Download Surrogate Genetics and Metabolic Profiling for Characterization of

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. We thank Georjana Barnes, Susanna Repo, and
Jonathan Wong for critical evaluation of the manuscript.
This work was supported in part by funds from a Howard
Hughes Medical Institute Professorship in support of undergraduate biology education. Additional support was provided by a grant from the U.S. Department of the Army
(W911NF-10-1-0496).
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Communicating editor: S. 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.