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xIP-MS: streamlined structural proteomics
1
xIP-MS: topological analysis of chromatin-associated protein complexes using single
affinity purification
Matthew M Makowski¹, Esther Willems¹, Pascal WTC Jansen¹, Michiel Vermeulen¹˒²˒*
1. Radboud Institute for Molecular Life Sciences, Radboud University Nijmegen, Geert
Grooteplein 28, 6525 GA Nijmegen, the Netherlands
2. Cancer Genomics Netherlands, University Medical Center Utrecht, 3584 CG Utrecht, the
Netherlands
Running Title: xIP-MS: streamlined structural proteomics
Keywords: Chemical cross-linking mass-spectrometry, chromatin, affinity purification
*Correspondence addressed to M.V. at:
Email: M.Vermeulen@ncmls.ru.nl
MCP Papers in Press. Published on November 11, 2015 as Manuscript M115.053082
Copyright 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
xIP-MS: streamlined structural proteomics
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Abbreviations
XL-MS Cross-linking Mass Spectrometry
xIP-MS Cross-linking Immunoprecipitation Mass Spectrometry
coIP Co-immunoprecipitation
PRPP Phosphoribosyl Pyrophosphate Synthetase Complex
SMC Structural Maintenance of Chromosomes
XRCC X-Ray Repair Cross-Complementing Protein
MCM Mini-Chromosome Maintenance
LFQ Label free quantification
DSB Double-strand breaks
PTM Post-translational modification
GFP Green fluorescent protein
SCX Strong cation exchange
SEC Size exclusion chromatography
xIP-MS: streamlined structural proteomics
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Summary
In recent years, cross-linking mass spectrometry (XL-MS) has proven to be a robust and
effective method of interrogating macromolecular protein complex topologies at peptide
resolution. Traditionally, XL-MS workflows have utilized homogenous complexes obtained
through time-limiting reconstitution, tandem affinity purification, and conventional
chromatography workflows. Here, we present cross-linking immunoprecipitation-MS (xIP-MS),
a simple, rapid, and efficient method for structurally probing chromatin-associated protein
complexes using small volumes of mammalian whole cell lysates, single affinity purification,
and on-bead cross-linking followed by LC-MS/MS analysis. We first benchmarked xIP-MS
using the structurally well-characterized phosphoribosyl pyrophosphate synthetase (PRPP)
complex. We then applied xIP-MS to the chromatin-associated cohesin (SMC1A/3), XRCC5/6
(Ku70/86), and MCM complexes, and we provide novel structural and biological insights into
their architectures and molecular function. Of note, we use xIP-MS to perform topological
studies under cell cycle perturbations, showing that the xIP-MS protocol is sufficiently
straightforward and efficient to allow comparative cross-linking experiments. This work,
therefore, demonstrates that xIP-MS is a robust, flexible, and widely applicable methodology for
interrogating chromatin-associated protein complex architectures.
xIP-MS: streamlined structural proteomics
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Introduction
The structural basis of specific protein-protein interactions and higher-order protein complex
multimerization crucially informs our understanding of many molecular and cellular processes.
AP-MS-based strategies have been a major player in the elucidation of specific protein-protein
interactions and core protein complexes [1-3]. However, while quantitative AP-MS/MS
experiments identify specific interactors for any given bait, they cannot differentiate between
direct and indirect interactors or provide structural or topological information on protein complex
assemblies. Furthermore, traditional structural methodologies often fail with large or dynamic
protein complexes including chromatin remodeling or chromatin associated protein complexes.
Cross-linking mass spectrometry (XL-MS), therefore, has emerged as a powerful technique for
analyzing protein complex architectures through direct observation of subcomplex interfaces at
the peptide level [4-6]. Landmark studies used XL-MS to reveal the architectures of the
chromatin remodeling complexes Ino80 and SWR1 [7, 8], and other chromatin-associated
complexes have been interrogated using traditional XL-MS workflows [9-14].
In general, cross-linked peptides represent a small fraction of the total pool of peptides measured
in an MS/MS analysis. Therefore, traditional XL-MS workflows have utilized homogenous
complexes obtained through time-limiting reconstitution, tandem affinity purification, and
conventional chromatography workflows to facilitate the detection of low abundance cross-
linked peptides from the target protein complex. For example, reconstitution of complexes to
near homogeneity using tandem tagging systems has been previously reported, using a variety of
tagging combinations [13, 15, 16]. Similarly, baculovirus over-expression and recombinant
yeast systems have also been used effectively to maximize protein yield [7-9, 14]. Further
strategies often used to enrich cross-link identifications include strong cation exchange
xIP-MS: streamlined structural proteomics
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chromatography (SCX), size exclusion chromatography (SEC), the use of multiple proteases, or
alternate cross-linking strategies including acid-acid cross-linkers, CID-cleavable cross-linkers,
or tagged, enrichable cross-linkers [16-20]. These steps have been necessary to enrich to an
appreciable degree the number of measurable cross-linked peptides from the target complex.
However, implementing and optimizing these workflows represents a considerable barrier to
entry to the XL-MS field for many molecular biologists.
Single-AP-MS strategies are commonly applied in chromatin biology, where specific interactors
can be identified in the presence of a vast amount of background proteins [2, 3, 21-23]. Our
group and others have previously established workflows for identifying specific protein
interactors and interaction stoichiometries using a GFP-tagging BAC transgene systems
expressing tagged baits at a near-endogenous level [22, 24-26]. However, thus far simple, single-
IP methodologies have not been widely used in XL-MS experiments. One main challenge is
sufficiently purifying protein complexes to facilitate the consistent identification of low-
abundance cross-linked peptides over background. For example, a recent study used specially
engineered high-affinity, lysine-free GFP-nanobodies to efficiently extract endogenous level
tagged baits [27]. Here, we present cross-linking immunoprecipitation mass spectrometry, or
xIP-MS, utilizing a simple, efficient GFP-AP workflow followed by a high-stringency washing
procedure to obtain highly pure protein complex from small volumes of human whole cell
lysates. xIP-MS couples single-AP GFP purification with on-bead crosslinking and sample prep
for MS/MS analysis. Dynamic exclusion settings, exclusion of lower charge-state peptides, and
the high speed of modern mass spectrometers facilitate the fragmentation and identification of
low abundance cross-linked peptides. Furthermore, computational analysis of cross-linked
peptides is a crucial and widely discussed aspect of XL-MS workflows [28-30]. In xIP-MS, we
xIP-MS: streamlined structural proteomics
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use straightforward data-filtering steps based on peptide length (selectively removing those
matches where one long, high scoring peptide compensates for a short, ambiguous peptide
match) and reproducibility in multiple experiments (to remove spurious matches) to increase
confidence in cross-link identifications.
We benchmark xIP-MS against the structurally well-characterized PRPP complex and provide
evidence for a structural ensemble of PRPP complexes in vivo [31]. We then apply xIP-MS to
the chromatin-associated cohesin, XRCC5/6, and MCM complexes. We use xIP-MS to analyze
the cohesion complex and observe numerous cross-links within the well-ordered head region,
complementing previous cross-linking experiments and directly supporting a model for the
human cohesin head interaction [11, 12]. Next, we used xIP-MS to analyze conformational
changes in the x-ray repair cross-complementing protein 5/6 complex (XRCC5/6, or Ku70/86)
[32]. We observe conformational flexibility in the Ku and SAP domains consistent with their
involvement in DNA binding during double-stranded break repair [33]. Finally, we use xIP-MS
to characterize soluble mini-chromosome maintenance (MCM) subcomplexes [34-37]. We
present an architecture for interactions between MCM subunits and show that soluble MCM
subcomplexes are generally cell-cycle invariant.
The xIP-MS workflow requires approximately the time and resources of a standard coIP
experiment, yet can provide additional structural information about subunit interfaces and
complex topologies. We further demonstrate the biological usefulness of xIP-MS in studying
complex structural ensembles, conformational flexibility, or subcomplex architectures under
perturbation. Thus, we present here xIP-MS as a simple, efficient, and broadly applicable
technique for probing protein complex architectures.
xIP-MS: streamlined structural proteomics
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Methods
Cell culture and lysate collection
Cell lysates were collected from stably transgenic HeLa Kyoto cells expressing near-endogenous
levels of GFP-tagged bait protein from a recombineered BAC transgene system [24, 25]. Cell
lines were cultured in DMEM plus 10% FBS and 100U/ml penicillin and streptomycin. For one
week, cells were kept under selection with 400ug/ul geneticin to ensure stable integration of the
tagged bait, then expanded in normal media. Cell lysates were collected by resuspending cells in
five cell pellet volumes of lysis buffer (150mM NaCl, 50mM Tris pH 8.0, 1mM EDTA, 20%
glycerol) supplemented with 1% NP-40, 1mM DTT, and Roche EDTA-free complete protease
inhibitors (CPIs). Cell lysates were rotated at 4C for two hours. The lysate was then centrifuged
for 30 minutes at 4,000rcf and 4C, and the supernatant was collected and snap-frozen. This lysis
method produced high-quality lysates of ~10mg/mL protein concentration.
GFP affinity purification for label free quantification (LFQ)
20uL GFP bead slurry was used per affinity purification (Chromotek). Beads were pre-washed
three times with Buffer C (300mM NaCl, 20mM HEPES pH 7.9, 20% glycerol, 2mM MgCl2,
0.2mM EDTA) supplemented with 1% NP-40, 0.5mM DTT, and EDTA-free Complete Protease
Inhibitors (CPIs, Roche). 400ug whole cell lysate was added to the pre-washed beads and
adjusted to 400uL with whole cell lysis buffer plus 1% NP-40, 1M DTT, and CPIs. Ethidium
bromide was added to 50ug/mL. Reactions were incubated on a rotating wheel for one hour at
4C. After IP, beads were washed twice with Buffer C increased to 1M NaCl and supplemented
with 1% NP-40, 0.5mM DTT, and CPIs. Beads were then washed twice with PBS supplemented
with 1% NP-40, and finally washed twice with PBS. All supernatant was removed carefully with
xIP-MS: streamlined structural proteomics
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a 30G syringe before sample prep for AP-MS/MS analysis. Control samples were prepared using
binding control agarose beads with the same protocol (Chromotek). All LFQ experiments were
performed in triplicate. GFP-AP and control samples from the same experiment were prepared
on the same day and analyzed by AP-MS/MS sequentially.
GFP affinity purification for xIP-MS
GFP affinity purifications for xIP-MS were performed essentially as described for LFQ GFP
affinity purifications. 30uL of GFP bead slurry was used per affinity purification, and 1mL of
total whole cell lysate was used per pulldown (~10mg/mL). All xIP-MS experiments were
performed in duplicate. Replicates were performed independently and measured by AP-MS/MS
separately.
On-bead chemical cross-linking for xIP-MS
On-bead cross-linking was performed by immediately resuspending beads in 50mM borate-
buffered saline containing 1mM BS3 (Thermo Scientific) following GFP affinity purification.
Cross-linking reactions were performed for one hour at room temperature with shaking at
1000rpms. Reactions were quenched by adding 100mM ammonium bicarbonate and incubated at
room temperature for ten minutes with shaking at 1000rpms. All supernatant was again carefully
removed with a 30G syringe.
Sample preparation for AP-MS/MS analysis
Sample preparation was performed in the same manner for LFQ and xIP-MS samples. Purified
or cross-linked proteins were denatured and reduced in elution buffer (2M urea, 100mM
xIP-MS: streamlined structural proteomics
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ammonium bicarbonate, 10mM DTT) for 20 minutes at room temperature with shaking at
1000rpms. Iodoacetimide was added to 50mM, and samples were incubated in the dark for ten
minutes at room temperature with shaking at 1000rpms. 0.25ug of trypsin was added, and
samples were digested overnight at room temperature to ensure complete release of tryptic
peptides from the beads. Digested peptides were acidified with 10% TFA and stored on C18
StageTips for mass spectrometry analysis.
AP-MS/MS analysis
All chromatography was performed on an Easy-nLC 1000 (Thermo Scientific). Buffer A was
0.1% formic acid and Buffer B was 80% acetonitrile and 0.1% formic acid. LFQ samples
collected on the LTQ-Orbitrap QExactive were measured by developing a gradient from 9-32%
Buffer B for 94 minutes before washes at 50% then 95% Buffer B, for 120 minutes of total data
collection time. LFQ samples collected on the LTQ-Orbitrap Fusion Tribrid were measured by
developing a gradient from 9-32% Buffer B for 114 minutes before washes at 50% then 95%
Buffer B, for 140 minutes of total data collection time. xIP-MS samples were measured by
developing a gradient from 5-32% Buffer B for 214 minutes before washing with 60% then 95%
Buffer B, for 240 minutes of total data collection time. The flow rate was 250nl/min for all
gradients.
SMC1A-GFP and XRCC6-GFP LFQ samples were measured on an LTQ-Orbitrap QExactive.
Full MS scans were collected from 300 to 1650 m/z with a resolution of 70,000 and an AGC
target of 3e6. MS/MS scans were collected in the orbitrap with a resolution of 17,500, an AGC
target of 1e5, an NCE of 25, and an intensity threshold of 8.3e2. TopN was set to 10, unassigned
and 1+ charged ions were excluded, and dynamic exclusion was set at 20 seconds.
xIP-MS: streamlined structural proteomics
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PRPS1-GFP and MCM6-GFP LFQ samples were measured on an LTQ-Orbitrap Fusion Tribrid.
Full MS scans were collected from 400 to 1500 m/z with a resolution of 120,000 and an AGC
target of 4e5. MS/MS scans were collected in the linear ion trap using CID activation with a
resolution of 30,000, an AGC target of 1e4, collision energy of 35, and an intensity threshold of
5e3. Scans were collected in data-dependent top speed mode, ions of charge state 2-7+ were
considered, and dynamic exclusion was set at 60 seconds.
All xIP-MS samples were measured on an LTQ-Orbitrap-QExactive. Full MS scans were
collected from 300 to 1650 m/z with a resolution of 70,000 and an AGC target of 3e6. MS/MS
scans were collected in the orbitrap with a resolution of 17,500, an AGC target of 1e5, an NCE
of 25, and an intensity threshold of 4e2. TopN was set to 10, unassigned, 1+, and 2+ charged
ions were excluded, and dynamic exclusion was set at 20 seconds.
LFQ peptide identification and analysis
Thermo RAW files from LFQ AP-MS/MS measurements were analyzed with MaxQuant version
1.5.1.0 using default settings and searching against the Uniprot curated human proteome (release
03/09/2014) [38, 39]. Cysteine carbamidomethyl was used as a fixed modification, and N-
terminal acetylation and methionine oxidation were used as variable modifications. Additional
options Match between runs, LFQ, and iBAQ were selected. Stoichiometry calculations and
volcano plots were produced essentially as described before using a one-way ANOVA test [22].
Statistical cutoffs were chosen such that no proteins were present as outliers on the control, non-
GFP side of the volcano plot.
xIP-MS: streamlined structural proteomics
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xIP-MS cross-linked peptide identification and analysis
For cross-link identification, Thermo RAW files were converted to mgf format using MSConvert
with the peak picking option for levels “1- “ selected and the “Prefer Vendor” option checked
[40]. mgf files were analyzed in pLink version 1.21 with default settings to identify cross-linked
peptides with an FDR threshold of 0.05 using a precursor mass tolerance of 10ppm and a
fragment ion mass tolerance of 20ppm searching against specific interactors as identified by LFQ
analysis [30]. BS3 was used as the crosslinker, trypsin was used as the enzyme with a maximum
of two missed cleavages allowed, cysteine carbamidomethylation was included as a fixed
modification, and methionine oxidation was included as a variable modification. pLink
identifications were further filtered to include only matches with >=5 and <=40 residues per
peptide. Only cross-linked sites identified in two out of two independent replicates were
considered for further structural analysis (Supplemental Figure 1) [29]. Cross-link maps were
produced with xiNet, and distance constraints were analyzed with Xlink Analyzer in UCSF
Chimera [41-43]. All molecular visualizations were performed with UCSF Chimera [41].
Homology modeling
For PRPS1, only short internal gaps in the crystal structure were modelled using MODELLER in
UCSF chimera (PDB: 2h06) [31, 44]. All PSPS1 structural alignments were performed using
MatchMaker in UCSF Chimera [45].
All cohesin homology models were produced using SWISS-MODEL using alignments
calculated with EMBOSS Needle [46-48]. For SMC1A (PDB: 1w1w) and SMC3 (PDB: 4ux3)
N- and C-terminal head regions were aligned with their respective yeast PDB structure, and then
the SMC1A model was further aligned with a second SMC3 head domain present as a dimer in
xIP-MS: streamlined structural proteomics
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the 4ux3 crystal structure for analysis of distance constraints. For comparative analysis using
prokaryote (PDB: 3zgx) and archea (PDB: 4i99) SMC homologs, a similar analysis was
performed. The cohesin hinge domain was similarly modeled from the mouse homolog (PDB:
2wd5)
Analysis of normal modes
Analysis of normal modes using anisotropic network analysis was conducted for XRCC5/6
(PDB: 1jeq) in Python with the prody package using default settings [49]. The twenty slowest
frequency modes were kept for visual analysis in VMD [50]. Figures were generated in prody,
and videos were made using VMD.
Data Access
The mass spectrometry RAW data, maxQuant identifications for LFQ analysis, and pLink
identifications for cross-linking analysis have been deposited to the ProteomeXchange
Consortium via the PRIDE partner repository with the dataset identifier PXD002987 [51].
xIP-MS: streamlined structural proteomics
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Results
High stringency washes effectively purify chromatin-associated complexes and permit chemical
cross-linking analysis
We first wanted to establish a protocol for effectively purifying stable protein complexes using a
simple, single affinity purification workflow. Our group previously optimized workflows for
high efficiency purification of GFP-tagged baits using a BAC transgene system [24-26]. Using
this method as a starting point, we tested whether more stringent washing conditions following
bead purification would be sufficient to enrich stable complexes with substantially increased
purity. After bead incubation in cell lysate buffer with 1% NP-40 and physiological salt, we
washed our beads twice with cell lysis buffer plus 1% NP-40 adjusted to 1M NaCl (Figure 1A).
This straightforward protocol effectively enriched a number of chromatin associated protein
complexes over background, on the order of hundreds of nanograms of purified material (Figure
2A, Supplemental Figure 1A-C). By gel and iBAQ analysis, we estimate this strategy isolates
stable, specific interactors with >95% purity. We were also able to efficiently cross-link purified
proteins on-beads directly following washing steps using the well-characterized BS3 cross-linker
in a borate-buffered saline buffer (Figure 2A).
Analysis of cross-linked peptides requires a database search that expands exponentially with the
number of peptides included. Such analysis becomes more computationally expensive and less
sensitive as the number of proteins included increases. Therefore, we used a standard targeted
method of defining a specific database of high-probability complex members for cross-link
searching. In our case, this involved identification of stable, specific interactors by LFQ analysis
[22, 39]. These high-confidence interactors were then included in our cross-link database for
targeted searching (Figure 1A). This approach is justified on two bases; first, cross-linked
xIP-MS: streamlined structural proteomics
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peptides are already low-abundance in the pool of total peptides, therefore cross-linked peptides
from highly enriched, specific interactors are substantially more likely to be measured than those
from low-abundance, non-specific proteins. Second, we used a filtering strategy that effectively
removed spurious identifications to background peptides and specifically identified cross-linked
samples. We filtered out those cross-links where either the identified peptide was shorter than
five residues or longer than forty residues. This selectively removed matches where one long,
high scoring peptide compensated for a short, ambiguous partner in the scoring function. We
then additionally filtered out those cross-link identifications that were not observed in both
duplicate experiments, thus selectively removing remaining spurious matches (Supplemental
Figure 2A, Supplemental Figure 3A). To test the specificity of this filtering procedure, we
analyzed duplicate LFQ AP-MS/MS runs (without cross-linking) against a database of specific
LFQ interactors for each of five baits used in this study. These samples were highly enriched for
peptides of specific interactors, yet were not cross-linked and were thus negative controls. We
identified only two spurious cross-link matches across all five analyses using this filtering,
neither of which were identified as positive identifications when analyzing cross-linked samples,
strongly indicating this filtering effectively precludes false positives. We therefore concluded
that our high-stringency purification conditions obtained protein complexes with sufficient purity
to allow the confident identification of low abundance cross-linked peptides.
Structural benchmarking against the PRPP complex
We used PRPS1-GFP to structurally benchmark xIP-MS against the PRPP complex, a
multimeric enzyme associated with nucleotide synthesis, which has a known crystal structure
(PDB: 2h06) [31]. For the PRPP complex, we identified the bait protein, PRPS1, as well as two
xIP-MS: streamlined structural proteomics
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associated proteins, PRPSAP1 and PRPSAP2, as significant interactors by LFQ analysis (Figure
3A). We then used iBAQ values from our LFQ experiment to calculate relative stoichiometries
for each subunit to the bait (Figure 3B). Using xIP-MS, we were able to identify 54 reproducible
cross-linked sites between these proteins (Figure 3C). Importantly, we were able to map all of
our unambiguous PRPS1 cross-linked sites onto the hexameric PRPS1 crystal structure within a
distance constraint of 34 Å (Figure 3D showing PRPS1 cross-links and Supplemental Figure 4A-
B showing all PRPS1 and PRPSAP1/2 cross-links). The distribution of identified cross-links
distances for PRPS1 was statistically distinct from the distribution of total distances and was thus
structurally informative (Figure 3E). This provides an important structural verification that xIP-
MS provides valid cross-link identifications.
A structural ensemble of PRPP complexes
PRPS1 has a canonical catalytically active hexameric form composed of three PRPS1 dimers.
The crystal structures of PRPSAP1 (PDB: 2c4k, RMSD: 0.901 Å with PRPS1) and PRPSAP2
(PDB: 2JI4, RMSD: 0.889 Å with PRPS1) are also known and indicate high structural homology
with PRPS1. PRPSAP1 and PRPSAP2 were observed at stoichiometries of 7-8% relative to
PRPS1, indicating either auxiliary subunit is present at slightly lower than one copy per two
PRPS1 hexamers (Figure 3B). We therefore considered whether our cross-linking data could
support the presence of an in vivo structural ensemble of PRPP complexes, where PRPSAP1 and
PRPSAP2 switch positions with canonical PRPS1 subunits within a single PRPP hexamer. This
possibility is particularly intriguing considering the reported role of PRPSAP1 in negative
regulation of PRPP catalytic function [52]. Their high structural homology enabled high-
confidence structural alignment of PRPSAP1 or PRPSAP2 with PRPS1 subunits, and we were
xIP-MS: streamlined structural proteomics
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able to map all 51 of our unambiguous cross-linked sites onto either PRPS1, PRPS1-PRPSAP1
(6 inter-links), PRPS1-PRPSAP2 (2 inter-links), or PRPSAP1-PRPSAP2 (2 inter-links)
subcomplexes within a distance constraint of 34 Å (Supplemental Figure 4A-B). High structural
homology and our cross-linking data thus suggest an ensemble model of PRPP hexamers,
potentially offer a functional explanation for PRPSAP1’s negative regulatory function of PRPP,
and, again, indicate the structural validity of high confidence, reproducible xIP-MS cross-link
identifications.
A model for cohesin head interactions
We next applied xIP-MS to the topological analysis of chromatin-associated protein complexes.
Cohesin is a dynamic and structurally intriguing protein complex involved in maintaining higher
order chromosome structure, most canonically during sister chromatid separation at mitosis. We
were able to effectively purify the core pentameric cohesin complex using SMC1A-GFP as a bait
(Figure 2A, Figure 4A). We purified SMC1A and SMC3 at essentially a 1:1 stoichiometric ratio,
consistent with their known dimeric interaction implicated in flexibly encircling chromosomes
(Figure 4B). However, we identified cohesin accessory proteins (RAD21, STAG1/2, PDS5B,
and WAPAL) at significantly lower stoichiometric ratios to the core cohesin dimer (Figure 4B).
This could indicate lower stoichiometric ratios in vivo, higher dynamism in bait interactions or
lower bait affinity, cell cycle effects, or sensitivity to washing conditions. We observed
numerous cross-links within the SMC1A and SMC3 head domains (Figure 4C). This data is
therefore complementary to previous studies, which both observed cross-linking predominantly
between the coiled-coils separating SMC1A and SMC3 head and hinge domains, potentially due
to different protein extraction methods or different cross-linking buffer conditions [11, 12]. We
xIP-MS: streamlined structural proteomics
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conjectured that our cross-linking data would provide direct experimental support for a model of
the human SMC1A/SMC3 head interaction derived from available crystal structures. Therefore,
we modelled the human SMC1A and SMC3 head regions using crystal structures from their
yeast homologs (PDB: 1w1w and PDB: 4ux3, respectively) [53, 54]. We then aligned our
SMC1A model with a dimeric SMC3 head from the 4ux3 crystal structure (Figure 4D,
Supplemental Figure 5A). Similarly, we modelled the SMC1A and SMC3 hinge regions from
their respective chains in the mouse homolog (PDB: 2wd5) (Supplemental Figure 5B) [55]. In
sum, we found that 24/26 mappable cross-links were within a distance constraint of 34 Å using
these models, a number of which sat directly at the SMC1A/SMC3 head interface, indicating that
this straightforward modeling approach captures many architectural features of the human
cohesin head interaction (Figure 4D, Supplemental Figure 5C). Using a similar homology
modeling approach with prokaryote and archaea SMC homologs resulted in an increased number
of violations, therefore indicating eukaryotic cohesin structures represent the best available
model for the human complex (Supplemental Figure 6A) [56]. Therefore, xIP-MS provides
cross-linking data that complements previous XL-MS studies and directly supports a model of
the human cohesin head domain.
Conformational flexibility in XRCC5/6
Because xIP-MS is efficient enough to facilitate the use of replicates to identify very high-
confidence cross-linked sites, we sought to broaden the applications of xIP-MS by using it to
study potential conformational changes in flexible proteins. Such studies are typically difficult to
interpret because cross-links identified in flexible regions might exceed static spatial constraints
and therefore be disregarded as false. However, identification of such cross-links in multiple
xIP-MS: streamlined structural proteomics
18
independent experiments substantially increases confidence in their structural validity and points
towards conformational flexibility. Towards this end, we performed xIP-MS on the XRCC5/6
DNA damage repair complex [32]. XRCC5/6 has a flexible SAP domain thought to be involved
in conformational shifts involved in DNA recognition and binding at double-strand breaks
(DSBs) [32, 33]. Indeed, the SAP domain is resolved in the XRCC5/6 heterodimer without DNA
bound, though a presumably flexible linker region, residues 539-558, is not resolved (PDB:
1jeq). Moreover, the SAP domain is not resolved in the XRCC5/6 crystal structure with DNA
bound, further indicating the functional flexibility of this region in DNA contact (PDB: 1jey).
We were able to effectively purify the XRCC5/6 heterodimer at nearly 1:1 stoichiometry using
xIP-MS (Figure 2A, Figure 5A-B). We observed numerous cross-links within the XRCC5/6
heterodimer (Figure 5C). Although approximately 84% of our identified cross-linked seemed
spatially valid, we observed a few reproducible cross-linked sites that exceeded a spatial
constraint of even 40 Å (Supplemental Figure 7A-B). These cross-links we deemed excessive
violations, potentially indicative of conformational flexibility. Upon closer inspection, we
realized these cross-links generally correlate with regions of high B-factor in the crystal structure
and could be explained by two major conformation shifts (Figure 5D, Supplemental Figure 7A).
First, the DNA-binding Ku domain loop appears to possess substantial flexibility in the vertical
axis (Supplemental Figure 7A). This could be a consequence of cross-linking in solution in the
absence of DNA, and may represent native flexibility of the unbound dimer. We also observed
cross-links connecting the SAP domain with the Ku domain, indicating a conformational shift
where the flexible SAP domain approaches the Ku domain DNA binding ring. Analysis of
normal modes further supported substantial flexibility in the Ku and SAP domains
(Supplemental Figure 7C, Supplemental Video 1). Intriguingly, such conformational shifts could
xIP-MS: streamlined structural proteomics
19
be potentially indicative of allowed functional motion involved in stabilizing and capping DNA
DSB ends between the Ku and SAP domains (Figure 5D). Therefore, xIP-MS experiments
provide potential functional insight into conformational changes involved in XRCC5/6 DNA-
binding action. This highlights the ability of xIP-MS to provide high-confidence cross-link
identifications relevant in the study of protein flexibility and conformational states. Thus,
importantly, xIP-MS complements traditional crystallographic structural studies, which reveal
only static conformational states.
Topology of cell-cycle independent MCM subcomplex interactions
Because xIP-MS is a straightforward protocol requiring relatively small volumes of cell lysates,
we sought to show that xIP-MS could methodologically compare protein topologies under states
of perturbation. Traditionally, performing comparative cross-linking experiments has been
difficult due to the typical requirement of tens or hundreds of micrograms of protein at high
purity. However, we were easily able to perform xIP-MS experiments in duplicate qualitatively
comparing previously observed soluble MCM complexes in asynchronous and S-phase blocked
cells [37]. MCM is activated during DNA replication and loaded onto processive replication
forks; therefore, we expected MCM subcomplex topologies might change dramatically in
association with MCM activation during S-phase. However, we noted similar banding patterns
by gel analysis, similar interactors via LFQ proteomics, and similar relative stoichiometries for
interactors in both cell cycle states after MCM6-GFP purification (Figure 2A, Figure 6A-F,
Supplemental Figure 8A). Furthermore, we observed cross-linking between MCM2/4/6/7
subcomplexes (Figure 6B, 6D). Our gel analysis indicated three predominant cross-linked
species present in both states (Figure 2A). Our xIP-MS analysis showed a high degree of overlap
xIP-MS: streamlined structural proteomics
20
between cross-linked sites observed in both cell cycle states, indicating soluble MCM complexes
are topologically cell-cycle invariant (Figure 6F). Therefore, our data suggests a sequential
model of MCM subcomplex assembly, where ubiquitous soluble MCM subcomplexes are
assembled during loading onto processive replication forks during S-phase [34-36]. Our data also
suggests these soluble MCM subcomplexes may be in vast excess of active replication forks, as
they do not seem to be depleted from the soluble fraction during S-phase (Figure 2A). Our xIP-
MS data additionally provides structural insights into MCM subunit interfaces within these
subcomplexes. Finally, these experiments indicate the ease with which xIP-MS can be applied to
studying protein complex topologies under a variety of possible cellular or molecular
perturbations.
xIP-MS: streamlined structural proteomics
21
Discussion
Chemical cross-linking coupled with mass spectrometry is becoming an increasingly popular
technique for studying large or difficult protein complex architectures and topologies at low
resolution. XL-MS is a particularly important tool for interrogating chromatin-associated protein
complexes, which are often highly dynamic, and subject to large conformational shifts when
enacting their functions. However, while affinity purification based strategies are commonly
coupled with mass spectrometry to identify specific protein interactions, typical XL-MS
workflows have traditionally demanded large (tens or hundreds of micrograms) amounts of pure,
homogenous complex coupled with time-consuming enrichment steps to facilitate detection of
cross-linked peptides over background. The difficulty of implementing and optimizing complex
cross-linking workflows has thus limited their widespread adoption. In general, XL-MS
workflows are scaling up towards proteome-wide studies often using cleavable cross-linkers, or
scaling down towards computational prediction of protein structures with high resolution using
broader-specificity or photo-activatable cross-linkers [16, 57]. We envision xIP-MS instead as a
workflow that could bridge the gap between proteome-wide and protein-specific XL-MS
workflows, offering peptide-resolution architectural and topological information with the ease of
coIP experiments particularly in the context of comparative cross-linking workflows [58-61].
This study establishes xIP-MS as an additional tool for molecular and structural biologists,
offering a flexible and robust methodological platform adaptable to a variety of diverse
applications.
It is worth noting that the xIP-MS protocol as presented is designed to enrich stable core
complexes with high efficiency and purity from relatively small lysate volumes. The high
stringency washing steps necessitated by this workflow can preclude highly dynamic or transient
xIP-MS: streamlined structural proteomics
22
interactions between even stoichiometric interactors. Similarly, salt sensitive interactions may be
impeded by xIP-MS. As a general rule, specific purification conditions may be required for
different complexes; this should be taken into consideration for the complex in question.
However, the workflow we present in this study represents a generally effective starting point, as
we have shown by applying xIP-MS successfully to a number of different protein complexes
with different downstream applications, including: heterogeneous assemblies, homology
modeling, structural dynamics, and comparative cross-linking. xIP-MS therefore represents a
simplified and flexible alternatative to existing on-bead cross-linking methodologies.
Although on-bead cross-linking workflows offer many experimental benefits, one notable
drawback to on-bead cross-linking workflows is the potential to cross-link purified proteins to
the bead itself, potentially facilitating misidentifications. Here, we use a small GFP nanobody
(12kDa) with stringent data filtering to decrease the likelihood of spurious identifications as
much as possible. However, alternate strategies include Ni-NTA purification for His-tagged
proteins as Ni-NTA is a non-amine containing substrate, using a membrane permeable cross-
linker prior to cell lysis and purification, or using engineered high-affinity, lysine-free
nanobodies [15, 16, 27]. In general, careful experimental design and data analysis should
minimize the risk of false positive identifications from on-bead cross-linking workflows.
xIP-MS also offers much promise as a functional follow up to more traditional structural
workflows. Because xIP-MS is sufficiently straightforward to allow multiple replicates, high
confidence, reproducible cross-linking with xIP-MS can facilitate structural dynamics analysis as
we have shown for XRCC5/6. Importantly, perturbation experiments now become substantially
streamlined, indicated by our analysis of cell cycle invariance in soluble MCM subcomplexes.
Quantitative cross-linking with isotopic linkers offers great potential for comparing
xIP-MS: streamlined structural proteomics
23
conformational states under perturbations, and it is possible xIP-MS could contribute towards
further developments in quantitative cross-linking workflows [58-61].
It is likely developments in protein purification reagents, novel cross-linking chemistries and
softwares, and faster, more sensitive instruments will improve xIP-MS workflows in the future.
For example, xIP-MS would benefit directly from novel ultrahigh-affinity GFP nanobody
dimers, as reported recently [62]. Also, developments in enrichable or cleavable cross-linkers
could facilitate higher cross-link identification rates [16, 20, 63]. Therefore, xIP-MS can also be
considered as an experimental platform for rapid optimization of novel cross-linking strategies,
thereby extending the toolbox of structural proteomics technologies.
Acknowledgements
M.M. and M.V. received funding for this project from the Marie Curie FP7 DevCom ITN.
xIP-MS: streamlined structural proteomics
24
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Figure Legends
Figure 1: xIP-MS: a workflow for the analysis of protein complex topologies
Figure 2: High stringency washes effectively purify protein complexes for on-bead cross-linking
A) BS3- lanes represent one half of an xIP-MS experiment using 1mL of cell lysate. The
second half was resuspended in cross-linking buffer for on-bead cross-linking as
described in text, and is shown in the BS3+ lanes. All lanes were resolved on the same
gel at the same exposure; black lines indicated where lanes were cropped together for
visibility.
Figure 3: xIP-MS analysis of PRPP reveals high confidence distance constraints
A) LFQ analysis of PRPS1 was performed with triplicate pulldowns. Outliers are indicated
in red, and background binders are indicated in black. Outlier cutoffs were drawn such
that no proteins were present in the non-GFP quadrant on the volcano plot. B)
Stoichiometry analysis was performed as decribed. All ratios are calculated by setting the
bait (PRPS1) equal to 1. Error bars indicate standard deviations from triplicate samples.
C) Identified cross-links for PRPP. The cross-link map was drawn in xiNet. Purple lines
indicate self-links, and green lines indicate inter-protein cross-links. Ambiguous cross-
links (the same peptide in multiple proteins) are indicated by dashed lines. Homotypic
cross-links (the same peptide cross-linked to itself, indicating multimerization) are drawn
in red. Uniprot annotated domains are colored variously along the protein sequence bar.
D) PRPS1 cross-links mapped onto the PDB: 2h06 crystal structure. Cross-links under 34
Å are colored in blue. PRPS1 monomers are colored in light grey. The silhouette of the
PRPS1 holo-hexamer surface is shown in transparent grey.
xIP-MS: streamlined structural proteomics
33
Figure 4: xIP-MS suggests a model for human cohesin head interactions
A) LFQ analysis identifies canonical cohesin tetrameric subunits as interactors of SMC1A.
Data is plotted as described previously. B) SMC1A and SMC3 interact at a near 1:1
stoichiometry as indicated by iBAQ values. C) Cross-links between SMC1A and SMC3
preferentially localize towards the head domains, indicated in green on the protein
sequence bars. D) Homology modeling allows mapping of SMC1A and SMC3 cross-
links onto models for the human proteins. SMC1A is colored light grey, and SMC3 is
colored in dark grey. Cross-links below 34 Å are shown in blue, and cross-links above 34
Å are shown in red. The silhouette represents the surface of the SMC3 dimer from the
PDB: 4ux3 crystal structure used for aligning the SMC1A and SMC3 models.
Figure 5: xIP-MS reveals conformational changes in XRCC5/6
A) LFQ identifies XRCC5/6 as robust interactors, in agreement with our gel analysis. B)
XRCC5/6 stoichiometry is nearly 1:1 as indicated by iBAQ values. C) Cross-linking
within the XRCC5/6 heterodimer. The cross-link map is colored as described previously.
D) XRCC5/6 are colored by B-factor as indicated on the key; the protein backbone radii
are scaled similarly by size. Cross-links within 40 Å are shown in blue, and cross-links
longer than this threshold are shown in red. Major conformational shifts explaining
observed cross-linking patterns are displayed as yellow arrows. The structure of PDB:
1jeq is used to display cross-links as the SAP domain is resolved only in this structure;
however, the surface of the DNA structure bound to XRCC5/6 from PDB: 1jey is
displayed in transparent yellow, after alignment with 1jeq using MatchMaker in UCSF
Chimera.
xIP-MS: streamlined structural proteomics
34
Figure 6: xIP-MS reveals S-phase independent MCM subcomplex topologies
A) MCM2/4/6/7, MCM10, and MCMBP are observed as interactors with MCM6 in
asynchronous cells. B) Cross-linking analysis reveals inter-protein contacts within
soluble MCM complexes in asynchronous cells. C) Similarly, MCM2/4/6/7, MCM10,
and MCMBP are observed as interactors with MCM6 in S-phase blocked cells. D)
Cross-linking analysis reveals a similar topology in soluble S-phase MCM complexes. E)
Relative stoichiometries to the bait as indicated by iBAQ values show MCM subunit
stoichiometries do not change substantially when cells are blocked in S-phase. F) Venn
diagram indicates substantial overlap of cross-linked sites between MCM subunits after
S-phase block.
Bait Protein
GFP
Collect whole cell
lysates with
singly-tagged bait
protein
Perform single-AP
with high stringency
washes
Identify specific
interactors via LFQ
proteomics
On-bead cross-linking
and sample preparation
b3
b4
b5
b6
y2
y3
y4
y5
b7
y6
y1
Identify cross-linked
peptides from specific
interactors
Identify relative subunit
stoichiometries
A
Figure 1
A
MCM6-GFP Asynchronous
MCM6-GFP S-phase
PRPS1-GFP
SMC1A-GFP
XRCC6-GFP
BS3 - + - + - + - + - +
250
130
100
70
55
35
25
15
Ladder
Figure 2
A
-log10(p-value)
GFP/Non-GFP Ratio
0
0.2
0.4
0.6
0.8
1
1.2
PRPS1 PRPSAP1 PRPSAP2
iBAQ Ratio to PRPS1
B
PRPSAP2
PRPS1
PRPSAP1
C
D
90
Figure 3
E
0
5
10
15
20
25
30
35
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Binned
Xlink Count
Xlink Distance (Å)
PRPP Theoretical Xlinks (All)
PRPP Observed Xlinks
Welch's T-test p -value: 2.09x10
-11
A
-log10(p-value)
GFP/Non-GFP Ratio
B
RAD21
SMC1A
SMC3
C
0
0.2
0.4
0.6
0.8
1
1.2
iBAQ Ratio to SMC1A
D
Figure 4
A
-log10(p-value)
GFP/Non-GFP Ratio
0
0.2
0.4
0.6
0.8
1
1.2
XRCC6 XRCC5
iBAQ Ratio to XRCC6
B
XRCC6
XRCC5
C D
Figure 5
Ku Domain
SAP Domain
0
0.2
0.4
0.6
0.8
1
1.2
MCM6 MCM4 MCM7 MCMBP MCM2 MCM10
iBAQ Ratio to MCM6
Asynchronous
S-phase
A
-log10(p-value)
GFP/Non-GFP Ratio
E
-log10(p-value)
GFP/Non-GFP Ratio
C
MCM4
MCM7
MCM2
MCM6
MCMBP
B
MCM4
MCM7
MCM2
MCM6
MCMBP
D
F
Asynchronous
S-phase
6
20
83
Figure 6
