blue). Images were captured at 100× magnification. (A) Representative images of cells transfected with multiple pBABE vectors carrying alternative selection markers demonstrating absence of PML/HSP70 aggregation. (B) Representative images of cells transfected with pBABE Puro del demonstrating absence of PML/HSP70 aggregation. pBABE Puro del was generated by removal of the pac gene sequence from parental vector pBABE PURO.

Transient and Stable Transfection
Fugene transfection reagent was equilibrated in serum free DMEM prior to mixing with vector DNA (2 μg). Fugene/ DNA was incubated at room temperature prior to being added dropwise to cells. To establish stable cell lines, media was refreshed on transfected cells 4 days later with media containing puromycin (0, 1, 5, 10 and 15 μg/mL). Transfected cells were treated with puromycin, refreshed every 3 days, for > 2 weeks.

Deletion of pac sequence from pBABE Puro
Primers were designed for flanking regions of the pac sequence in the pBABE Puro plasmid. Deletion of the pac gene was performed using the Quikchange XL mutagenesis kit (Strgatagene, La Jolla, CA) exactly as the manufacturer described and the resulting plasmid was renamed pBABE Puro del. Deletion of the pac sequence was confirmed by DNA sequencing of the pBABE Puro del plasmid.

Detection of intracellular ROS
Cells were grown to 70% confluency in 35 mm dishes. Cells were trypsinized and incubated with 25 μM Carboxy H 2 DCFDA (Invitrogen, Carlsbad, CA) for 30 min at 37°C in dark. Cells were next washed with ice-cold PBS. Fluorescence was quantified by flow cytometry using a BD FACS-Canto (BD, Franklin Lakes, NJ). Data was analyzed using FlowJo 8.8. Geometric Mean fluorescence was used as average fluorescence value for each population.
PML/HSP70 co-aggregation is dependent upon ROS and is not maintained in puromycin resistant selected cells (B) U2OS cells on glass coverslips were transiently transfected with pBABE Puro or pEGFP Neo. ROS scavengers, catalase (CAT; 50 μg/mL) or N acetyl cysteine (NAC; 10 mM), were added to media of transfected cells 15 h after transfection. Transfected cells were immunostained for HSP70 and PML 48 h after transfection. Cells displaying aggregation of PML/HSP70 were quantified and expressed as a percentage of EGFP expressing cells. Data represents the average ± SEM from 3 independent experiments. Asterisk represents p-value < 0.01 compared to cells without ROS scavengers (Student T Test). (C) Representative images of puromycin selected cells demonstrating the absence of PML/ HSP70 aggregation. U2OS cells were transfected with pBABE puro and selected in puromycin as described in materials and methods and then immunostained for HSP70 (green) and PML (red). PML and HSP70 antibodies were detected using a rhodamine-x conjugated goat anti mouse IgG and Alexa 488 goat anti rabbit IgG respectively. Cell nuclei were counterstained with DAPI (blue). Images were captured at 100× magnification.
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Relationship between human oral lichen planus and oral squamous cell carcinoma at a genomic level: a datamining study.

The leader gene approach is a data mining method based on the systematic search for genes involved in a specific process and their ranking according to the number of interconnections with the other genes identified. The genes with the strongest interconnections are termed leader genes, since they may be supposed to play an important role in the process. The potential of malignant progression of OLP to oral squamous cell carcinoma (OSCC) is still not completely clear. In this study, the leader gene approach is applied to investigate the association between OLP and OSCC at a molecular level. Results were integrated with those obtained in an experimental analysis (see paper 1 of this series). Genes involved in OLP and OSCC were identified by systematic queries to dedicated databases. Interconnections among identified genes were calculated and given a confidence value using STRING database. Leader genes were identified by clustering genes according to their interconnections. This theoretical analysis shows that OLP and OSCC share two leader genes: TP53 and CDKN1A, involved in the PI3K signalling events mediated by AKT pathway. This finding and those obtained in the experimental analysis suggest the possible involvement of some key genes/proteins LCK, PIK3CA, BIRC5, TP53 and CDKN1A in the malignant progression from OLP to OSCC. Moreover, these findings support the role of some molecular pathways, namely IL2 signalling events mediated by PI3K, PI3K signalling events mediated by AKT, and, possibly, Aurora A signalling in the association between OLP and OSCC.

Background:
Oral lichen planus (OLP) is a T-cell-mediated chronic inflammatory oral mucosal disease of unknown etiology [1]. The histological lesions are characterized by a sub-epithelial inflammatory infiltrate, mainly constituted by T lymphocytes and focused to the basal keratinocytes [1]. OLP lesions are characterized by a higher degree of cell turnover than healthy tissue: the proliferation, the maturation and the apoptosis of basal keratinocytes require a fine regulation at a genomic level [2]. From these observations, OLP may be seen as a complex multifactorial disease [2]. The World Health Organization defined OLP as a premalignant condition, with a possible progression to oral squamous cell carcinoma (OSCC) [1,2]. The progression from OLP to OSCC is a relatively rare event: although frequencies ranging from 0.4 to 6.5% have been reported, most studies suggest that the malignant progression rate is around 1% [2,3]. The molecular mechanisms determining the possible malignant development in OLP lesions are still not completely elucidated [3]. Further research is therefore advocated to clarify the molecular aspects of this potential relationship, including the identification of potential prognostic markers at a genomic and proteomic level [4].
Bioinformatics and data-mining can play a central role in the analysis and interpretation of genomic and proteomic data [5,6]. In particular, these disciplines may be useful to further clarify the pathophysiology of complex diseases, which are characterized by various biologic pathways, dependent upon the contribution of a large number of genes forming complex networks of interactions [5,6]. Interactions between genes may be direct (physical interactions between the proteins, confirmed by experimental techniques, such as NMR or crystallography) or indirect (involvement in the same metabolic pathway or co-expression in different conditions) [7].
Recently, a data-mining method, defined as the "Leader Gene approach" have been proposed [5,6]. This mining algorithm is based on the systematic search for the genes involved in a given process; the interaction among these genes are then calculated and genes are ranked according to the number and the confidence of all experimentally established interactions [5, 6], as derived from free Web-available databases, such as STRING (Search Tool for the Retrieval of Interacting Genes, Heidelberg, Germany) [7]. Genes in the highest rank are defined as ''leader genes'', since they can be preliminarily supposed to play an important role in the analyzed process [5,6]. These genes may become potential targets for a targeted experimentation, which may be simpler than mass-scale molecular genomics and, at the same time, powerful [5, 6]. The Leader Gene approach was applied to different cellular processes and pathological conditions, such as the human T lymphocyte cell cycle, human kidney transplant and periodontitis [5, 6]; the results were integrated with a targeted experimental analysis, to draw an overall picture of these processes [8]. Recently, the Leader Gene approach was applied to infer the epidemiologically-established correlation between human periodontitis and type-2 diabetes [6]. Overall, the results showed that periodontitis and diabetes share four leader genes and that all leader genes are linked in a complex map of interactions. This finding may suggest an important role of leader genes in the association between these diseases; leader genes may be supposed, at least preliminarily, to act as hubs in the interaction map [5,6]. Leader genes may therefore become promising targets for a dedicated experimentation. In this data-mining ab-initio study, we apply the leader gene approach to preliminarily investigate the molecular mechanisms underlying the potential association between OLP and OSCC. The theoretical results are integrated with some experimental findings, recently obtained by mean of immunohistochemistry and tissue micro-array on patient biopsies.

Methodology: General architecture:
The data mining algorithm followed is represented in Figure 1 [5, 6]. First, a preliminarily set of genes with an established role in a specific process is identified by an iterative search of large-scale gene databases (PubMed, GeneBank, Geneatlas, Genecards), using several keyword-based searches and the official HGNC nomenclature. Second, the preliminary set of genes is expanded using the STRING database (version 8.2), excluding textminingderived interactions, to identify genes linked to those playing an established role in the process under study, and therefore potentially involved in it [7]. Only interactions with a confidence score >0.9, as given by STRING, are considered. Results are then filtered to discard false positives via a keyword-based query in PubMed, until no new genes are retrieved. Third, the interactions between all the genes identified are mapped using STRING. This database gives a combined association score to each gene-gene interaction, representing its strength. The combined association scores referring to each single gene are then summed to obtain a weighted number of links (WNL

Leader genes in OLP and OSCC
The above-described leader gene algorithm is applied to both OLP and OSCC. The resulting leader genes are compared. Research was last updated on 2th November 2009. Overall, 48 human genes were identified as involved or potentially involved in OLP; 7 of them were classified as leader genes (p<0.001 for their WNL vs other classes). In total, 208 human genes resulted as involved or potentially involved in OSCC; 5 of them were classified as leaders (p<0.001 for their WNL vs other classes). Table 1 (supplementary material) summarizes the established or putative role of all leader genes. OLP and OSCC share 2 leader genes: TP53 and CDKN1A.
All leader genes involved in the control of cell cycle are closely interacting (Figure 2a).

Pathways characterization and comparison with experimental data
PI3K signalling pathway may play a role in the pathogenesis of OSCC [9]. The involvement of leader genes in this pathway has been checked in the Pathway Interaction Database (PID). Both shared leader genes and MDM2 are involved in PI3K signalling mediated by ATK1 pathway. The results of the data-mining process are compared and integrated, using STRING and PID databases, with the results of a recent experimental study, which identified LCK, PIK3CA and survivin (BIRC5) as potential biomarkers of the progression from OLP to OSCC. These genes are strongly interconnected with the two shared leader genes between OLP and OSCC, TP53 and CDKN1A (Figure 2b). The interactions seem to be mediated by AKT1 gene; three molecular pathways are involved in this network, namely (1) IL2 signalling events mediated by PI3K,

Discussion
We applied the Leader Gene approach, a previously-validated datamining algorithm [5, 6,8], to obtain a preliminary evaluation of the potential correlation between OLP and OSCC at a genomic level. Overall, two leader genes, i.e. those with the strongest interconnections among all genes involved in OLP or OSCC, were shared between these conditions: TP53 and CDKN1A. All the other leader genes involved in cell cycle were close interconnecting. These findings might suggest that leader genes may play an important role in the association between OLP and OSCC: even a small variation in the expression, in the sequence or in the regulation of these genes might have an impact on several other genes [8]. Moreover, the shared leader genes can be supposed, at least preliminarily, to act as hubs in the interaction map [5,6].
Recently, the Leader Gene approach was applied to formulate new hypotheses on the correlation between periodontitis and diabetes: results showed that 4 leader genes were shared between the two diseases, while all the remaining leader genes were strongly linked [6]. In the present analysis, only two genes were linked; this may suggest, at least preliminarily, that the association between OLP and OSCC is weaker than that between periodontitis and diabetes. This hypothesis is in line with the rates of malignant progression from OLP to OSCC and those referring to periodontitis-diabetes comorbidity [2, 3, 6]. Data-mining was completely conducted abinitio [6]. A blind search might represent a proof of the validity of this approach, if the retrieved results are in line with current knowledge. After the ab-initio identification of leader genes, scientific literature was mined to verify the role of leader genes in OLP and OSCC. . TP53 and CDKN1A, the two shared leader genes, play a major role in the potential malignant progression. TP53 is associated to genome repair and pro-apoptotic signalling. An increase in TP53 expression is observed in OLP lesions [16].

Evidence of the role of leader genes in OLP and in OSCC
Mutations in this gene are associated with progression to OSCC and the expression of TP53 protein correlates with poor prognosis in OSCC patients [16]. CDKN1A inhibition and misregulation frequently occur in OSCC [17].

Molecular pathways potentially involved between OLP and OSCC
The potential association between impairment in the regulation of PI3K signalling pathway mediated by AKT1 and the pathogenesis of OSCC has been recently suggested [9]. Both TP53 and CDKN1A are involved in this pathway [18,19], as well as another leader gene in OLP, MDM2 [20]. This finding may support the possible correlation between the two conditions. Recent findings, obtained in OLP and OSCC patients, have shown that the overexpression of three key proteins (LCK, PIK3CA and BIRC5) may be associated to an high risk of malignant progression (Oluwadara, paper 1 of this series). These proteins form a complex network of direct and experimentally-established interactions with TP53 and CDKN1A. Such network includes two other genes (AKT1 and AURKA) and three different pathways: the PI3K signalling pathway mediated by AKT1, the IL2 signalling events mediated by PI3K, and the Aurora A signalling. These pathways may play a role in the malignant progression from OLP to OSCC. For instance, it may be very preliminary suggested that an impairment in IL2 signalling, which promotes T-cell proliferation and subsequent continuous T-cell signalling and activation, may be associated to a reduction in immune activity and to an enhancement in the malignant potential of OLP lesions.

Limitations:
The present analysis presents several limitations. The first limitation is the lack of an experimental validation; however, like all data-mining processes, the Leader Gene approach is only able to provide new well-grounded hypotheses, which may be either verified or discarded by a targeted experimentation, e.g. with microarrays or real-time polymerase chain reaction (RT-PCR) [5, 6]. Another limitation is the possible bias related to database mining [5,6]. However, only strong and experimentally-established gene and protein interactions were considered [7]. These choices might limit, at least partially, a possible bias related to database mining.

Conclusions:
This analysis could further confirm that data-mining of existing databases may represent a starting point to improve our knowledge about cellular processes and diseases, to formulate new hypotheses and to plan targeted experimentation [5,6]. In particular, the analysis of gene interaction maps and the ranking of genes according to their interconnections might help in identifying new targets for dedicated experimental analyses, which may confirm or discard each hypothesis and suggest potential risk factors and therapy targets [5,6]. The results of this study must be interpreted together with the findings obtained in an experimental analysis conducted on a large number of biopsies from OLP and OSCC patients (Oluwadara, paper 1 of this series). Overall, these studies suggest the possible involvement of some key genes and of the encoded proteins (LCK, PIK3CA, BIRC5, TP53 and CDKN1A) in the malignant progression from OLP to OSCC. Moreover, these findings support the role of some molecular pathways, namely IL2 signalling events mediated by PI3K, PI3K signalling events mediated by AKT, and, possibly, Aurora A signalling in the association between OLP and OSCC. Further details about these complex molecular networks will likely be provided by targeted DNA or protein microarrays, as previously suggested [4, 5, 6]. These analyses will be focused only on selected molecular targets and therefore will be much easier to interpret than mass-scale experiments. On this basis, further insights towards a better understanding of the molecular mechanisms underlying the potential progression from OLP to OSCC may be retrieved.