Efficient assignment and NMR analysis of an intactvirus using sequential side-chain correlations andDNP sensitizationIvan V. Sergeyeva, Boris Itinb, Rivkah Rogawskia, Loren A. Dayc, and Ann E. McDermotta,1

aDepartment of Chemistry, Columbia University, New York, NY 10027; bNew York Structural Biology Center, New York, NY 10027; and cPublic HealthResearch Institute, Rutgers University, Newark, NJ 07103

Contributed by Ann E. McDermott, March 27, 2017 (sent for review July 1, 2016; reviewed by Bjoern Corzilius, Ayyalusamy Ramamoorthy,and Chad M. Rienstra)

An experimental strategy has been developed to increase theefficiency of dynamic nuclear polarization (DNP) in solid-state NMRstudies. The method makes assignments simpler, faster, and morereliable via sequential correlations of both side-chain and Cα reso-nances. The approach is particularly suited to complex biomoleculesand systems with significant chemical-shift degeneracy. It wasdesigned to overcome the spectral congestion and line broadeningthat occur due to sample freezing at the cryogenic temperaturesrequired for DNP. Nonuniform sampling (NUS) is incorporated toachieve time-efficient collection of multidimensional data. Addition-ally, fast (25 kHz) magic-angle spinning (MAS) provides optimal sen-sitivity and resolution. Data collected in <1 wk produced a virtuallycomplete de novo assignment of the coat protein of Pf1 virus. Thepeak positions and linewidths for samples near 100 K are perturbedrelative to those near 273 K. These temperature-induced perturba-tions are strongly correlated with hydration surfaces.

Pf1 bacteriophage | DNP | SSNMR

By providing potential enhancements of up to 300-fold (1, 2), andobserved enhancements of 250-fold for biological samples (3),

dynamic nuclear polarization (DNP) is revolutionizing solid-stateNMR (SSNMR) spectroscopy for many applications (4). DNPspectrometers have eliminated the notion of being “signal-limited”in most practical cases and, together with nonuniform sampling(NUS) techniques (5–7), make it possible to collect 3D and four-dimensional (4D) NMR spectra of biological macromolecules in12–48 h. For practical purposes, n-dimensional spectra enablecorrelations between n interacting nuclei. DNP studies of smallmolecules (8, 9), a variety of biological systems (refs. 3 and 10–16;reviewed in refs. 17 and 18), inorganic clusters (19–21), and mate-rial surfaces (20, 22–25) have yielded insights that would have beenotherwise impossible.Despite its successes, DNP has been limited by reduced resolu-

tion at the cryogenic temperatures required. Linewidths are typi-cally increased by at least twofold, and peak positions may change.Partial protein assignments have been made (10, 15, 26, 27). Inmost studies, however, assignments are carried over to the analysisof DNP data. Such approaches, although user-friendly, are prob-lematic if one is interested in resonances that are inaccessible at oraround room temperature or those that are sensitive to changes inconformation or solvation at cryogenic temperatures, as is commonfor 15N chemical shifts (28, 29).A common paradigm for assignment is the N–Cα–CX (NCACX)-

N–C′–Cα (NCOCA) “backbone walk” (26, 30, 31)—first demon-strated on bovine pancreatic trypsin inhibitor (32), ubiquitin (33),and α-spectrin SH3 domain (34) —which allows correlations be-tween neighboring residues based on their amidic 15N chemicalshifts (see Fig. 2A for graphical depiction). However, this NCACX-NCOCA backbone walk paradigm does not generally succeed forproteins under DNP conditions. At 100 K, intrinsic protein line-widths are too broad to avoid massive spectral overlap in 2D and3D 15N–(13C)–13C spectra. For C′ and N, the resonances key to

making sequential interresidue assignments, limited chemical-shiftdispersion means that the spectral congestion under DNP condi-tions impedes backbone assignments.We show here that sequential assignments at 100 K with DNP

enhancement are fully tractable by means of a method we termsequential side-chain–side-chain (S3) correlation spectroscopy. S3

experiments are conceptually similar to the 4D Cα–N–C′–Cα(CANCOCA) experiment, pioneered by Rienstra and coworkers toassign regions with overlapping Cα chemical shifts (35), which hasenabled the assignment of complex proteins and assemblies byconventional SSNMR (36–39). Such experiments remain highlychallenging near room temperature; data-acquisition times areoften on the order of weeks to months, making the experimentsvery demanding of sample and instrument stability. DNP at cryo-genic temperatures, conversely, affords the key benefit of enor-mously enhanced starting signals, enabling long-range polarizationtransfers with high sensitivity. In this context, DNP is able to deliveron its promise of acquiring high-quality data in vastly less time.The S3 method helps to reduce spectral overlap and to com-

pensate for broader linewidths without reducing signal intensity. Themethod also significantly reduces acquisition time. It is used here tocollect and fully assign spectra for the major coat protein of Pf1 inthe frozen state near 100 K, without reference to data for unfrozensamples near 273 K. Pf1 is an extensively studied filamentous phage(40–52). It has been used to demonstrate promising enhancementsin whole-virus samples by DNP, including assignment of Pf1 DNA

Significance

This work presents a technique for dynamic nuclear polarization(DNP)-enhanced magic-angle spinning (MAS) solid-state NMRstudies of complex proteins and biological assemblies. The se-quential side-chain correlation approach streamlines the site-specific assignment of NMR peaks in multidimensional spectra, acritical step in determining structural information such as distances.When combined with DNP enhancement, fast MAS, and non-uniform sampling, this technique allows for faster data acquisitionthan previously possible. Applied to the intact Pf1 bacteriophage,sequential side-chain correlation spectra have enabled a virtuallycomplete assignment using DNP data alone. These assignmentsshed insight into the chemical shift and linewidth changes associ-ated with cryogenic temperatures. Our data point to hydration asa key variable influencing these parameters.

Author contributions: I.V.S., B.I., L.A.D., and A.E.M. designed research; I.V.S., B.I., and R.R.performed research; L.A.D. contributed new reagents/analytic tools; I.V.S., R.R., and A.E.M.analyzed data; and I.V.S., R.R., L.A.D., and A.E.M. wrote the paper.

Reviewers: B.C., Goethe University, Frankfurt am Main; A.R., University of Michigan;and C.M.R., University of Illinois at Urbana–Champaign.

The authors declare no conflict of interest.1To whom correspondence should be addressed. Email: aem5@columbia.edu.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1701484114/-/DCSupplemental.

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resonances (51, 53). Comparison of chemical-shift datasets ofPf1 near 100 K (DNP-enhanced) and 273 K (non-DNP) providesinsight into the causes of chemical-shift perturbations (CSPs). TheS3 method eliminates the need to use inappropriate near-room-temperature chemical-shift tables for assignment of DNP data.

ResultsInformation Richness and Rationale for S3 Spectroscopy. PromisingDNP signal enhancements for Pf1 spectra at 600-MHz field havebeen obtained: ∼35-fold in a 3.2-mm sapphire rotor and 60-fold ina 1.9 mm rotor. However, linewidths of DNP-enhanced spectrataken near 100 K were considerably broadened relative to spectrataken at 273 K (Fig. 1). The broadening for 13C lines ranged from0.5 to 1.3 ppm (parts per million); for 15N, it was from2.0 to >4.0 ppm. This broadening caused nuclei such as N or C′that have small isotropic chemical-shift dispersion to lose value forassignment. In unfavorable cases, a single broad DNP resonancecould extend over virtually the entire chemical-shift dispersion of agiven residue type (SI Appendix, Fig. S2). Resonances from Cα, theother backbone atom, which have dispersions of several parts permillion within a residue type and >10 ppm between residue types,provided sufficient chemical-shift discrimination, but could remaincrowded. Amino acid side chains, however, provided maximalchemical-shift dispersion and excellent discrimination betweenamino acid types. The ratio of dispersion to linewidth serves as ameasure of information value; assigning resonances with DNPenhancement should therefore emphasize information-rich Cα andside-chain resonances. Dimensions such as N or C′ have less dis-crimination value. However, because directing polarization trans-fers through the N afforded directionality, high efficiency, andsimplified phase cycling, the amidic nitrogen dimension was oftenincluded in our experiments, whereas carbonyl was omitted.Moreover, linewidths were primarily broadened by static in-

homogeneity, making absolute peak positions less certain in DNPspectra. In Pf1 datasets at 100 K, absolute 13C chemical shifts formultiple peaks assigned to the same atom ranged over 0.3 ppm,

which is double the range for spectra at 273 K. Thus, identificationof an amino acid based on a single chemical shift became signifi-cantly error-prone. Double-chemical-shift correlations for each res-idue for confident assignment could be achieved by walking betweenneighboring residues both forward and backward (Fig. 2A).To this end, we present a modular pulse sequence that can en-

code 3D, 4D, or five-dimensional (5D) datasets (Fig. 2 B and C).The S3 pulse sequence exploits the chemical-shift dispersion of theside chains, as correlated through their Cα resonances. In brief,side-chain polarization was transferred first to the correspondingbackbone Cα or C′ by 13C–13C recoupling, then through the amidenitrogen and to the preceding or following amino acid via a double-spectrally induced filtering in combination with cross-polarization(SPECIFIC-CP) (54) step (13C→15N, then 15N→13C), and, finally,out to the side chain of the second amino acid by a longer 13C–13Crecoupling element. A full 5D S3 experiment correlated CXi–Cαi–Ni–C′i-1–CXi-1 in the “backward,” or i→i − 1, direction, and

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Fig. 1. (A) The 2D 13C–13C DARR spectra (100 ms mixing time) of Pf1 illus-trating linewidth differences between DNP conditions at 106 K (purple) and thesame sample at 273 K (green). (B) Expansions around several assigned peakswith unique chemical shifts are shown. Although some well-resolved peaks at273 K remained well resolved at 106 K, peaks in more crowded regions canbecome unrecognizable. Even for well-resolved peaks, linewidths broadenedapproximately twofold, from <100 Hz (0.5 ppm) to >200 Hz (1.3 ppm), makingassignments more challenging. See SI Appendix for additional experimentaldetails, including demonstration of 35-fold enhancement in 3.2-mm rotor and60-fold enhancement in 1.9-mm rotor (SI Appendix, Fig. S1).

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Fig. 2. (A) Contrast of the polarization transfer pathways (Upper) and keychemical-shift correlations (Lower) for NCACX/NCOCA and S3 assignmentstrategies, as depicted on a protein backbone. Regions of overlap between theforward and backward correlation experiments for each assignment strategyare shown in dashed outlines. The S3 approach covers the full transfer pathwayof both NCACX and NCOCA experiments in a single experiment and provides amuch larger overlap region, enabling multiple chemical-shift correlations be-tween neighboring residues (e.g., N–Cα–N and direct Cα–Cα) for maximumrobustness and ease of assignment. (B and C) Schematics of the pulse sequencesfor backward [B; 4D CX(Cα)NC′CX i→i − 1] and forward [C; 3D CX(C′)N(Cα)CXi→i + 1] S3 correlation experiments. In both experiments, a short (60–80 us) H–Ctangential CP was used to maximize side-chain 13C polarization, before a short13C–3C homonuclear recoupling period to maximize transfer to Cα or C′. Tenmilliseconds of DARR mixing was typically used for Cα, and 20 ms for C′ (em-pirically optimized). To transfer polarization to the previous or subsequentresidue, 13C–15N SPECIFIC-CP (Cα–N in the backward case, and C′ –N in theforward case), a 15N chemical shift encoding period, followed by 15N–13CSPECIFIC-CP (N–C′ in the backward case, N–Cα in the forward case) was used.After optional 13C chemical-shift encoding on Cα/C′, a second 13C–13C homo-nuclear recoupling element transferred polarization to the side chain, whichwas detected directly. This transfer required longer mixing times to achieveseveral-bond transfers; 50 ms of DARR mixing was used for short-range cor-relations and 250 ms for long-range correlations. Spinal-64 decoupling (dec)was used during evolution periods; continuous wave (CW) decoupling wasapplied during cross-polarization.

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CXi–C′i –Ni+1–Cαi+1–CXi+1 in the “forward,” or i→i + 1, direction,thus combining information-rich side-chain chemical shifts withdirectional selectivity to provide a robust and reliable assignmenttool. Although the pulse sequence incurred significant signal lossesdue to the number of transfers involved, a much larger startingsignal (relative to non-DNP SSNMR) allowed sufficient signal tonoise at detection. Interestingly, we found the efficiencies of the twoN↔C transfers to be nonmultiplicative, presumably due to the

selection of homogeneous volume by the first transfer. We foundthat the overall efficiency of a triple cross-polarization (CP) transferunder DNP was quite favorable, at 35% and 21% for S3 i→i − 1 andS3 i→i + 1, respectively. This efficiency allowed S3 spectra to retainadequate signal to noise while maintaining transfer selectivity. S3

data could be collected in 1–2 d for 4D experiments and in ∼1 wkfor 5D experiments. The 3D spectra presented here were collectedin <1 d, despite substantial signal averaging.

DNP-Based de Novo Assignment of Pf1 Coat Protein.We demonstratedthe robustness of our S3 assignment protocol by using DNP data,including 3D NCACX, NCOCA, and 3D S3 i→i + 1 and S3 i→i −1 spectra, to assign de novo the Pf1 major coat protein. We assigned205 13C resonances and 51 15N resonances, corresponding to 100%and 94% completeness, respectively (SI Appendix, Fig. S3). Mostof the S3 experiments shown here were performed on sparsely13C-labeled samples to minimize 13C linewidths by eliminating13C–13C nearest-neighbor couplings. However, it is importantto note that these experiments also worked well for uniformly la-beled samples. As Fig. 3 demonstrates, uniform labeling enabledlonger-range transfers. A 250-ms dipolar-assisted rotational reso-nance (DARR) (55) 13C–13C transfer step allowed correlations todistant side-chain sites and, in some cases, to residues beyond thenearest neighbor. For challenging regions with high levels of residueand chemical-shift redundancy, the availability of both short- andlong-range S3 data greatly improved the efficiency of assignment(Fig. 4). Additionally, by using faster magic-angle spinning (MAS;up to 25 kHz) in 1.9-mm rotors, we reduced 13C peak widths to1.0 ppm and 15N widths to 3.5 ppm. The resulting sharper peaksenabled high-resolution and high signal-to-noise spectra despite thepresence of multiple internuclear transfers and long mixing times.Furthermore, faster MAS rates allowed spinning sidebands to beplaced further away from peaks of interest, preventing problems ofoverlap. The primary drawback of faster MAS—namely, smallersample volume as a result of using smaller diameter rotors—wasmore than offset by the superior DNP enhancement factorsafforded (SI Appendix, Fig. S1).

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Fig. 3. Long-range S3 spectra of Pf1 enabled assignment of distant side-chainsites, whereas comparison with short-range S3 helped to identify nearest-neighbor backbone correlations, as shown in 13C–13C planes (A) and 13C–15Nplanes (B) at the indicated 15N and 13C indirect dimension frequency, re-spectively, from short-range (green) and long-range (orange) CX(Cα)N(C′)CXi→i − 1 S3 spectra. DARR transfers of 10 and 50 ms were used for the short-range experiment; 50- and 250-ms DARR were used for long-range S3. 13C and15N linewidths were as low as 1.0 and 3.5 ppm, respectively. See SI Appendixfor additional experimental details.

22IleCa-N-21AlaCa

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25%-13C,U-15N Pf1 U-13C,15N Pf1 U-13C,15N Pf1

Fig. 4. Strip plot of assignments for residues 21–29 of the Pf1 coat protein, showing representative backbone and side-chain interresidue “walks.” Data from50-ms NCACX (blue), “short-range” S3 i→i − 1 10,50 ms (green), and “long-range” S3 i→i − 1 50, 250 ms (orange) are overlaid at the indicated 15N frequency ineach slice. Other spectra, including NCOCA and S3 i→i + 1, were used to confirm and extend these assignments. See SI Appendix for more experimental details.

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In assigning the highly repetitive, highly helical Pf1 coat protein,NCACX/NCOCA correlations were only useful for small stretches(SI Appendix, Fig. S4). These correlations relied on a single 15Nchemical shift to correlate the intraresidue NCACX resonances tothe interresidue NCOCA resonances, limiting sequential assignmentto the i→i − 1 direction. In regions lacking notable 15N outliers likeglycine (the Pf1 coat protein contains no proline or histidine resi-dues), congestion became insurmountable, and NCOCA correla-tions were largely useless for interresidue walks because both N andC′ resonances were overlapping. In contrast, the S3 technique pro-vided a direct interresidue Cα–Cα correlation. The superior reso-lution of 13C alongside the larger chemical-shift dispersion of Cα/CXsites allowed for straightforward and bidirectional assignment of theprotein backbone via S3 i→i − 1 and i→i + 1. Additionally, S3

provided both intraresidue and interresidue correlations in the sameexperiment without increased congestion. In the present work,NCACX/NCOCA spectra were used alongside better-resolved S3

data in a confirmatory fashion, where possible.NCACX/NCOCA spectroscopy relies on the directional selec-

tivity of the N→C transfer, as provided by SPECIFIC-CP (54). TheS3 scheme improves on this directional selectivity by using twoSPECIFIC-CP N↔C transfers; ideally, each of these transferspasses <10% of the undesired transfer pathway (e.g., N→C′ wouldbe undesired in a selective N→Cα transfer). Because only asingle transfer pathway is preferentially followed, cross-peaks in13C–13C planes show up on one side of the diagonal, as opposed tothe diagonally symmetric pattern normally observed in 13C–13Ccorrelations, helping to avoid spectral congestion. Reversing thedirection of transfer along the protein backbone causes cross-peaks to appear on the opposite side of the diagonal; the S3

i→i − 1 and i→i + 1 spectra thus complement each other forassignment purposes and, when overlaid, provide chemical-shiftredundancy, as shown in Fig. 5. In comparing cross-peak patternsbetween S3 i→i − 1 and i→i + 1 spectra, we found S3 directionalselectivity to be nearly perfect in isolated 15N slices. Importantly,the S3 i→i − 1 experiment showed very few intraresidue 13C–13Ccross-peaks. The vast majority of the detected cross-peaks followedthe intended i→i − 1 transfer pathway. For S3 i→i + 1 experiments,some intraresidue diagonal intensity was observed due to the lowerselectivity of N→Cα transfers (∼25% leakage to C′) relative toN→C′ transfers (∼10% leakage to Cα) as optimized (SI Appendix,Fig. S5). However, the S3 i→i − 1 transfer scheme did effectivelysuppress most intraresidue correlations, as demonstrated bycomparison with an S3 experiment intentionally made nonselectiveby using a Cα→N→Cα transfer. When overlaid with canonical S3

spectra (SI Appendix, Fig. S6), the nonselective variant had manyintraresidue cross-peaks absent in the S3 i→i − 1 experiment.Although ambiguity arises in many forms throughout the process

of assignment, the S3 approach was designed to avoid severalcommon sources. It is clear from a metaanalysis of SSNMRchemical shifts by Fritzsching et al. (56) that C′–Cα correlations arerarely distinctive enough to identify a particular amino acid incongested spectra. Cα–Cβ cross-peaks, conversely, tend to occupyunique fingerprint regions. By relying heavily on the latter, analysisof S3 spectra avoids deconvolution of myriad overlaid C′ –Cα peaksin poorly resolved 15N planes, eliminating a major potential sourceof error. Also avoided is the need to align two separate spectra tocorrelate residues, as in the case of NCACX/NCOCA. Spectralalignment is prone to error under DNP conditions, where widenitrogen resonances can span multiple planes of an n-dimensionalspectrum. An example of such difficulties is illustrated in SI Ap-pendix, Fig. S4. Pair ambiguity (e.g., ability to confidently assignpeaks of interest to an isoleucine-glycine pair, but inability to specifywhich isoleucine-glycine pair in the protein sequence) was alsolargely avoided because S3 data permit forward and backwardbackbone walks (example shown in Fig. 5). By avoiding ambiguousassignments, the S3 approach not only cut down on assignmenterror, but also saved analysis time. Compared with the multiple

weeks typical of a full de novo protein assignment by SSNMR, allassignments presented here were performed in ∼60 person-hours.

Chemical-Shift Perturbation and Line Broadening Correlated withHydration. To date, several DNP studies have reported significantCSPs near 100 K (27, 57). Having assigned the coat protein ofPf1 both with and without DNP enhancement independently, wewere able to examine the magnitude and sequence/structural dis-tribution of CSPs. Large experimental CSPs (Fig. 6A and SI Ap-pendix, Fig. S7) were clustered into three major regions: theoutward-facing N-terminal domain (residues 1–20), the kink re-gion (residues 24–26), and the inward-facing C terminus (residues

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Fig. 5. Sequential assignment of A36–L38 shown in 13C–13C slices of 3D NCACX(green), 3D S3 i→i+ 1 (purple), and i→i − 1 (orange) at the indicated 15N chemicalshifts. Notably, the two S3 spectra show very different patterns. (A) In S3 i→i − 1,G37-A36 cross-peaks appeared at the glycine frequency in the indirect dimension(y axis) and were “read out” at alanine frequencies in the direct dimension(x axis), whereas in S3 i→i + 1, these frequencies were reversed. No S3 i→i −1 intensity was detected at the glycine frequency, and no S3 i→i + 1 intensity wasobserved on the alanine slice, except for a diagonal peak representing G37Cα–N–Cα. (B) A similar pattern was observed for G37–L38 interresidue cross-peaks.(C) With the exception of some diagonal intensity, the observed cross-peakpatterns were exactly as expected from the transfer diagram, demonstratingthe excellent selectivity of S3 experiments. See SI Appendix for additional ex-perimental details.

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40–46), which is the DNA-interaction domain. The spatial distri-bution of CSPs thus correlated extremely well with the hydrationmap of the major coat protein (52), derived at 273 K from long-range 1H–

13C and 1H–15N NMR contacts (Fig. 6B). The high

degree of overlap between hydrated residues and residues withsignificant CSPs implies that the majority of CSPs under DNPconditions are linked to solvation effects, consistent with earlierresults from amyloid-forming oligopeptides (27) and amyloidfibrils (58).A similar analysis to assess trends in 13C and 15N linewidths near

100 K revealed differences between hydrated and nonhydratedresidues. Broader linewidths were found predominantly in thehydrated N-terminal region and at the C terminus, with a smallerincrease in linewidth observed in the kink region near residue 25(SI Appendix, Fig. S8). Residues that were not hydrated at 273 Kdid not exhibit as much line broadening at cryogenic temperaturesas residues that were hydrated.CSPs and linewidth both report on the immediate chemical en-

vironment of a residue; linewidth especially can serve as a strongmarker of conformational inhomogeneity. As a result, the strikingpositional similarities between CSPs, linewidths, and solvent-exposedsurfaces point to solvation and inhomogeneity being closely linkedat cryogenic temperatures. Our data suggest that, when theirclosest layer of hydration water becomes frozen or glassy atcryogenic temperatures, previously hydrated biomolecular sitesare likely to undergo structural rearrangements as a result ofcoupling to the glassy solvent, causing both broader linewidths andpossible changes in chemical shift. Unlike at higher temperatures(59), these effects are not ameliorated by the addition of even highmolar ratios of cryoprotectants, such as glycerol, to the aqueoussolvent mixture. Sites that are not normally solvent-exposed,however, are not necessarily subject to the same constraints andcan maintain favorable linewidths and relatively low CSPs, even atcryogenic temperatures down to 100 K, and potentially lower.

ConclusionsWe used S3 correlation experiments to acquire and assign de novothe highly repetitive and almost fully helical coat protein of the

Pf1 bacteriophage under DNP conditions. The backbone assign-ments were complete for all 46 residues, and the overall assignmentwas 95% complete. Furthermore, we found that S3 experimentsallow accurate assignments to be carried out efficiently, with fea-tures such as chemical-shift redundancy across the diagonal be-tween S3 i→i − 1 and S3 i→i + 1 spectra. Fast-spinning DNP at25 kHz gave further improvements in signal to noise and enabledlong-range side-chain–side-chain polarization transfers. Together,DNP NCACX and S3 (3D) experiments can be acquired in under2 d by using NUS, allowing efficient use of DNP instrumentation.With advances in both the speed and ease of assignment, DNPhas the potential to provide a wealth of structural informationon a timescale not previously possible. In our hands, S3 ex-periments have been used to aid in the assignment of severalbiological systems of interest, including viral capsids, amyloidfibrils, and membrane proteins.Comparison of DNP data collected near 100 K and near 273 K

revealed that 13C and 15N CSPs cluster into distinct regions of theprotein. Observed DNP 13C and 15N linewidths adhered to a similarpattern, with larger linewidths correlated to larger CSPs. Regionswith significant perturbations and increased linewidths were highlycorrelated with a previously determined hydration map, suggestingthat CSPs and linewidths under DNP conditions are both closelyrelated to solvation phenomena, but do not necessarily require ex-posure to bulk solvent. These observations can be used to predictwhich regions of a biomolecule are likely to experience significantCSPs at cryogenic temperatures and provide clues toward furtherDNP sample optimization.

Materials and MethodsSamples of Pf1 bacteriophage were prepared by using published protocols (45,52). DNP requirements, of high MAS speeds and cryogenic conditions, did notaffect phage infectivity on host Pseudomonas aeruginosa, strain K. For U-15N,25%–

13C Pf1, 25% 13C-glucose with random isotopic distribution was usedduring the growth stage to minimize the effect of 13C–13C J-couplings onlinewidth, while retaining sufficient 13C–13C pairs to record 13C homonuclearcorrelations. For U-15N,13C Pf1, 99% 13C6-glucose was used.

DNP samples were prepared by mixing 2% (wt/vol) PEG 8000 precipitates ofPf1 (from 100 mM Tris buffer at pH 8.4 and 50 mM MgCl2) in D2O with a 60%glycerol-d8/40% D2O solution containing 20 mM AMUPol to achieve a finalsolvent mixture of 30% glycerol-d8/70% D2O with 10 mMAMUPol. Because thevirions were fully protonated, sufficient protons were present in the sample tomake the addition of H2O unnecessary. No differences in linewidth, polariza-tion buildup time, or enhancement were observed between 30% and 60%glycerol solvent mixtures; 30% was used to maximize sample concentration inthe rotor.

DNP-SSNMR spectroscopy was carried out at the New York Structural BiologyCenter on a 14.1-T Bruker AVANCE-III 600/89 spectrometer (600-MHz 1H field)equipped with a 395-GHz gyrotron, low-temperature MAS cabinet, and a three-channel 1H–13C–15N (HCN) 3.2-mm DNP probe. A MAS frequency of 11 kHz wasused, with variable-temperature (VT)/bearing/drive temperatures all within therange of 98 to 106 K. Maximum field strengths used were 120 kHz 1H, 62.5 kHz13C, and 50 kHz 15N; high-power proton decoupling was performed at 115 kHz.Where indicated, Pf1 samples were instead packed in a 1.9-mm zirconia DNProtor, and spectroscopy was performed by using a Bruker 1.9-mm three-channelHCN probe on the same spectrometer, allowing MAS rates up to 25 kHz, withVT/bearing/drive temperatures in the range of 98 to 108 K. Although faster MASis theoretically possible with 1.9-mm rotors, the density of cold nitrogen gas,coupled with flow limitations, precluded regular spinning >25 kHz near 100 K.Maximum power levels of 150 kHz 1H, 62.5 kHz 13C, and 62.5 kHz 15N were used,with proton decoupling calibrated at 120 kHz.

The 3D spectra were acquired at a level of 25%NUS, by using 50% samplingin each indirect dimension. NUS tables were generated in Bruker Topspin(Version 3.1) by using a double-exponential biasing scheme based on the ex-perimental T2*. NUS spectra were reconstructed by using the MDD protocol inTopspin (Version 3.1) and qMDD (Version 2.2) (60). No significant differenceswere observed in processed spectra between NUS and uniformly sampledNCACX/NCOCA spectra.

Additional details regarding optimization of NMR parameters, experimentalsetup, and assignment protocol are presented in SI Appendix.

0 2 0 3

15N13C Hydration

HydratedNon-Hydrated

A B

-2 +2 -3 +3

CSP CSP CSP CSP

ppm ppm ppm ppm

Fig. 6. (A) Mappings of average 13C and 15N CSP for each residue of thePf1 coat protein. Signed CSPs and absolute value CSPs (jCSPj) were averagedover all atoms of each residue; CSPs were computed as σ106 K

– σ273 K in allcases. The shade and intensity of color correspond to perturbation levels, asindicated. A plot of residue average CSPs by residue number is shown in SIAppendix, Fig. S7. Large CSPs are clustered in three main regions: theoutward-facing N terminus, a central kink region, and the inward-facing Cterminus, which is the DNA interaction domain. (B) An independent map ofwhere water molecules contact the protein at 278 K shows very similarpatterns (52) on a single copy of the coat protein as well as on sections of thePf1 assembly looking perpendicular to and down the central symmetry axis.The high degree of correlation suggests that solvent exposure represents asignificant driving force of chemical shift changes in moving from conditionsnear 273 K to DNP conditions near 100 K.

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ACKNOWLEDGMENTS. We thank Dr. Michael J. Goger of the New YorkStructural Biology Center (NYSBC) for help with instrumentation; andDr. Tatyana Polenova and Chris Suiter for many helpful discussions of nonuniformsampling techniques and their application to biological SSNMR. This work wassupported by National Science Foundation GrantMCB 1412253 (to A.E.M.), as wellas by National Institutes of Health Grant NIH R01 GM 88724 (to A.E.M.). R.R. was

supported by the National Institutes of Health Training Program in MolecularBiophysics T32GM008281. A.E.M. is a member of the NYSBC. The data collected atNYSBC was made possible by a grant from Empire State Division of ScienceTechnology and Innovation and Office of Research Infrastructure Programs/NIH facility improvement Grant CO6RR015495. The 600 MHz DNP/NMRspectrometer was purchased with funds from NIH Grant S10RR029249.

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