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INVESTIGATION Surrogate Genetics and Metabolic Profiling for Characterization of Human Disease Alleles Jacob A. Mayfield,*,1 Meara W. Davies,*,2 Dago Dimster-Denk,* Nick Pleskac,† Sean McCarthy,* Elizabeth A. Boydston,*,3,4 Logan Fink,*,3 Xin Xin Lin,*,3 Ankur S. Narain,*,3,5 Michael Meighan,‡ and Jasper Rine*,6 *Department of Molecular and Cell Biology, California Institute of Quantitative Biosciences, University of California, Berkeley, California 94720, †Berkeley High School, Berkeley, California 94704, and ‡University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, California 94720 ABSTRACT Cystathionine-b-synthase (CBS) deficiency is a human genetic disease causing homocystinuria, thrombosis, mental retardation, and a suite of other devastating manifestations. Early detection coupled with dietary modification greatly reduces pathology, but the response to treatment differs with the allele of CBS. A better understanding of the relationship between allelic variants and protein function will improve both diagnosis and treatment. To this end, we tested the function of 84 CBS alleles previously sequenced from patients with homocystinuria by ortholog replacement in Saccharomyces cerevisiae. Within this clinically associated set, 15% of variant alleles were indistinguishable from the predominant CBS allele in function, suggesting enzymatic activity was retained. An additional 37% of the alleles were partially functional or could be rescued by cofactor supplementation in the growth medium. This large class included alleles rescued by elevated levels of the cofactor vitamin B6, but also alleles rescued by elevated heme, a second CBS cofactor. Measurement of the metabolite levels in CBS-substituted yeast grown with different B6 levels using LC–MS revealed changes in metabolism that propagated beyond the substrate and product of CBS. Production of the critical antioxidant glutathione through the CBS pathway was greatly decreased when CBS function was restricted through genetic, cofactor, or substrate restriction, a metabolic consequence with implications for treatment. T HE first complete human genome sequence seeded the defining challenge of human genetics for the foreseeable future: interpreting the impact of variations in the sequences Copyright © 2012 by the Genetics Society of America doi: 10.1534/genetics.111.137471 Manuscript received December 5, 2011; accepted for publication January 9, 2012 Supporting information is available online at http://www.genetics.org/content/ suppl/2012/01/20/genetics.111.137471.DC1. Reference numbers for publicly available data; GenBank: L14577.1 (CBS); dbSNP: rs17849313 (A69P), rs2229413 (P70L), rs11700812 (R369P); SGD: YGR155W (CYS4) and YDR232W (HEM1). 1 Present address: Department of Veterinary and Animal Science, 470 Integrated Sciences Bldg., University of Massachusetts, Amherst, MA 01002. 2 Present address: Department of Genome Sciences, Foege Bldg. S-250, Box 355065, 3720 15th Ave NE, University of Washington, Seattle, WA 98195-5065. 3 These authors contributed equally to this work. 4 Present address: Department of Cellular and Molecular Pharmacology, 403B Byers Hall, Howard Hughes Medical Institute, California Institute of Quantitative Biosciences, University of California, San Francisco, CA 94158. 5 Present address: National Institute of Child Health and Human Development, Bldg. 6, Rm. 2A01, 6 Center Dr. 2753, Laboratory of Molecular Growth Regulation, National Institutes of Health, Bethesda MD 20892-275. 6 Corresponding author: Department of Molecular and Cell Biology, 374A Stanley Hall, California Institute of Quantitative Biosciences, University of California, Berkeley, CA 94720. E-mail: [email protected] of individual human genomes. Comparative genome sequencing reveals an average of one single-nucleotide change per 1200 bp between any two individuals. In the absence of strong Mendelian inheritance and linkage, confirming that any human genotype actually caused a phenotype is a significant challenge given the approximately 3 million genetic variants per person. Indeed, 4000 traits of medical interest show evidence for inheritance but lack a clear determinant (Online Mendelian Inheritance in Man 2012). Next-generation sequencing within small pedigrees (Ng et al. 2010a,b; Fan et al. 2011), or a more narrowly defined clinical phenotype (Schubert et al. 1997), can sometimes disentangle the underlying contribution of a gene to disease. In this work we have taken an approach that complements both increased sequencing capacity and expanded phenotypic description. We used surrogate genetics to assay directly the function of allelic variants and then evaluate their potential contribution to phenotypes of clinical importance. Homocystinuria, elevated levels of the sulfur-containing metabolite homocystine in the urine, illustrates several Genetics, Vol. 190, 1309–1323 April 2012 1309 challenges inherent to elucidating the molecular bases of human genetic diseases. Worldwide, 1 in 335,000 individuals are affected (Mudd et al. 1995), but the frequency approaches 1 in 1800 in certain populations (Gan-Schreier et al. 2010). A few well-characterized alleles of the gene encoding cystathionine b-synthase (CBS) correlate with disease symptoms, providing an appealing molecular mechanism. The enzyme CBS converts homocysteine to cystathionine in the cysteine biosynthesis pathway (Supporting Information, Figure S1). In people with homocystinuria, free homocysteine accumulates and can covalently bind to proteins or oxidize to the dimer homocystine. Disease indicators include homocystinuria or hyperhomocysteinemia, an abnormally high concentration of serum total homocysteine, the sum of free, oxidized, and protein-bound forms. CBS catalyzes a committed step in the pathway that produces cysteine and ultimately glutathione, the major endogenous intracellular antioxidant. Upstream of CBS, homocysteine is an intermediate in the pathway that recycles S-adenosylmethionine (AdoMet), the major methyl donor in the cell, back to methionine. The wide range of symptoms may reflect the fact that CBS and its variants have the potential to alter regulatory methylation of DNA and histones, as well as the redox state of the cell. Yet, elevated homocysteine levels occur in many people, including heterozygotes for some CBS alleles, without any clinical symptoms (Motulsky 1996; Guttormsen et al. 2001). Additionally, defects in several different genes tangential to cysteine biosynthesis, such as MTHFR, can lead to homocysteinemia and similar symptoms (Frosst et al. 1995; Gaughan et al. 2001; Pare et al. 2009). Hence, elevated homocysteine level is a convenient marker for a metabolic imbalance, but the cause and consequences may be elusive. The genetic contributions are complex, but because early medical intervention, including a diet low in protein and methionine, successfully alleviates many homocystinuria symptoms, neonatal screening is widespread (Mudd et al. 2001). Vitamin supplementation can replace dietary restriction as a therapy in a highly allele-dependent manner. CBS uses a vitamin B6 cofactor to form cystathionine by the condensation of serine and homocysteine. Hence, elevated B6 is thought to partially compensate for vitamin-responsive alleles with a lower affinity for the B6 cofactor (Chen et al. 2006). Human CBS also forms multimers, coordinates heme with a bound iron, and contains a regulatory domain that binds the metabolite AdoMet as a possible regulatory mechanism (Shan and Kruger 1998; Meier et al. 2001; Christopher et al. 2002; Scott et al. 2004; Chen et al. 2006; Sen and Banerjee 2007). These features suggest control points for enzyme regulation and function, or targets for nutritional and pharmaceutical therapies, that CBS alleles may affect differently. Directed sequencing efforts of patients afflicted with homocystinuria have produced a large catalog of alleles (Kraus et al. 2012), with both common and rare alleles (Mudd et al. 1985; Kraus 1994; Gallagher et al. 1995, 1998). However, clinical association does not guarantee cau- 1310 J. A. Mayfield et al. sality. In many cases, the sequenced alleles are further analyzed by genetic or biochemical means, providing most of our knowledge of CBS deficiency. Despite these heroic efforts, the piecemeal identification of alleles, variations in assessment strategies, diploid nature of the human genome, and increasing numbers of rare alleles all lead to uncharacterized alleles that may cause subtle, but important, differences in phenotype. As ever more CBS alleles are found, the need for reliable measures of allele impact will increase. CYS4 is the Saccharomyces cerevisiae ortholog of CBS and has the same function in yeast as in humans (Ono et al. 1988). Although yeast Cys4p lacks a heme binding domain and may differ in details of its biochemical regulation, human CBS complements cys4 yeast for cysteine and glutathione production (Kruger and Cox 1994, 1995). Furthermore, nonfunctional or B6-remedial CBS alleles recapitulate their human phenotypes in yeast cys4 mutants (Kim et al. 1997; Shan and Kruger 1998). We took advantage of the foundation built by previous, elegant cross-species complementation experiments (Kruger and Cox 1994, 1995) to develop a quantitative, comprehensive, and direct test of how variation in a single human disease gene correlated with disease and treatment via nutritional supplementation. Materials and Methods Plasmids The plasmid pHUCBS was the kind gift of Warren Kruger and served as the template for generating alternative CBS alleles using the QuikChange II Kit (Agilent). We selected single-base pair missense mutations from the CBS Mutation Database (Kraus et al. 1999, 2012), from published literature, and from the RefSeq database for A69P (rs17849313), P70L (rs2229413), and R369P (rs11700812). We verified the sequence of the entire open reading frame of each allele (Table 1). The pHUCBS plasmid and all subsequent clones contain a single, silent base pair change (909C . T) relative to the RefSeq sequence for CBS (L14577.1). A BstEII/FseI fragment containing CBS variants was subcloned between the S. cerevisiae TEF1 promoter and CYC1 terminator in pJR2983, a CEN–ARS URA3 shuttle plasmid. Strains All S. cerevisiae strains serving as a host for a human CBS allele contained a complete deletion of CYS4 (MATa cys4D:: KanMX his3D1 leu2D0 lys2D0 ura3D0, JRY9292) derived from the yeast knockout collection (Winzeler et al. 1999). A hem1 cys4 strain was created by disruption of HEM1 with LEU2 (hem1Δ::LEU2). CBS transformants were selected by uracil prototrophy. Growth assays Strains containing CBS plasmids were maintained on complete synthetic medium lacking uracil (CSM-Ura) and supplemented with glutathione, a stable source of cysteine. cys4 complementation was assayed by growth on solid CSM-Ura medium without glutathione and with 400 ng/ml vitamin B6 (pyridoxine–HCl). CBS alleles that complemented cys4 were further characterized in a quantitative growth assay using a minimal liquid medium made with yeast nitrogen base lacking vitamin B6 or other vitamins and amino acids (MP Biomedicals). Vitamins (biotin, pantothenate, inositol, niacin, p-aminobenzoic acid, riboflavin, and thiamin) were included at standard concentrations, and vitamin B6 was supplemented at six different concentrations: 0, 0.5, 1, 2, 4, and 400 ng/ml B6. Histidine, leucine, and lysine were added to relieve auxotrophies in the parent strain, and methionine was included in all minimal media. Growth rate assays used 250 ml volumes and started with cells at OD600 = 0.002, inoculated from cells pregrown in minimal medium that lacked B6 and contained glutathione. The pregrowth medium in the hem1 experiments contained 50 mg/ml d-aminolevulinc acid (d-ALA) and the cells were washed twice with minimal medium to prevent carry-over. For the sake of clarity, we refer to supplementation with the soluble heme precursor d-ALA as “heme supplementation” in the text. Heme is sparingly soluble and d-ALA supplementation was more efficient. The optical density (A600 nm) was measured every 30 min for 96 hr at 28 in a stationary microplate reader (Molecular Devices VersaMax). We accounted for settling of the cells over time by resuspending the cells after the final kinetic read and measuring the OD600 value. Data were then normalized using the time-weighted ratio of the endpoint kinetic OD600 value to the resuspended OD600 value, according to the formula, Endpoint kinetic OD time point 21 þ 1; Resuspended OD final time point and were log10 transformed. Due to the stationary-phase ceiling, growth rate better described the growth of alleles than end-point measurement. Growth rate was calculated as the slope of the regression line for data values between OD600 = 0.05 and OD600 = 0.1. Data were compared to the major allele grown in the same medium on the same plate. Outliers were detected using Grubb’s test and removed from growth rate calculations. The raw growth rate data are available as File S1. Immunoblots for CBS protein quantification The total protein concentration of boiled, NaOH-extracted yeast pellets was measured using the Pierce BCA Protein Assay Kit (Thermo Scientific) to normalize sample concentrations. Proteins were visualized on an Odyssey Infrared Imager (Li-COR Bioscience) after separation on a denaturing gel. Mouse anti-CBS polyclonal antibody (Abnova H00000875-A01), a rabbit anti-3-phosphoglycerate kinase (PGK) antibody (a gift from Jeremy Thorner, University of California Berkeley) and an anti-proliferating cell nuclear antigen (PCNA) antibody (Abcam ab70472) were used to detect target proteins. Metabolite measurements Cells were cultured in liquid minimal medium that contained glutathione before washing with, and inoculation into, minimal medium lacking glutathione. Equal numbers of cells from log-phase cultures were harvested 12 hr after inoculation. Metabolite extraction combined previously described methods (Canelas et al. 2008; Boer et al. 2010; Godat et al. 2010) as follows: 8.0 · 108 (G307S data set) or 1.9 · 109 (V320A data set) cells were pelleted by centrifugation at 3200 · g. The cell pellets were resuspended with 9.5 ml of their spent medium supernatant, then quenched with 20 ml 280 methanol. The cells were pelleted at 4000 · g at 210 in a rotor (Sorvall SS-34), prechilled to 280, and then resuspended with 1.0 ml of 4 extraction solvent [0.1% perchloric acid with 400 mM glycine-1-13C,15N (Sigma 299340) and 20 mM isotopically labeled methionine-13C5,15N (Sigma 608106)]. The samples were boiled for 5 min, and cell debris and precipitated proteins were removed by centrifugation for 2 min at 4000 · g in a 4 microfuge. The supernatants were diluted 1:4 in 0.1% perchloric acid and 0.1% formic acid. Liquid chromatography–mass spectrometry (LC–MS) analysis used 20-ml injection volumes. Chromatographic separation (2.1 · 250 mm, 5 mm Discovery HS-F5 column; Supelco) used a water-to-acetonitrile gradient (Godat et al. 2010) and was followed by detection on an LTQ-Orbitrap XL hybrid mass spectrometer equipped with an IonMax electrospray ionization source (Thermo Fisher Scientific, Waltham, MA). For the G307S data set, a fourfold dilution series of a mixture of 17 metabolite standards was added to a pooled cell extract that contained equal volumes from each experimental sample, and was then used for metabolite identification and calibration. A full calibration panel was included in the V320A experiment, but was not added to a pooled standard. LC–MS data were converted to centroids and the mzXML file format using ReAdW 4.3.1 (Deutsch et al. 2010) with an Xcalibur library (ThermoFisher Scientifics, v. 2.0.7). Peak processing used the BioConductor package XCMS (Smith et al. 2006; Tautenhahn et al. 2008); processed data are available as File S2. Metabolites were identified using the pooled calibration standards and the Human Metabolome Database (Wishart et al. 2009) for the G307S study and by exact mass only for the V320A analysis. Zeros in the data were imputed using local minima, data were normalized using upper quartiles, and intensities were log transformed for analysis using R (scripts and centroided data files are provided as File S3). Results The surrogate assessment of clinically associated CBS alleles in Saccharomyces cerevisiae We selected all alleles of CBS documented prior to 2011 that could be generated by a single base-pair change and that affected an amino acid (Table 1). Each human CBS allele was synthesized, inserted into a yeast plasmid, and individually Surrogate Genetics of Human CBS Mutations 1311 Table 1 CBS alleles tested for function in yeast Mutation pJR Protein cDNA Initial citation and clinical characterization, or RefSeq number pJR3044 pJR3045 pJR3046 pJR3047 pJR3048 pJR3049 pJR3050 pJR3051 pJR3052 pJR3053 pJR3054 pJR3055 pJR3056 pJR3057 pJR3058 pJR3059 pJR3060 pJR3061 pJR3062 pJR3063 pJR3064 pJR3065 pJR3066 pJR3067 pJR3068 pJR3069 pJR3070 pJR3071 pJR3072 pJR3073 pJR3074 pJR3075 pJR3076 pJR3077 pJR3078 pJR3079 pJR3080 pJR3081 pJR3082 pJR3083 pJR3084 pJR3085 pJR3086 pJR3087 pJR3088 pJR3089 pJR3090 pJR3091 pJR3092 pJR3093 pJR3094 pJR3095 pJR3096 pJR3097 pJR3098 pJR3099 pJR3100 pJR3101 H65R A69P P70L P78R G85R T87N P88S L101P K102Q K102N C109R A114V G116R R121C R121H R121L M126V E128D E131D G139R I143M E144K P145L G148R G151R I152M G153R L154Q A155T A155V A158V C165Y V168M E176K V180A T191M D198V R224H A226T N228S N228K D234N E239K T257M G259S T262M R266G R266K C275Y I278T A288T A288P P290L E302K G307S V320A A331E A331V 194A . G 205G . C 209C . T 233C . G 253G . C 260C . A 262C . T 302T . C 304A . C 306G . C 325T . C 341C . T 346G . A 361C . T 362G . A 362G . T 376A . G 384G . T 393G . C 415G . A 429C . G 430G . A 434C . T 442G . C 451G . A 456C . G 457G . C 461T . A 463G . A 464C . T 473C . T 494G . A 502G . A 526G . A 539T . C 572C . T 593A . T 671G . A 676G . A 683A . G 684C . A 700G . A 715G . A 770C . T 775G . A 785C . T 796A . G 797G . A 824G . A 833T . C 862G . A 862G . C 869C . T 904G . A 919G . A 959T . C 992C . A 992C . T Janosik et al. (2001b) rs17849313 rs2229413 de Franchis et al. (1994) Maclean et al. (2002) Kraus et al. (2012) Sebastio et al. (1995) Gallagher et al. (1998) Kozich et al. (1997) de Franchis et al. (1994) Gaustadnes et al. (2002) Kozich et al. (1993) Sperandeo et al. (1996) Katsushima et al. (2006) Bermudez et al. (2006); Katsushima et al. (2006) Kraus et al. (2012) de Franchis et al. (1999) Coude et al. (1998) Marble et al. (1994) Shih et al. (1995) Orendae et al. (2004) Shih et al. (1995) Kozich et al. (1993) Orendae et al. (2004) Kraus et al. (2012) Kraus et al. (2012) Kraus et al. (2012) Lee et al. (2005) Janosik et al. (2001b) Lee et al. (2005) Shan and Kruger (1998) Kluijtmans et al. (1995) Kraus et al. (2012) Kozich et al. (1997) Kluijtmans et al. (1999) Urreizti et al. (2003) Kraus et al. (2012) Kruger and Cox (1995) Kruger et al. (2003) Kruger et al. (2003) Gallagher et al. (1998) De Lucca and Casique (2004) de Franchis et al. (1994) Sebastio et al. (1995) Kraus et al. (2012) Kim et al. (1997) Katsushima et al. (2006) Kim et al. (1997) Urreizti et al. (2003) Kozich and Kraus (1992) Lee et al. (2005) Linnebank et al. (2004) De Lucca and Casique (2004) Sperandeo et al. (1996) Hu et al. (1993) Kim et al. (1997) Dawson et al. (1997) Kruger and Cox (1995) (continued) 1312 J. A. Mayfield et al. Table 1, continued Mutation pJR Protein cDNA pJR3102 pJR3103 pJR3104 pJR3105 pJR3106 pJR3107 pJR3108 pJR3109 pJR3110 pJR3111 pJR3112 pJR3113 pJR3114 pJR3115 pJR3116 pJR3117 pJR3118 pJR3119 pJR3120 pJR3121 pJR3122 pJR3123 pJR3124 pJR3125 pJR3126 pJR3127 R336H G347S S349N S352N T353M V354M A355P A361T R369C R369H R369P C370Y V371M D376N R379W K384E K384N M391I P422L T434N I435T R439Q D444N L456P S466L Q526K 1007G . A 1039G . A 1046G . A 1055G . A 1058C . T 1060G . A 1063G . C 1081G . A 1105C . T 1106G . A 1106G . C 1109G . A 1111G . A 1126G . A 1135C . T 1150A . G 1152G . T 1173G . A 1265C . T 1301C . A 1304T . C 1316G . A 1330G . A 1367T . C 1397C . T 1572C . A transformed into a cys4 yeast strain lacking the CBS ortholog CYS4. Centromere-based vectors were used to reduce copynumber variation. Eighty-one alleles derived from patients with homocystinuria plus three additional variants found in public databases were assayed. This collection of 84 missense mutations included alterations in the heme-binding, catalytic, and AdoMet-binding regulatory domains of the CBS protein. This strain could not grow on minimal media, but the defect in cysteine biosynthesis was bypassed by the addition of cysteine or the more stable downstream metabolite glutathione. Critically, the endogenous CYS4 gene supports more robust growth than any CBS allele, suggesting that CBS function was rate-limiting in yeast. Therefore, all assays necessarily compared CBS alleles to the major allele of human CBS (major allele, MA), not to CYS4 (Figure 1 and Figure S2). We discriminated functional from nonfunctional CBS alleles by plating cells onto media containing or lacking glutathione: only CBS alleles that restored CYS4 function supported growth on either medium. Of the 84 alleles, 46 required glutathione supplementation to support growth, indicating severe loss of function (listed as “nonfunctional” in Table 2). Disease alleles often encode misfolded proteins (Yue et al. 2005), and there is precedence for lower protein levels among some nonfunctional CBS alleles due to aggregation (Katsushima et al. 2006) or degradation (de Franchis et al. 1994; Urreizti et al. 2006; Singh et al. 2007, 2010). Nonetheless, while we inferred misfolding or aggregation of Initial citation and clinical characterization, or RefSeq number Coude et al. (1998) Gaustadnes et al. (2002) Urreizti et al. (2003) Dawson et al. (1997) Dawson et al. (1997) Coude et al. (1998) Gallagher et al. (1998) Castro et al. (1999) Kim et al. (1997) Kraus et al. (2012) rs11700812 Tsai et al. (1997) Kluijtmans et al. (1999) Kruger et al. (2003) Linnebank et al. (2004) Aral et al. (1997) Kraus et al. (2012) Kraus et al. (2012) Maclean et al. (2002) Kraus et al. (2012) Maclean et al. (2002) Dawson et al. (1997); Tsai et al. (1997) Kluijtmans et al. (1996) Urreizti et al. (2003) Janosik et al. (2001a) Kruger et al. (2003) some CBS proteins, degradation may differ in yeast and human cells, perhaps because an appropriate E3 ligase is missing. We observed ample steady-state levels of the CBS protein encoded by 17/17 different human CBS alleles, representative of different growth classes, regardless of B6 availability, as determined by immunoblot (Figure 2, Figure S3, and Table 2). Hence, our data measured the effect of mutations on the intrinsic functions of the enzyme without complication from protein turnover. Although many of the alleles tested were identified in individuals with clinically significant homocysteinemia, 38 CBS alleles were capable of supporting growth on medium lacking glutathione and hence retained substantial function (alleles that are not listed as nonfunctional in Table 2). These Figure 1 Growth of CBS-complemented yeast on solid media. Cultures grown to saturation in liquid minimal medium containing glutathione and lacking B6 were plated in a fivefold dilution series onto solid medium 6 glutathione. Growth was imaged after 3 days at 30. The growth of the major allele and representative alleles of the nonfunctional and B6-responsive classes are shown. Surrogate Genetics of Human CBS Mutations 1313 Table 2 Summary of clinical and yeast phenotypes Mutation Clinical Response to B6 Enzyme activity H65R A69P P70L Nonvariable NA NA Lowa P78R G85R T87N P88S L101P K102N K102Q C109R A114V G116R R121C R121L R121H M126V E128D E131D G139R I143M E144K P145L G148R G151R I152M G153R L154Q A155T A155V A158V C165Y V168M E176K V180A T191M D198V R224H A226T N228S N228K D234N E239K T257M G259S T262M R266G R266K C275Y I278T A288P A288T P290L E302K G307S V320A Variable Partial response ND ND Conflicting Variable ND Conflicting Conflicting Variable ND ND Nonvariable Nonvariable Nonvariable Nonvariable Variable Nonvariable Conflicting Nonvariable Nonvariable ND Conflicting NA NA Conflicting NA NA Conflicting ND Nonvariable Variable Nonvariable Nonvariable ND Variable Nonvariable Nonvariable Nonvariable Variable Nonvariable ND Nonvariable Nonvariable Variable Nonvariable Conflicting NA NA Variable Conflicting Conflicting Conflicting Meda,b Lowc A331E A331V R336H ND ND Variable Lowd Meda,b Lowd Mede/higha Lowf Lowg Lowa,h Lowi Lowa Lowj Lowk Lowk Lowa,j Lowa Meda,j Lowa,j Medl Lowa,c Meda Lowl Lowa,m Lowk Lowe/higha Lowa,n Lowh Lowl Yeast phenotype and remediation Nonfunctionalo Similar to major allele Intermediate growth, B6 remedial, hem1 rescue Similar to major allele High growth, B6 and heme remedial Low growtho Low growtho Nonfunctional Similar to major alleleo Similar to major allele Nonfunctionalo Low growth Nonfunctional Nonfunctional Nonfunctional Nonfunctional Nonfunctionalo Similar to major allele Low growtho Intermediate growtho Nonfunctional Nonfunctionalo Nonfunctionalo Nonfunctional Nonfunctionalo hem1 rescue Nonfunctional Nonfunctional Low growth, B6 and heme remedial hem1 rescue Low growth Nonfunctional Nonfunctionalo hem1 rescue Intermediate growth, B6 remedial Nonfunctional Low growtho Low growth Low growtho Nonfunctional Nonfunctional Intermediate growth, heme remedial Nonfunctional Nonfunctional Nonfunctional Low growth, B6 remedial Nonfunctional High growth, B6 and heme remedial Nonfunctional Low growth Nonfunctional Nonfunctional hem1 rescue Nonfunctional Nonfunctionalo Intermediate growth, B6 and heme remedial Nonfunctional Low growth hem1 rescue; not tested in liquid media (continued) 1314 J. A. Mayfield et al. Table 2, continued Mutation Clinical Response to B6 G347S S349N S352N T353M V354M Variable Nonvariable Nonvariable Conflicting Nonvariable A355P A361T R369P R369H R369C C370Y V371M D376N R379W K384E K384N M391I P422L T434N I435T R439Q D444N L456P S466L Q526K ND Nonresponsive NA ND Responsive Responsive Partial response ND ND Responsive Nonresponsive Nonresponsive B6 nonresponsive B6 responsive ND Conflicting Conflicting B6 nonresponsive ND B6 nonresponsive Enzyme activity Lowd Lowl Lowh Lowj/meda Lowj Higha,c Higha,c Meda Higha/medl Lowl Higha,c Yeast phenotype and remediation Nonfunctional Nonfunctional Low growth Low growth, B6 and heme remedial High growth, B6 remedial Nonfunctional Nonfunctional Nonfunctional Similar to major allele Similar to major allele Nonfunctional Similar to major allele Nonfunctional hem1 rescue Nonfunctionalo hem1 rescue Nonfunctional Similar to major allele High growth, B6 remedial Similar to major allele Similar to major allele Similar to major allele Intermediate growth Similar to major allele Intermediate growth, hem1 rescueo Alleles with yeast growth phenotypes inconsistent with clinical (underlined) or in vitro activity (italics) are indicated. Alleles identified in the clinic but without information about B6 response (ND, no data) and alleles identified from available sequence only (NA, not applicable) are indicated. Enzyme activity summarizes several different assays including expression in Escherichia coli or in human fibroblast cell culture. Low indicates activity at or below the level of detection, med indicates an intermediate activity and high indicates activity indistinguishable from the major allele. a Kozich et al. (2010). b de Franchis et al. (1994). c Maclean et al. (2002). d Gaustadnes et al. (2002). e de Franchis et al. (1999). f Marble et al. (1994). g Orendae et al. (2004). h Dawson et al. (1997). i Kozich et al. (1993). j Kraus et al. (1999). k Lee et al. (2005). l Urreizti et al. (2006). m Kozich and Kraus (1992). n Hu et al. (1993). o The alleles we analyzed by immunoblot. The original publication and a recent reanalysis were cited. alleles were further assayed in liquid medium at varying concentrations of vitamin B6 to expand the qualitative phenotype to a quantitative assessment of function and B6 responsiveness. All CBS alleles grew poorly without B6 supplementation (Table S1). Although S. cerevisiae is a B6 prototroph, the endogenous B6 level was insufficient to support the B6 requirement of human CBS. However, cells with the major CBS allele grew relatively well in medium supplemented with as little as 1 ng/ml of B6 (Figure S2 and Figure 3A). When compared to cells with the major allele, the growth phenotypes of cells with other CBS alleles varied greatly (Figure 3B and Table S1). Hierarchical clustering by growth rate under all conditions was used to describe allele behavior. This nonbiased method separated alleles into roughly three bins, in addition to the nonfunctional bin defined above (Figure 4A). Cells with 14 different CBS alleles had evidence of some function but grew poorly even at high levels (400 ng/ml) of B6 (listed as “low growth” in Table 2). Cells with 7 alleles showed an intermediate phenotype with growth rates between that of cells with the major allele and cells with poorly functioning CBS (listed as “intermediate growth” in Table 2B). Cells with each of the remaining 17 alleles grew at rates similar to those of cells with the predominant allele (listed as “high growth” or “similar to major allele” in Table 2). Ten alleles, spanning all growth classes, shifted from a lower growth-rate class to a higher growth-rate class at 400 ng/ml B6 (listed as “B6 remedial” in Table 2). All functional alleles benefitted from increased B6 concentrations; however, cells with these 10 alleles were especially sensitive. Surrogate Genetics of Human CBS Mutations 1315 Figure 2 CBS protein levels in yeast whole cell extracts. (A) Immunoblotting of yeast cells with the CBS major allele (MA), a B6-responsive allele (A226T), an AdoMet-domain mutation (Q526K), or an empty expression vector (EV) were grown in minimal medium with 400 ng/ml B6 alone, with glutathione alone, or with glutathione and 400 ng/ml B6. (B) Yeast cells with the CBS MA and five variant alleles were grown in minimal medium with glutathione alone or with glutathione and 400 ng/ml B6. Representative alleles from the nonfunctional (T87N and P88S) and sick (P145L, V168M, and M126V) phenotypic classes were processed for immunoblotting. 3-Phosphoglycerate kinase (PGK) was detected as a loading control. The importance of cofactor concentration to CBS function extended to heme The CBS enzyme coordinates a second cofactor, heme, through a heme-binding domain. Certain mutations in the heme-binding domain disrupt CBS function in human cells, indicating that heme is critical to protein activity (Janosik et al. 2001b). Furthermore, heme increases the activity and dynamics of some CBS alleles (Kopecka et al. 2011). Indeed, one of the mutations in our set, H65R, alters a heme-coordinating residue and was not functional in yeast. In contrast, S. cerevisiae Cys4p lacks a heme-binding domain and does not require heme. Yeast produce heme for other purposes, and the media in our previous experiments lacked additional heme. Therefore, endogenous heme production was sufficient for human CBS function. We hypothesized that some alleles of CBS might be heme responsive under sufficiently challenging conditions. We tested this hypothesis using a yeast hem1 strain that was unable to synthesize d-aminolevulinic acid (d-ALA), the first committed step in heme biosynthesis, and was therefore a heme auxotroph. We varied in vivo heme levels by amending the medium with d-ALA and determined the affect on CBS function. A two-cofactor titration of all alleles in the hem1 background revealed intriguing information about the heme cofactor and about allele function (Figure 4B and Table S1 and Figure S4). hem1 yeast with the predominant CBS allele were incapable of growth without heme supplementation and showed growth dose dependence on both B6 and heme levels. Likewise, strains with each of the 38 alleles with measurable growth in the B6-only titration grew better in media with higher heme concentrations, suggesting heme was required for CBS function and was limiting for growth 1316 J. A. Mayfield et al. Figure 3 CBS yeast exhibited B6-dependent growth. (A) Representative growth curves of yeast with the major allele of human CBS cultures supplemented with six different levels of B6 (colored lines). Average growth rate (6SD) is shown for each B6 level (n = 84–90). (B) The growth of each mutant (n $ 4) was expressed as the percentage of average growth rate of yeast with the major allele of human CBS at each B6 level (6SD). in hem1 yeast. Cells with 6 alleles grew worse than the predominant allele at 2.5 ng/ml heme, but had growth rates approaching that of cells with the predominant CBS allele at 50 ng/ml heme, indicating that some defective CBS variants were especially sensitive to heme (listed as “heme remedial” in Table 2). Five of these heme-responsive alleles were also remedial with B6, apparently identifying proteins whose deficiency could benefit from increased concentration of either cofactor. The D234N allele alone benefited more from increased heme than from increased B6. The remaining 32 alleles were no more sensitive to heme than the predominant CBS allele, with two interesting exceptions. Cells with the P70L and Q526K alleles clustered with the low-growth alleles in the HEM1 background but with the predominant CBS allele in the hem1 background. Similarly, cells with 7 of the 46 alleles that appeared nonfunctional in the HEM1 strain grew in medium containing high B6 and high heme, albeit poorly, revealing partial function of these alleles (Figure 4B; listed as “hem1 rescue” in Table 2). Although counterintuitive, rescue of allele function in the hem1 strain may occur because the hem1 mutation induced heme uptake (Protchenko et al. 2008) or increased substrate availability. The dynamic range of CBS-dependent growth in the hem1 background was larger than in a HEM1 Figure 4 CBS yeast growth responses to B6 and heme grouped alleles into distinct classes. Heat maps of growth rates normalized to the growth of the major allele after titration of (A) B6 in HEM1 yeast or (B) B6 and heme in hem1 yeast. The column Z-score indicates the mean growth rate (Z-score of 0) and standard deviation (Z-score of 61) of all alleles per column, with positive Z-scores indicating higher than average growth. Arrowheads indicate alleles that respond to cofactor titration more strongly than other alleles in their cluster. Asterisks (*) denote alleles that failed to grow in HEM1 yeast but were capable of growth in hem1 yeast. strain, manifested as both saturation at higher cell density and better growth at lower B6 concentration (Figure S4). CBS alleles with clinical association but no apparent defect The majority of alleles tested supported less growth than the major allele, as might be expected for disease-causing alleles, yet 13 appeared indistinguishable from the major allele (listed as “similar to major allele” in Table 2). Since yeast are typically grown at 30, we considered the possibility that these 13 alleles encoded temperature-sensitive mutant proteins whose defects were not apparent at lower temperature. We tested the growth of 10 nominally benign substitutions and found that none had growth defects at 37 (Figure S5), nor on medium containing the denaturant formamide, which can reveal partial loss of function (Aguilera 1994). One allele, A69P, even appeared less sensitive to denaturing stress than the predominant allele. Therefore, these alleles encoded fully functional enzymes within the limits of this assay. Intracellular metabolic imbalances caused by CBS variants Our previous assays for CBS function relied on growth as a proxy for enzymatic function. As an independent assessment of CBS function, we used LC–MS to measure directly the metabolite profiles of cells with different CBS alleles grown in medium with different levels of B6. Metabolite levels mirrored the trends observed in the growth data: cells with the major CBS allele grown under B6 limitation and cells with a nonfunctional CBS allele induced similar metabolic profiles that differed from profiles of cells with the major CBS allele grown under nonlimiting B6 conditions (Figure 5, Table S1, and File S2). Yeast cells carrying the G307S allele, a nonfunctional allele in clinical and yeast growth assays, failed to produce glutathione and instead accumulated homocystine, sharing the namesake diagnostic phenotype of homocystinuria. Analysis of a second allele class, represented by the B6 remedial V320A allele, further defined the correlation between growth rate and metabolite flux (Table S2). Cells relying on the V320A allele accumulated significantly more Surrogate Genetics of Human CBS Mutations 1317 Figure 5 Metabolite profiles of CBS yeast grown under nutrient replete or limiting conditions. Heat map of amino acid or derivative metabolite levels in cell extracts from yeast grown with either the major CBS allele (MA) or the G307S (nonfunctional) allele, as measured by mass spectrometry. Each column represents the average of four biological replicates. B6 was supplemented at doses that produced robust growth of the major allele (400 ng/ml) or measurable, but compromised, growth (1 ng/ml). Metabolite levels were scaled for each row and both metabolites and experimental conditions were subject to hierarchical clustering. The row Z-score indicates the mean and standard deviations for each metabolite, such that the mean metabolite level has as a Z-score of 0. Duplicate columns were independent cell extracts and demonstrated trial-to-trial variation that was not significant in any of the known metabolites (t-test P . 0.05). The oxidizing conditions used for extraction strongly favored isolation of homocystine over homocysteine. Similarly cystathionine and cysteine were not detected because of limitations in sample processing or because intracellular pools are small. homocystine and produced less glutathione than the major allele regardless of B6 level. However, in contrast to the nonfunctional G307S allele, glutathione production increased and homocystine accumulation decreased when cells with the V320A allele were grown with a high dose of B6. These data revealed perfect concordance with the relative growth rates of these alleles at these doses of B6 (Figure 3 and Table S1). The massively parallel nature of LC–MS allowed us to measure metabolites upstream and downstream of CBS, as well as those in shunt pathways. The accumulation of upstream metabolites was not restricted to homocystine in cells with the G307S allele or under B6 limitation of cells with the major CBS allele. Elevated levels of AdoMet, SAH, and methionine, the substrates involved in homocysteine recycling by one-carbon metabolism, were detected (Figure 5 and Figure 6, A–D). Overall, our data suggested that the metabolic footprint of CBS deficiency extended far beyond the immediate substrate and product of the enzyme, homocysteine, and cystathionine, respectively. For example, the block at CBS, through mutation or B6 limitation, caused a detectable drop in 59-methylthioadenosine, a metabolite in the methionine salvage pathway with the potential to reduce homocysteine levels in favor of increased methionine. Instead, flux through this pathway was also reduced (Figure 5). 1318 J. A. Mayfield et al. The growth rate of cells with functional CBS alleles in B6supplemented medium was significantly greater than that in medium lacking B6 or in cells with a loss-of-function allele. To distinguish the metabolic signature of loss of CBS function from the signature of lack of growth per se, we profiled cells with the major allele under methionine starvation. Although the csy4 yeast strain used in these assays synthesizes methionine, additional methionine supplementation was necessary for growth of all CBS-substituted strains. The growth defect without exogenous methionine is as severe as without B6; however, the metabolic profile was strikingly different. Specifically, cells limited for methionine produced low levels of glutathione, but without homocystine accumulation, regardless of B6 concentration (Figure 5 and Figure 6, C and D). These data confirmed that CBS-deficiency generated a unique metabolic profile not due simply to poor growth. Discussion Building on Garrod’s Inborn Errors of Metabolism (Garrod 1909), technological innovations have shaped our understanding of how an individual’s genetics cause disease. The Human Genome Project facilitated rapid progress in linking genes and diseases, but also exposed a gap between Figure 6 Levels of metabolites critical in CBS function. Scatter plots of the levels of four different metabolites measured by mass spectrometry. The average of four biological replicates (bars) and their individual measurements (squares) are shown. Duplicated columns show trial-to-trial variation in independent cell extracts. (A) Methionine, (B) AdoMet, (C) homocystine, and (D) glutathione. The levels of all four metabolites are significantly different (ANOVA P , 0.0001); all significant differences between the MA at high B6 and other classes are indicated (Tukey’s honest significance test **, P , 0.005; ****, P , 0.0001). an increasing number of minor associations and an actual assessment of causality (Bansal et al. 2010; Cirulli and Goldstein 2010; McClellan and King 2010). The so-called “missing heritability” lies, in part, in the failure to define disease with sufficient phenotypic precision. Here, we developed techniques that provided a quantitative assessment of clinically associated alleles that confirmed some expectations and led to unexpected insights about one human genetic disease and presumptive causative alleles. Using yeast growth, we quantified the relative function of 84 alleles of human CBS, binning alleles according to growth rate and ability to be rescued by B6 or heme cofactors. We also measured the levels of metabolites in cells with three different human CBS alleles by LC–MS, confirming that yeast growth was a relevant proxy for enzyme function and revealing the tight coupling between trans-sulfuration pathway flux and growth. These quantitative phenotypes confirmed that many clinically associated CBS alleles are indeed nonfunctional, with a few notable exceptions. Although computational prediction may eventually replace or supplement laboratory research in the corroboration of genetic associations, the exceptions derived from functional studies offer a starting point for future analyses of protein function and disease (Wei et al. 2010). Similar primary culture-independent, quantitative assays for human alleles in a surrogate organism should be broadly applicable to any gene that fits into an orthologous pathway (Shan et al. 1999; Zhang et al. 2003; Marini et al. 2008). Methods like this are increasingly important given the expanding sequence landscape: since 2010, 38 novel missense alleles of CBS have been identified (NHLBI Exome Sequencing Project 2012). Eighty-one of the alleles we tested were identified in people with homocystinuria. For 33 alleles, there either are no clinical data about B6-responsiveness or the evidence is conflicting: our data could help to resolve some of these cases. For example, the K102Q allele functioned similarly to the major allele in our growth assay. Recent exome sequencing revealed that this allele, rare in previously sequenced populations, has an allele frequency close to 4% in the African-American population (NHLBI Exome Sequencing Project 2012). Therefore, additional information about this allele is critical to assessing disease risk. For the remaining alleles, growth in yeast and clinical data correlated well, especially for alleles identified in patients who were B6 nonresponsive (Table 2). In addition to clinical data, the in vitro enzymatic activities of many CBS alleles have been assessed. Our growth-rate measurements were consistent with published biochemical studies in 36 of the 40 cases of overlap (exceptions are italicized in Table 2). Sixteen of the 81 alleles had clinical features that did not match our yeast growth data (underlined in Table 2). Some discrepancies may have resulted from an unrecognized second mutation in CBS in the patient. Additionally, rare alleles Surrogate Genetics of Human CBS Mutations 1319 Figure 7 CBS phenotypes in relation to primary structure. Diagram of the domain structure of the CBS protein with the location of the 84 alleles used in this analysis represented by colored bars above the diagram. Each bar represents an allele; colors indicate the affect of the allele on growth. The Robust row reports the position of alleles indistinguishable from the predominant allele. generally occurred in a single individual, heterozygous with a different allele, making it difficult to assess the individual connection to disease. However, there may be interesting cases in which CBS function in yeast and humans differ. For example, the P422L and S466L mutations in the C-terminal regulatory domain encode biochemically active proteins that are unable to bind AdoMet and cause a distinctive, mild form of homocystinuria (Maclean et al. 2002). We tested both of these alleles plus six other AdoMet domain mutations and found that all supported growth, suggesting that AdoMet regulation may not be critical for growth in yeast. However, cells with the L456P and Q526K alleles, both altering the AdoMet domain, had reduced growth, while cells with the T434N allele were B6 responsive, indicating that some mutations in the AdoMet domain diminish CBS function. AdoMet regulatory mutations accounted for some, but not all, discrepancies between yeast growth and clinical data. We emphasize that the power of an allelic series lies in the diversity of phenotypes, which derive from distinct protein functions and reveal allele classes that may respond differently to treatment. The full set of alleles demonstrated that mutation of any CBS domain could abrogate function, and remediation was not specific to cofactor-binding residues (Figure 7). B6 and heme sites are separated in the tertiary structure of CBS (Meier et al. 2001), yet some variants were remedial by either cofactor. Dual remedial alleles favored a global mechanism for cofactor rescue over the simpler model that increasing the cofactor concentration overcomes mutations that decrease the Km of cofactor binding (Ames et al. 2002; Wittung-Stafshede 2002). Since many characterized disease-causing mutations alter protein function via folding/stability (Yue et al. 2005; Kozich et al. 2010), alleles encoding unstable proteins may benefit from the binding energy provided by protein–cofactor interaction. Rescue of CBS function by biological or chemical chaperones is consistent with this hypothesis (Singh et al. 2007, 2010; Majtan et al. 2010). Regardless of the biochemical mechanism, cofactor availability regulated enzyme function for all CBS alleles within a narrow and physiologically relevant range of cofactor concentrations. While fully functional alleles supported growth at lower cofactor concentrations, metabolite levels of cells with a functional allele grown with a low B6 level and of cells with a nonfunctional allele were similar. This similarity of profiles may reflect a bone fide regulatory mechanism 1320 J. A. Mayfield et al. coupling pathway flux to nutrient availability. Similarly, substrate limitation affected trans-sulfuration flux as strongly as cofactor limitation. Methionine limitation reduced the level of homocystine in yeast cells regardless of whether CBS was functional or attenuated by limiting B6 (Figure 6). Indeed, since methionine catabolism leads to homocysteine formation, a low methionine diet is part of the treatment strategy for homocystinuria. Critically, glutathione production was also compromised by loss of CBS function or methionine limitation, with similar consequences to growth but different effects on homocystine production. Although patients with homocystinuria have relatively normal serum glutathione levels (Hargreaves et al. 2002; Orendac et al. 2003), tissue concentrations may be significantly lower (Maclean et al. 2010). Our data suggest that glutathione deficiency and homocysteine toxicity should be considered in evaluating the pathology of CBS deficiency. Overall, inability to drive sufficient flux through the transsulfuration pathway, regardless of cause, led to growth defects (Figure 5 and Figure 6). Conventional thought about inborn errors is that metabolites accumulate at the point of the block. However, reversible reactions, circular connections, shunts in or out of a pathway, and feedback regulation, can establish new ratios among even distant metabolites. Thus, a more thorough understanding comes from parsing the symptoms as a function of alleles and related metabolites. For example, our quantitative assays revealed the subset of alleles that were more sensitive to B6 level and also provided evidence that the proteins encoded by six alleles benefited from increased heme level more than the predominant CBS allele. The behavior of these alleles suggested that heme deficiencies could complicate the diagnosis and treatment of homocystinuria. Conversely, the successful demonstration of heme supplementation could have utility in the clinic, either in addition to current treatments or as a second treatment formulation for certain alleles. Acknowledgments We thank Warren Kruger for plasmid pHUCBS, Tony Ivaronie for help with LC–MS, Nicholas Marini for help with yeast assays, Sandrine Dudoit for the impute zeros script, and a reviewer for pointing out the increased K102Q allele frequency. 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Fields Surrogate Genetics of Human CBS Mutations 1323 GENETICS Supporting Information http://www.genetics.org/content/suppl/2012/01/20/genetics.111.137471.DC1 Surrogate Genetics and Metabolic Profiling for Characterization of Human Disease Alleles Jacob A. Mayfield, Meara W. Davies, Dago Dimster-Denk, Nick Pleskac, Sean McCarthy, Elizabeth A. Boydston, Logan Fink, Xin Xin Lin, Ankur S. Narain, Michael Meighan, and Jasper Rine Copyright © 2012 by the Genetics Society of America DOI: 10.1534/genetics.111.137471 FIGURE S1 Methionine Salvage Methylthioadenosine Methionine AdoMet Folate Biosynthesis Methylation SAH Homocysteine Homocystine CBS Cystathionine Cysteine Glutathione Figure S1 Biochemical pathway of relevant metabolites. Arrowheads represent the direction of the reaction in human cells. Double arrows indicate that intermediate metabolites are not shown. The reaction performed by CBS is circled; shunts in or out of the pathway are summarized in boxes. 2 SI J. A. Mayfield et al. FIGURE S2 MA Glutathione 400 ng/ml B6 1 ng/ml B6 0.1 ng/ml B6 E131D E131D E131D EV V168M V168M V168M MA R224H R224H R224H EV R302K R302K R302K MA EV R266K R266K R266K R266G R266G R266G 4-fold dilution of cells Figure S2 Growth of nonfunctional and low-‐growth alleles on solid medium lacking glutathione. A 5-‐fold dilution series of cultures grown in minimal medium containing glutathione and lacking B6 was replica plated on solid medium +/-‐ glutathione or with defined concentrations of B6. Three independent transformations of representative nonfunctional (V168M, R302K, R266G), low growth (E131D, R224H), and B6 responsive (R266K) alleles are shown, with the major allele (MA) and empty vector (EV) controls included on each plate for reference. J. A. Mayfield et al. 3 SI PCNA A226T G307S K102N C109R K384E H65R G151R E131D E144K D198V G139R CBS MA FIGURE S3 Figure S3 CBS protein levels of 11 alleles in yeast cell extracts. Immunoblot of yeast cell extracts from cells containing the major allele of CBS (MA) or one of 11 other alleles after growth in minimal medium containing 400 ng/ml B6. 4 SI J. A. Mayfield et al. FIGURE S4 growth rate (logOD/hr) 0.12 Heme (ng/ml) 0 5 50 0.08 0.04 0 1 ng/ml B6 2 ng/ml B6 HEM1 400 ng/ml B6 1 ng/ml B6 2 ng/ml B6 hem1 400 ng/ml B6 Figure S4 hem1 CBS yeast responses to B6 and heme. Growth rates of hem1 yeast with the major human CBS allele were measured under 6 conditions of B6 and heme supplementation. The average (± SD) is shown (n=4). J. A. Mayfield et al. 5 SI FIGURE S5 6 SI MA vector only V320A (remedial) K102N V354M V371M P422L P78R Day: Glutathione: Temperature: Formamide: 3 + 30 - 3 30 - 3 30 + MA vector only V320A (remedial) K102N V354M V371M P422L P78R Day: Glutathione: Temperature: Formamide: 5 37 - 5 37 + 5 30 + MA vector only V320A (remedial) E128D K102Q S466L A69P I435T Day: Glutathione: Temperature: Formamide: 3 + 30 - 3 30 - 3 30 + MA vector only V320A (remedial) E128D K102Q S466L A69P I435T Day: Glutathione: Temperature: Formamide: 5 37 - 5 37 + 5 30 + J. A. Mayfield et al. Figure S5 CBS function during denaturing stress. A 5-‐fold dilution series of cultures grown in minimal medium containing glutathione and lacking B6 was replica plated on solid medium +/-‐ glutathione or +/-‐ 1% formamide. Plates were grown at 30° or 37° and imaged at 3 or 5 days after plating to allow equivalent growth. The major allele (MA) is shown for reference. J. A. Mayfield et al. 7 SI File S1 Raw growth rate data and normalized averages of growth rates in the HEM1 and hem1 strains, as used in heat maps. File S1 is available for download at http://www.genetics.org/content/suppl/2012/01/20/genetics.111.137471.DC1 as a compressed folder. This folder contains Raw growth rate data.xls, which is an Excel spreadsheet containing yeast growth data. All raw growth data are included on sheet "Growth Rate Data". The sheet "Summary HEM1" includes mean growth rate at each B6 concentration for each allele normalized to the major allele control grown on the same plate after removal of outliers using Grubbs test. "Summary hem1-‐" includes mean growth rates after two-‐way titration of B6 and heme in the hem1 strain. Each allele is normalized to the major allele controls grown on the same plate and outliers were removed after using Grubbs test. 8 SI J. A. Mayfield et al. File S2 Summary of metabolite data and analysis methods. File S2 is available for download at http://www.genetics.org/content/suppl/2012/01/20/genetics.111.137471.DC1 as a compressed folder. This folder contains metabolite data.xls, which is an Excel spreadsheet containing the measured metabolite levels from LC/MS analyses. These data can be regenerated using the raw data files and R scripts included as File S3. For the G307S dataset, all samples were generated in a single Orbitrap run and are therefore directly comparable. The metabolite extraction was performed in two batches on separate days, indicated as experiment 1 or 2. There were slight, but not significant, differences in metabolite levels of positively identified compounds between the two days. The sheet “G307S peaks” contains an abbreviated XCMS output. Missing peaks were replaced either through the fillPeaks function in XCMS or through imputation using local minima, the intensities were normalized using upper quartiles and the data were log transformed. Note that zero values occurred, but were replaced to facilitate normalization and transformation. Columns 1 and 2 were appended according to matches between the XCMS output and the HMDB database and give the names of the top 3 matches for each given peak and the number of potential hits. The Metlin column gives the URL matches to the Metlin database. The Anova column indicates peaks that were significantly different between sample classes. The sheet “G307S Metabolites” contains the subset of data used to generate Figure 5 and includes amino acids and other metabolites. In addition to database matching using the mass/charge ratio, seventeen target compounds were included in Calibration Standards (Cal) in a 4-‐fold dilution series added to a pooled experimental sample. Hence, peaks that corresponded to a chemical included in the calibration standard decreased in intensity as the amount added decreases, while the retention time and mass/charge ratio remain accurate. Peaks with the expected decrease in intensity were identified by two statistical methods. The “p value exp” columns use a linear model to match the measured intensity of a peak in the calibration standard dilution series to the theoretical value, such that a low p value indicates a good fit. The “Pearsons R exp” columns measure the correlation coefficient between the measured level of an identified metabolite in the calibration standards and the theoretical level, such that an R value approaching one indicates better correlation. The undiluted calibration standard contained 100 μg/ml glycine, 25 μg/ml serine, 5 μg/ml proline, 25 μg/ml threonine, 15 μg/ml leucine, 50 μg/ml aspartic acid, 15 μg/ml lysine, 50 μg/ml glutamic acid, 25 μg/ml methionine, 5 μg/ml histidine, 20 μg/ml cystathionine, 25 μg/ml glutathione, 50 μg/ml J. A. Mayfield et al. 9 SI cystine, 15 μg/ml homocystine, 10 μg/ml methylthioadenosine, 30 μg/ml s-‐adenosyl homocysteine (SAH), and 50 μg/ml s-‐adenosyl methionine (AdoMet). Isotopically labeled glycine and isotopically labeled methionine were spiked into all samples at 50 μM and 2.5 μM, respectively. Glycine was not detected; isotopically labeled methionine did not vary significantly in any sample or sample class (ANOVA p > 0.05). The V320A dataset differed in several significant ways, reflected in the data. First, ~2X as many cells were used in the extraction, increasing both metabolite concentrations and noise. Second, the calibration panel was analyzed in solvent, not in a pooled standard; hence, metabolite identification was by exact mass and more stringent criteria were employed in metabolite identification. Finally, the 400 and 1 ng/ml B6 experiments were performed on different days and although they can be grouped together, are not directly comparable by ANOVA. The sheet “V320A” peaks contains the XCMS output of peak groups, appended and treated for G307S. The sheet “V320A Metabolites” lists only the peaks with a single, unambiguous exact mass match. When multiple group peaks shared the same identity, the more abundant peak was used. 10 SI J. A. Mayfield et al. File S3 Data files and R script for processing metabolite data. File S3 is available for download at http://www.genetics.org/content/suppl/2012/01/20/genetics.111.137471.DC1 as a compressed folder. Centroided mass spectrum provided in the mzXML format, organized according to class, are included as Mayfield_LC_MS_Files.zip. A full executable R script, CBS_Analysis_Scripts.R.zip, is provided to align peaks using XCMS, normalize and transform the output, match peaks to metabolite databases and target compounds, and output data tables or figures. J. A. Mayfield et al. 11 SI Table S1 Cofactor responses of 44 functional alleles. Mutant growth rates are expressed as a percent of the major allele at the same dose of B6 or heme; averages represent data from 4-‐24 biological replicates and error bars show standard deviation. Table S2 Critical metabolites measured in the major allele and a B6 remedial allele under high and low concentration of B6. Metabolite levels from cell extracts are expressed as the log2 of the mean intensity ± standard deviation (SD) measured by LC/MS for the cells containing the major allele (MA) or the B6 remedial allele V320A, grown at 400 or 1 ng/ml B6. Significant differences are indicated (T test, NS = not significant). Homocystine was not detected in two 400 ng/ml B6 replicates. High and low B6 experiments were performed on separate dates. Tables S1 and S2 are available for download at http://www.genetics.org/content/suppl/2012/01/20/genetics.111.137471.DC1 as Excel files. 12 SI J. A. Mayfield et al.