Databases

For single nucleotide variation data we used the Exome Aggregation Consortium browser (beta version) ([11]; Exome aggregation consortium (ExAC), Cambridge, MA (URL: http://exac.broadinstitute.org/) accessed August 2016). The ExAC is a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a wide variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on the above mentioned website spans 60,706 unrelated individuals sequenced as part of various disease-specific and population genetic studies and 17 projects contribute to the data.

Short linear motifs were identified using the Eukaryotic Linear Motif (ELM) resource [19]. For information about catalogue of human mutations and related genetic disorders, the Online Mendelian Inheritance in Man^® was used (Online Mendelian Inheritance in Man, OMIM^®. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, MD), {07/16/2016}. World Wide Web URLs: http://omim.org/). MIM Numbers and accession dates: F13a: {134570}{07/16/2016}; TGM1: {190195}{07/16/2016}; TGM5: {603805}{07/16/2016}; TGM6: {613900}{05/08/2016}. This article only uses anonymous human data from freely available public databases that have been obtained in a manner conforming to the respective IRB and/or granting agency ethical guidelines.

The mis_z scores were taken from the ExAC dataset [11]. In order to create a constraint metric and to contrast observed and expected number of variants per gene, mis_z scores were calculated. The mis_z score is based on a previous mutational model of probabilities of mutation for regional genomic divergence between humans and macaques [20] but with some modifications [11]. In Lek et al. [11] instead of probability of mutation, the expected number of variants were adjusted for depth of sequencing coverage for each exon. This depth adjusted correction was implemented to account for poorly sequenced regions with fewer variants than expectation. Across canonical transcripts all exon level variant counts were added and then a chi-squared value (Chi-square is a statistical test commonly used to compare observed data with data one would expect to obtain according to a specific hypothesis) for each mutational types (synonymous, missense, and protein-truncating) was calculated. If the observed variants are smaller than expected the square root of the chi-squared values were multiplied by 1 and if the observed variants are greater than expected then the values were multiplied by -1 to create a Z score. Finally, a corrected missense z score was created by dividing all missense z scores by standard deviation of the mirrored distribution. Mirrored or Gumbel distribution is an Extreme Value distribution Type-I; it is used for modelling extreme values of a random variable when the mean of smaller and larger values are farther apart.

Gene damage index (GDI) scores were taken from [21]. GDI is a metric which defines the non-synonymous mutational load in each protein-coding gene in the general population [21]. The damage caused to the exonic regions of the gene was predicted by calculating GDI score for each human gene g with n minor alleles (minor allele frequency < 0.5). For Phred I-score the ranking of the gene of interest i relative to all other human genes T = 19,558 genes, with values ranging from 0 (lowest Phred) to 42.91 (highest Phred) was calculated: I_i = −10[log 10(i/T)].

Bioinformatic tools

To predict the possible impact of single amino acid substitutions on the structure and function of a human protein, Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant From Tolerant (SIFT) analyses were applied for nsSNVs in the ExAC database. If more than one change is present at an amino acid residue and both having same scores, PANTHER (Protein ANalysis THrough Evolutionary Relationships) prediction was carried out to determine which of the two was the damaging nsSNV [22]. The deleterious, possibly or probably damaging nsSNVs are mentioned as damaging in the text.

GORIV was used to predict the secondary structures (https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_gor4.html accessed on 15 March 2016) of wild type and mutant human TGM2 proteins. Stability analysis was performed by algorithm FoldX [23] using default parameters of the program. Changes in the overall stability of the proteins (ΔΔG [kcal/mol]) for damaging nsSNVs were calculated in both opened (PDB ID: 2Q3Z) and closed (PDB ID: 1KV3) forms. TGM2 involving residues 1–14 and 323–326 for which the coordinates in either or both crystal structures are not available were excluded from the stability analysis.

Homology modelling of TGM2

Homology models of TGM2 to represent one Ca²⁺ and a three Ca²⁺-bound states were built with SWISS-MODEL using the X-ray crystal structures of either FXIIIa (pdb: 4KTY) or TGM3 (pdb: 1L9M), respectively, as templates [24, 25, 26]. The models were then repaired for energy minimization using the FoldX forcefield. The R222 residue was mutated to glutamine using FoldX and the structures were visualized with the help of the FoldX plugin in YASARA [27, 28]. Figures were prepared using PyMol Molecular Graphics System (version 1.8 Schrödinger LLC).

Transglutaminase enzyme preparations

The TGM2 variants were constructed using the QuikChange II Site-Directed Mutagenesis Kit Manual (Stratagene, La Jolla, California, USA) and were checked by restriction analysis and DNA sequencing (Capillary sequencing runs were performed by Genomic Medicine and Bioinformatics Core Facility at University of Debrecen). Wild-type TGM2 and homozygous nonsynonymous variants were expressed in N-terminally (His)₆-tagged form (pET-30 Ek/LIC-TGM2) and purified by Ni-NTA affinity chromatography as described previously [29]. The protein concentrations were determined based on Bradford method (Bio-Rad Protein Assay, Bio-Rad, München, Germany). Finally, protein purity was checked after staining of SDS-polyacrylamide gels by PageBlue Protein Staining Solution (Thermo Fisher Scientific, Waltham, Massachusetts, USA). GenBank Accession Number of the wild-type TGM2 used in this study: RefSeq NM_004613. The dbSNP identifiers of the TGM2 homozygous nonsynonymous variants: p.Arg76His (rs41274720), p.Arg222Gln (rs200551434), p.Arg433Gln (rs142184177), p.Val542Phe (rs115436227), p.Pro612Thr (rs199563008), p.Asp671Asn (rs141236503).

Transamidase assays

The kinetic amine incorporation assay was performed with slight modification of a previously published procedure [29]: The reaction mixture contained 50 mM Tris-HCl buffer pH 7.5, 0.5 mM dansyl-cadaverine, 2 mg/ml N,N’ dimethylated casein, 3 mM DTT, and 3 mM CaCl₂ or 10 mM EDTA. The reaction volume was 100 μl and the assay was started with the addition of 20 μl enzyme (100 nM TGM2 final concentration). The reaction rate was calculated based on the initial slopes of the kinetic curves (Ex/Em: 360/490 nm; at 37°C) using GraphPad Prism version 7.00 for Windows (GraphPad Software, La Jolla, California USA, www.graphpad.com).

A real time fluorescence anisotropy assay was also used to measure the crosslinking activity [17]. The crosslinking of FLpepT26 into S100A4 (GST) by TGM2 was monitored by increase in the fluorescence anisotropy. The volume of the reaction mixture was 35 μl and performed for 30 mins at 37°C with 100 nM FLpepT26, 13.15 μM S100A4 (GST), 10 nM TG2, and 3 mM CaCl₂ (5 mM EDTA was used as negative control). The reaction buffer contained 20 mM Tris–HCl, pH 7.5, 150 mM NaCl, 5 mM DTT, and 0.01% Tween 20. A 384-well untreated Polystyrene Black Microplate was used (Nunc, Thermo Scientific, Denmark, cat. no. 262260) and the change of the fluorescence anisotropy was measured by Synergy H1 microplate reader (GreenFP filter cube, excitation 485 nm, emission 528 nm; BioTek, Winooski, VT, USA). The reaction rate was calculated from the initial slopes of the kinetic curves using GraphPad Prism version 7.00 for Windows (GraphPad Software, La Jolla California, USA, www.graphpad.com).

Isopeptidase assays

The basis of the Zedira assay is that transglutaminase cleaves the isopeptide bond in the synthesized substrate releasing the dark quencher (2, 4-dinitrophenyl) linked to the cadaverine spacer followed by the increase of fluorescence from the N-terminally attached fluorophore 2-aminobenzoyl (2-Abz). The reaction was performed based on previously published method [29]. In detail the reaction mixture was: 50 mM MOPS buffer, pH 6.8, containing 5 mM CaCl₂, 100 mM NaCl, 0.1% (w/v) PEG8000, 100 nM TGM2, 50 μM A102 isopeptidase assay substrate (Zedira, Darmstadt, Germany), and 2.8 mM DTT (added with the starting solution which contained the enzyme). The reaction was monitored at 37°C by a Synergy H1 microplate reader (Ex/Em: 318/413 nm) and the activities were calculated from the initial slopes of the kinetic curves.

The isopeptidase assay using novel crosslinked protein–peptide substrate was carried out using previously published real-time fluorescence method [18]. The cleavage of the isopeptide bond on FLpepT26–S100A4 (GST) substrate by TGM2 was followed by decrease in fluorescence anisotropy. The volume of the reaction was 35 μl and performed for 60 mins at 37°C with 0.5 μM FLpepT26–S100A4 (GST), 300 nM TGM2, and 5 mM CaCl₂ or EDTA. The reaction buffer contained 20 mM MOPS (pH 6.8), 150 mM NaCl, 6 mM glycine methyl ester, 5 mM DTT, and 0.1% Tween 20. A 384-well untreated Polystyrene Black Microplates (Nunc, Thermo Scientific, Denmark, cat. no. 262260) and Synergy H1 microplate reader (GreenFP filter cube, excitation 485 nm, emission 528 nm; BioTek, Winooski, VT, USA) was used to measure changes of fluorescence anisotropy. The reaction rates were calculated from the initial slopes of the kinetic curves in terms of anisotropy per minute using GraphPad Prism version 7.00 for Windows (GraphPad Software, La Jolla California USA, www.graphpad.com).

BODIPY FL GTPγS nucleotide binding assay

500 nM BODIPY FL GTPγS, (Invitrogen, Carlsbad, CA, United States) [29] a GTP analog was used to compare nucleotide binding to increasing amounts of TGM2 variants in the presence of 20 mM HEPES pH 7.5, 150 mM NaCl, 0.1 mM TCEP, 0.05% Tween-20, 0.1 mM EGTA, and 1 mM MgCl₂. There is an increase in fluorescence when BODIPY FL GTPγS binds to GTP-binding proteins providing a non-radioactive alternative tool to analyse protein-nucleotide interactions.

Fibronectin binding assay

The fibronectin-binding property of the variants was tested using a previously published direct ELISA assay [16] with the following modifications. After fibronectin coating and washing, 0.3 μg TGM2 wild-type or variant was incubated in each well for 1 h at room temperature in TTBS buffer containing 2.5 mM CaCl₂. The amount of bound TGM2 variants were detected using CUB7402 (1:5,000, Neo markers, Fremont, CA) monoclonal antibodies and then anti-mouse IgG/ HRP (1:7,500) with TMB substrate at 450 nm.

Synonymous, non-synonymous and LOF nucleotide variants in genes of the human transglutaminase family

Recent advances in next-generation sequencing technologies and initiatives such as the 1000 Genomes and other exome sequencing projects have uncovered a broad range of genetic variations among individuals. For analysis of variants in the transglutaminase enzyme family the ExAC database was chosen as a source of SNV data. As of August 2016 it contained high quality exon sequencing data from 60,706 unrelated individuals displaying one variant at every eight bases [11]. There were 5,766 SNV entries for transglutaminases of which 3623 SNVs fall under synonymous, non-synonymous or LOF categories in exons (Table 1). Out of the total entries only 4.5–6% of SNVs in case of each family were non-synonymous SNVs. TGM2, TGM4, TGM5 had the lowest and TGM6 had the highest number of nsSNVs (Table 1). The range of loss-of-function (LOF; including frameshift, splice acceptor and stop gained) variants were from 19 in TGM1 to 40 in TGM5, while TGM2 had 29 LOF variants (Table 1). The number and percentage of residues polymorphic to nsSNVs in each family was also calculated. F13a, TGM1, TGM2, and TGM5 had less percent of such residues while TGM3 and TGM6 had the highest (Fig 1A).

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Fig 1. Analyses of non-synonymous variants in the transglutaminase family.

(A) Amino acid residues polymorphic to non-synonymous variants. The percentage of polymorphic residues was obtained as a ratio of the total number of amino acid residues polymorphic to nsSNVs and the sequence length. The percentage of polymorphic residues is shown. (B) Proportion of damaging and benign non-synonymous variants by the PolyPhen score. Ratio of damaging nsSNVs: F13a (42.8%), TGM1 (60.8%), TGM2 (43.7%), TGM3 (52.2%), TGM4 (51%), TGM5 (55.3%), TGM6 (52.5%), and TGM7 (49.5%). (C) Location of damaging nsSNVs in amino acid sequence of TGM2 by PolyPhen/SIFT scores. Lane 1: sequence of human TGM2, Lane 2: damaging nsSNVs in human TGM2. Functional regions of human TGM2: Intrinsically disordered regions (dark red) [4], amino acid clusters in light blue [30], fibronectin binding sites (FN) (green) K30, R116, and H134 [31], GDP binding residues (orange) S171, K173, R476, R478, V479, R580, Y583 [32], catalytic residues (pink); non-canonical Ca²⁺-binding sites: S4: 149–159, S1: 228–236, S3A: 305–311, S3B: 326–333, S2A: 395–401, S5: 432–440, and S2B: 445–455 (underlined and bolded) [33]. Domains of human TGM2 are presented vertically: β sandwich (1–139), catalytic core (147–460), β-barrel 1 (472–583), and β-barrel 2 (584–687).

https://doi.org/10.1371/journal.pone.0172189.g001

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Table 1. Number of different single nucleotide variants and gene constraints in human transglutaminase genes.

https://doi.org/10.1371/journal.pone.0172189.t001

TGM1, TGM2 and F13a show evolutionary constraint to non-synonymous variants

In order to determine the constraint on a particular gene, mis_z scores were calculated for non-synonymous variations of each gene in the ExAC dataset [11]. The mis_z values for the transglutaminase nsSNVs are given in Table 1. Increased constraint is indicated by positive mis_z scores and decreased constraint with negative mis_z scores. TGM1, TGM2 and F13a had positive, highest mis_z scores and, therefore, they had fewer variants than expected but other members had negative mis_z scores indicating that they had more variants than expected (Table 1).

Recently, by using gene level approach, load of disease causing mutations and mutational damage on protein-coding human genes was estimated by gene damage index scores (GDI) [21]. The genes with low GDI score tend to be under strong purifying selection and biologically indispensable and thus harbor fewer mutations. But those with high GDI scores are under less purifying selective pressure and are likely biologically redundant with more mutations. Based on Phred I-score, the ranking of the gene of interest i relative to all other human genes (T = 19,558 genes used in the analyses in ref [21]) was also calculated to estimate the damaged human genes. Lowest Phred I-score refers to least damaged human gene with lowest GDI and highest Phred I-score refers to most damaged human gene. The GDI and GDI-Phred I values are listed for transglutaminases in Table 1. Among transglutaminases, TGM2 and TGM1 with lowest values are under strong selective pressure as they cannot tolerate more mutations. Mutations are tolerated by other transglutaminases, particularly TGM4 and F13a with highest Phred I-score. F13a is under less purifying selection based on the GDI values, but F13a deficiency results in bleeding disorder [34].

TGM2 and F13a have lowest ratio of damaging non-synonymous SNVs

The SIFT and polymorphism phenotyping scores provided in the ExAC database were used. According to SIFT analysis, F13a and TGM6 have lowest and highest ratios of damaging nsSNVs, respectively (data not shown). PolyPhen analysis revealed that TGM2 and F13a have the lowest, while TGM1 and TGM5 have the highest ratios of damaging nsSNVs (Fig 1B). Around 45% of nsSNVs in TGM2 are damaging and out of these 54% are concentrated in the catalytic core domain and 17% in the β-sandwich domain (Fig 1C).

Effect of damaging nsSNVs on TGM2 structure and function

The damaging nsSNVs affect the stability and biochemical functions of the native proteins [35]. We analyzed how rare PolyPhen or SIFT predicted damaging nsSNVs (indicated in Fig 1C) influence protein stability, secondary structure and functional sites including novel amino acid clusters, IDRs, SLiMs, and LC3 (microtubule-associated protein light chain) interacting regions (LIRs).

Occurrence of nsSNVs at intrinsically disordered regions embedding short linear motifs.

The sequences of many proteins contain short, loosely-defined protein interaction sites that mediate recognition and targeting activities and provide wide range of functionality to proteins [51]. These interaction sites are called Short Linear Motifs (SLiMs) composed of low complexity short peptide regions (3–20 residues long) which mediate post-translational modifications and protein-protein interactions. Mostly SLiMs are embedded in polypeptide segments that lack well-defined tertiary structure. These unstructured regions are referred to as intrinsically disordered regions (IDRs) and they are involved in diverse functions. About 22% of human disease mutations occur in intrinsically disordered regions [51]. Recently we reported 13 IDRs embedding 39 SLiMs in human TGM2 [4] and we looked for the presence of damaging nsSNVs in these regions. The damaging nsSNVs located in IDRs embedding SLiMs are given in Table 2. They target 8 IDRs embedding 27 SLiMs and most of the nsSNVs are concentrated in the IDRs 208–217, 411–414, and 428–473 located in the catalytic core domain (Table 2).

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Table 2. Damaging nsSNVs located in ID regions embedding SLiMs in TGM2.

https://doi.org/10.1371/journal.pone.0172189.t002

Occurrence of nsSNVs at LC3 interacting regions.

Autophagy was initially considered to be a nonselective process for bulk breakdown of cytosolic material. However, recent evidence points towards a selective mode of autophagy mediated by the so-called selective autophagy receptors [52]. Interaction between selective autophagy receptors and proteins of the autophagy-related protein 8 families are mediated by short linear sequence motifs called LIRs which ensures the targeting of autophagy receptors to LC3 or other autophagy-related protein 8 family proteins anchored in the phagophore membrane. The canonical LIR motif consists of a short tetrapeptide sequence WxxL (where x could be any residue), which interact with two distinct hydrophobic pockets of LC3 [52]. As TGM2 was shown to be involved in autophagy [53], SNVs in LIRs motifs could impact this process. LIR motifs and 11 damaging nsSNVs in TGM2 are shown in Table 3. Two damaging nsSNVs target xLIR motif ³⁵²EGWQAL³⁵⁷ and WxxL motifs are targeted by nine damaging nsSNVs (Table 3). Non-synonymous SNVs present within LIRs might have functional implications in autophagic process, given the role of TGM2 in autophagosome maturation [53] and its interaction with autophagy cargo proteins [54].

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Table 3. Damaging nsSNVs located in potential LC3 interacting regions.

https://doi.org/10.1371/journal.pone.0172189.t003

Population scale occurrence of non-synonymous SNV in TGMs

The influence of nsSNVs of proteins arising in the human population is significantly determined by their penetrance. The nsSNV allele counts in the population covered in the ExAC dataset are the highest for TGM3 and TGM4 (over 0.2 million) and lowest for TGM2 and TGM1 (2601 and 5174, respectively) (Table 4). Common variants are typically defined as those found with > 5% allele frequency and rare variants as those found with < 0.5% allele frequency [55]. The F13a, TGM3, TGM4, TGM5, and TGM6 have common nsSNV variants, TGM1 and TGM7 nsSNV variants occur in frequencies less than 5%. The allele frequency value for the three most frequent variants in case of each family member is showed in Fig 2. All the TGM2 nsSNVs were rare with allele frequency values less than 0.5%. The TGM2 nsSNV with highest allele frequency values are p.Arg76His (0.47%), p.Val542Phe (0.38%), p.Glu366Lys (0.11%), p.Arg433Gln (0.10%) and p.Glu469Gly (0.10%); of these only p.Val542Phe has potentially damaging PolyPhen score.

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Fig 2. Allele frequencies of three most frequent non-synonymous variants in transglutaminase family genes.

Values were calculated based on the ExAC database. For each family, nsSNVs with top three allele frequency (%) values are shown. F13a: p.Pro565Leu (21%), p.Glu652Gln (20.8%), p.Val35Leu (20.6%); TGM1: p.Val518Met (1.04%), p.Glu520Gly (0.56%), p.Ser42Tyr (0.40%); TGM2: see in text; TGM3: p.Gly654Arg (28.7%), p.Thr13Lys (19%), p.Ser249Asn (11.2%); TGM4: p.Glu313Lys (49%), p.Val409Ile (44.7%), p.Arg372Cys (42.8%); TGM5: p.Ala352Gly (14.8%), p.Val504Met (1.4%), p.Gln521Arg (1.25%); TGM6: p.Met58Val (9.2%), p.Arg448Trp (2.80%), p.Ala141Glu (0.9%); TGM7: p.Pro564Leu (3.4%), p.Val103Leu (1.07%), p.Val515Leu (0.82%).

https://doi.org/10.1371/journal.pone.0172189.g002

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Table 4. Summary of population frequencies of nsSNVs alleles of transglutaminases in the ExAC database covering 60,706 individuals.

https://doi.org/10.1371/journal.pone.0172189.t004

Homozygous occurrence of TGM2 non-synonymous SNVs

Since damaging TGM2 nsSNVs occur at some functional sites of the protein we have decided to screen databases to see whether homozygous occurrence of nsSNVs is tolerated by individuals as compared to nsSNV variants of the other transglutaminase family members. Furthermore, we wanted to learn how the protein products of TGM2 nsSNVs alleles found in homozygotes function in biochemical tests.

The current ExAC dataset contains the revealed existing homozygous nsSNVs for transglutaminase family members (Table 4). TGM3, TGM4, and TGM6 have the highest (in the range of 47 to 73 thousands), while TGM2, TGM1, and TGM7 have the lowest (12, 25, and 170 respectively) numbers of such homozygous occurrences (Table 4). The number of nsSNV alleles associated with the homozygotes is lowest for TGM2 and F13a. There are only six TGM2 nsSNVs which occur all together in 12 individuals in homozygous form in various populations in the World, by far the lowest number in the TGM family (Table 5). Amidst these, three nsSNVs have probably damaging PolyPhen scores (p.Arg222Gln, p.Val542Phe and p.Pro612Thr), p.Pro612Thr is destabilizing in both closed and opened conformations, whereas p.Val542Phe and p.Asp671Asn mostly affect the closed conformation (Table 5).

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Table 5. The 12 human TGM2 homozygotes related to 6 nsSNVs.

https://doi.org/10.1371/journal.pone.0172189.t005

Biochemical analysis of homozygous non synonymous TGM2 variants

Since homozygous nsSNVs can be associated with various diseases we analyzed the functional impact of TGM2 homozygous nsSNVs. We produced all the six homozygous occurring TGM2 variants containing the respective nsSNVs by site directed mutagenesis and tested them in biochemical assays. We measured transglutaminase activity of the variants using two previously published kinetic assays [17, 56]. Except p.Arg222Gln, the transamidase activity of variants is comparable in the two assays. p.Arg222Gln was completely active in amine incorporation assay but inactive in the protein crosslinking assay (Fig 3). The variant p.Arg76His showed increase in transamidase activity compared to the wild type enzyme and variant p.Val542Phe showed 40% less activity than wild type TGM2 in both assays. Compared to the wild type, p.Pro612Thr variant showed 40% less activity in the amine incorporation assay but only 18% less activity in the protein crosslinking assay. Interestingly both p.Val542Phe and p.Pro612Thr variants have predicted damaging PolyPhen/SIFT scores (Table 5). Calcium dependence of the transamidase reaction was also measured based on the amine incorporation assay (Fig 3). Variant p.Arg76His exhibited high transamidase activity and variants p.Val542Phe, p.Pro612Thr had less activity than wild type at both measured Ca²⁺ concentrations (Fig 3). Variants p.Arg433Gln, p.Asp671Asn manifested a several fold increase in transamidase activity compared with wild type at 0.25 mM Ca²⁺ concentration. Variant p.Arg222Gln showed the lowest efficiency at 0.25 mM calcium concentration, increasing of which restored activity. It is known that Ca²⁺ and nucleotides reciprocally regulate transglutaminase reactions. The nucleotide binding of the variants were examined using an analog, BODIPY FL GTPγS. At 250 nM enzyme concentration, 18% higher GTP binding was observed for p.Arg76His and p.Asp671Asn than wild type and 24% lower GTP binding in case of p.Pro612Thr (Fig 3).

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Fig 3. Biochemical characterization of the six homozygous nsSNVs of TGM2.

Kinetic characterization of the transamidase activity of TGM2 variants and wild type at 3 mM CaCl₂ concentration using amine incorporation assay [56] and protein crosslinking assay [17]. Calcium dependence of kinetic transamidase reaction with 0.25 and 1 mM calcium concentrations using amine incorporation assay. Comparison of the kinetic isopeptidase activity of TGM2 variants at 5 mM CaCl₂ concentration using Zedira assay and crosslinked protein substrate [18]. The relative activities are calculated as a percentage of the activity values of the wild type TGM2. Comparison of BODIPY FL GTPγS binding of variants and wild type TGM2 proteins with different concentrations of TGM2 (50 and 250 nM). The change in the fluorescence intensity (Ex/Em: 485/520 nm) was determined after 15 minutes of incubation. Binding is shown as a percentage of maximum binding in case of wild type TGM2 [29]. The Fibronectin binding property of the TGM2 variants was tested using a previously published direct ELISA assay [16]. Data are presented as means with ± standard deviations from three separate experiments done in triplicate. All the data were analyzed by GraphPad Prism 7.

https://doi.org/10.1371/journal.pone.0172189.g003

TGM2 also possess isopeptidase activity when previously formed isopeptide bonds are cleaved. The isopeptidase activity of the six variants was also compared using a commercially available small chemically produced substrate and a recently published protein based real-time kinetic method [18]. The p.Arg222Gln variant is only 15% active in the commercial Zedira assay and completely inactive in the protein based method (Fig 3). Compared to wild type, the variants p.Val542Phe and p.Pro612Thr showed less isopeptidase activity in the Zedira assay but normal activity in the protein based method. While variants p.Arg76His, p.Asp671Asn showed increase in activity compared to the wild type in both the assays. Since interaction of TGM2 with fibronectin has a crucial role in scaffolding processes in the extracellular matrix of the cells, the fibronectin-binding property of the variants was tested by an ELISA method. The variants p.Val542Phe, p.Pro612Thr showed 15% less fibronectin binding but other variants bound fibronectin similarly to the wild type enzyme (Fig 3).

Homozygous variants p.Arg76His and p.Asp671Asn with high transamidase, isopeptidase activities and GTP binding ability do not coincide with any of the functional sites, predicted IDRs, novel clusters and have benign or tolerated scores. The p.Arg433Gln variant with almost normal activity compared to wild type is part of the Ca²⁺ binding site S5 (432–440) and IDR (428–473) embedding SLiMs like USP7 binding motif, TRAF2 binding motif, and CK1 and CK2 phosphorylation motif. A PolyPhen damaging variant with decreased activity is p.Val542Phe located within the MOD CK1 phosphorylation site and MOD PLK site phosphorylated by polo like kinases. Another potentially damaging variant p.Pro612Thr with less transamidase, isopeptidase and GTP binding is near to an IDR (597–602) and a novel amino acid cluster PVA (613–615) [30]. The homozygous variant p.Asp671Asn is located in the C-terminal class 3 PDZ-binding motif.

The PolyPhen damaging variant p.Arg222Gln, located to the catalytic core domain near Ca²⁺ binding site S1 (226–233) and the SLiM, STAT5 Src Homology 2 (SH2) domain binding motif, has very low transamidase activity at physiological Ca²⁺ concentration. Moreover, the isopeptidase activity of this variant is completely lost. To assess the effect of the p.Arg222Gln allele on the structure we compared the situations where of the calcium binding sites none, only site 1, or all three are occupied by metal using the existing crystal structures and newly built homology models of TGM2 (Fig 4). We attribute the observed behavior of the Q222 variant to a disrupted H-bond network that leads to altered conformation of the loop, P359-G372, and consequently to reduced calcium affinities at site 1 and 2, and to a topology which disfavors proper interaction with a protein amine donor. Taken together, biochemical data demonstrates that only one of the very rarely occurring homozygous nsSNVs containing variant of TGM2 lead to significant decrease of one of its basic functional properties.

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Fig 4. Structural interpretation of the effect of the p.Arg222Gln variation on enzyme activity.

We analyzed the interactions of R222 in a homology model of TGM2 containing three bound calcium ions (pink spheres), which supposedly corresponds to the active form (cyan: N-terminal, grey: catalytic, green and red: first and second beta barrel domains respectively). The squared area in the left panel is magnified on the right. R222 is located in the middle of the solvent accessible surface of the α-helix leading up to calcium binding site S1 (226–233). R222 is at the core of an H-bond network (light blue dashed lines) that serves to bundle neighboring structural elements of TGM2 together. Upon binding of calcium to site 1, H-bonds between E232, N229 and backbone atoms of Y369, and H-bonds of R222 to S365, E366, G372, and D389 cooperatively tether the flexible loop, P359-G372. The changing conformation of this loop leads to reorganization of another non-covalent interaction network near calcium binding site 2, including a directly calcium binding residue, N306, for metal binding, and to honing of the charge relay duad, E305-E363 that has recently identified importance for catalysis [26]. The Q222 variant (wheat) fails to establish the critical H-bonds with S365, E366, and E389, thus the calcium binding of both sites are impaired and the charge relay system is also negatively affected. The same loop, most probably, also contributes residues to the amine substrate binding surface and controls access to the active site (C277/H335/D358), likely explaining that the Q222 enzyme has conserved transamidase activity for a small molecular amine, but compromised cross-linking activity towards a protein amine donor and lost isopeptidase activity for a protein-peptide conjugate.

https://doi.org/10.1371/journal.pone.0172189.g004

Heterozygous and homozygous LOF variants of TGMs

The very rare generation of damaging nsSNVs alleles of TGM2 in humans and the observation that even the so far found homozygous TGM2 nsSNVs keep their basic biochemical properties (with one exception with decreased activities), prompted us to check the population frequency of its LOF variants compared to the other genes. Disease causing TGM2 LOF variants have not been reported so far in humans. Neither TGM2 nor the other TGMs are among the 3230 genes of the ExAC database which are unable to function normally after loss of one copy of the gene, even if the other copy is intact (haploinsufficiency) [11]. In general, large-scale sequencing projects revealed a surprisingly large number of LOF variants and fully knocked out (homozygous or compound heterozygous) genes in genomes of healthy individuals [57]. We compiled the LOF variants of transglutaminase family members from different populations with available data (S2 Table). Heterozygous LOF variants for all the transglutaminases were identified in the dataset of the Atherosclerosis Risk in Communities (ARIC) cohort study (S2 Table) [58]. In the ExAC dataset (where full knock outs can be found), LOF heterozygotes were identified for all the members of the family but in homozygous form only for TGM4 and TGM6 [11]. Transglutaminase LOF variants with highest allele frequency values were observed for TGM4 (0.83%) and F13a (0.24%) while the LOF (MAF) values were very low for the others: TGM1 (0.03%), TGM2 (0.015%), TGM3 (0.003%), TGM5 (0.006%), TGM6 (0.04%), TGM7 (0.017%). Exon sequencing data from 185 individuals as part of the pilot phase of the 1000 Genomes Project was analyzed and 2951 LOF variants, rare and likely deleterious LOF alleles (including 26 known and 21 predicted severe disease-causing variants) were reported [57]; this dataset contains a homozygous TGM6 LOF variant. A list of autosomal genes that are completely knocked out in the Icelandic bottlenecked population by rare LOF mutations have been published [10]; these data show that 7.7% (1171) of protein coding genes are completely knocked out by loss-of-function variants including TGM1, TGM4, and TGM5 (S2 Table). Recently, 3222 exomes of British adults of Pakistani heritage, a consanguineous population, was sequenced and 1111 rare gene knockouts in 781 genes were identified finding one homozygous TGM4 LOF variant [12]. A homozygous TGM4 LOF variant was also identified in the Simons Simplex Collection (SSC) dataset, a project aimed to improve the understanding and research of autism spectrum disorders [59]. TGM2, TGM3, and TGM7 LOF variants in homozygous or compound heterozygous form have not been identified in any of these datasets.

Summary of transglutaminase mutations listed in OMIM database

Allelic variations responsible for human inherited diseases are listed in the Online Mendelian Inheritance in Man (OMIM) database, an Online Catalog of human genes and genetic disorders. We collected OMIM data for transglutaminase family which is shown in S3 Table. F13a autosomal recessive mutations lead to F13a deficiency [60, 61, 62], TGM1 has disease causing mutations in autosomal recessive congenital ichthyosis [63, 64], TGM5 homozygous LOF mutations cause acral peeling skin syndrome [65, 66, 67] and TGM6 mutations are associated with spinocerebellar ataxia 35 [68]. Data have not been found for inherited disease related to TGM2, TGM3, TGM4, and TGM7 mutations.