Download 1 Surrogate Genetics and Metabolic Profiling for Characterization of

Genetics: Published Articles Ahead of Print, published on January 20, 2012 as 10.1534/genetics.111.137471
Surrogate Genetics and Metabolic Profiling for Characterization of Human
Disease Alleles
Jacob A. Mayfield*,2, Meara W. Davies*,3, Dago Dimster-Denk*, Nick Pleskac†, Sean
McCarthy*, Elizabeth A. Boydston*,1,4, Logan Fink*,1, Xin Xin Lin*,1, Ankur S. Narain*,1,5,
Michael Meighan‡ and Jasper Rine*,6
Author Affiliations
*
Department of Molecular and Cell Biology
California Institute of Quantitative Biosciences
University of California, Berkeley
Berkeley, California 94720
†
Berkeley High School
Berkeley, CA 94704
‡
University of California, Berkeley
Department of Molecular & Cell Biology
Berkeley, CA 94720
Reference numbers for publically available data: L14577.1 (CBS) , rs17849313 (A69P),
rs2229413 (P70L), rs11700812 (R369P), YGR155W (CYS4) and YDR232W (HEM1).
1 Copyright 2012.
Running Head: Surrogate Genetics of Human CBS Mutations
Keywords: cysteine metabolism, human disease model, glutathione, homocystine, LCMS.
1
These authors contributed equally to this work
2
Present address Department of Veterinary and Animal Science, University of
Massachusetts, Amherst, 470 Integrated Sciences Building, Amherst, MA 01002
3
Present address University of Washington, Department of Genome Sciences, Foege
Building S-250, Box 355065, 3720 15th Ave NE, Seattle, WA 98195-5065
4
Present address Department of Cellular and Molecular Pharmacology, Howard
Hughes Medical Institute, California Institute of Quantitative Biosciences, 403B Byers
Hall, University of California, San Francisco, San Francisco, California 94158
5
Present address National Institute of Child Health and Human Development,
Laboratory of Molecular Growth Regulation, National Institutes of Health, Building 6, Rm
2A01, 6 Center Drive 2753, Bethesda MD, 20892-275
6
corresponding author
Jasper Rine
Department of Molecular and Cell Biology, California Institute of Quantitative
Biosciences, 374A Stanley Hall ,University of California, Berkeley ,Berkeley, California
94720, Phone: 510-642-7047, Fax: 510- 666-2768
Email: [email protected]
2 ABSTRACT
Cystathionine-beta-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.
3 The first complete human genome sequence seeded the defining challenge of human
genetics for the foreseeable future: interpreting the impact of variations in the
sequences of individual human genomes. Comparative genomes sequencing reveals an
average of one single-nucleotide change per 1200 base pairs 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). Next-generation sequencing within small pedigrees (FAN et al.
2011; NG et al. 2010a; NG et al. 2010b), 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 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 1,800 in certain populations (GAN-SCHREIER et
al. 2010). A few well-characterized alleles of the gene encoding Cystathionine BetaSynthase (CBS) correlate with disease symptoms, providing an appealing molecular
4 mechanism. The enzyme CBS converts homocysteine to cystathionine in the cysteine
biosynthesis pathway (Figure S1). In people with homocysteinuria 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 proteinbound 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 AdoMet, the major methyl
donor in the cell, back to methionine. The wide range of symptoms may reflect that 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 (GUTTORMSEN et al. 2001; MOTULSKY 1996). 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
5 symptoms, neonatal screening is widespread (MUDD SH 1999). 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 S-adenosylmethionine (AdoMet) as a
possible regulatory mechanism (CHEN et al. 2006; CHRISTOPHER et al. 2002; MEIER
2001; SCOTT et al. 2004; SEN and BANERJEE 2007; SHAN and KRUGER 1998). These
features suggest control points for enzyme regulation and function, or targets for
nutritional and pharmaceutical therapies, that CBS alleles may impact differently.
Directed sequencing efforts of patients afflicted with homocystinuria have produced a
large catalog of alleles (KRAUS et al.), with both common and rare alleles (GALLAGHER et
al. 1998; GALLAGHER et al. 1995; KRAUS 1994; MUDD et al. 1985). However, clinical
association does not guarantee causality. 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
6 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; KRUGER and COX 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 1999; KRAUS et al.), 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)
7 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 (MATα cys4Δ::KanMX his3Δ1 leu2Δ0 lys2Δ0 ura3Δ0, JRY9292)
derived from the yeast knockout collection (WINZELER et al. 1999). A hem1 cys4 strain
was created by disruption of HEM1 with LEU2 (hem1∆::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
8 auxotrophies in the parent strain, and methionine was included in all minimal media.
Growth rate assays used 250 μl volumes and started with cells at OD600=0.002,
inoculated from cells pre-grown in minimal medium that lacked B6 and contained
glutathione. The pre-growth medium in the hem1 experiments contained 50 μg/ml δaminolevulinc acid (δ-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 δ-ALA as “heme supplementation” in the text. Heme is sparingly
soluble and δ-ALA supplementation was more efficient. The optical density (A600 nm)
was measured every 30 minutes for 96 hours 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
Resuspended OD
&
− 1 (
'
time point
final time point
+ 1
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 supplemental information.
9 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 (LiCOR 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 antiproliferating 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 hours after inoculation. Metabolite
extraction combined previously described methods (BOER et al. 2010; CANELAS et al.
2008; GODAT 2010) as follows. 8.0 × 108 (G307S dataset) or 1.9 × 109 (V320A dataset)
cells were pelleted by centrifugation at 3,200 × g. The cell pellets were resuspended
with 9.5 ml of their spent medium supernatant, then quenched with 20 ml -80° methanol.
The cells were pelleted at 4000 × g at -10°C in a rotor (Sorvall SS-34), prechilled to -80°
then resuspended with 1.0 ml of 4°C extraction solvent [0.1% perchloric acid with 400
μM glycine-1-13C,15N (Sigma 299340) and 20 μM isotopically-labeled methionine-
10 13
C5,15N (Sigma 608106)]. The samples were boiled for 5 minutes, and cell debris and
precipitated proteins removed by centrifugation for 2 minutes at 4,000 × g in a 4°
microfuge. The supernatants were diluted 1:4 in 0.1% perchloric acid and 0.1% formic
acid. LC-MS analysis used 20 μl injection volumes. Chromatographic separation (2.1 ×
250 mm, 5 μm Discovery HS-F5 column; Supelco) used a water-to-acetonitrile gradient
(GODAT 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 dataset, a 4-fold 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, version 2.0.7). Peak processing used the
BioConductor package XCMS (SMITH et al. 2006; TAUTENHAHN et al. 2008); processed
data are available as supplemental information. 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 supplemental information).
11 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
transformed into a cys4 yeast strain lacking the CBS ortholog CYS4. Centromere-based
vectors were used to reduce copy-number 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 (MA), not to
CYS4 (Figure 1, Figure S2).
We discriminated functional from non-functional 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
12 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 non-functional
CBS alleles due to aggregation (KATSUSHIMA et al. 2006) or degradation (DE FRANCHIS et
al. 1994; SINGH et al. 2007; SINGH et al. 2010; URREIZTI et al. 2006). Nonetheless, while
we inferred misfolding or aggregation of 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, 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 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 (Tables S1). Although Saccharomyces cerevisiae is a B6
prototroph, the endogenous B6 level was insufficient to support the B6 requirement of
13 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, Figure 3A).
When compared to cells with the major allele, the growth phenotypes of cells with other
CBS alleles varied greatly (Figure 3B; Table S1). Hierarchical clustering by growth rate
under all conditions was used to describe allele behavior. This non-biased 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
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.
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).
14 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, Saccharomyces 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 δ-aminolevulinic acid (δ-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 δ-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; Table S1-2).
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 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
15 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 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 diseasecausing alleles, yet 13 appeared indistinguishable from the major allele (listed at Similar
to Major Allele in Table 2). Since yeast are typically grown at 30°C, we considered the
possibility that these 13 alleles encoded temperature-sensitive mutant proteins whose
16 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°C (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 liquid chromatography-mass spectrometry (LCMS) 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 non-limiting B6 conditions (Figure 5,
Table S3-4). 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 homocystine and produced less
17 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, 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, Figure 6A-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 5’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).
The growth rate of cells with functional CBS alleles in B6–supplemented medium was
significantly greater than 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
18 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, Figure 6C-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 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.
19 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 non-functional, 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 (MARINI et al. 2008; SHAN et al. 1999; ZHANG et al. 2003). 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 is either 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
20 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 non-responsive
(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
(bolded in Table 2). Some discrepancies may have resulted from an unrecognized
second mutation in CBS in the patient. Additionally, rare alleles 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 where 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 6 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-
21 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 (KOZICH et al. 2010; YUE et al. 2005),
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 (MAJTAN et al. 2010; SINGH et al. 2007;
SINGH 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
22 concentrations, metabolite levels of cells with a functional allele grown with a low B6
level and of cells with a non-functional allele were similar. This similarity of profiles may
reflect a bone fide regulatory mechanism coupling pathway flux to nutrient availability.
Similarly, substrate limitation impacted 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 glutathione deficiency and
homocysteine toxicity should be considered in evaluating the pathology of CBS
deficiency.
Overall, inability to drive sufficient flux through the trans-sulfuration pathway, regardless
of cause, led to growth defects (Figure 5, 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
23 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 6 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:
This work was supported in part by funds from an HHMI Professorship in support of
undergraduate biology education. 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 Reviewer 2 for pointing out the increased K102Q
allele frequency. We thank Georjana Barnes, Susanna Repo, and Jonathan Wong for
critical evaluation of the manuscript. Additional support was provided by a grant from the
US Department of the Army (W911NF-10-1-0496).
24 FIGURE LEGENDS
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 5-fold dilution series onto solid medium +/- glutathione. Growth was imaged after 3
days at 30°. The growth of the major allele (MA) and representative alleles of the
nonfunctional and B6-responsive classes are shown.
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 AdoMetdomain 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 major allele (MA) and 5 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. 3phosphoglycerate kinase (PGK) was detected as a loading control.
FIGURE 3.– CBS yeast exhibited B6-dependent growth. (A) Representative growth
curves of yeast with the major allele of human CBS cultures supplemented with 6
different levels of B6 (colored lines). Average growth rate (± SD) is shown for each B6
level (n=84-90). (B) The growth of each mutant (n ≥ 4) was expressed as the
25 percentage of average growth rate of yeast with the major allele of human CBS at each
B6 level (± SD).
FIGURE 4.– CBS yeast growth responses to B6 and heme grouped alleles into
distinct classes. Heatmaps 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 ±1) 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.
FIGURE 5.–Metabolite profiles of CBS yeast grown under nutrient replete or
limiting conditions. Heatmap 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 4 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
26 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.
Figure 6.–Levels of metabolites critical in CBS function. Scatter plots of the levels
of 4 different metabolites measured by mass spectrometry. The average of 4 biological
replicates (bars) and their individual measurements (circles) 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 4 metabolites are
significantly different (ANOVA p<0.0001); all significant differences between the major
allele (MA) at high B6 and other classes are indicated (Tukey’s honest significance test
p<0.005 **, p<0.0001 ****).
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.
27 TABLES
TABLE 1. CBS alleles tested for function in yeast.
Mutation
Initial citation and clinical characterization, or
pJR
protein
cDNA
RefSeq number
pJR3044
H65R
194A >G
(JANOSIK et al. 2001b)
pJR3045
A69P
205G >C
rs17849313
pJR3046
P70L
209C >T
rs2229413
pJR3047
P78R
233C >G
(DE FRANCHIS et al. 1994)
pJR3048
G85R
253G >C
(MACLEAN et al. 2002)
pJR3049
T87N
260C >A
(KRAUS et al.)
pJR3050
P88S
262C >T
(SEBASTIO et al. 1995)
pJR3051
L101P
302T >C
(GALLAGHER et al. 1998)
pJR3052
K102Q
304A >C
(KOZICH et al. 1997)
pJR3053
K102N
306G >C
(DE FRANCHIS et al. 1994)
pJR3054
C109R
325T >C
(GAUSTADNES et al. 2002)
pJR3055
A114V
341C >T
(KOZICH et al. 1993)
pJR3056
G116R
346G >A
(SPERANDEO et al. 1996)
pJR3057
R121C
361C >T
(KATSUSHIMA et al. 2006)
pJR3058
R121H
362G >A
(BERMUDEZ et al. 2006; KATSUSHIMA et al. 2006)
pJR3059
R121L
362G >T
(KRAUS et al.)
pJR3060
M126V
376A >G
(DE FRANCHIS et al. 1999)
pJR3061
E128D
384G >T
(COUDE et al. 1998)
pJR3062
E131D
393G >C
(MARBLE et al. 1994)
pJR3063
G139R
415G >A
(SHIH et al. 1995)
pJR3064
I143M
429C >G
(ORENDAE et al. 2004)
28 pJR3065
E144K
430G >A
(SHIH et al. 1995)
pJR3066
P145L
434C >T
(KOZICH et al. 1993)
pJR3067
G148R
442G >C
(ORENDAE et al. 2004)
pJR3068
G151R
451G >A
(KRAUS et al.)
pJR3069
I152M
456C >G
(KRAUS et al.)
pJR3070
G153R
457G >C
(KRAUS et al.)
pJR3071
L154Q
461T >A
(LEE et al. 2005)
pJR3072
A155T
463G >A
(JANOSIK et al. 2001b)
pJR3073
A155V
464C >T
(LEE et al. 2005)
pJR3074
A158V
473C >T
(SHAN and KRUGER 1998)
pJR3075
C165Y
494G >A
(KLUIJTMANS et al. 1995)
pJR3076
V168M
502G >A
(KRAUS et al.)
pJR3077
E176K
526G >A
(KOZICH et al. 1997)
pJR3078
V180A
539T >C
(KLUIJTMANS et al. 1999)
pJR3079
T191M
572C >T
(URREIZTI et al. 2003)
pJR3080
D198V
593A >T
(KRAUS et al.)
pJR3081
R224H
671G >A
(KRUGER and COX 1995)
pJR3082
A226T
676G >A
(KRUGER et al. 2003)
pJR3083
N228S
683A >G
(KRUGER et al. 2003)
pJR3084
N228K
684C >A
(GALLAGHER et al. 1998)
pJR3085
D234N
700G >A
(DE LUCCA and CASIQUE 2004)
pJR3086
E239K
715G >A
(DE FRANCHIS et al. 1994)
pJR3087
T257M
770C >T
(SEBASTIO et al. 1995)
pJR3088
G259S
775G >A
(KRAUS et al.)
pJR3089
T262M
785C >T
(KIM et al. 1997)
pJR3090
R266G
796A >G
(KATSUSHIMA et al. 2006)
29 pJR3091
R266K
797G >A
(KIM et al. 1997)
pJR3092
C275Y
824G >A
(URREIZTI et al. 2003)
pJR3093
I278T
833T >C
(KOZICH and KRAUS 1992)
pJR3094
A288T
862G >A
(LEE et al. 2005)
pJR3095
A288P
862G >C
(LINNEBANK et al. 2004)
pJR3096
P290L
869C >T
(DE LUCCA and CASIQUE 2004)
pJR3097
E302K
904G >A
(SPERANDEO et al. 1996)
pJR3098
G307S
919G >A
(HU et al. 1993)
pJR3099
V320A
959T >C
(KIM et al. 1997)
pJR3100
A331E
992C >A
(DAWSON et al. 1997)
pJR3101
A331V
992C >T
(KRUGER and COX 1995)
pJR3102
R336H
1007G >A
(COUDE et al. 1998)
pJR3103
G347S
1039G >A
(GAUSTADNES et al. 2002)
pJR3104
S349N
1046G >A
(URREIZTI et al. 2003)
pJR3105
S352N
1055G >A
(DAWSON et al. 1997)
pJR3106
T353M
1058C >T
(DAWSON et al. 1997)
pJR3107
V354M
1060G >A
(COUDE et al. 1998)
pJR3108
A355P
1063G >C
(GALLAGHER et al. 1998)
pJR3109
A361T
1081G >A
(CASTRO et al. 1999)
pJR3110
R369C
1105C >T
(KIM et al. 1997)
pJR3111
R369H
1106G >A
(KRAUS et al.)
pJR3112
R369P
1106G >C
rs11700812
pJR3113
C370Y
1109G >A
(TSAI et al. 1997)
pJR3114
V371M
1111G >A
(KLUIJTMANS et al. 1999)
pJR3115
D376N
1126G >A
(KRUGER et al. 2003)
pJR3116
R379W
1135C >T
(LINNEBANK et al. 2004)
30 pJR3117
K384E
1150A >G
(ARAL et al. 1997)
pJR3118
K384N
1152G >T
(KRAUS et al.)
pJR3119
M391I
1173G >A
(KRAUS et al.)
pJR3120
P422L
1265C >T
(MACLEAN et al. 2002)
pJR3121
T434N
1301C >A
(KRAUS et al.)
pJR3122
I435T
1304T >C
(MACLEAN et al. 2002)
pJR3123
R439Q
1316G >A
(DAWSON et al. 1997; TSAI et al. 1997)
pJR3124
D444N
1330G >A
(KLUIJTMANS et al. 1996)
pJR3125
L456P
1367T >C
(URREIZTI et al. 2003)
pJR3126
S466L
1397C >T
(JANOSIK et al. 2001a)
pJR3127
Q526K
1572C >A
(KRUGER et al. 2003)
31 TABLE 2. Summary of clinical and yeast phenotypes.
Clinical Response
Enzyme
Mutation
to B6
Activity
H65R
Non-Variable
low
A69P
NA
Similar to major allele
P70L
NA
Intermediate growth, B6 remedial, hem1 rescue
P78R
Variable
med
G85R
Partial response
low
T87N
ND
Low growth
*
P88S
ND
Low growth
*
L101P
Conflicting
low
K102N
Variable
med
K102Q
ND
C109R
Conflicting
low
A114V
Conflicting
med /high
G116R
Variable
Nonfunctional
R121C
ND
Nonfunctional
R121L
ND
Nonfunctional
R121H
Non-Variable
Nonfunctional
M126V
Non-Variable
Nonfunctional
E128D
Non-Variable
Similar to major allele
E131D
Non-Variable
G139R
Variable
I143M
Non-Variable
low
g
Nonfunctional
E144K
Conflicting
low
a,h
Nonfunctional
*
P145L
Non-Variable
low
i
Nonfunctional
*
Yeast Phenotype and Remediation
a
Nonfunctional
a,b
*
Similar to major allele
c
High growth, B6 & heme remedial
d
Nonfunctional
a,b
Similar to major allele
Similar to major allele
d
Nonfunctional
e
low
f
a
*
Low growth
Low growth
*
*
Intermediate growth
32 *
*
a
G148R
Non-Variable
G151R
ND
I152M
Conflicting
G153R
NA
L154Q
NA
A155T
Conflicting
A155V
NA
A158V
NA
C165Y
Conflicting
V168M
ND
E176K
Non-Variable
low
V180A
Variable
med
T191M
Non-Variable
low
D198V
Non-Variable
Low growth
R224H
ND
Low growth
A226T
Variable
N228S
Non-Variable
N228K
Non-Variable
D234N
Non-Variable
Intermediate growth, heme remedial
E239K
Variable
Nonfunctional
T257M
Non-Variable
Nonfunctional
G259S
ND
Nonfunctional
T262M
Non-Variable
Low growth, B6 remedial
R266G
Non-Variable
Nonfunctional
R266K
Variable
med
C275Y
Non-Variable
low
low
Nonfunctional
Nonfunctional
low
j
*
hem1 rescue
Nonfunctional
low
k
Nonfunctional
Low growth, B6 & heme remedial
low
k
hem1 rescue
Low growth
low
a,j
Nonfunctional
Nonfunctional
a
hem1 rescue
a,j
a,j
med
*
l
Intermediate growth, B6 remedial
Nonfunctional
Low growth
*
*
Nonfunctional
low
a,c
l
a
Nonfunctional
High growth, B6 & heme remedial
Nonfunctional
33 a,m
I278T
Conflicting
A288P
NA
A288T
NA
P290L
Variable
E302K
Conflicting
low /high
G307S
Conflicting
low
V320A
Conflicting
A331E
ND
A331V
ND
R336H
Variable
low
l
hem1 rescue; not tested in liquid media
G347S
Variable
low
d
Nonfunctional
S349N
Non-Variable
low
l
Nonfunctional
S352N
Non-Variable
T353M
Conflicting
V354M
Non-Variable
High growth, B6 remedial
A355P
ND
Nonfunctional
A361T
Non-responsive
Nonfunctional
R369P
NA
Nonfunctional
R369H
ND
Similar to major allele
R369C
Responsive
C370Y
Responsive
V371M
Partial response
D376N
ND
Nonfunctional
R379W
ND
hem1 rescue
K384E
Responsive
Nonfunctional
K384N
Non-responsive
hem1 rescue
low
Low growth
Nonfunctional
low
k
Nonfunctional
hem1 rescue
e
a
a,n
Nonfunctional
Nonfunctional
*
Intermediate growth, B6 & heme remedial
low
h
Nonfunctional
Low growth
Low growth
low
h
j
low /med
Low growth, B6 & heme remedial
a
Similar to major allele
Nonfunctional
low
j
Similar to major allele
34 *
M391I
Non-responsive
P422L
B6 non-responsive
T434N
B6 responsive
I435T
ND
high
R439Q
Conflicting
med
D444N
Conflicting
high /med
L456P
B6 non-responsive
low
S466L
ND
high
Q526K
B6 non-responsive
Nonfunctional
high
a,c
Similar to major allele
High growth, B6 remedial
a,c
Similar to major allele
a
Similar to major allele
a
l
l
Similar to major allele
Intermediate growth
a,c
Similar to major allele
Intermediate growth, hem1 rescue
*
Alleles with yeast growth phenotypes inconsistent with clinical (bold) or in vitro activity (italics) are
indicated. Alleles identified in the clinic but without information about B6 response (No data, ND) and
alleles identified from available sequence only (Not applicable) are indicated. Enzyme activity summarizes
several different assays including expression in E. 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. The alleles we analyzed by immunoblot are indicated. The
original publication and a recent re-analysis were cited.
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)
35 l
(URREIZTI et al. 2006)
m
n
(KOZICH and KRAUS 1992)
(HU et al. 1993)
36 SUPPLEMENTAL MATERIALS
SUPPLEMENTAL FIGURE LEGENDS
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.
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.
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.
37 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).
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.
38 SUPPLEMENTAL TABLE LEGENDS
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.
39 SUPPLEMENTAL INFORMATION
SI–Raw growth rate data and normalized averages of growth rates in the HEM1
and hem1 strains, as used in heatmaps. 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.
SI–Summary of metabolite data and analysis methods. 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 Supplemental
Information. 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
40 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
41 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.
SI.–Data files and R script for processing metabolite data. Centroided mass
spectrum provided in the mzXML format, organized according to class, are included. A
full executable R script 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.
42 References
AGUILERA, A., 1994 Formamide sensitivity: a novel conditional phenotype in yeast.
Genetics 136: 87-91.
AMES, B. N., I. ELSON-SCHWAB and E. A. SILVER, 2002 High-dose vitamin therapy
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55 FIGURE 1
B6 + Glutathione
B6 - Glutathione
Major Allele
Empty Vector
G307S (Nonfunctional)
V320A (Remedial)
5-fold dilution of cells
FIGURE 2
A
MA
A226T
Q526K
EV
CBS
PGK
B6+GTH
B6+GTH
GTH
B6
B6+GTH
GTH
B6+GTH
GTH
B6
B
B6 (ng/ml):
CBS
PGK
0
MA
400
T87N
0 400
P88S
0 400
P145L
0 400
V168M
0 400
M126V
0 400
FIGURE 3
A
Growth (OD600)
0.5
B6
(ng/ml)
400
4
2
1
0.5
0
0.25
0
growth rate
( logOD/ hours ± SD)
0.074 ± 0.006
0.072 ± 0.006
0.053 ± 0.005
0.034 ± 0.004
0.023 ± 0.003
0.014 ± 0.002
0
24
Time (hours)
48
72
B
growth rate relative to WT
125%
100%
75%
B6 (ng/ml)
0
0.5
1
2
4
400
50%
25%
0%
I278T
Q526K
K102Q
CBS allele
V320A
Figure 4
B
A
−1 0 1
Column Z−Score
B6 (ng/ml)
2
2
2
400
400
400
HEME
(ng/ml)
2.5
5
50
2.5
5
50
Growth worse than major allele
Poor growth
Intermediate growth
400
4
2
1
0.5
Growth worse than major allele
Growth similar to major allele
Poor growth
Intermediate growth
V354M
A69P
R439Q
Q526K
D444N
R369H
S466L
K102N
P78R
E128D
T434N
L456P
I435T
K102Q
V371M
R369C
P422L
P70L
R266K
D234N
G85R
A155T
R224H
G139R
V180A
S352N
T262M
V320A
A331V
D198V
A226T
A114V
T353M
P88S
I152M*
R379W*
A155V*
E176K*
K384N*
P290L*
T87N
E131D
I278T
A158V
Heme Remedial
B6 (ng/ml)
B6 Remedial
V371M
K102Q
K102N
P78R
P422L
R369C
A69P
R369H
D444N
R266K
G85R
V354M
T434N
E128D
R439Q
S466L
I435T
Q526K
D234N
L456P
G139R
P70L
A155T
V320A
D198V
P88S
T87N
S352N
A226T
A114V
A331V
R224H
I278T
A158V
E131D
V180A
T262M
T353M
Growth similar to major allele
−1 0 1
Column Z−Score
FIGURE 5
Row Z−Score (n=4)
−2 −1 0
1
Tryptophan
Threonine
Valine
Phenylalanine
Aspartic acid
Glutamine
Proline
Methionine
AdoMet
SAH
Methylthioadenosine
Homocystine
Glutathione
B6 (Pyridoxine)
Arginine
Lysine
Leucine/Isoleucine
Tyrosine
Allele: MA
B6 (ng/ml): 400
Methionine:
-
MA
1
-
MA
MA
400
400
+
+
MA
1
+
MA
1
+
G307S G307S
1
400
+
+
Figure 6
B
A
Log2 Intensity
Methionine
24
25
AdoMet
22
20
20
18
16
15
14
****
****
**
****
D
C
28
Log2 Intensity
Homocystine
22
26
20
24
18
22
20
16
****
****
7S
7S
30
G
7S
7S
30
+
A
M
+
G
M
A
M
-
M
-
A
+
A
+
A
+
A
+
M
1 400 1 400 1
M
A
30
+
30
+
G
400 400 1
G
A
M
-
M
M
A
-
A
+
A
+
A
M
+
M
Methionine: +
****
1 400 1 400 1
M
B6 (ng/ml): 400 400 1
Allele:
Glutathione
FIGURE 7
Robust
Remedial
Slow Growing
Nonfunctional
Heme
1
51
Catalytic
101
151
201
251
AdoMet
301
351
401
451
501
551
FIGURE S1
Methionine Salvage
Methylthioadenosine
Methionine
AdoMet
Folate
Biosynthesis
Methylation
SAH
Homocysteine
CBS
Cystathionine
Cysteine
Glutathione
Homocystine
CBS
PCNA
A226T
G307S
K102N
C109R
K384E
H65R
G151R
E131D
E144K
D198V
G139R
MA
FIGURE S3
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
Table S1
Growth Rate (Percentage of Major Allele Growth Rate)
B6 (ng/ml)
0.0
0.5
Heme (ng/ml)
Allele
Mean ± SD
n Mean ± SD
n
A69P
100.2 ± 43.5 7 102.5 ± 47.5 7
P70L
0.0 ± NA
7
15.6 ± 19.8 8
P78R
92.2 ± 1.7
6
97.4 ± 2.3
6
G85R
49.3 ± 1.9
6
69.0 ± 0.9
6
T87N
0.0 ± NA
5
0.0 ± NA
4
P88S
0.0 ± NA
5
0.0 ± NA
4
K102N
131.6 ± 29.7 6 105.1 ± 15.0 6
K102Q
94.2 ± 1.7
6
113.4 ± 0.9
5
A114V
0.0 ± NA
8
0.0 ± NA
8
E128D
118.0 ± 25.3 4 135.6 ± 53.9 4
E131D
19.2 ± 1.7
6
19.7 ± 3.1
6
G139R
49.2 ± 11.4 6
47.7 ± 19.5 6
I152M
ND
ND
A155T
0.0 ± NA
6
25.1 ± 1.8
4
A155V
ND
ND
A158V
0.0 ± NA
6
0.0 ± NA
6
E176K
ND
ND
V180A
0.0 ± NA
6
0.0 ± NA
6
D198V
0.0 ± NA
5
3.7 ± 3.6
6
R224H
0.0 ± NA
6
0.0 ± NA
6
A226T
0.0 ± NA
6
0.0 ± NA
6
D234N
52.4 ± 20.9 6
49.9 ± 16.3 6
T262M
0.0 ± NA
6
0.0 ± NA
6
R266K
71.9 ± 26.9 6
80.8 ± 40.7 6
I278T
0.0 ± NA
6
0.0 ± NA
6
P290L
ND
ND
V320A
0.0 ± NA
6
30.7 ± 17.0 5
A331V
0.0 ± NA
6
0.0 ± NA
5
S352N
0.0 ± NA
6
0.0 ± NA
6
T353M
0.0 ± NA
6
7.3 ± 6.5
6
V354M
89.6 ± 33.3 6
82.6 ± 14.8 6
R369H
107.0 ± 17.4 6
99.1 ± 4.4
5
R369C
109.8 ± 39.4 6 127.7 ± 46.5 6
V371M
131.5 ± 40.1 6 106.8 ± 15.6 6
R379W
ND
ND
K384N
ND
ND
P422L
83.7 ± 0.7
6
91.8 ± 2.4
6
T434N
72.3 ± 16.1 6
82.5 ± 13.8 5
I435T
125.2 ± 19.5 4 141.9 ± 16.5 4
R439Q
104.5 ± 23.5 6
118.9 ± 8.1
6
D444N
97.6 ± 4.2
4 106.7 ± 1.5
4
L456P
71.9 ± 16.0 6
62.2 ± 9.0
6
S466L
117.6 ± 35.3 6 156.3 ± 44.5 6
Q526K
57.8 ± 1.7
6
63.3 ± 3.0
6
1.0
Mean
130.9
32.7
97.2
86.7
9.3
6.2
99.1
100.6
0.0
138.5
16.4
43.4
ND
28.4
ND
0.0
ND
6.5
7.6
3.2
0.0
73.0
0.9
85.7
0.0
ND
26.8
0.0
0.0
9.3
89.4
131.5
103.4
105.6
ND
ND
94.5
91.4
89.3
140.8
117.9
55.0
126.5
78.8
2.0
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
43.7
13.3
2.5
1.9
7.2
9.4
12.9
1.7
NA
40.4
1.1
8.3
n
8
7
6
6
5
4
6
6
8
4
6
6
± 3.9
4
± NA
6
±
±
±
±
±
±
±
±
1.3
0.8
3.6
NA
18.0
1.9
25.2
NA
6
4
6
6
6
5
6
6
±
±
±
±
±
±
±
±
10.4
NA
NA
3.6
16.2
16.0
37.2
20.8
6
6
5
6
6
6
6
6
±
±
±
±
±
±
±
±
1.3
19.3
36.1
16.4
9.8
11.8
20.2
3.4
6
6
4
6
4
6
6
5
Mean
107.3
65.8
102.1
98.8
19.6
16.8
97.0
101.7
5.8
114.4
25.5
74.9
ND
49.9
ND
4.7
ND
18.6
16.0
7.7
4.7
84.4
9.7
104.8
8.3
ND
79.2
4.6
6.4
14.8
88.8
101.9
93.9
98.7
ND
ND
98.8
83.3
125.6
114.2
122.6
84.6
111.5
73.0
4.0
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
39.2
38.5
0.7
3.2
4.2
15.7
11.5
1.7
0.9
14.4
3.4
12.9
n
8
8
6
6
6
6
6
6
8
5
6
6
± 1.0
4
± 0.6
6
±
±
±
±
±
±
±
±
2.4
4.3
1.1
0.9
12.5
6.2
24.9
0.5
6
6
6
6
6
6
5
5
±
±
±
±
±
±
±
±
13.8
1.1
1.7
4.2
11.6
12.9
21.7
13.1
6
6
6
5
6
6
6
6
±
±
±
±
±
±
±
±
0.7
23.4
26.3
14.7
1.4
20.1
14.8
0.8
6
6
4
6
4
5
5
6
Mean
105.4
82.0
92.4
98.8
40.2
30.9
91.0
101.4
21.6
120.4
40.6
79.8
ND
60.0
ND
20.2
ND
58.9
35.1
29.4
22.4
88.9
51.4
100.8
20.6
ND
80.5
23.6
30.9
71.1
103.7
102.0
94.1
104.5
ND
ND
96.0
98.6
102.5
102.4
107.1
88.4
105.4
85.5
400.0
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
29.1
22.1
1.2
0.2
5.7
5.3
15.7
0.4
5.5
14.3
4.0
11.4
n
8
8
6
6
6
6
6
6
8
5
6
6
± 1.0
4
± 2.5
6
±
±
±
±
±
±
±
±
5.1
3.3
6.3
4.4
6.2
13.0
10.9
2.1
5
6
6
6
5
6
6
6
±
±
±
±
±
±
±
±
12.0
6.1
6.4
32.5
18.9
7.9
19.1
20.0
6
5
6
6
6
6
6
6
±
±
±
±
±
±
±
±
1.5
14.1
16.3
14.7
2.7
13.7
6.3
2.0
6
6
4
6
4
6
6
6
Mean
105.7
75.0
97.5
100.3
47.1
39.9
106.2
94.9
36.1
99.8
44.4
77.1
0.0
70.4
0.0
30.1
0.0
60.2
39.7
42.1
36.8
88.9
66.6
110.6
29.7
0.0
98.3
39.6
55.4
95.0
100.2
99.4
97.5
96.9
0.0
0.0
94.7
99.1
109.3
101.1
102.9
87.8
109.2
84.9
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
15.9
17.2
0.9
0.9
2.7
3.3
16.6
1.1
6.4
16.1
1.9
6.3
NA
1.4
NA
2.4
NA
2.5
3.1
7.1
4.0
9.8
7.7
22.0
3.2
NA
6.0
4.5
5.2
14.3
14.7
10.0
14.5
12.3
NA
NA
0.4
15.4
13.1
7.8
2.8
16.2
8.1
1.2
n
7
7
6
6
5
6
6
6
8
5
6
6
4
4
4
5
4
6
6
6
6
5
6
6
6
4
6
6
5
6
6
6
6
6
4
4
5
6
4
6
4
6
6
6
2.0
2.5
Mean
90.8
84.8
92.1
65.2
0.0
0.0
98.4
94.8
9.4
99.8
7.7
33.5
0.9
61.4
0.0
6.2
0.2
49.9
28.4
39.6
11.8
76.9
12.5
77.0
7.0
0.0
32.8
21.4
20.1
0.0
91.5
85.8
81.9
108.7
0.0
2.1
81.4
99.2
102.0
88.7
82.9
102.1
90.4
94.3
2.0
5.0
± SD
n Mean
± 6.0
3
95.8
± 11.3 4
84.9
± 7.4
3
89.2
± 5.3
3
81.6
± NA
4
0.0
± NA
3
4.4
± 13.4 3
94.8
± 4.5
3 103.3
± 2.4 10
23.0
± 10.4 8
98.3
± 1.2
4
11.3
± 4.4
4
49.7
± 0.8
4
3.0
± 4.7
4
65.7
± 0.0
4
0.0
± 0.5
7
8.6
± 0.4
3
0.8
± 5.5
3
63.3
± 4.6
4
36.3
± 7.5
4
45.5
± 3.8
4
28.7
± 7.9
7
86.3
± 6.3
7
38.3
± 5.5
3
89.4
± 1.7 11
10.8
± 0.0
3
1.9
± 2.1
3
61.9
± 2.5
9
32.7
± 6.8
4
41.5
± NA
3
2.3
± 6.2
3
98.9
± 7.8
4
92.0
± 11.0 15
84.5
± 7.2
3 101.9
± 0.0
3
2.0
± 2.5
4
5.4
± 8.5
7
85.9
± 4.8
3
93.0
± 7.7 4 105.6
± 7.0
4
95.5
± 5.1
6
94.0
± 6.7
3
80.7
± 4.3
3
92.0
± 6.7
6
95.0
2.0
50.0
± SD
n Mean
± 10.1 3
95.6
± 3.1
3
84.5
± 3.9
3
91.5
± 3.9
3
86.7
± NA
3
6.3
± 0.2
3
7.4
± 0.8
3
92.4
± 3.4
3 103.3
± 2.3 10
35.6
± 8.0
7 104.2
± 0.3
3
15.0
± 2.9
4
60.8
± 0.4
4
4.7
± 2.1
3
82.1
± 0.0
3
8.1
± 0.8
6
13.2
± 1.3
4
4.8
± 6.4
3
70.8
± 1.6
4
41.4
± 4.5
4
54.6
± 1.8
4
38.7
± 3.3
8 101.1
± 5.3
7
61.4
± 9.6
3 100.7
± 1.0 12
13.9
± 1.1
4
5.2
± 3.3
4
90.3
± 3.3
9
49.1
± 2.1
4
49.6
± 0.6
4
76.8
± 2.6
3
96.3
± 5.5
3
93.3
± 5.2 13
90.2
± 6.1
4 103.0
± 2.3
4
7.1
± 0.6
3
8.3
± 4.5
7
87.2
± 2.2
3
98.3
± 6.1 3 103.2
± 5.4
4
95.8
± 3.3
6
97.9
± 3.1
3
87.4
± 2.6
3
96.2
± 5.3
7
99.8
400.0
2.5
± SD
n Mean
± 7.7
4 101.2
± 2.7
3
88.5
± 2.8
4
89.5
± 2.6
3
80.7
± 0.3
3
0.0
± 0.3
3
0.0
± 5.1
3
93.3
± 4.2
3
99.0
± 2.9 11
39.6
± 5.1
6 102.1
± 1.2
3
17.7
± 2.7
3
47.9
± 0.3
4
0
± 5.4
4
73.7
± 0.8
3
0
± 1.5
7
18.4
± 0.8
4
0
± 5.1
4
66.7
± 3.2
4
47.0
± 3.3
3
64.6
± 3.3
4
45.3
± 6.1
7
82.9
± 3.8
6
48.6
± 6.0
4
87.4
± 0.7 12
18.1
± 1.3
4
0
± 3.0
3
60.0
± 3.3
9
42.5
± 4.4
4
64.5
± 2.5
3
10.1
± 8.0
4
99.5
± 2.9
3
91.9
± 4.5 14
90.7
± 8.5
4 102.1
± 0.9
4
0
± 1.2
3
9.1
± 5.9
7
88.7
± 6.0
3 102.1
± 3.4 4 105.6
± 3.7
3
97.0
± 3.2
7
93.6
± 8.0
4 101.9
± 5.9
3
97.5
± 4.6
7
96.7
400.0
5.0
± SD
n Mean
± 4.6
3
98.3
± 5.5
4
89.9
± 3.4
3
91.6
± 4.7
3
83.6
± NA
4
0.0
± NA
3
18.8
± 5.6
3
93.3
± 5.4
3
98.5
± 2.4
9
46.5
± 6.9
7 102.5
± 1.0
4
23.2
± 4.0
3
63.0
± NA
4
18.2
± 4.4
4
81.8
± NA
4
12.5
± 0.8
6
25.4
± NA
4
10.0
± 5.2
3
69.8
± 2.5
3
49.3
± 2.8
3
63.3
± 2.0
3
50.7
± 4.4
7
92.3
± 5.5
7
65.7
± 5.2
3
94.1
± 0.5
9
22.4
± NA
4
24.0
± 5.3
3
73.3
± 3.6
9
56.5
± 8.4
4
76.3
± 1.2
3
29.1
± 5.6
4
98.4
± 3.3
4
92.0
± 5.8 14
92.1
± 4.0
3
97.7
± NA
4
15.4
± 7.2
4
17.8
± 4.8
7
90.9
± 5.0
4
95.2
± 4.3 4 107.1
± 4.4
4
99.5
± 5.2
6
93.6
± 3.3
3
97.7
± 4.6
4
90.2
± 4.6
7
99.3
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
4.1
8.1
5.6
10.1
NA
7.8
1.9
3.9
3.6
6.6
1.6
4.8
1.4
2.4
2.1
1.8
6.9
6.9
1.7
1.5
1.2
5.0
4.5
7.0
1.2
7.4
6.0
4.1
5.7
2.3
4.6
3.2
6.8
4.0
1.3
3.7
4.6
3.4
3.1
10.3
6.6
3.8
2.2
3.9
n
3
4
4
4
3
4
3
4
10
7
4
4
4
3
4
7
4
5
3
3
3
8
7
4
10
4
4
10
3
3
4
4
15
3
4
4
6
3
4
3
8
3
4
7
400.0
50.0
Mean
98.0
94.6
100.6
96.0
18.2
20.3
95.6
105.4
48.2
97.0
27.4
69.3
22.4
87.2
20.7
28.4
20.5
75.4
54.6
61.3
60.0
101.9
81.2
103.1
26.1
33.2
94.2
65.7
77.4
99.6
99.6
95.3
91.4
101.4
18.3
19.9
91.9
93.6
109.5
100.3
99.1
94.3
90.2
99.5
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
SD
9.1
3.5
5.5
6.4
0.8
1.6
3.0
6.2
3.1
4.6
2.2
3.9
0.8
3.8
3.0
1.3
0.6
0.3
2.6
2.6
1.9
4.3
6.0
12.2
1.9
4.2
7.4
4.2
3.9
4.9
3.5
4.3
6.0
3.2
1.5
1.4
8.3
4.4
4.4
5.2
5.0
3.0
3.6
4.1
n
3
4
3
4
4
4
3
4
10
8
4
3
4
4
4
7
3
3
4
3
3
8
7
4
11
4
3
10
3
4
4
3
15
4
4
3
7
4
3
4
7
3
3
7
Table S2
Metabolite levels of the major allele and V320A remedial allele
Allele
MA
V320A
MA
B6 (ng/ml)
400
400
1
Metabolite
Mean ± SD
n Mean ± SD
n p value Mean
0.001 25.34
Methionine
19.94 ± 0.80 4 24.70 ± 0.26 4
0.01 22.44
Homocystine
18.63 ± 0.75 3 22.17 ± 0.32 3
Glutathione
27.36 ± 0.08 4 24.97 ± 0.22 4 0.0001 24.11
± SD
± 0.20
± 0.20
± 0.24
n
4
4
4
V320A
1
Mean ± SD
26.48 ± 0.73
23.03 ± 0.38
23.69 ± 0.32
n p value
4
NS
4
0.05
4
0.05