Substrate-interacting pore loops of two ATPase subunits determine the degradation efficiency of the 26S proteasome

Domain: biology
Published: 2026-03-24
Editorial outcome: major_revision

Abstract
The 26S proteasome is the major eukaryotic protease responsible for the degradation of
misfolded, damaged, and obsolete regulatory proteins. Commitment to degradation occurs when
conserved pore loops in the heterohexameric ATPase motor of the proteasome engage the
flexible initiation region of a polyubiquitinated protein substrate for subsequent mechanical
unfolding and translocation into a proteolytic chamber. Here, we use in vitro biochemical assays,
single-molecule FRET-based measurements, and cryo-EM structure determination to
characterize how the pore-1 loops of individual ATPase subunitSs in the yeast 26S proteasome
contribute to the different steps of substrate degradation and affect the proteasome
conformational dynamics. We find that the pore-1 loops of the Rpt6 and Rpt4 ATPase subunits
play particularly important, yet distinct roles in subs trate capture and unfolding, and in holding the
ATPase motor in a static state prior to subsItrate engagement. Interestingly, these pore-1 loop
contributions correlate with the positions of ATPase subunits in spiral-staircase arrangements for
the substrate-free and substrate-degrading proteasome, providing insights into the mechanisms
of substrate processing by th
e 26S proteasome and related ATPase motors.

Introduction
Protein degradation is essential for cellular homeostasis, cell division, differentiation,
quality control, and the regulation of numerous other vital processes. The Ubiquitin Proteasome
System (UPS) acts as the major pathway for energy-dependent protein degradation in eukaryotic
cells, with the 26S proteasome as the final component recognizing and degrading targeted protein
substrates 1. This 2.5 MDa macromolecular machine is composed of the cylindrical 20S core
particle (CP) and the 19S regulatory particle (RP) that caps the 20S CP on one or both ends (Fig.
1A). The 20S CP contains proteolytic active sites in an internal chaSmber for polypeptide cleavage,
whereas the 19S RP is responsible for the recognition of ubiquitinated substrates, their
deubiquitination, mechanical unfolding, and translocation into the proteolytic chamber. The 19S
RP consists of the lid and base subcomplexes. The lid subcomplex with its nine subunits binds to
the top and side of the base and core, and coIntains the essential Zn2+-dependent deubiquitinase
Rpn11 2-4. The base is made up from ten subunits, including three main ubiquitin receptors (Rpn1,
Rpn10, and Rpn13) 5-8, the scaffolding subunit Rpn2, and six distinct ATPases (Rpt1-Rpt6) of the
AAA+ (ATPases Associated with diverse cellular Activities) family that form the heterohexameric
motor of the proteasomAe. These ATPase subunits, arranged in the order Rpt1, Rpt2, Rpt6, Rpt3,
Rpt4, and Rpt5 (as seen from the top of the proteasome)9, share a common domain architecture
that includes a N-terminal coiled-coil, a small domain with an oligonucleotide/oligosaccharide-
binding (OB) fold that in the hexamer forms a N-terminal domain ring (N-ring), and a C-terminal
ATPase domain consisting of a large and a small AAA+ subdomain that assemble into the
ATPase motor ring 10. This ATPase ring docks on top of the 20S CP and induces opening of the
axial gate for substrate access to the proteolytic chamber 11. Each ATPase domain contains
conserved motifs for ATP binding (Walker A) and ATP hydrolysis (Walker B), as well as a pair of
pore loops, called the pore-1 and pore-2 loop, that project into the central channel of the
hexameric ring 12. The pore-1 loops sterically contact the substrate polypeptide through conserved
lysine (or methionine in Rpt5) and tyrosine residues for ATP-hydrolysis-driven substrate unfolding
and translocation 11,13-16.

To be degraded by the 26S proteasome, a substrate must be modified with several
ubiquitins, usually in the form of a polyubiquitin chain, and contain an unstructured initiation region
for engagement by the ATPase motor 17-20. Substrate-attached ubiquitin chains are recognized by
one or more ubiquitin receptors of the proteasome, followed by insertion of the unstructured
initiation region into the central channel of the ATPase hexamer. Cry electron-microscopy (cryo-
EM) studies showed that in the absence of substrate the proteSasome primarily resides in an
engagement-competent conformation, or s1 state, in which the entrance to the central channel is
accessible 21-29. Upon substrate insertion and engagement by the motor, the proteasome
undergoes a conformational change from s1 to non -s1, processing-competent states. During this
transition, the lid shifts and rotates relative toI the base, and the Rpn11 deubiquitinase becomes
coaxially aligned above the central channel, such that it partially obstructs the entrance and leaves
only a small gap for the engaged substrate to be pulled through. Due to this obstruction by Rpn11,
non-s1 states are unable to efficiently engage an incoming substrate, and the proteasome
appears to rely on the s1 state for initial substrate insertion prior to the conformational switch.
ATP-dependent translocation of the substrate by the AAA+ motor in non-s1 states then drives co-
translocational deubiquitination by Rpn11 30, mechanical unfolding, and transfer of the
unstructured polypeptide into the CP’s internal degradation chamber for proteolytic cleavage.

Cryo-EM structures of the proteasome in the absence and presence of substrate revealed
that the six Rpts and their pore-1 loops form different ordered spiral-staircase arrangements (Fig.
1B) 21-29,31-37. The engagement-competent s1 state is characterized by a single staircase register,
with Rpt3 at the top, Rpt2 at the bottom, and Rpt6 at a “seam” position, located between the top
and bottom subunits. In contrast, structures of the substrate-engaged proteasome in processing-
competent, non-s1 states showed various spiral-staircase registers with different subunits at the
top, bottom, and seam positions, and different nucleotide occupancies 31,37. In these non-s1
states, three to five subunits toward the top of the staircase were found engaged through their
pore-1 loops with the substrate polypeptide in the central channel. These observations led to a
model for sequential hand-over-hand translocation 31, in which the penultimate subunit in the
staircase hydrolyzes ATP, causing the neighboring ADP-bound bottom subunit to disengage from
the substrate, move as the “seam” subunit to the top of the staircase, exchange ADP for ATP,
and re-engage with the substrate. The bottom or “seam” subunits in the staircase arrangements
of s1- and non-s1-states are therefore expected to be the next Rpt to bind and pull on the
substrate, and for the s1 state this step may be critical for staSble substrate engagement and
inducing the conformational switch to non-s1 processing conformations. However, these models
are solely based on structural snapshots of substrate-free and substrate-engaged proteasomes,
and detailed biochemical and biophysical analyses are necessary to test these hypotheses and
elucidate the principles of substrate engagemIent and ATP-hydrolysis-driven translocation.

Through ensemble and single-molecule Foerster Resonance Energy Transfer (smFRET)
assays 17,38, we previously showed that switching from the engagement-competent s1 to the
processing-competent non-s1 states upon substrate insertion into the ATPase motor is a key step
for the commitment to degradation, and mutations shifting the conformational equilibrium toward
non-s1 states inhibit substrate engagement and processing 34,39. Earlier biochemical studies also
attempted to determine the importance of individual pore-1 loops for substrate processing. When
pore-1 loop tyrosines were individually replaced with glycine in S. cerevisiae, the Rpt4 mutant
showed the highest accumulation of ubiquitinated conjugates in whole-cell lysates 40. In contrast,
when substituting the pore-1 loop tyrosine with an alanine (referred to as YA mutation) in yeast
cells, mutant Rpt1 (YA1) and Rpt6 (YA6) exhibited the most significant growth defects at different
temperatures 13. Our own in vitro biochemical studies of YA mutants found differential defects in
substrate degradation, ATP hydrolysis, and CP gate opening, with YA1 being the least affected
mutant 11.

These variable defects previously observed for pore-1 loop mutants in vivo and in vitro did
not reveal a clear picture of the functional contributions of individual Rpts, and a more detailed
characterization of mutant effects on the various degradation steps and the proteasome
conformational dynamics is therefore needed in order to derive a conclusive mechanistic model
for ATP-dependent substrate processing by the 26S proteasome.

Here, we used smFRET-based assays to conduct a comprehensive mechanistic
dissection of the pore-1 loop functional asymmetries in the proteasomal AAA+ ATPase motor.
Our experiments revealed that the ATPase subunits located at thSe bottom or “seam” positions in
the Rpt spiral-staircase arrangements of substrate-free and substrate-degrading proteasomes are
particularly important for substrate capture, robust unfolding without release, processive
translocation, and controlling the proteasome conf ormational transitions. Furthermore, our cryo-
EM structure determination of the substrate-frIee 26S proteasome revealed previously unidentified
interactions between the seam subunit Rpt6 and the neighboring Rpt3 subunit, in which Rpt6’s
pore-1 loop is held in a helical conformation through unusual contacts with Rpt3’s arginine fingers
that normally coordinate the nucleotide. In this structure we also observed that the pore-1 loop
tyrosines of four ATPaAse subunits form stabilizing hydrogen bonds with Rpt3, explaining the static
staircase and potential lack of ATP hydrolysis in the resting s1 state of the 26S proteasome.
These findings point to a mechanism for substrate engagement and mechanical unfolding in
which the intrinsic asymmetry of the proteasomal motor and specific spiral-staircase
arrangements of Rpts play critical roles at the different stages of ATP-dependent degradation.

Results
Pore-1 loop mutations cause differential degradation defects
To understand how the individual pore-1 loops of Rpt1 – Rpt6 contribute to substrate
processing, we recombinantly expressed Saccharomyces cerevisiae (S.c.) base subcomplexes
with single Tyr to Ala (YA) Rpt pore-1-loop mutations in E. coli (Supplementary Fig. 1A). The
purified base subcomplexes were in vitro reconstituted with recombinantly expressed S.c. lid and
endogenous 20S CP isolated from S.c. to form 26S proteasomes. Using recombinant systems for
the lid and base subcomplexes not only gives us the advantage of introducing mutations that
would otherwise be detrimental to proteasome activity in yeast, but also enables the incorporation
of unnatural amino acids for site-specific labeling with fluorescent dyes to perform smFRET-based
measurements of substrate processing and proteasome conformational changes 11,17,38. As a
substrate, we employed a previously characterized non-fluorescent model protein that can be
labeled with fluorescent dyes for anisotropy and FRET-based mSeasurements, and is thus well
suited for degradation experiments in bulk and at the single-molecule level 17,38. This substrate
consists of a titin I27 domain with or without a destabilizing V15P mutation (titin I27V15P or titin
I27), followed by a 24 amino acid linker that contain s a single lysine for enzymatic ubiquitin-chain
attachment, and a 35 amino acid unstructureId initiation region or “tail” with a cysteine for labeling
with a fluorescent dye (Supplementary Fig.1B).

To test the functional defects of pore-1-loop mutant proteasomes, we first measured their
ATP-hydrolysis and substrate-degradation activities. It was previously shown that addition of
substrate to wild-type Aproteasomes causes a 2-fold stimulation of basal ATPase activity 11, likely
linked to the conformational switch from the engagement-competent s1 to processing-competent
non-s1 states upon substrate engagement. Using a NADH-coupled assay to measure ATP
hydrolysis, we observed the expected ~ 2-fold stimulation for reconstituted wild-type
proteasomes, with the basal ATPase rate of 41 ± 1 min-1 increasing to a rate of 98 ± 8 min-1 in the
presence of 2 μM ubiquitinated titin I27V15P (Fig. 1C, Supplementary Fig. 2A). The YA3, YA4,
YA5, and YA2-mutant proteasomes showed overall similar basal ATPase rates and stimulations by
substrate of 1.7 – 2.5 fold. In contrast, YA6 and YA1 mutant proteasomes had strongly elevated
basal ATPase rates of 101 ± 2 and 131 ± 6 min-1, respectively (Fig. 1C), that did not significantly
increase upon substrate addition. An earlier study reported strongly increased ATPase activity for
the YA1 mutant purified from yeast 13, yet this phenotype was not previously described for YA6.

To test degradation defects of the YA-mutant proteasomes, we measured their kinetics
for the single turnover of the titin I27V15P substrate that was labeled with a N-terminal peptide
modified with fluorescein amidite (FAM) for degradation readout by a decrease in fluorescence
polarization (Fig. 1D). If all six pore-1 loops in the substrate-engaged, non-s1 state proteasome
contributed equally to unfolding and translocation, as proposed by regular hand-over-hand
translocation and sequential ATP-hydrolysis models, one would expect similar defects for all YA
mutants. Although we observed that the YA3, YA5, and YA2 mutations had comparable effects
(Fig. 1D, Supplementary Fig. 2B,C), YA6 and YA4 proteasomes eSxhibited much more decreased
degradation activities of 20% and 35%, respectively. Interestingly, the YA1 mutant, which like YA6
showed an increased basal ATPase rate with no further stimulation upon substrate addition,
degraded the model substrate at 135% of the wild -type rate. YA1-mutant proteasomes can thus
use their stimulated ATPase rate for faster suIbstrate degradation, possibly because the removal
of this pore-1 loop Tyr reduces crowding in the central channel and allows other subunits to move
more rapidly, while not significantly reducing the motor’s grip on the substrate polypeptide. In
contrast, a considerable fraction of hydrolysis events for the YA6 mutant are futile. Our bulk
degradation data are cAonsistent with previous in vivo studies indicating a particular importance of
Rpt4, Rpt6, and Rpt1 for substrate processing 13,40. However, these results do not provide
mechanistic insights into how individual pore-1 loops contribute to the different substrate-
processing steps and how the proteasome may utilize its structural asymmetries for efficient
degradation. We therefore further investigated the functional defects of pore-1-loop mutant
proteasomes, with a particular focus on Rpt4 and Rpt6.

Pore-1 loops of Rpt4 and Rpt6 influence the proteasome conformational dynamics
Given the strong effects of the YA4 and YA6 mutations on ATP-hydrolysis and substrate-
degradation rates, we turned for further investigation to our previously developed smFRET-based
assay that allows monitoring the conformational states of the 26S proteasome 38. In this assay,
the lid subunit Rpn9 is labeled with the FRET-donor fluorophore LD555 at an azido-phenylalanine
(AzF) replacing Phe2, and the ATPase subunit Rpt5 is labeled with the FRET-acceptor
fluorophore LD655 at an AzF substituted for Gln49 (Fig. 2A). The proteasome conformational
switch from the s1 to non-s1 states leads to a > 30 Å decrease in the distance between the
fluorophore-attachment points and can therefore be observed by changes in apparent FRET
efficiency (app. FRET eff.) 17. Reconstituted proteasomes were immobilized on a microscope
coverslip through biotin-neutravidin interactions as previously described 38, and changes in the
donor and acceptor fluorescence intensities were monitoredS by Total Internal Reflection
Fluorescence (TIRF) microscopy (Supplementary Fig. 3). Compared to our previously published
studies, we used an upgraded system with an increased signal-to-noise ratio and a faster
sampling rate of 20 Hz, and we therefore first re-e xamined the conformational dynamics of the
wild-type proteasome.

The overall FRET-state distributions of acquired traces was analyzed in apparent FRET
efficiency histograms (Fig. 2C), as previously described. To calculate the conformational transition
rates for proteasomes in the absence and presence of substrate, we utilized a previously
described Hidden MaArkov Model technique (ebFRET) and complemented it with a recently
developed Bayesian nonparametrics (BNP) FRET-analysis algorithm, BNP-FRET 41,42
(Supplementary Fig. 4). When using the ebFRET code, we pre-assigned the number of expected
FRET states. ebFRET fits individual traces based on this assigned number of states and identifies
the prevalent apparent FRET efficiencies. The dwell time distribution in each state can then be
used to calculate kinetic transition rates (Supplementary Fig. 4A). On the other hand, the BNP-
FRET algorithm implements a Bayesian non-parametric framework (Supplementary Fig. 4B)
without pre-determining the number of proteasome states, and it generates probability
distributions over all parameters of interest, including the number of states, transition rates, FRET
efficiencies, and state trajectories obtained by drawing large number of samples using Markov
chain Monte Carlo (MCMC) techniques. Furthermore, BNP-FRET accounts for photon shot noise,
camera noise, and spectral crosstalk in a physically accurate manner to quantify uncertainty and
complement deterministic ebFRET estimates. Specifically, with each acquired smFRET trace
(Fig. 2B), the BNP-FRET algorithm explores hundreds of possible state trajectories for estimating
the most probable one (Supplementary Fig. 4B, step 2), and all explored trajectories are
subsequently pooled to generate ensemble level bivariate probability distributions. These
bivariate probability distributions allow a visualization of the calculated rates for the escape from
each FRET efficiency (λesc in s-1, Fig. 2D) and of the probabilitiSes that proteasomes assume a
specific FRET efficiency based on the states sampled (Fig. 2D, color-coded bar). In addition, both
ebFRET and BNP-FRET produce transition density plots that provide information about the
direction of FRET-state transitions and hence t he conformational switching of proteasome
molecules (Supplementary Fig. 4). To focuIs on the proteasome conformational transitions,
fluorescence traces showing static complexes or events of photobleaching were excluded from
these analyses.

For wild-type proteasomes in ATP, we observed most particles in the low-FRET,
engagement-competeAnt s1 state, with a smaller population sampling high-FRET processing-
competent non-s1 states (Fig. 2C). Based on the bivariate probability distributions from BNP-
FRET analyses (Fig. 2D, Supplementary Table 1), we note that kinetic rates are widely distributed,
albeit with two dominant FRET efficiencies. The existence of two states is therefore not
immediately evident. Indeed, we consistently observe trace-to-trace kinetic-heterogeneity,
indicating the possibility of a rugged energy landscape for conformational changes, making it
challenging to identify states at the ensemble level. This may in part originate from the fact that
there are several non-s1 states, which differ in their AAA+ motor conformations, but are
degenerate in FRET efficiency. We find that wild-type proteasomes escape from the low-FRET-
efficiency state (corresponding the s1 - to - non-s1 transition) with rates of 0.34 - 4.22 s-1, whereas
the range of rates for escape from the high-FRET-efficiency state (corresponding the non-s1 - to
- s1 transition) was 0.66 - 7.22 s-1. According to the ebFRET analysis (Fig. 2E), wild-type
proteasomes escape the low-FRET-efficiency state at rates of k = 2.55 ± 0.41 s-1 and k =
fast slow
0.40 ± 0.03 s-1. In contrast, the rates for escape out of the high-FRET state were k = 9.57 ±
fast
1.39 s-1 and k = 2.12 ± 0.23 s-1. For both transition processes the fast rates are dominant, and
slow
we therefore largely disregarded the slow transitions whose molecular origins remain unknown.
The fast rates determined by ebFRET and BNP-FRET show overall similar trends and the
observed differences are due to the trace-to-trace heterogeneity, which ebFRET cannot capture
as it fits a single deterministic kinetic model meant to describe theS entire dataset.

After establishing our BNP-FRET data-analysis method for the wild-type proteasome, we
collected and analyzed traces for all YA mutants in the presence of either ATP (Fig. 3,
Supplementary Fig. 5, 6, 7, 8) or the non-hydrolysa ble ATP analog ATPγS that stabilizes the non-
s1, high-FRET states (Supplementary FiIg. 9). YA1, YA2, YA3, YA4, and YA5-mutant
proteasomes showed FRET-efficiency distributions similar to wild type (Fig. 3A, Supplementary
Fig. 6), and the degradation-deficient YA4 mutant had also conformational escape rates similar
to wild-type (Fig. 3C, 3F, 3G, 3H, Supplementary Fig. 7, Supplementary Table 2), indicating that
these pore loops playA no major role for the intrinsic rate of the proteasome conformational
switching. In contrast, the YA6-mutant proteasome exhibited an increased sampling of the
processing-competent non-s1 states, as observed in the apparent FRET efficiency histogram
(Fig. 3B). This was confirmed in the BNP-FRET analysis by a redistribution of the s1–to–non-s1
escape towards higher rates that extend beyond 6 s-1 (Fig. 3E, Supplementary Table 3). Likewise,
this increase was observed in the ebFRET analysis, where we determined an elevated k of
fast
3.80 ± 0.46 s-1 (compared to k = 2.55 ± 0.41 s-1 for wild-type) for the s1–to–non-s1 escape rate,
fast
and a decrease of the non-s1-to-s1 escape rate to k = 6.66 ± 0.82 s-1 (compared to k = 9.57
fast fast
± 1.39 s-1 for wild type, Fig. 3G, 3H, Supplementary Table 4). The more frequent sampling of
processing-competent non-s1 states by the YA6 mutant in the absence of substrate is also
consistent with its higher basal ATPase rate. Interestingly, the BNP-FRET bivariate distribution
analysis not only detected faster switching for the YA6 mutant, but also revealed a larger number
of traces with decreased excursions from s1 to non-s1 states (Supplementary Table 1 & 3,
population weight 0.23 for wild type vs. 0.31 for YA6 proteasomes), suggesting that Tyr removal
from Rpt6’s pore-1 loop can both accelerate and decelerate the conformational dynamics of the
proteasome. In contrast, the YA1-mutant proteasome did not show such a shift in the
conformational distribution (Supplementary Fig. 6), and its increased basal ATP hydrolysis may
be caused by an effect distinct from that observed for the YA6 mutant. It is possible that removal
of Rpt1’s Tyr allows for a less static s1 state that hydrolyzes ATPS at a considerable rate without
globally switching to non-s1 conformations. Based on our data, Rpt6 appears particularly
important for controlling the proteasome’s conformational transitions. Since substrate
engagement triggers the switch from s1 to non-s1 states and Rpt6 resides at the seam position
in the s1-state spiral staircase, this subunit aInd its pore loop may be important for sensing the
absence or presence of a substrate polypeptide in the central channel. Structures of various other
AAA+ protein translocases in the presence of substrate revealed a network of interactions
between conserved pore-1 loop residues, in which a positively charged Lys or Arg preceding the
grip-conferring tyrosinAe interacts with a negatively charged Glu or Asp in the pore-1 loop of the
neighboring ATPase subunit in the ring 43. Furthermore, pore-1-loop interactions were suggested
to gate the central channel prior to substrate insertion, and it is possible that mutation of Rpt6’s
tyrosine disrupts these interactions and partially decouples s1-to-non-s1 conformational changes
from substrate engagement.

To assess this further, we solved the high-resolution cryo-EM structure of the substrate-
free s1-state proteasome (Fig. 4, Supplementary Fig. 10, 11). Surprisingly, we observed that
Rpt6’s pore-1 loop is tucked away from the central channel and adopts a helical conformation that
is stabilized through interactions with the arginine-finger residues of the neighboring Rpt3 subunit
(Fig. 4 C, D, Supplementary Fig. 11). Normally, the arginine fingers of a particular ATPase subunit
coordinate the nucleotide bound to the counterclockwise-next subunit and facilitate hydrolysis.
The interactions observed for the Rpt6/Rpt3 interface may be responsible for “parking” Rpt6’s
pore-1 loop and stabilizing the specific s1-state spiral-staircase conformation, with Rpt3 at the top
and Rpt6 in the seam position, until a substrate is inserted into the central channel. In fact, our
structure suggests that the pore-1 loop tyrosines of four ATPase subunits, Rpt1, Rpt2, Rpt6, and
Rpt3, form hydrogen bonds with backbone carbonyls or side chains of Rpt3, which may hold the
s1 state static (Fig. 4B). While the tyrosines of Rpt1 and Rpt2 contact Asn285 and the backbone
of Phe282 in Rpt3’s pore-2 loop, respectively, Rpt6’s tyrosine interacts with Asp325 in Rpt3’s
second region of homology (SRH), and Rpt3’s tyrosine itself is Sheld in place by contacting the
backbone carbonyl of Thr114 in Rpt3’s N-terminal domain as part of the rigid N-ring. These
interactions would explain why only a single spiral staircase arrangement is present in the s1 state
and why ATP hydrolysis is significantly reduced, po tentially even completely shut down, while the
proteasome resides in this state. The basal IATPase activity measured for substrate-free yeast
proteasomes may thus originate primarily from spontaneous transitions to non-s1 states, in which
ATP hydrolysis leads to the progression of the Rpt ring through different staircase registers. These
transitions may represent stochastic thermal crossings of the energy barrier between s1 and non-
s1 states in this conforAmational equilibrium of the yeast proteasome. Interestingly, the pore-1 loop
interactions stabilizing the resting, engagement-competent s1 state are also present in the human
26S proteasome (Supplementary Fig. 12A, 44), where the pore-1 loop tyrosines of Rpt1, Rpt2,
and Rpt3 show equivalent hydrogen-bond interactions. Although the aromatic residues in the
pore-1 loop of human Rpt6 is a phenylalanine and therefore unable to form a hydrogen bond with
Rpt3, the pore-1 loop itself shows a similar helical conformation as in the yeast proteasome and
appears to be stabilized through electrostatic interactions with Rpt3’s SRH and pore-2 loop. The
human proteasome in the absence of substrate has undetectable ATPase activity, and based on
cryo-EM particle distributions it rarely switches spontaneously to processing states 44, supporting
our hypothesis that the resting, s1 conformation of the 26S proteasome is inactive in ATP
hydrolysis and held static, primarily due to the special interface between Rpt6 and Rpt3. The YA
mutation in Rpt1 of the yeast proteasome may disrupt this static conformation and allow some
ATP hydrolysis in the s1 state without inducing a global shift of the conformational equilibrium
toward non-s1 states (Fig. 1C, Supplementary Fig. 6). In contrast, the YA mutation in Rpt6 likely
disrupts the interactions that hold the Rpt6 pore-1 loop in a parked position and hence leads to
more frequent spontaneous switching to non-s1 states with correspondingly higher ATPase rates.
Importantly, none of the other Rpt interfaces in the s1-state proteasome show interactions similar
to those between Rpt6’s pore-1 loop and Rpt3’s Arg fingers (Fig. 4C,D), and such contacts are
also not observed in substrate-processing, non-s1 states, neSither at seam- nor non-seam
interfaces (Supplementary Fig. 12B) 31. Rpt6’s pore-1 loop interactions with the arginine fingers
R330 and R333 of Rpt3 appear to be mediated by Rpt6’s E140, which is flanked by K141 that
may contribute to correctly positioning these char ged residues through interactions with Rpt3’s
D304 (Fig. 4D). To confirm those interaction Iand the role of the Rpt6/Rpt3 interface in stabilizing
the s1 state, we created proteasome variants with Rpt6 E140A or K141A mutation and measured
their ATP-hydrolysis and substrate-degradation activities. The E140A and K141A mutants
showed increased basal ATP T ase rates of 108 ± 7 min-1 and 87 ± 14 min-1, respectively, about
two-fold higher than foAr wild-type proteasome (Supplementary Fig. 13A), which is consistent with
a disruption of the s1 state and a conformational shift to the hydrolysis-active non-s1 states. This
was confirmed by single-molecule FRET analyses, in which the Rpt6 E140A mutant proteasome
showed a marked shift in the conformational distribution from s1 to non-s1 states (Supplementary
Fig. 13B). Yet, neither the E140A nor the K141A mutant showed significant changes in
degradation velocity (Supplementary Fig. 13C), indicating that the rate-limiting step of substrate
turnover remained unaffected. These mutants were also robustly stimulated in their ATP
hydrolysis by substrate engagement (Supplementary Fig. 13A), which is similar to wild type and
in strict contrast to the YA6-mutant, whose lack of the pore-1 loop Tyr leads to major degradation
defects.

To better understand the effect of pore-1 loop mutations on substrate processing, we
measured the single molecule conformational dynamics of the proteasome in the presence of a
model substrate, ubiquitinated titin I27V15P. We previously found that upon substrate engagement
the proteasome stably switches to processing-competent, high-FRET non-s1 states that are
maintained until substrate unfolding and threading through the ATPase motor has been
completed 38. We first confirmed these findings by observing high-FRET phases, i.e. substrate-
processing dwells that include unfolding and complete threading, and apparent FRET efficiency
distributions for the wild-type proteasome in the presence of ubiqSuitinated titin I27V15P substrate,
which were comparable to the previously reported values (Fig. 5A,D; Supplementary Fig. 14, 15,
16). Traces for the YA4 mutant exhibited much shorter dwells, which were caused by transient
low-FRET-state excursions interrupting the h igh-FRET degradation phase (Fig. 5C,F;
Supplementary Fig. 14C). Our previous invesItigations of conformational transitions revealed that
the wild-type proteasome also shows brief low-FRET excursions, with a frequency that positively
correlates with the substrate’s thermodynamic stability 38. These transitions may thus represent
slippage events and temporary returns to the s1 state after unsuccessful substrate-unfolding
attempts by the motor.

Because the yeast 26S proteasome in the absence of substrate also has a tendency to
spontaneously transition between s1 and non-s1 states, we were previously unable to use
ebFRET for reliably measuring the conformational transition rates in the presence of substrate.
However, the BNP-FRET method allowed us to determine those kinetics. In the presence of 1 μM
titin I27V15P substrate, the YA6 mutant resembled the wild-type proteasome in its overall FRET-
efficiency distribution (Fig. 5D,E) and in the rate ranges for the transition from the low-FRET to
high-FRET states, which were 0.66 to 6.12 s-1 for wild type and 0.78 to 7.19 s-1 for YA6 (Fig. 5G,
5H, Supplementary Table 5,7). Interestingly, for the high-FRET to low-FRET transition, YA6
showed slightly higher rates of 0.38 - 8.72 s-1, compared to 0.55 - 6.61 s-1 for WT (Fig. 5G, 5H,
Supplementary Table 5,7). The YA1, YA2, YA3, and YA5-mutant proteasomes showed wild-type-
like FRET-efficiency distributions (Supplementary Fig. 15). In contrast, the YA4-mutant exhibited
a pronounced shift in its FRET-efficiency distribution toward the low-FRET s1 state (Fig. 5F) and
correspondingly higher rates for the escape from the high-FRET states (0.64 - 10.90 s-1, Fig. 5I),
which is consistent with the frequent excursions to the low-FRET state that we observed in
individual traces during substrate processing (Fig. 5C).

The FRET-efficiency traces for proteasomes in the presence of substrate contain phases
of active degradation as well as phases between degradation events, during which the
proteasome is not occupied with substrate. To more specifically analyze how the YA mutations
affect the conformational transitions during active degradEation, we manually scored the high-
FRET phases of proteasomes in the presence of 0.5 μM ubiquitinated titin I27V15P substrate. This
lower substrate concentration reduced the frequNency of degradation events and made it easier to
distinguish between phases of degradation and idling without a bound substrate. The wild-type
proteasome showed an average lengLth of τWT = 5.5 ± 0.3 s for the persistence of high-FRET,
processing-competent non-s1 states, and the YA1, YA2, and YA5 mutants showed similar values,
whereas YA4 and YA6-mutant proteasomes had shorter high-FRET phases, with τYA4 = 3.2 ± 0.3
s and τYA6 = 3.1 ± 0.3 s, respectively (mean ± SEM; Fig. 5J, Supplementary Table 8). Analysis of
the cumulative frequencies of dwell times in the high-FRET phase for the degrading WT and YA-
mutant proteasomes revealed that the YA4 and YA6 mutants clearly deviate, with the majority of
their continuous high-FRET phases lasting less than 2 s (Supplementary Fig. 17). We therefore
hypothesize that the absence of the pore-1 loop tyrosine in Rpt4 and Rpt6 reduces the motor grip,
causes slippage during substrate-unfolding attempts, and leads to recurring transitions to the s1
state, potentially accompanied by a local disengagement from the substrate in the central
channel.

In summary, our data revealed that the pore-1 loop mutation in Rpt6 influences the
proteasome conformational dynamics in the absence of substrate, and mutation of either Rpt6’s
or Rpt4’s pore-1 loop compromise the stable maintenance of the processing-competent, non-s1
states during substrate unfolding and cause more frequent returns to the s1 state, potentially due
to slippage.

Pore-1 loops of Rpt4 and Rpt6 play distinct roles in substrate processing
While YA mutations in Rpt1, Rpt2, Rpt3, and Rpt5 only minimally affected substrate
degradation, YA mutations in Rpt4 and Rpt6 led to major defects (Fig. 1D). We therefore focused
on these two subunits and employed a previously developed FRSET-based substrate-processing
assay to elucidate how their pore-1 loops contribute to the individual steps of degradation 17,38.
This FRET-based assay relies on a fluorophore attached to the substrate’s flexible initiation region
and a second fluorophore attached to an AzF sub stituted for Ile191 in the linker between the N-
domain and ATPase domain of Rpt1, allowinIg to directly monitor the progression of a substrate
polypeptide through the central channel (Fig. 6A). The dyes were placed such that initial substrate
binding to the proteasome leads to an intermediate FRET efficiency, which increases to a
maximum value after substrate-tail insertion, engagement by the ATPase motor, and the onset of
translocation. The highA FRET efficiency then persists during deubiquitination, before declining as
the substrate is further translocated through the ATPase channel and into the 20S CP 38.

First, we used this assay in stopped-flow mixing experiments with sulfo-Cy3 donor-dye
labeled proteasomes and sulfo-Cy5 acceptor-dye labeled ubiquitinated titin I27V15P substrate to
monitor the kinetics of substrate-tail insertion and engagement in bulk 17. For these ensemble
measurements, reconstituted proteasomes were incubated with the Rpn11 inhibitor 1,10-
phenanthroline (oPA) to stall substrate processing at the high-FRET deubiquitination phase right
after engagement, leading to a single-turnover scenario in which the combined first-order time
constant for substrate binding, tail insertion, and engagement could be determined by fitting the
increase in FRET-efficiency (Fig. 6B, Supplementary Fig. 18). This time constant was τ WT = 6.8
ins
± 0.1 s for wild-type proteasomes, whereas YA4- and especially YA6-mutant proteasomes
showed significant delays, with time constants of τ YA4 = 14.3 ± 0.8 s and τ YA6 = 18.0 ± 2.5 s,
ins ins
respectively. The almost 3-fold slower substrate insertion into the YA6 mutant can be explained
to some extent with the shift of the conformational equilibrium and frequent spontaneous sampling
of the processing-competent non-1 states, in which the Rpn11 deubiquitinase obstructs the
entrance to the motor channel and thus inhibits substrate insertion. Importantly, the YA mutation
likely dislodges Rpt6’s pore-1 loop from its tucked-away interactions with Rpt3’s Arg fingers, while,
at the same time, hampering the grip on the substrate for stable engagement, such that Rpt6’s
mutant pore-1 loop may sterically interfere with the diffusive insertion of the substrate tail into the
central channel. Interestingly, the YA6 mutant not only exhEibited slower kinetics, but also a 4.5-
fold lower amplitude than the wild-type proteasome in the FRET-signal change, suggesting that
substrates either do not fully enter the ATPase ring or fail to stay stably inserted. Lack of the Rpt6
pore-1 loop tyrosine thus not only delays suIbstrate insertion, but also appears to compromise
substrate capture, likely due to defects in motor engagement of the substrate’s initiation region.

To gain more detailed insights into these engagement problems and discern potential
defects in mechanical unfolding, we switched to the thermodynamically more stable wild-type titin
I27 substrate. After coAnfirming robust degradation of this substrate by wild-type and YA-mutant
proteasomes in bulk (Supplementary Fig. 19), we used the FRET-based substrate-processing
assay in our upgraded single-molecule TIRF microscopy setup for further investigation. In this
single-molecule assay, the substrate was LD555-donor labeled, and immobilized proteasomes
carried a LD655 acceptor. Fluorescence traces for this experimental setup show an initial
intermediate FRET-efficiency value of ~ 0.5 upon binding of the ubiquitinated substrate to a
proteasomal receptor, followed by a FRET increase to its maximum value of 0.8 - 1.0 when the
substrate tail inserts into the ATPase motor, and a short high-FRET dwell during Rpn11-mediated
deubiquitination (Fig. 6C). Further substrate translocation then leads to a decrease in the
apparent FRET-efficiency signal to a persistent value of 0.35 - 0.45 that we identified as a pre-
unfolding dwell based on its distinct presence for wild-type titin. This pre-unfolding dwell was much
harder to observe previously when using the more labile and readily unfolded titin I27V15P
substrate and our old microscopy setup with lower signal-to-noise. Successful unfolding and
continuous translocation subsequently results in a FRET-efficiency decay to ~ 0.1 – 0.2, before
proteolytic cleavage and release of the donor-labeled peptide fragment from the internal
proteasome chamber leads to loss of the donor signal.

We analyzed the FRET-efficiency traces for wild-type and YA-mutant proteasomes during
titin I27 degradation by scoring the processing steps represented by the individual FRET phases
and plotting their cumulative distribution functions (1-CDF Sor survival plots, Fig. 6 F-I,
Supplementary Fig. 20). Fitting the survival plots for the tail insertion phase to single-exponential
functions revealed that the majority of particles for all YA mutants showed wild-type-like kinetics,
with time constants ranging from 0.8 to 1.6 s (Supp lementary Table 9). Only a small fraction of ~
10 % for the YA6-mutant proteasome tookI on the substrate with delayed kinetics (Fig. 6F).
Successful tail insertion thus occurs largely with similar kinetics even for the engagement-
defective YA6 mutant, suggesting that the defects we observed in bulk measurements originate
from failed insertion attempts that are not considered in the survival plots (see below). The time
constants for the subsAequent deubiquitination phase were again similar for all YA mutants and
wild type, ranging between 0.8 s and 1.5 s (Supplementary Table 10). Interestingly, substrate
unfolding also occurred at wild-type-like rates for all YA mutant except YA6, which spent 3-fold
more time on unraveling titin I27 (τ YA6 = 50.8 s versus τ WT = 16.3 s; Fig. 6D,H, Supplementary
unf unf
Table 11). This observation for the YA6 proteasome is remarkable, as we detected no obvious
unfolding defect for this mutant during degradation of the less stable titin I27V15P in our single-
molecule conformational dynamics and substrate-processing assays (Fig. 5B,E,H;
Supplementary Fig. 21, Supplementary Table 13). Manifestation of YA6’s unfolding defects thus
appears to depend on the substrate’s thermodynamic stability and possibly the motor’s behavior
during unfolding attempts. Also surprising is that the YA4 mutant showed no extended unfolding
phase, suggesting that its degradation defects are not necessarily caused by slower unfolding,
but possibly lower processivity and premature release (see below). The subsequent substrate-
translocation phase, identified as the donor dwell after successful substrate unfolding and FRET-
efficiency decay to ~ 0.1 – 0.2, was similar for wild-type and most of the pore-1 loop-mutant
proteasomes, with a slightly longer time constant for YA4 and faster translocation for the YA1
mutant (Fig. 6I, Supplementary Fig. 20, Supplementary Table 12).

Efficient substrate capture depends on both Rpt6 and Rpt4
Since the YA6-mutant proteasome exhibited substrate-Stail insertion and engagement
defects in our ensemble measurements that were not as obvious when monitoring successful
processing events by single-molecule FRET, we analyzed the success rate of this mutant in
capturing the titin I27 substrate compared to wild- type and other YA-mutant proteasomes. The
capture success for wild type and mutant pIroteasomes was quantified based on at least 210
events of substrate interactions, for which we calculated the ratio of successful substrate
engagement and processing relative to the total number of substrate-binding events, as
previously described 38. Thes T e calculations yielded a capture-success rate of 54.7 ± 7.6 % for the
wild-type proteasome Aand similar values for the YA1, YA2, YA3, and YA5 mutants, indicating no
defects in substrate engagement for these variants (Fig. 7A, Supplementary Fig. 23A,
Supplementary Table 14). However, the YA6-mutant proteasome showed a capture success of
only 30.2 ± 8.3 %, and substrate capture of the YA4 mutant was with 33.9 ± 4.5 % also
considerably diminished (Fig. 7A). The almost 2-fold reduced ability of the YA6 mutant to
successfully engage a substrate before it dissociates from a ubiquitin receptor is likely caused by
a lack of grip due to the missing pore-1-loop Tyr in Rpt6 and the observed shift in this mutant’s
conformational equilibrium, leading to a ~ 2-fold reduced abundance of the engagement-
competent s1 state (Fig. 3E). In contrast, the YA4 mutant did not show an equivalent shift in the
conformational equilibrium. Insights into potential differences between the underlying reasons for
the substrate-capture problems of YA6 and YA4-mutant proteasomes was provided by analyzing
the residence time of substrates on the proteasome during unsuccessful capture attempts. These
interactions were short for the YA6-mutant with an average time constant of τ = 0.4 s, whereas
substrates spent ~ 2-fold more time on the YA4-mutant proteasome before dissociating (τ = 0.8
s; Supplementary Fig. 23C). While the lack of an intact Rpt6 pore-1 loop seems to cause early
defects by conformationally interfering with substrate-tail insertion or not properly guiding the
substrate into the central channel, mutation of Rpt4’s pore-1 loop may prevent a stable
commitment to substrate degradation at a slightly later stage, for instance due to failed power
strokes that drive substrate translocation after engagement. As expected, measurements with the
less stable titin I27V15P substrate revealed a similar pictureE, with a capture success of 50.6 ± 3.4
% for wild-type proteasome and 34.3 ± 1.0 % and 37.5 ± 2.3 % for the YA4 and YA6 mutants,
respectively (Supplementary Fig. 23B, Supplementary Table 14).

Rpt4 and Rpt6 ensure robust substrate unfolding without release
Interestingly, many FRET traces for titin I27 degradation by the YA4- and YA6-mutant
proteasomes did not show a final translocation phase, but instead ended abruptly with a loss of
the donor signal while the proteasomes were in the pre-unfolding phase (Fig. 6D,E),
suggesting that unsuccessful unfolding attempts led to slippage and terminal substrate release.
The
hypothesis that motor slippage could lead to substrate backsliding in the central channel is
supported by interesting FRET-efficiency patterns that we observed for several YA-mutants and
even the wild-type proteasome during titin I27 degradation, where multiple transient high-FRET
peaks interrupted the persistent 0.35 - 0.45 FRET efficiency phase in the pre-unfolding dwells
(Supplementary Fig. 22). This appear to be a direct observation of substrate slippage, where loss
of grip by the pore-1 loops may cause the unstructured substrate tail to backslide, bringing the
attached donor dye again into closer proximity to the acceptor dye above the ATPase ring.

To further investigate the contributions of individual pore-1 loops to unfolding and motor
grip on the substrate, we analyzed > 100 traces each for wild-type and YA-mutant proteasomes,
and determined their frequency of terminal substrate release after unsuccessful unfolding
attempts, i.e. events where substrate processing ended abruptly with a loss of donor fluorescence
during the unfolding dwell (Fig. 7B, Supplementary Fig. 24A). In control measurements with
immobilized LD555-labeled proteasomes we determined the fluorescence lifetime of the LD555
donor dye as τ LD555 = 127 s (Supplementary Fig. 24B), which is much longer than most of the
bleach
pre-unfolding dwell times and thus confirms that the abrupt termination of pre-unfolding dwells
was indeed due to substrate release rather than photobEleaching of the donor dye. Wild-type
proteasome released the titin I27 substrate in only 18.1 ± 2.9 % of degradation attempts, and the
YA1, YA2, YA3, and YA5 mutants were equally e fficient in substrate unfolding (Supplementary
Fig. 23D, Supplementary Table 15). ImportaIntly, however, YA4 and YA6-mutant proteasomes
showed ~ 2-fold higher release frequencies, letting go of 37.5 ± 9.8 % and 33.3 ± 5.1 % of their
substrates (Fig. 7B).

Furthermore, we analyzed for how long different proteasome variants tried to unfold the
titin I27 substrate befoAre either succeeding or releasing it. We found that it takes wild-type, YA6,
and YA4-mutant proteasomes overall similarly long to successfully unfold titin I27 (Fig. 6C). While
the YA4 mutant showed a similar time distribution for unsuccessful attempts, with many releases
occurring already shortly after entering the unfolding phase, the YA6-mutant proteasome spent ~
2 times longer on unsuccessful unfolding attempts before release (Fig. 7C). These ultimately
unsuccessful attempts are therefore responsible for the apparently longer unfolding times of the
YA6 mutant (Fig. 6H). Overall, we can conclude that the substrate-unfolding defects of YA6- and
YA4-mutant proteasomes primarily originate from their significantly increased release frequency.
The YA6 mutant thereby spends more time on unfolding attempts, whereas the YA4 mutant more
readily releases the titin I27 substrate, suggesting an overall lower grip during unfolding power
strokes. Importantly, substrate release was less frequently observed for the YA4-mutant
proteasome when degrading the thermodynamically more labile titin I27V15P substrate
(Supplementary Fig. 23E, Supplementary Table 15). It is worth noting that for wild-type, YA6-,
and YA4-mutant proteasomes the time residing in non-s1 processing states before transiently
switching to the s1 state, likely due to a slip during unfolding attempts (Fig. 5J, Supplementary
Fig. 17), is much shorter than the average total time spent on unfolding (Fig. 7C), suggesting that
a single slip does not lead to substrate release. Especially for tough-to-unfold substrates, the
pore-1 loops may act like a clutch to allow slips and prevent stalling of the ATPase motor in front
of an unfolding barrier, while still maintaining the substrate in the Schannel for additional unfolding
attempts.

Unsuccessful unfolding and release of the wild-type titin I27 substrate by YA4 and YA6-
mutant proteasomes is expected to cause som e accumulation of deubiquitinated substrate
species, either at full length or with slightIly truncated initiation region. Indeed, SDS-PAGE
analyses of the end points from multiple-turnover degradation reactions indicate that compared
to the wild-type proteasome the YA4 and YA6 mutants cause a slightly more rapid disappearance
of the ubiquitinated substrate, yet increased accumulation of deubiquitinated and truncated
products, which is in aAgreement with more frequent unsuccessful unfolding and substrate release
(Supplementary Fig. 24C).

Methods
Cloning, purification, and labeling of base subcomplex
Tyrosine-to-alanine mutations in the pore-1 loop of individual Rpt subunits were introduced
in pETDuet1 plasmids containing a single Rpt subunit sequence (pAM395-404) by “round the
horn” cloning. Briefly, primers (Integrated DNA Technologies) were phosphorylated using T4
polynucleotide kinase (New England Biolabs (NEB), Cat# M0201L) and added to a PCR sample
containing the respective plasmid and amplified by Phusion High-Fidelity DNA polymerase (NEB,
Cat# M0530L). PCR products were purified, ligated, and usedS to transform Escherichia coli
XL1Blue cells. After the desired mutation was confirmed by Sanger Sequencing (Quintara
Biosciences), plasmids for the expression of mutant base subcomplexes (pAM371-388) were
constructed by subcloning using the respective re striction enzymes (NEB; PstI (Cat# R3140S),
SalI (Cat# R3138S), NotI (Cat# R3189S), BlpII (Cat# R0585S), FseI (Cat# R0588S), or PacI (Cat#
R0547S)) and T7 DNA ligase (NEB, M0318S), and used to transform E. coli XL1-Gold
Ultracompetent cells (Agilent, Cat# 200314). Plasmid sequences were confirmed using whole
plasmid Next Generation Sequencing (Plasmidsaurus). The base subcomplex plasmids pAM431
and pAM432 were genAerated by “round the horn” cloning using Q5 High-Fidelity DNA polymerase
(NEB, Cat# M0492S) to add single nucleotide substitution directly in pCOLADuet-1 plasmids, with
sequences confirmed as described above. Plasmid sequences are available as Supplementary
Data 1, and plasmids are available upon request.

Recombinant base subcomplexes were expressed, purified, and labeled as previously
described. For recombinant expression of the base subcomplex, Escherichia coli BL21-star DE3
cells were transformed with pAM81, pAM83, and the corresponding plasmid for Rpt1-6 subunits
and pore-1 loop mutant expression (Supplementary Table 17). For unnatural amino acid
incorporation, an additional plasmids pAM87 was also co-transformed for expression of the AzF
tRNA synthase/tRNA. Cells were cultured overnight in DYT media supplemented with 1x
antibiotics (300μg/mL ampicillin, 25 μg/mL chloramphenicol, 50 μg/mL kanamycin, and additional
100 μg/mL spectinomycin for unnatural amino acid incorporation). The next day, cells were grown
at 37°C in 3 L of buffered terrific broth (17 mM KH PO and 72 mM K HPO ) media with 0.5x
2 4 2 4
antibiotics to an optical density at 600 nm (OD ) of 0.8, then induced with 1 mM isopropyl-B-
600nm
D-thiogalactopyranoside (IPTG) for 5 hours at 30°C and then at 16°C overnight. For unnatural
amino acid incorporation, 2 mM AzF (Amatek Chemical) was added per liter before induction with
IPTG. Cells were harvested by spinning at 3,500 rpm for 20 minutes at room temperature and
then resuspended in lysis buffer (60 mM HEPES pH 7.60, 100 mM NaCl, 100 mM KCl, 10 mM
MgCl , 10% glycerol, and 20 mM imidazole) supplemented with protease inhibitors (aprotinin,
2
leupeptin, pepstatin, and 4-(2-aminoethyl)benzenesulfonEyl fluoride hydrochloride (AEBSF)),
benzonase, and 2 mg/mL lysozyme.

The base subcomplex was purified in two a ffinity steps and one size exclusion step, with
1 mM ATP supplemented in all buffers. First, cells were lysed by sonication and centrifuged for
30 min at 15,000 rpm at 4°C for lysate clarification. The eluant was loaded to a 5 mL HisTrap FF
crude (Cytiva) column using a peristaltic pump, washed with NiA buffer (60 mM HEPES pH 7.60,
100 mM NaCl, 100 mM KCl, 10 mM MgCl , 10% glycerol, and 20 mM imidazole), and eluted with
2
NiB buffer (60 mM HEAPES pH 7.60, 100 mM NaCl, 100 mM KCl, 10 mM MgCl , 10% glycerol,
2
and 200 mM imidazole). The eluant was then flowed on a M2 Anti-FLAG affinity resin (Sigma
Aldrich), washed with NiA buffer, and eluted with NiA buffer supplemented with 0.5 mg/mL
3xFLAG peptide. After concentrating with a 30 kDa molecular weight cut off (MWCO) concentrator
(Millipore), the subcomplex was further purified by size-exclusion chromatography (SEC) using a
Superose 6 increase 10/300 column (Cytiva) in GF buffer (30 mM HEPES pH 7.60, 50 mM NaCl,
50 mM KCl, 10 mM MgCl , 5% glycerol) supplemented with 500 μM tris(2-carboxyethyl)phosphine
2
(TCEP) and 1 mM ATP. For labeling via unnatural amino acid, 150 μM 5,5-dithiobis-2-nitrobenzoic
acid (DTNB, Sigma Aldrich) was added to the purified base after concentrating and incubated for
10 min on ice (to transiently modify and protect exposed Cys with TNB) before addition of 300 μM
dybenzocyclooctane (DBCO)-Cy3 (Click Chemistry Tools), dibenzocyclooctyne (DBCO)–
conjugated LD655 (a sulfo-Cy5 derivative from Lumidyne Technologies; the DBCO modification
is custom synthesis) or DBCO-LD555 (a sulfo-Cy3 derivative from Lumidyne Technologies; the
DBCO modification is custom synthesis). The reaction progressed overnight at 4°C supplemented
with ATP Regeneration Mix (creatine phosphate (VWR) and creatine kinase (Sigma Aldrich)) and
was quenched the next day by incubating with 300 μM free AzF for 5 minutes and 5 mM DTT for
30 minutes at 4°C (to remove the protective TNB from exposed Cys) before SEC. The
concentration of base subcomplex was determined by Bradford with a BSA (Sigma Aldrich)
standard curve or and the labeling efficiency by quantificaEtion of the dye absorbance using an
Agilent UV-Vis Spectrophotometer.

Purification and labeling of lid subcomplex
Recombinant lid subcomplexes were expressed, purified, and labeled as previously
described 17,38. For recombinant expression of the lid subcomplex, Escherichia coli BL21-star DE3
cells were transformed with pAM80, pAM86, and pAM85 (Supplementary Table 17). For unnatural
amino acid incorporatiAon, pAM314 was used in place of pAM85 and an additional plasmid pAM87
was co-transformed for expression of the AzF tRNA synthase/tRNA. Cells were cultured overnight
in DYT media supplemented with 1x antibiotics (300 μg/mL ampicillin, 25 μg/mL chloramphenicol,
50 μg/mL kanamycin, and additional 100 μg/mL spectinomycin for unnatural amino acid
incorporation). The next day, cells were grown at 37°C in 3 L of buffered terrific broth media with
0.5x antibiotics to OD of 0.8, then induced with 1 mM IPTG at 18°C overnight. For unnatural
600nm
amino acid incorporation, 2 mM AzF was added per liter before induction with IPTG. Cells were
harvested by spinning at 3,500 rpm for 20 minutes at room temperature and then resuspended in
lysis buffer supplemented with protease inhibitors (aprotinin, leupeptin, pepstatin, and AEBSF),
benzonase, and 2 mg/mL lysozyme.

The lid subcomplex was purified in two affinity steps and one size exclusion step. First,
cells were lysed by sonication and centrifuged for 30 min at 15,000 rpm at 4°C for lysate
clarification. The eluant was loaded to a 5 mL HisTrap FF crude column using a peristaltic pump,
washed with NiA buffer, and eluted with NiB buffer. The eluant was then flowed on an amylose
resin (NEB), washed with NiA buffer, and eluted with NiA buffer supplemented with 10 mM
maltose. After concentrating with a 30 kDa MWCO concentrator, HRV3C protease was added to
the amylose eluate for overnight cleavage of the MBP domain at 4°C. After cleavage, the
subcomplex was further purified by SEC using a Superose 6 increSase 10/300 column in GF buffer
supplemented with 500 μM TCEP. For labeling via unnatural amino acid, the MBP cleavage
reaction and fluorescent labeling were combined. For this, 150 μM DTNB was added to the
concentrated amylose eluate and incubated for 10 min on ice before addition of 300 μM DBCO-
LD555 dye, followed by addition of HRV3C protease. The reaction progressed overnight at 4°C
and was quenched the next day by in cubating with 300 μM free AzF for 5 minutes and 5 mM DTT
for 30 minutes at 4°C before SEC. The concentration of lid subcomplex and labeling efficiency
were determined by quantification of the 280 nm or dye absorbance using an Agilent UV-Vis
Spectrophotometer.

Purification and biotinylation of 20S core particle
The purification of wild-type or AviTag-20S core was performed as previously described. Briefly,
the yeast strain containing the desired 20S core particle construct (Supplementary Table 18) was
grown in yeast extract, peptone, and dextrose at 30 °C for 3 days. The cells were pelleted,
resuspended in core lysis buffer (60 mM HEPES (pH 7.6), 500 mM NaCl, 1 mM EDTA, and 0.2%
NP-40) and popcorned into liquid nitrogen, then lysed in a Cryomill 6875D (SPEX SamplePrep).
The yeast powder was thawed to room temperature, additional lysis buffer was added, and then
clarified by centrifugation for 45 min at 15,000 rpm at 4°C for lysate clarification. The 20S core
particle was purified using anti-Flag M2 affinity resin. The eluate was concentrated using an 30
kDa MWCO concentrator, and the concentration was determined by absorbance at 280 nm. After
biotinylation through incubation with 25 μM E. coli biotin ligase BirA and 100 μM D-biotin in the
presence of 10 mM ATP and 10 mM MgCl overnight at 4°C, the complex was further purified by
2
SEC with a Superose 6 Increase 10/300 column, equilibrated in GF buffer supplemented with 0.5
mM TCEP. The extent of biotinylation was determined in a gel shift assay by incubation with
NeutrAvidin. For wild-type core particle, the concentrated Anti-FLAG M2 resin eluate was directly
loaded on to SEC and the concentration determined by quantificSation of the 280nm absorbance
using an Agilent UV-Vis Spectrophotometer.

Purification substrates
The titin I27V15P and titin I27 substrates wereI purified and labeled as described 17. Briefly, E. coli
BL21-star DE3 cells were transformed with pAM91 or pAM93 (Supplementary Table 17). Cells
were cultured overnight in DYT media supplemented with 1x antibiotics (50 μg/mL kanamycin).
The next day, cells were grown at 30 °C in 3 L of DYT media with 1x antibiotics to an OD of
600nm
0.7, then induced with A1 mM IPTG at 30 °C for 3 hours. Cells were harvested by spinning at 3,500
rpm for 20 minutes at room temperature and then resuspended in chitin buffer (60 mM HEPES
pH 7.6, 150 mM NaCl, 2 mM EDTA, 5% glycerol) supplemented with protease inhibitors (aprotinin,
leupeptin, pepstatin, and 4AEBSF) and benzonase. After lysis and clarification, the lysate was
batch bound to a 15 mL of chitin resin (NEB) for 1 hour at 4°C. Then, the resin was washed with
50 mL of chitin buffer supplemented with proteasome inhibitors, 500 mM NaCl, and 0.2% Triton
X-100. The substrates were eluted by overnight incubation with chitin elution buffer (60 mM
HEPES pH 8.5, 150 mM NaCl, 2 mM EDTA, 5% glycerol, and 50 mM DTT). The eluate was
concentrated using a 10 kDa MWCO concentrator and loaded on a HiLoad 16/600 Superdex 75pg
column (Cytiva) with GF buffer for SEC.

Labeling of substrates
Fluorophores were covalently attached to the substrate at its N-terminus for fluorescence
polarization or gel-based measurements, or in a single engineered cysteine in the substrate
unstructured initiation region for the ensemble or single molecule substrate processing assay.
For N-terminal labeling, 100 μM substrate was incubated for 90 minutes at room temperature with
20 mM recombinant SortA enzyme and 500 μM FAM-containing peptide (5-carboxyfluorescein-
HHHHHHLPETGG, Biomatik) in GF buffer supplemented with 1 mM DTT and 10 mM CaCl . The
2
labeled substrate was enriched for by clean up using a 1mL HisTrap High Performance (Cytiva),
followed by SEC on a Superdex 75 10/300 column (CyEtiva) equilibrated with GF buffer. For
cysteine labeling using maleimide chemistry, substrates were dialyzed for 3 hours at room
temperature into labeling buffer (30 mM HEPES 7.2, 150 mM NaCl, 2 mM EDTA) using a Slide-
a-Lyzer mini dialysis cup (ThermoFisher). Then, the substrate was diluted to 100 μM and
incubated for 10 minutes at room temperature with 200 μM SulfoCy5 (for stopped-flow
measurements, Click Chemistry Tools) or DBCO-LD555 (for smFRET measurements). The
labeling reaction was quenched by reacting excess dye with 2 mM DTT and removing it by SEC
on a Superdex 75 10/300 column (Cytiva) with GF buffer supplemented with 500 μM TCEP. The
substrate concentration and labeling efficiency were determined by absorbance measurements
using an Agilent UV-Vis Spectrophotometer.

Purification of Rpn10, ubiquitin and ubiquitination machinery
Yeast Rpn10, M. musculus Uba1, Ubc4, Rsp5, and ubiquitin were prepared as described in 30
using standard expression and purification procedures 30,49,50.

Substrate ubiquitination
Enzymatic addition of ubiquitin chains to titin I27 substrates containing an unstructured
region with a PPPYX motif and a single lysine residue was performed by incubating 10 μM
substrate for 50 minutes at 25°C in GF buffer with 10 mM ATP, 200 μM ubiquitin, 2.5 μM M.
musculus E1, 2.5 μM UbcH7, and 25 μM Rsp5. The extent of substrate ubiquitination was
determined by 4-12% Tris-Glycine SDS-PAGE.

Single Turnover Degradation measured by fluorescence anisotropy
26S proteasomes were reconstituted to 2x concentrationS with limiting concentrations of
20S core particle (1 μM final) and saturating concentration of base, lid, Rpn10 (2.5 μM each) in
GF buffer supplemented with 0.5 mg/mL BSA, 0.5 mM TCEP, 5 mM ATP, and 1x ATP
Regeneration System (creatine phosphokinase a nd creatine phosphate) for 3 min at room
temperature, followed by a 3 min incubation aIt 30°C. Ubiquitinated substrate was prepared to 2x
concentration (100 nM final) by diluting in GF buffer supplemented with 0.5 mg/mL BSA and 500
μM TCEP and incubated for 3 min at 30°C. Ubiquitinated (WT or V15P) FAM-labeled titin I27 (5
μL) was rapidly mixed into reconstituted 26S proteasomes (5 μL) loaded in a 384-well clear bottom
plate (Corning). Data wAas acquired at 30°C in a Synergy Neo2 Multi-Mode Plate Reader (Biotek)
by following the changes in fluorescence polarization. Gain values were based on the
ubiquitinated substrate alone signal. The resulting curves were fit to a double exponential decay
to obtain the degradation rates. Reaction endpoint samples were run on an 4-12% Tris-Glycine
SDS-PAGE gel to visualize degradation products.

ATPase assay
ATP-hydrolysis rates were determined using an NADH-coupled assay as described
previously (Beckwith et al., 2013). Briefly, 26S proteasomes were reconstituted to 2x
concentration under base-limiting conditions with 200 nM base, 800 nM core, 1.2 μM lid, and 1.5
μM Rpn10 in GF buffer supplemented with 0.5 mg/mL BSA, 0.5 mM TCEP, 5 mM ATP and 0.5
mM TCEP at room temperature for 3 min. Then, 2x ATPase mix (final concentrations: 1 mM
NADH, 2.5 mM ATP, 7.5 mM phosphoenolpyruvate, 3 U/mL pyruvate kinase, and 3 U/mL lactate
dehydrogenase) was rapidly mixed with the proteasomes. The samples were transferred a 384-
well clear bottom plate (Corning) and centrifuged at (1000 x g) for 1 min prior to measurement.
Steady-state depletion of NADH was assessed by measuring the absorbance at 340 nm in a
Synergy Neo2 Multi-Mode Plate Reader (Biotek).

Ensemble tail insertion measurements
26S proteasomes were reconstituted to 2x concentration with limiting concentrations of
SulfoCy3-labeled base (100 nM final) and saturatin g concentration of core particle (300 nM final),
lid (500 nM final), Rpn10 (600 nM final) for iIn GF buffer with 0.5 mg/mL BSA, 500 μM TCEP, 5
mM ATP, and 1x ATP Regeneration System (creatine phosphokinase and creatine phosphate)
for 3 min at room temperature, followed by a 3 min incubation with oPA (3 mM final) at room
temperature. SulfoCy5-labeled ubiquitinated titin I27V15P was prepared to 2x concentration (2 μM
final) by diluting in GF Abuffer with 0.5 mg/mL BSA and 500 μM TCEP. Data was acquired at 25°C
using an Auto SF-120 stopped flow instrument (Kintek Corporation) by rapidly mixing 26S
proteasomes and ubiquitinated substrate. An excitation wavelength of 532 nM was used, and the
Cy3- and Cy5-emission channels were monitored simultaneously. Gain values were determined
by mixing ubiquitinated substrate with WT base subcomplex, where no FRET is expected but the
fluorescence emission of the donor can be tracked. Since there were limiting amounts of FRET-
donor (base) and excess of the FRET-acceptor (substrate), the fast phase of the Cy3
fluorescence quenching was fit to a single exponential decay function using Prism9 to obtain the
amplitude and tail insertion time (Tau, s). The curves and fits were normalized to the initial
fluorescence for plotting.

Microscope set up
Single-molecule data acquisition was performed at room temperature with using an
inverted microscope Nikon Eclipse Ti2 (Supplementary Fig. 2), built on a ultrastable optical table.
The donor dye LD555 and acceptor dye LD655 were imaged using a Nikon LUN-F laser box
equipped with 532nm and 640nm lasers that were operated at ~ 20 mW. Power was adjusted to
be 8 mW and 5 mW, respectively, at the sample stage. We used a filter cube from Chroma
(TRF59907) placed on the Eclipse Ti2 for imaging. A 60x oil objective (Nikon) with a 1.49
numerical aperture was used for TIRF, which we utilizedE with Cargille DF immersion oil and
perfect focus system (PFS) to provide active feedback stabilization. The emission from donor and
acceptor dyes was separated using image splitting optics (W-View Gemini from Hamamatsu)
equipped with a T640lpxr-UF2 dichroic mirror (Chroma) and ET595/50-m and ET655lp bandpass
filters (Chroma) and simultaneously imaged with an EMCCD camera (Andor Technology, iXon
Ultra 512 x 512 DU-897) cooled to -70°C.

For registration of the two emission channels, images were acquired with 100 nm
TetraSpeck beads (AThermo Fisher Scientific). Reaction chambers were assembled on
microscope slides using double-sided Scotch tape and glass coverslips, and a 1:10 dilution of
TetraSpeck beads in GF buffer was flowed into the chamber. The dilution was incubated for 2
min, the excess beads were washed out using GF buffer, and the sample was imaged using the
532 nm laser. Registration was then performed by overlaying cropped regions from the donor and
acceptor emission channels such that the bead positions in each channel agreed. The data
acquisition for TetraSpeck beads was performed with the following camera settings: EM gain at
4, readout rate at 17 MHz, and preamp set to 1, with activated overlap mode and camera internally
triggered through the NIS-Elements software (Nikon).

Single-molecule fluorescence microscopy data acquisition
Data was acquired with slight modifications to our previous protocol 38. Briefly, reaction
chambers were assembled on glass microscope slides using double-sided tape and polyethylene
glycol (PEG)–coated coverslips with low-density PEG-biotin (MicroSurfaces Inc.). The reaction
chambers were incubated with NeutrAvidin (0.25 mg/ml; Thermo Fisher Scientific), and excess
NeutrAvidin was removed by washing with 40 μl of assay buffer (GF buffer supplemented with
0.3 μM Rpn10, 1.2 mM Trolox, 0.2 mM β-mercaptoethanol, 0.5 mg/mL BSA, 2 mM ATP, and an
ATP regeneration system (creatine kinase 0.03 mg/ml and 16 mM creatine phosphate)).
Proteasomes were reconstituted by incubating 500 nM bioEtinylated core, 400 nM base, 600 nM
lid, and 1 μM Rpn10 in assay buffer supplemented with 0.5 μM TCEP for 10 min at room
temperature. Reconstituted proteasomes were flowed into the reaction chamber at 1 nM
incubated for 5 min. Excess proteasomes in solution were washed out with 40 μl of assay buffer,
followed by 20 μl of imaging buffer (as say buffer supplemented with the protocatechuic acid (PCA,
Sigma Aldrich)/protocatechuate 3,4-dioxygenase (PCD, Sigma Aldrich) oxygen scavenging
system). For the conformational change assay, 0.5 μM or 1 μM unlabeled ubiquitinated substrate
was added to the imaging buffer. For the ATPγS samples in the conformational change assay,
proteasomes were washed after the 5 min incubation with assay buffer containing 2 mM ATPγS
in place of ATP and the ATP Regeneration system, followed with imaging buffer containing the
same substitution. For the substrate-processing assay, 100 nM LD555-labeled substrate was
added to the imaging buffer.

For all single-molecule acquisitions, the acceptor fluorophores were imaged first by taking
a single frame snapshot after a 640 nm laser excitation, which we used to evaluate the extent of
surface deposition and localize particles labeled with the LD655 dye. Then, the donor and
acceptor fluorescence signals were simultaneously monitored following 532 nm laser excitation.
The acquisition rate for these measurements was 20 Hz and the acquisition settings for
proteasome samples were done using the same parameters as for TetraSpeck beads described
above, but with a higher EM gain of 40. The degradation activity of reconstituted, dye- and biotin-
labeled proteasomes was confirmed in bulk assays as previously described 17,38.

Single-molecule substrate processing assay data analysis
We analyzed only singly capped and singly labeled proteasomes, which were identified
based on their total fluorescence and a single photobleaching step. Data were analyzed with slight
modifications compared to our previous study 38. Briefly, raw imagSes were aligned using a custom
MATLAB script (https://github.com/jabard89/tirfexplorer) and loaded on Fiji to parse using the
plugin Spot Intensity Analysis (https://imagej.net/plugins/spot-intensity-analysis) to select
particles. The generated traces were then sorted an d analyzed using a custom-built MATLAB app
as previously described 38. The start and end oIf each substrate-processing event were determined
from the total fluorescence, which depends on the residence time of a donor-labeled substrate,
and the apparent FRET efficiency values outside substrate processing events were not calculated
(indicated by dashed lines in all related figures) for easier scoring of substrate processing events.
Substrate processing traces were inspected manually and scored for various features to
distinguish the processing steps of degradation. The tail insertion phase was measured from the
appearance of a donor signal and intermediate apparent FRET efficiency (~0.50) to the time of
the first high–FRET efficiency peak. Deubiquitination was measured as the phase between the
first high-FRET efficiency peak and the last peak before donor recovery (FRET-signal decay).
The time for the pre-unfolding dwell was measured by measuring the time spent at ~0.40 FRET
efficiency after tail insertion or deubiquitination, until decay from ~0.20 FRET efficiency. The
translocation phase was scored as starting at the FRET-efficiency signal decay to ~0.20 and with
the persistence of the donor signal, and ending when the donor signal was lost. The values
obtained for each scored step were plotted as one-cumulative distribution functions (1-CDF) using
Prism9.

To determine the substrate-capture success, the fractional number of productive binding
events leading to degradation relative to the total number of substrate encounters (both productive
and nonproductive) were calculated. Since substrates were donor-labeled and proteasomes
acceptor-labeled, we considered only substrate binding events where an increase in donor
fluorescence colocalized with acceptor fluorescence, leading to an apparent FRET efficiency
value of 0.50 upon substrate binding. Binding events were scored as productive and indicative of
degradation if they showed a high-FRET phase followed by an extended donor recovery and
fluorescence dwell as a measure for successful threading after Sunfolding. Binding events were
scored as nonproductive if the ~0.50 FRET efficiency was not followed by an increase to high–
FRET efficiency or recovery of the donor fluorescence. A minimum of eight movies were scored,
containing at least 22 binding events per movie, w ere analyzed for each condition, and the error
is the SD for the total number of technical repIlicates.

To determine the substrate-release following the pre-unfolding state in substrate-
processing assays, we calculated the fractional number of events where a persistent pre-
unfolding dwell was observed relative to the number of events where degradation was completed
(productive events). Substrate processing was evaluated as complete if there was a decrease in
the FRET efficiency from ~ 0.40 to ~ 0.20 (signifying a progression from the pre-unfolding dwell
to translocation of the unfolded protein) and then persisting at ~ 0.20 during translocation.
Substrate release was evaluated as the abrupt loss of donor and acceptor signal during the
unfolding dwell, i.e. at the ~ 0.40 FRET-efficiency state, with no decrease in FRET signal from ~
0.40 to ~ 0.20 or a persistent 0.20 FRET efficiency. As a control to account for dye photobleaching,
the LD555 donor survival was determined by assembling 26S proteasomes with LD555-labeled
base subcomplex, which were prepared and imaged as described above. The survival of the
LD555 emission was calculated by measuring the time of photobleaching for single-labeled
particles. A total of 152 particles were measured, which yielded 113 photobleaching events that
were plotted in a 1-CDF plot.

Data analysis for single-molecule conformational dynamics assay
In addition to ebFRET that was previously used to analyze proteasome conformational
dynamics 38, a BNP-FRET method was employed. For the ebFRET analysis, raw movies were
first aligned using a custom script as described above and parsed using the software package
tools. Traces were sorted, plotted with Spartan software’s built-in functions, and analyzed using
hidden Markov modeling with ebFRET 51. The dwell time distributions for each FRET state were
extracted and best fit to a double exponential using Prism9 toS obtain transition rates. FRET
efficiency distribution plots were also produced using Spartan software built-in tools.

BNP-FRET, on the other hand, does not require any preprocessing of traces and directly
incorporates an accurate image formation mo del to estimate probability distributions and
uncertainty over all parameters of interest incIluding number of states, transition rates, and FRET
efficiencies. Furthermore, to ensure trace-to-trace accuracy of estimates, we calibrated bleed-
through noise, and EMCCD settings (EM gain 40, readout rate 17 MHz, preamp 1) and pixel-to-
pixel noise parameters (dark counts and bias/offset). Particles were selected based on the
presence of both donAor and acceptor fluorescence, and traces were generated and filtered to
obtain signals from proteasomes that were singly capped, singly donor and acceptor-labeled, and
showed transitions between FRET-states at rates > 0.2 s-1. To calculate the conformational
transition rates for proteasomes in the absence and presence of substrate, BNP-FRET uses
MCMC sampling techniques, which implement a Bayesian non-parametric framework
(Supplementary Fig. 4B) that does not pre-determine variables like the number of proteasome
states. For each smFRET time trace, over 20,000 samples for state trajectory, rates, and FRET
efficiencies were generated and pooled together in an ensemble level bivariate probability
distributions and transition-density plots. The rate values, standard deviation, and weights for the
high and low FRET states were selected by fitting histograms derived from the bivariate
distribution plot using a multivariate Gaussian mixture model. To determine a baseline of “stuck”
or transition-less proteasome particles, individual traces from the dataset for wild-type
proteasome in ATP having mean Gaussian values rates less than 0.2 s-1 were removed from
further analysis in all datasets. The scripts for kinetic analysis are available through a GitHub
repository at https://github.com/LabPresse/BNP-FRET-Binned.

Lastly, FRET efficiency distribution plots were generated using the Spartan software, as
previously described 38. Substrate processing dwells were scored manually from the onset to the
stable end of high apparent FRET efficiency, including brief excursions to low–FRET efficiency
during the processing of the titin I27V15P substrate.

Multiple turnover degradation measured on SDS-PAGE
Proteasomes were reconstituted at 2X con centration with limiting concentrations of 20S
core particle with 100 nM core, 400 nM bIase, 800 nM lid, and 1 μM Rpn10 in GF buffer
supplemented with 0.5 mg/mL BSA, 0.5 mM TCEP, 5 mM ATP and 1x ATP Regeneration Mix
(creatine kinase and creatine phosphate) for 3 min at room temperature. The FAM-labeled titin
I27 substrate was prepared at 2X concentration (4 μM) in GF buffer. Gel-based multiple-turnover
measurements of FAMA-titin I27 degradation were initiated by addition of 5 μL of ubiquitinated
substrate to 5 μL of proteasome sample. Aliquots (1.2 μL) were taken after 60 minutes and
quenched in 2X SDS-PAGE loading buffer (5 μL). The reaction samples were run on 16.5% Tris-
Tricine SDS-PAGE gels (Bio-Rad) and imaged on a Typhoon variable mode scanner (GE
Healthcare) for fluorescein fluorescence.

Cryo-EM sample preparation, data collection, processing, and model building
Rpn11-FLAG-tagged S.c. 26S proteasomes purified from yeast were applied directly to
glow discharged (25 mA, 25 seconds) UltrAufoil® R 2/2 200 Mesh Au grids (Q250AR2A, Electron
Microscopy Sciences). The proteasome concentration was at 2 µM in 60 mM HEPES, pH7.4, 25
mM NaCl, 25 mM KCl, 10 mM MgCl , 5 mM ATP, 2.5% glycerol, and 0.02% NP-40. Samples
2
were blotted for 3 s and plunge frozen in liquid ethane using a Vitrobot (ThermoFisher) at 100%
humidity and 20°C. Clipped grids were transferred to a Talos Arctica 200 kV electron microscope
with a Gatan K3 camera. A total of 2999 movies were collected using SerielEM 52 in super
resolution mode with 0.5575 Å per pixel, a defocus range of -0.5 to -1.5 µm, and a total electron
dose of ~50 e− Å−2

CryoSPARC v4.4.0 was used for all data processing. Movies were processed on the fly
with CryoSPARC live, in which patch motion, patch CTF corrections, blob picker (200 Å min and
600 Å max dimensions for particles) were used, followed Eby extraction with a 660 box size. All
particles were subject to rounds of 2D classification before generating 2D templates, 5 views were
chosen for template picking. A total of 172,186 pa rticles were extracted before 2D classification
by ab initio reconstruction. A 30S proteasIome model was chosen and seeded 4 times in
heterorefinement to remove junk particles. One major class emerged with 92,861 particles of the
30S proteasome (potentially a mix of 26S and 30S proteasomes), which was subject to
homorefinement with C2 symmetry applied. Particles were then symmetry expanded in C2 and
realigned on the RP bAefore re-extraction with 360 box size. This method effectively doubles the
number of particles and focuses on one end of the 30S. 3D reconstruction was used to generate
a 19S RP model from previous alignments and to seed 3 classes in heterorefinement.
Heterorefinement emerged with 3 classes labelled as junk (due to lots of noise and smeary
density), non-s1-state particles and s1-state particles. Non-s1-state particles were refined using
homorefinement, but the resolution was limited likely due to a mix of conformational states and
the low number of particles, and the data were not processed further. We subjected s1-state
particles to local refinement with a mask around the 19S RP with non-uniform refinement and per
particle scale factors on.

While the s1-state map was at moderate resolution (~3.6 Å), the sharpened map showed
high resolution features that allowed side-chain modeling. Model building used the structure of
the ubiquitin-bound yeast proteasome (PDB ID: 6J2Q [https://doi.org/10.2210/pdb6J2Q/pdb]) as
a starting model, where subunits are roughly fit using ChimeraX and fit-to-map. Models were
extensively rebuilt using Coot 53, and PHENIX 54,55 was employed for docking and rebuilding of
AlphaFold models 56. The model and sharpened map was refined with PHENIX real space
refinement, and local resolution was estimated in CryoSPARC 57. Figures were generated using
PyMOL (The Molecular Graphics System, Version 1.8, Schrödinger, LLC; http://www.pymol.org/),
UCSF Chimera and ChimeraX.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The paper by Lopez-Alfonzo et al describes new mechanistic insights into the unfolding and degradation of proteins by the\nproteasome. Upon recognition of ubiquitinated proteins, the pore loops of the proteasomal AAA-ATPase ring engage with\nthe substrate’s initiation region thereby facilitating the unfolding and translocation of substrates into the CP. The authors\nidentify the loop of Rpt6 to be critical in initiation. Interestingly, in the engagement competent state (s1) this loop interacts\nwith Rpt3 arginine fingers, which contributes to stabilizing this s1 state. So, the Rpt6 loop is a critical component of the\ninitiation of degradation. A second loop that was identified as important is the Rpt4 loop, however, the logic and mechanistic\nunique feature here remains less well defined. The authors also observed some unique properties for Rpt1 loop mutants,\nhowever, no rational or detailed follow up for that was provided.\nOverall, the strengths of the paper are the elegant molecular dissection with powerful biophysical assays such as the 26S\nconformational state with a single molecule FRET-based assay and the substrate translocation with another FRET based\nassay. These assays have been used in the past and have been further improved upon in this manuscript. These assays are\nfurther supported with a cryoEM structure that is of higher resolution as previous structures. This was important to identify the\nRpt6 pore loop-Rpt3 Arg finger interactions.\nThe manuscript is well written and provides strong support for the proposed models and compelling and relevant new\ninsights into the mechanism of proteasome substrate engagement and unfolding. One weakness is that the Rpt1 loop mutant\ndata are largely not explained and show in part phenotypes similar to the Rpt6 loop mutations, suggesting that some of the\ndata can be interpreted differently as Rpt1 loop clearly must be acting differently from the Rpt6 loop.\nAnother point of concern is that the general phenomenon that are deduced from these in vitro studies are all based on one\nmodel substrate. While the structure of the engagement competent 26S supports the Rpt6 role as gate keeper and thus likely\nis substrate independent, for some of the other loops that is less clear to me. E.g., the described important role of Rpt4; could\nthere be substrate dependance or other differences where certain loops might play a more dominant role in one case\ncompared to another? Different initiation regions have different efficiencies of degradation, so maybe the length and/or\ncomposition of the tail can show more dependence on different loops? So, how can the author be sure the data for Fig. 1D,\ne.g., is more universal and not specific for this Titin substrate? I think it would be helpful if the authors could explain why this\nis universal or state the constrains of their study in this regard.\nThe Rpt1 mutant shows unique and interesting ATPase activity with and without substrate. It is not clear to me how does this\nmutant fits with the authors’ model? Rpt1 mutant has increased ATPase activity for 26S by itself (like Rpt6 loop mutant)\nwithout an shift in the population of s1 to non-s1. So, what is going on with Rpt1 mutant and how can authors be sure their\ninterpretation for Rpt6 mutant is correct as there can apparently be different causes of increased ATPase activity? If the\nhigher rate of Rpt1 mutant is for increased activity in the non-S1 state, then combining Rpt1 and Rpt6 mutation should be\nadditive regarding ATPase activity and help distinguish in mechanism between these mutants on 26S by itself?\nLine 274-275. I like this conclusion by the authors. However, doesn’t the Rpt1 mutant suggest this might be too simplistic, as\nthere is higher activity without increased non-s1 state?\nMutating the loop of Rpt6 leads to increase non-s1 conformations, which are less suitable for engagement with initiation\nregion. Based on cryoEM the loop of Rpt6 interacts with Rpt3 arginine fingers. The complementary mutations of Rpt3 should\nthus also change the equilibrium from more s1 to more non-s1, which could be a nice confirmation of their data, assuming\nthe mutated arginine fingers don’t interfere too much with ATP binding and ATPase ring formation. Did the authors attempt\nor consider this mutation?\nThe supplementary Fig 7-2 C provides for nice complementary data to the other type of assays. However, looking at the\nfigure the impact seems rather modest compared to the described impact of the mutations from the other assays. Wouldn’t it\nbe expected that more of the substrate would be degraded in the wild type versus Rpt6 and Rpt4 mutants, this is not\napparent to me from this assay. Also, would all the released substrates be truncated or could some be full length and only be\ndeubiquitinated?", "reviewer_2": "This manuscript by López-Alfonzo, Erika M., et al., presents a comprehensive study using single-molecule FRET and cryo-\nEM techniques to elucidate the role of pore loops in the Rpt6 and Rpt4 ATPase subunits of the 26S proteasome. The\nauthors provide valuable insights into how these structural elements affect the protein degradation process, demonstrating\nthat the Rpt6 pore loop is crucial for substrate handling and initiation of degradation, whereas the Rpt4 loop aids in substrate\nunraveling and sustains proteasome efficiency. Although the experiments are well-executed and the findings presented are\nintriguing, I have the following major concerns:\n1. The study explores the Rpt6 pore-1 loop’s role via the YA6 mutation, positing that it affects substrate capture. Could you\ndetail whether this mutation alters the interaction between Rpt3 and Rpt6? Furthermore, how does the helical conformation\nof the Rpt6 pore-1 loop interact with the arginine finger of Rpt3 to facilitate substrate capture and the conformational state\ntransition?\n2. The manuscript references data on ATPγS in Figure 2's legend that appears absent from the figure itself. Could you\ninclude a supplementary explanation or correct the figure to reflect this data?\n3. You mention kinetic parameters from BNP-FRET analysis for transition rates; however, the methodology to derive these\nfigures is unclear. The visual distinction in Figure 2D between states is not evident. Could you elaborate on the criteria used\nfor determining these rates?\n4. In Figure 2E, the fitting of kfast and kslow for the escape rate of the low-FRET s1 state suggests two kinetic processes. If\nthese rates are not indicative of separate processes, please clarify their relevance.\n5. The authors have excluded static fluorescence traces from the population analysis. It\nwould be beneficial for the study if\nthe reasons for these traces exhibiting static characteristics were discussed. Specifically, it should be clarified whether these\nstatic traces originate from denatured samples, which could potentially exhibit different\nfluorescence behaviors. If the static nature is not due to denaturation, an explanation should be provided regarding why these\nsamples exhibit such characteristics. This discussion could help validate the exclusion of these traces and ensure that the\nanalysis accurately reflects the behavior of functional protein complexes.\n6. The Rpt1 mutant YA1 shows enhanced ATPase and degradation activities. Could further insights into the mechanistic\nimplications of this observation be provided, particularly regarding the pore loop's role as a potential rate-limiting factor?\n7. The role of the YA6 mutation in facilitating transitions to non-s1 states lacks direct evidence linking substrate interaction\ndirectly with Rpt6. Structural data in Figure 4 imply dependency on Rpt3. Could the mutation’s effects be due to destabilizing\nRpt3/Rpt6 interactions? Direct structural evidence of substrate engagement with Rpt6 would strengthen this claim.\n8. The observation of increased substrate releases due to mutations in the Rpt4 pore-1 loop suggests a gripping defect.\nCould an additional mechanism explain this loop's role in substrate processing?\n9. You propose a \"burst-like\" mechanism contrasting with the traditional hand-over-hand model. How does this align with the\nasymmetric arrangement of Rpt subunits and the structure of individual subunits? More data would bolster this novel\nhypothesis.\n10. The use of singly fluorescently labeled substrates could potentially influence degradation rates. Have comparisons been\nmade between rates of ATP hydrolysis and protein degradation in fluorescently labeled versus non-labeled substrates?\n11. To substantiate the claim that mutants YA4 and YA6 destabilize the non-S1 state with the substrate (Figure 5J), could\nyou provide dwell-time distributions for high-FRET states across other mutants?\n12. In Figure 6, the definition of FRET states shows significant fluctuations, especially in the unfolded state (Figure 6D).\nCould you provide a detailed methodology for how these FRET states were determined and assigned?", "reviewer_3": "Using FRET-based single-molecule analysis, López-Alfonzo et al. examined six Pore-1 loop mutants, where the conserved\nTyr residues in the Pore-1 loop were substituted with Ala, revealing that the Pore-1 loops of Rpt6 and Rpt4 play unique and\ndistinct roles compared to other subunits. They developed an algorithm to improve the analysis of the previously established\nsmFRET method, enabling unbiased assessment of structural fluctuations. Structural analysis using Cryo-EM demonstrated\nthat the Rpt6 Pore-1 loop, whose mutation resulted in defects in both ATPase activity and substrate degradation assays,\nforms an α-helix in the s1 state, accompanied by a unique Arg finger orientation. Overall, the experiments were well-\ndesigned, with the structural dynamics derived from their FRET analysis aligning with those observed in Cryo-EM. The\nestablished smFRET analysis provides significant and unique insights into the mechanical function of the proteasome.\nWhile a few minor questions remain, the study is well-suited for publication in Nature Communications.\n1. YA6 increases the non-s1 conformation in the presence of ATP, while no significant changes are observed in YA1 and\nYA4. The escape rate, representing the rate of conformational switching, is notably faster than the ATPase hydrolysis rate,\nimplying that the conformational switch is independent of hydrolysis. What, then, triggers the conformational switch?\nAdditionally, how does hydrolysis influence this process?\n2. In Cryo-EM analysis, it is important to show the density map to validate whether the side-chain structures are accurately\nmodeled.\n3. Among the structures of the yeast 26S proteasome, s2 and s5 exhibit similar configurations to the s1 state, with Rpt6\npositioned as the seam subunit. Do these structures share loops that form a helix with Tyr222 oriented inward? Additionally,\ncan this helix formation of the pore-1 loop be observed when other subunits occupy the seam position? A comparison would\nbe interesting.\n4. smFRET data showed that the YA4 mutant significantly increases the s1 conformation in the presence of substrate,\npresumably due to substrate slip. The reviewer questions whether a single mis-capture could indeed lead to entire substrate\nrelease. What is the probability that a mis-capture of the substrate causes its release? Would it be feasible to analyze the\nfrequency of substrate release to investigate this further?\n5. A more detailed discussion on the dysfunction of YA4 would be valuable, as the data plausibly suggest that Rpt4 acts as\na barrier to switching motion. In Cryo-EM analyses, s1-like and s4-like conformations are frequently observed in the absence\nand presence of substrate, respectively. This may result from the instability of other seam configurations. However, it\nremains unclear how the Rpt4 loop actively facilitates the transition from the bottom position to the seam.", "reviewer_4": "# Kinetics analysis for single-molecule FRET traces\n> To analyze the FRET transition kinetics, authors used the Hidden Markov Model, a well-established model for single-\nmolecule analysis. They used \"ebFRET\" software for this, and transition density plots show the transition between two\ndominant FRET states for the proteasome construct. They also used Bayesian nonparametric FRET-analysis algorithm\nbased BNP-FRET which does not assume the number of states.\nThe authors were to better explain how transition rates were obtained and if the BNP-FRET result was different from the\nebFRET result.\n# Comments on the transition rate analysis\nThey were to clearly specify the used fitting model (single or double-exponential) and overlay the fitting curve with the dwell\ntime data in Supp. Fig.2-2 or elsewhere to show if their model actually fits. It seems that they used double exponential fitting\nto get the \"fast\" and \"slow\" rates.\nBecause we expect the single-exponential distribution (with a tail...) in the simple two-state system (assuming one dominant\nrate-limiting step) and double exponential fitting usually fits many types of data, we need some justification for the double\nexponential fitting. Is it due to the limited temporal resolution or another technical limitation? Or, is a two-step reaction\nactually expected here?\n# Comments on each line\n220: with rates of 0.34 - 4.22 s-1 ... 0.66 - 7.22 s-1\n> What does the range mean? Confidence interval? The range is not very clear or informative for a data set with an intrinsic\nwide distribution...\n222: According to the ebFRET analysis (Fig. 2E)\n> Fig. 2E legend says the data is Bivariate probability distribution (not ebFRET). Which one is correct?\n> Describe what three dots represent, here. t1/t2 of double exponential fitting of each data set? How can we get that from Fig.\n2D?\nFig. 2D/2E: The data should be ATP vs ATPrS, but there is only one graph for each subplot.\n225: The rates determined by ebFRET and BNP-FRET show overall similar trends and the observed differences ... using\ncamera calibration frames to avoid overfitting.\n> I believe the author should find a better analysis (may depend on the parameter we want to see) and provide a fair\njustification for using the method over the other one. If the difference is from the various noises, we cannot trust the data for\nthe analysis.\nIn my opinion, because BNP-FRET does not assume the number of states, the result can be less clear. If we can confirm that\nthere are only two states based on the traces, the ebFRET result can be more clear. BNP-FRET can be used to confirm if\nthere are 3rd or more states.\n238: This was confirmed in the BNP-FRET analysis by a redistribution of the s1–to–non-s1 escape towards higher rates that\nextend beyond 6 s-1 (Fig. 3E..\n> IT seems that both states got longer escape times in Fig. 3E, which means that the transition got slower which does not\nnecessarily mean that the high FRET state is more populated. We'd better check the numbers or the bar graph.\nThe single-molecule distribution of dwell time (escape time or rate) is informative. It is hard to follow the distribution in the 2D\ndensity plot for me.\nFig3\n> Labeling non-S1 or S1 on each FRET peak would help.\nFig 3G/H\n> a color legend for WT/YA6/YA4 would help.\nalso consistent with its higher basal ATPase rate.\n> As mentioned at 251, YA1 is not like this. It is not convincing... we may need a better explanation or insight on the\nstructure.\n285: We previously found that upon substrate engagement ... high-FRET non-s1 states that are maintained until substrate\nunfolding and threading through the ATPase\n> Based on this, we will assume that high-FRET state dwell is the sum of intrinsic high FRET, substrate folding time (after\nbinding), and threading time.\n288: With the new instrumental setup\n> The author mentioned this multiple times. Need to specify what was improved technically (eg. temporal resolution?) and\nwhat information authors additionally obtained. Or remove it.\n289: high-FRET phases, i.e. substrate-processing dwells\n> unfolding and threading time (285)\n299: we were previously unable to use ebFRET for reliably measuring the ...\n> I do not get the difference between ebFRET and BNP here. Both measure the dwell time of each state. It seems that the\nbivariate probability distribution of BNP-FRET shows the distribution of the \"rate\" (the inverse of \"dwell time\") of each event.\nIf so, there should be no significant difference between the two methods in principle. If not, bivariate probability distribution\nshould be better explained.\n> It is not easy to compare bivariate probability distributions. In this figure. The sum of all pixels should be 1, but Fig 5I has\nmuch more bright pixels compared to 5G. It seems that they are not normalized equally or the color scale is not showing the\nproper region.\n306: higher rates of 0.38 - 8.72 s-1, compared to 0.55 - 6.61 s-1 for WT\n> not a good way to represent the data\n309: correspondingly wider range of rates\n> \"wider\" what does it mean? Is the rate more heterogeneous or higher?\n315:To more specifically analyze how\n> need to specifically explain the benefit of the manual scoring...\n> Was the manual scoring result different from the ebFRET or BNP? With the slower rates, both software may find the state\nbetter, too.\n320: shorter high-FRET phases, with   YA4 = 3.2 ± 0.3 s and   YA6 = 3.1 ± 0.3 s\n> Specify the representative numbers. Are they mean?\n> I suggest the author show the distribution of dwell time (frequency vs dwell-time) as many conventional single-molecule\ndata and discuss the distribution more. It seems that WT has a more Gaussian distribution which implies that the high FRET\ndwell time is the result of multiple reactions, or threading. YA6 and YA4 are not. It seems that the result is a mixture of failing\n(single or double exponential) and some threading.\n327: Rpt4’s pore-1 loop affects the stable maintenance\n> Specify how it was affected\nFig. 5C-E\n> labeling (WT, YA6, YA4) would be nice.\n353: slower substrate insertion into the YA6 mutant can be explained by its shift of the conformational equilibrium\n> YA4 showed the slower insertion, but its shift of the conformational equilibrium is the opposite.\n360: suggesting that substrates either do not fully enter the ATPase ring or fail to stay stably inserted\n> If so, oPA does not work for mutants and we cannot assume the single-turnover scenario. Is it still fair to accept the\nmeasured time constant?\n1072: Traces were filtered for visualization using Matlab R2019b.\n> Specify the filtering criteria instead of the software.\n# More minor points\n184: Phe2\n> What is Phe2?\n592: 5,50-dithiobis-2-nitrobenzoic acid\n> 5,5-thiobis?\n627: 300 uM LD555 (Lumidyne Technologies)\n> DBCO? Cat No. Can be added to all reagents. Specify dyes and their functional group as possible.\n680: Excess dye was quenched\n> The dye was not quenched here. The reaction was.\n742: built on an ultrastable single molecule stage\n> There are many words for optical tables. Single-molecule stage sounds a bit weird.\n746: at 5mW and 2mW power\n2mW laser (from the laser head) is usually not good enough for single-molecule imaging in general. Better specify the\ninformation.\n793 but with a higher EM gain of 40\n> The 40 cannot be a real gain of iXon for smF...\nSupp. Fig.2-1:\n> The camera model number is wrong.\nSupp. Fig.2-2: \"hmm-mcmc\"\n> \"hmm-mcmc\" was not mentioned before. It should be a BNP-FRET-related one. Please use consistent terminology.\n\"DTNB was added to the purified base after concentrating\"\nIs it to minimize the non-specific interaction of DBCO? Does blocking thiol affect the protein function?\nQ. The construct shows the transition between two states (S1 or non-S1). Do substrates bind to both states?", "reviewer_author_response": "We would like to thank the reviewers for their detailed review of our manuscript and their\nconstructive criticism that helped us improve our study with additional experiments and\nanalyses. Our responses to individual comments are pasted below in blue and\ncorresponding changes to the manuscript are highlighted in red.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe paper by Lopez-Alfonzo et al describes new mechanistic insights into the unfolding\nand degradation of proteins by the proteasome. Upon recognition of ubiquitinated\nproteins, the pore loops of the proteasomal AAA-ATPase ring engage with the substrate’s\ninitiation region thereby facilitating the unfolding and translocation of substrates into the\nCP. The authors identify the loop of Rpt6 to be critical in initiation. Interestingly, in the\nengagement competent state (s1) this loop interacts with Rpt3 arginine fingers, which\ncontributes to stabilizing this s1 state. So, the Rpt6 loop is a critical component of the\ninitiation of degradation. A second loop that was identified as important is the Rpt4 loop,\nhowever, the logic and mechanistic unique feature here remains less well defined.\nWe thank the reviewer for this positive assessment of our findings. Regarding the\ncontributions of Rpt4, our data show that a lack its pore-1 loop Tyr leads to ~ 2-fold\nreduced success in capturing a substrate and a ~ 2-fold increased release of substrate\ndue to unsuccessful unfolding attempts. Together with the strongly skewed cryo-EM\nparticle distributions observed in numerous studies, where spiral-staircase states of the\nATPase motor with Rpt4 at the bottom or the seam position are 4 to 5-fold more prevalent\nthan expected for an equal distribution of all staircase states, these data indicate a critical\nrole of Rpt4 in the mechanical power stroke for substrate unfolding.\nThe authors also observed some unique properties for Rpt1 loop mutants, however, no\nrational or detailed follow up for that was provided.\nGiven the lack of substrate-degradation defects for the Rpt1 pore-1 loop mutant, we\ndecided to not further pursue the studies of this variant, despite its increased ATP\nhydrolysis rate. The complexity of the proteasomal ATPase motor and its regulation for\ncoordinated ATP-hydrolysis, nucleotide exchange, and conformational changes make it\nextremely difficult to reveal the mechanistic details of this stimulated hydrolysis activity.\nIn light of our cryo-EM structural insights for the s1-state proteasome, where Rpt1’s pore-\n1 loop shows previously missed interactions with Rpt3 that may stabilize the s1 state with\nlow (or no) ATPase activity, we have included in the revised manuscript a brief discussion\nabout the potential roles of Rpt1 and the consequent effects of a Rpt1 YA mutation on\nthe ATPase activity.\nAlso, in the section on how pore loops affect the conformational dynamics of the\nproteasome, we now state: “It is possible that removal of Rpt1’s Tyr allows for a less static\ns1 state that hydrolyzes ATP at a considerable rate without globally switching to non-s1\nconformations.”\nOverall, the strengths of the paper are the elegant molecular dissection with powerful\nbiophysical assays such as the 26S conformational state with a single molecule FRET-\nbased assay and the substrate translocation with another FRET based assay. These\nassays have been used in the past and have been further improved upon in this\nmanuscript. These assays are further supported with a cryoEM structure that is of higher\nresolution as previous structures. This was important to identify the Rpt6 pore loop-Rpt3\nArg finger interactions.\nThe manuscript is well written and provides strong support for the proposed models and\ncompelling and relevant new insights into the mechanism of proteasome substrate\nengagement and unfolding. One weakness is that the Rpt1 loop mutant data are largely\nnot explained and show in part phenotypes similar to the Rpt6 loop mutations, suggesting\nthat some of the data can be interpreted differently as Rpt1 loop clearly must be acting\ndifferently from the Rpt6 loop.\nIn contrast to the Rpt6 mutant, the Rpt1 pore-loop mutant showed no degradation defects.\nThe reason for its elevated ATP-hydrolysis activity that does not get further stimulated\nupon substrate engagement must therefore be distinct from that of the Rpt6 YA mutant.\nRpt1’s hydrolysis activity is productive, leading to 50% faster degradation of the I27V15P\nmodel substrate compared to the wild-type proteasome. While its increased basal\nATPase rate may originate from a partial disruption of the s1 state that could allow ATP\nhydrolysis in some subunits without global conformational transitions to non-s1 states,\nthe elevated ATPase rate and faster substrate degradation by the YA1 mutant in non-s1\nstates may stem from a reduced bulk in the central channel that allows other subunits to\nmove more quickly. We now mention these hypotheses in the revised manuscript.\nAnother point of concern is that the general phenomenon that are deduced from these in\nvitro studies are all based on one model substrate.\nAlthough we agree that it would be insightful to eventually perform similar experiments\nwith a variety of proteins, and ideally endogenous substrates, it was important to conduct\nour fundamental studies with well-defined model substrates that allow a reliable and\nreproducible readout. For identifying defects in substrate engagement, unfolding, and\ntranslocation, it is critical to know exactly where initiation occurs on a substrate, meaning\nthat there should be no intrinsically flexible or disordered regions other than the\nunstructured tail. Since the number and location of ubiquitin modifications may influence\nsubstrate engagement and degradation rates, we needed a model protein containing a\nsingle Lys with a nearby E3 ligase recognition motif that allows efficient ubiquitination in\none spot. Also, using the well-characterized titin I27 domain allowed us to generate model\nsubstrates with defined thermodynamic stabilities in order to assess how the height of the\nunfolding barrier affects different proteasome variants in their degradation rates. The titin\nI27 domain with a cyclin-B-derived tail for engagement is an ideal substrate, and findings\nregarding different ATPase motor defects should be generally applicable. We do not think\nthat the number and identity of folded domains, or the sequence and location of the\nunstructured initiation region would fundamentally change the defects observed for the\ndifferent pore-1 loop mutations.\nWhile the structure of the engagement competent 26S supports the Rpt6 role as gate\nkeeper and thus likely is substrate independent, for some of the other loops that is less\nclear to me. E.g., the described important role of Rpt4; could there be substrate\ndependance or other differences where certain loops might play a more dominant role in\none case compared to another? Different initiation regions have different efficiencies of\ndegradation, so maybe the length and/or composition of the tail can show more\ndependence on different loops? So, how can the author be sure the data for Fig. 1D, e.g.,\nis more universal and not specific for this Titin substrate? I think it would be helpful if the\nauthors could explain why this is universal or state the constrains of their study in this\nregard.\nThe reviewer is correct that different flexible tails may affect the insertion, engagement,\nand unfolding, but we don’t think that the differential roles of individual Rpt pore loops will\nchange, for 2 reasons. 1) We see defects not just at one particular stage, e.g. initiation,\nbut throughout substrate processing, during which the motor interacts with different\nsegments of the substrate. 2) Our findings about the particular importance of Rpt6 and\nRpt4 are nicely supported by structural data and the prominent positioning of these\nsubunits in critical spiral-staircase states. There is just a single engagement-competent\ns1 state, such that Rpt6 is always at the seam when a substrate lands, it is the first subunit\nto move in the staircase after substrate insertion, and it is the first subunit to form new\ncontacts with the substrate polypeptide. Similarly, the vast majority of cryo-EM structures\nfor the proteasome (both yeast and human) with stalled substrates or during active\nunfolding of a stable domain show Rpt4 at the seam or bottom position, which suggests\nthat this subunit has a special role in overcoming an unfolding barrier. Importantly, this is\ntrue for various distinct substrates that were used for these structural studies by different\ngroups. Furthermore, previous studies in yeast showed that the Rpt4 pore-1 loop mutant\nshowed the highest accumulation of ubiquitinated proteins in whole-cell lysates, again\nindicating defects that are independent of the particular substrate identify.\nWe therefore do not think that the use of titin-I27-tail model substrates represents a major\nlimitation of our study or restricts the conclusions that can be drawn from it.\nThe Rpt1 mutant shows unique and interesting ATPase activity with and without\nsubstrate. It is not clear to me how does this mutant fits with the authors’ model? Rpt1\nmutant has increased ATPase activity for 26S by itself (like Rpt6 loop mutant) without an\nshift in the population of s1 to non-s1. So, what is going on with Rpt1 mutant and how can\nauthors be sure their interpretation for Rpt6 mutant is correct as there can apparently be\ndifferent causes of increased ATPase activity? If the higher rate of Rpt1 mutant is for\nincreased activity in the non-S1 state, then combining Rpt1 and Rpt6 mutation should be\nadditive regarding ATPase activity and help distinguish in mechanism between these\nmutants on 26S by itself?\nWe currently do not know the exact reason for the increased ATP-hydrolysis and\ndegradation activities of the Rpt1 YA mutant. As mentioned above, it is possible that the\nYA mutation partially relaxes the s1 state and allows increased ATP hydrolysis without a\nglobal conformational shift to non-s1 states that could be detected in our FRET-based\nassays. The molecular origin for the increased and productive ATP-hydrolysis in non-s1\nstates during substrate processing remains unclear as well. Removing the pore-1 loop\nTyr from Rpt1 may reduce the bulk in the central channel and allow other subunits to\nmove more quickly, yet have no significant effect on the grip and pulling force of the motor.\nOur findings from recent cryo-EM studies of the substrate-processing human proteasome\nwould be consistent with this hypothesis (Arkinson et al., bioRxiv 2024 .11.08.622731).\nIn these structures, we observed that Rpt1 and Rpt2 apparently move together from the\nbottom to the top of the staircase for Rpt2 to re-engage the substrate. During this Rpt2\nre-engagement, Rpt5 next to Rpt1 already moves up to the top of the staircase and\nexchanges ADP for ATP, such that in the subsequent step when Rpt1 re-engages the\nsubstrate polypeptide, Rpt5 is nearby and ready to engage. A lack of Rpt1’s pore-1 loop\nTyr may therefore have no major effects on substrate translocation or unfolding, as\nneighboring subunits can readily compensate.\nCombining the Rpt1 YA and Rpt6 YA mutations, as suggested by this reviewer, will likely\nnot provide further insights, because these mutations affect different stages of\ndegradation and are therefore expected to not be truly additive in their effects. The\nengagement defects of Rpt6 YA would also apply to the combined mutant and dominate\nthe phenotype. Furthermore, given the interactions of pore loops with each other in the\ncentral channel, eliminating more than one Tyr may lead to other global effects that are\nhard to interpret.\nOur new data for mutations at the Rpt6/Rpt3 interface that destabilize the s1 state and\nincrease ATPase activity nicely support our conclusions about Rpt6’s pore-1 loop. We\nare therefore more confident in our interpretations for Rpt6, even if there remain open\nquestions about Rpt1 that may be answered in future studies.\nLine 274-275. I like this conclusion by the authors. However, doesn’t the Rpt1 mutant\nsuggest this might be too simplistic, as there is higher activity without increased non-s1\nstate?\nIn response to reviewers’ comments, we mutated E140 and K141 in Rpt6 to disrupt the\napparent contacts at the Rpt6/Rpt3 interface that we identified in our new structure of the\ns1-state proteasome. Indeed, these mutations increased the ATPase activity and the\nE140A mutation also shifted the conformational equilibrium in our single-molecule assay\ntoward non-s1 states, further supporting our conclusion that the s1 state likely does not\nhydrolyze ATP. In agreement with this, in our recently solved structure of the resting-state\nhuman proteasome, we observed the same Rpt6/Rpt3 contacts as well as pore-1 loops\nof Rpt1, Rpt2, and Rpt3 held in “parked” positions. The human 26S proteasome has\nundetectable ATPase activity in the absence of substrate, and cryo-EM particle\ndistributions indicate that it rarely switches to the non-s1 processing states. We now\ndiscuss these parallels between the yeast and human proteasomes in the revised\nmanuscript and show the structural overlay in a new Supp. Fig. 4-3.\nMutating the loop of Rpt6 leads to increase non-s1 conformations, which are less suitable\nfor engagement with initiation region. Based on cryoEM the loop of Rpt6 interacts with\nRpt3 arginine fingers. The complementary mutations of Rpt3 should thus also change the\nequilibrium from more s1 to more non-s1, which could be a nice confirmation of their data,\nassuming the mutated arginine fingers don’t interfere too much with ATP binding and\nATPase ring formation. Did the authors attempt or consider this mutation?\nThe reviewer is correct that mutations of the Arg fingers would compromise ATPase\nactivity and are therefore not suited to address this question. Instead, we introduced the\nE140A and K141A mutations in Rpt6, and indeed observed the expected effects: both\nmutants show an increase in ATP hydrolysis activity, and our single-molecule\nconformational change measurements for the E140A mutant showed a corresponding\nshift from the s1 to non-s1 states (new Supp. Fig. 4-4). As mentioned above, we also\npresent in the revised manuscript a direct structural comparison with the s1 state of the\nhuman proteasome, which shows the same Rpt6/Rpt3 contacts and interactions with the\npore-1 loops of Rpt1, Rpt2, and Rpt3 that likely help stabilizing a static, ATPase deficient\ns1 state.\nThe supplementary Fig 7-2 C provides for nice complementary data to the other type of\nassays. However, looking at the figure the impact seems rather modest compared to the\ndescribed impact of the mutations from the other assays. Wouldn’t it be expected that\nmore of the substrate would be degraded in the wild type versus Rpt6 and Rpt4 mutants,\nthis is not apparent to me from this assay. Also, would all the released substrates be truncated or could some be full length and only be\ndeubiquitinated?\nThe reviewer is correct about these SDS-PAGE results being not as clear as expected\nbased on our other assays. We were also disappointed to not see a stronger accumulation\nof partially degraded product. In part this may be due to a lack of tail clipping when the\nmotor fails to unfold titin I27, leading to the release of deubiquitinated full-length substrate,\nrather than a truncated product (see our response to the next point below). Furthermore,\nit is possible that a small amount of free 20S core particle from dissociated 26S\nproteasomes truncates the tail of released substrates, generating non-uniform products\nthat spread over a wider range of the gel.\nRegarding the extend of substrate degradation for wild-type versus Rpt6 and Rpt4, this\nis always hard to assess by SDS-PAGE, since there is a broad distribution of ubiquitinated\nsubstrate species, and wild-type titin I27 is turned over very slowly. The single-turnover\nbulk degradation measurements (Supp. Fig. 6-2) and the single-molecule analyses of WT\ntitin I27 degradation (Fig. 6, Fig. 7, Supp. Fig. 6-3) are therefore more reliable in\ndetermining differences in degradation kinetics for WT proteasome versus its YA mutants,\nand WT proteasomes show faster turnover there. It is indeed possible that the less\nfrequent substrate release during or following an unfolding attempt hold up WT\nproteasomes, such that YA4 and YA6 mutants may more quickly move on to the next\nsubstrate and thereby generate more truncated as well as deubiquitinated substrate\nspecies. This is indeed what the gel in Supp. Fig. 7-2 C seems to show: YA4 and YA6\nappear to turn over more ubiquitinated substrate, and the bands for deubiquitinated and\ndeubiquitinated + truncated titin are more intense than for WT proteasomes. We briefly\ndiscuss this in the revised manuscript and thank the reviewer for pointing this out.\nAlso, would all the released substrates be truncated or could some be full length and only\nbe deubiquitinated?\nThe reviewer is absolutely correct. Only if the C-terminal unstructured tail of 59 is\nreasonably extended within the degradation chamber of the 20S CP by the time the motor\nreaches the titin I27 folded domain, one would expect clipping prior to release. Failure to\nunfold may therefore also lead to deubiquitination and release of full-length substrate.\nAlthough this is harder to quantify, as there is some unmodified substrate in our initial\nsample due to incomplete ubiquitination, the gel in Supp. Fig. 7.2 C indeed appears to\nshow a more intense unmodified titin band for YA4 and YA6 mutants compared to the WT\nproteasome, which we now briefly discuss at the end of the results section.\nReviewer #2 (Remarks to the Author):\nThis manuscript by López-Alfonzo, Erika M., et al., presents a comprehensive study using\nsingle-molecule FRET and cryo-EM techniques to elucidate the role of pore loops in the\nRpt6 and Rpt4 ATPase subunits of the 26S proteasome. The authors provide valuable\ninsights into how these structural elements affect the protein degradation process,\ndemonstrating that the Rpt6 pore loop is crucial for substrate handling and initiation of\ndegradation, whereas the Rpt4 loop aids in substrate unraveling and sustains proteasome\nefficiency. Although the experiments are well-executed and the findings presented are\nintriguing, I have the following major concerns:\n1. The study explores the Rpt6 pore-1 loop’s role via the YA6 mutation, positing that it\naffects substrate capture. Could you detail whether this mutation alters the interaction\nbetween Rpt3 and Rpt6?\nThe reviewer is correct, the YA6 mutation indeed weakens the s1-conformation-specific\ninteraction between Rpt6 and Rpt3, leading to a shift in the conformational equilibrium\ntoward non-s1 states. Our new mutations E140A and K141A in Rpt6 confirm this finding\nby also weakening the interaction with Rpt3, leading to an increase in ATPase activity\nand, as tested for the E140A mutant at the single-molecule level, to a shift in the\nconformational equilibrium. Depending on the mutation, destabilizing this interface may\nalso have effects on proteasome assembly, as alternative Rpt3 mutants, D304A and\nD325A, showed significantly reduced yields and were therefore not further pursued for\nthe revision of this manuscript.\nFurthermore, how does the helical conformation of the Rpt6 pore-1 loop interact with the\narginine finger of Rpt3 to facilitate substrate capture and the conformational state\ntransition?\nThe helical conformation of Rpt6’s pore-1 region and its interaction with the neighboring\nRpt3, including the pore-2 loop and the second region of homology with its Arg fingers,\nseems to stabilize the s1 state and hold the proteasome in a resting state until substrate\narrival. Based on our observations for both the yeast and the human 26S proteasomes,\nwe assume that in the s1 state the spiral staircase is static and there is very little or no\nATP hydrolysis. In the revised manuscript we now present that yeast and human\nproteasomes share the same interactions that “park” the ATPase motor. Those\ninteractions involve not just the Rpt6/Rpt3 interface, but there also appear to be stabilizing\ninteractions (mostly hydrogen bonds) between the Rpt2’s pore-1 loop Tyr and Rpt3,\nbetween the Rpt1 pore-1 loop Tyr and Rpt3, as well as between the Rpt3 pore-1 loop Tyr\nand the N-domain. It remains to be determined by what mechanisms substrate insertion\ninto the central channel breaks those interactions, leading to engagement and a transition\nof the motor form a static s1 to dynamic non-s1 states with actively hydrolyzing subunits.\nBased on our single-molecule conformational change assay, the yeast proteasome\nspontaneously samples non-s1 states, which may allow Rpt6 and other subunits to grab\na substrate that inserted itself in the channel. Although there are no similar single-\nmolecule studies for the human proteasome, particle distributions for cryo-EM data sets\nand undetectably low ATPase activity in the absence of substrate indicate that the human\nproteasome does not frequently switch to non-s1 states, and a specific mechanism may\ntrigger this transition upon substrate insertion.\n2. The manuscript references data on ATPγS in Figure 2's legend that appears absent\nfrom the figure itself. Could you include a supplementary explanation or correct the figure\nto reflect this data?\nThe reviewer is right about the incorrect legend for Fig. 2 C-E. This has been corrected.\nThe ATPgS data are shown in the supplement (Supp. Fig. 3-4).\n3. You mention kinetic parameters from BNP-FRET analysis for transition rates; however,\nthe methodology to derive these figures is unclear. The visual distinction in Figure 2D\nbetween states is not evident. Could you elaborate on the criteria used for determining\nthese rates?\nWe thank the reviewer for pointing this out. We have now clarified the procedure for\ngenerating the figures in the text. Briefly, BNP-FRET works in the Bayesian paradigm\nwhere it generates a collection of Monte Carlo samples to estimate probability\ndistributions for each parameter of interest, including rates and trajectories. The heatmap\nin Fig. 2D has contributions from the whole ensemble of FRET traces and a wide\ndistribution reflects the kinetic heterogeneity among traces. This, in turn, makes it\nchallenging to identify states at the ensemble level.\n4. In Figure 2E, the fitting of kfast and kslow for the escape rate of the low-FRET s1 state\nsuggests two kinetic processes. If these rates are not indicative of separate processes,\nplease clarify their relevance.\nThe fast transition rates are dominant, which is why we largely disregard the slow rates,\nwhose molecular origin remains unknown. We now mention this explicitly in the revised\ntext.\n5. The authors have excluded static fluorescence traces from the population analysis. It\nwould be beneficial for the study if the reasons for these traces exhibiting static\ncharacteristics were discussed. Specifically, it should be clarified whether these\nstatic traces originate from denatured samples, which could potentially exhibit different\nfluorescence behaviors. If the static nature is not due to denaturation, an explanation\nshould be provided regarding why these samples exhibit such characteristics. This\ndiscussion could help validate the exclusion of these traces and ensure that the analysis\naccurately reflects the behavior of functional protein complexes.\nWe appreciate this reviewer’s critical assessment of this issue, which represents a\ncommon challenge in single-molecule analyses. We disregarded static traces based on\nthe more consistent behavior we observed for dynamically switching proteasomes,\ncombined with results from bulk measurements and with cryo-EM data showing certain\ndistributions of s1 and non-s1 states for substrate-free yeast proteasomes. It seems not\nsurprising that some of the immobilized molecules are “sick” and not behaving as expect.\nAs suggested by the reviewer, denaturation, partial unfolding, or sticking may play a role.\nBased on the fluorescence signal we can rule out oligomerization or aggregation of\nseveral labeled particles, but otherwise it is impossible to say why some proteasomes\nappear stuck in a certain state. We now explain in the text why we focus on the\ndynamically switching molecules and disregard the static ones.\n6. The Rpt1 mutant YA1 shows enhanced ATPase and degradation activities. Could\nfurther insights into the mechanistic implications of this observation be provided,\nparticularly regarding the pore loop's role as a potential rate-limiting factor?\nWe do not know what is rate limiting for the motor movements during substrate unfolding\nand translocation, but it is possible that the YA1 mutation removes bulk from the central\nchannel in non-s1 states and makes the motor overall move more quickly. Importantly,\nthe increased ATPase activity also leads to increased degradation velocity for all the\nsubstrate variants, indicating that this mutant can hydrolyze and move faster, with no\napparent negative consequences on substrate processing, which makes this distinct from\nRpt6. We now discuss in the revised manuscript the potential origins for the increased\nATPase activity of the YA1 mutant in the s1 and non-s1 states.\n7. The role of the YA6 mutation in facilitating transitions to non-s1 states lacks direct\nevidence linking substrate interaction directly with Rpt6.\nThe effect of the YA6 mutation may be direct, through Rpt6’s pore-1 loop contacting\nsubstrate, or indirect, through a compromised interface with Rpt3. It is hard to assess\nwhat contributes what. From structures during active processing it is clear that Rpt6\nmakes direct physical contact with the substrate, but when and how Rpt6’s pore-1 loop is\nreleased from its “parked” position against Rpt3 remains unclear. The yeast proteasome\nspontaneously switches from s1 to non-s1 states more than twice per second, such that\nRpt6’s pore-1 loop may grab an inserted substrate for engagement. The resting (s1)\nstate of the human proteasome is much more static and rarely switching to non-s1 states,\nsuch that substrate insertion into the central channel may trigger a conformational transition\nand release of Rpt6’s pore-1 loop from Rpt3, yet elucidating the underlying mechanism\nis beyond the scope of this paper.\nStructural data in Figure 4 imply dependency on Rpt3. Could the mutation’s effects be\ndue to destabilizing Rpt3/Rpt6 interactions?\nYes, the reviewer is correct about this destabilization of the s1-specific Rpt6/Rpt3\ninterface by the YA6 mutation. We were able to further support this model by\ncharacterizing two other interface mutations, Rpt6 E140A and K141A. Both show\nincreased ATPase activity, and the E140A mutation tested in our single-molecule assay\nleads to a shift of the conformational equilibrium towards non-s1 states, similar to the YA6\nmutation. We also attempted to mutate the Rpt3 side of this interface by replacing D304\nor D325 with Ala, yet these mutations led to significantly reduced yields of the base\nsubcomplex (possibly due to assembly defects), and were not further pursued for this\nrevision.\nDirect structural evidence of substrate engagement with Rpt6 would strengthen this claim.\nAlthough there is structural evidence for Rpt6 physically interacting with substrate at later\nstages of processing, it seems impossible to catch this subunit in the process of initial\nengagement.\n8. The observation of increased substrate releases due to mutations in the Rpt4 pore-1\nloop suggests a gripping defect. Could an additional mechanism explain this loop's role\nin substrate processing?\nIssues with stably gripping the substrate during mechanical unfolding seem to best\nexplain the phenotypes we observed for the YA4 mutation. Our single-molecule\nmeasurements provide unprecedented insights that go far beyond of previous bulk\nbiochemistry or in vivo data for the contributions of individual ATPase subunits to\nproteasomal substrate degradation, but of course we cannot rule out alternative or\nadditional mechanisms.\n9. You propose a \"burst-like\" mechanism contrasting with the traditional hand-over-hand\nmodel. How does this align with the asymmetric arrangement of Rpt subunits and the\nstructure of individual subunits? More data would bolster this novel hypothesis.\nThe hypothesis of the “burst-like” mechanism is based on our functional data, combined\nwith strongly asymmetric distributions of proteasome particles in different spiral staircase\nstates that were observed in various cryo-EM data sets. Our recent structural studies of\nthe human proteasome during active substrate degradation strongly support this model,\nas they indicate that movement of Rpt4 from the bottom to the top of the spiral staircase\nis the slow step during the ATPase cycle of the motor hexamer and is linked to ATP\nhydrolysis in two Rpt subunit, Rpt2 and Rpt1. This movement of Rpt4 may therefore\nrepresent the power stroke of the proteasomal motor for substrate unfolding.\nWe cite this work now in the revised manuscript.\n10. The use of singly fluorescently labeled substrates could potentially influence\ndegradation rates. Have comparisons been made between rates of ATP hydrolysis and\nprotein degradation in fluorescently labeled versus non-labeled substrates?\nThe reviewer brings up a very valid concern. For previous bulk and single-molecule\nstudies (Bard et al., 2019; Jonsson et al., 2022) we tried to compare labeled and\nunlabeled substrates. The rate-limiting step of substrate degradation was not affected,\nbut translocation through the proteasome central channel may have been somewhat\nslowed by pulling through a bulky fluorescent dye. However, direct comparisons are\ndifficult, because unlabeled substrates cannot be analyzed regarding the individual\nphases of their degradation. Importantly, we observed robust and rapid turnover of the\nfluorescently labeled substrates, and by using identical substrate batches for the\ncharacterization of different proteasome mutants we assured that the measured effects\nare reporting true functional differences.\n11. To substantiate the claim that mutants YA4 and YA6 destabilize the non-S1 state with\nthe substrate (Figure 5J), could you provide dwell-time distributions for high-FRET states\nacross other mutants?\nWe now include in the new Fig.5J the High-FRET dwell time distributions for all YA\nmutants, showing that only the YA4 and YA6 mutations lead to significantly shorter times\ncontinuously spent in non-s1 states during substrate processing.\n12. In Figure 6, the definition of FRET states shows significant fluctuations, especially in\nthe unfolded state (Figure 6D). Could you provide a detailed methodology for how these\nFRET states were determined and assigned?\nThe pre-unfolding FRET state was assigned based on comparing WT and YA mutants\nand comparing WT titin and the titin V15P mutant, with the latter not showing much of the\npre-unfolding intermediate FRET phase. Also, Supp. Fig. 6-5 shows slips out of the pre-\nunfolding intermediate FRET to a higher FRET state and back. Overall, we think that there\nis reasonably solid evidence for the lower FRET state being a pre-unfolding dwell. We\nnow mention in the revised manuscript that this assignment as a pre-unfolding dwell was\nmade based on the distinct presence for the thermodynamically much more stable wild-\ntype titin, while being much shorter or absent for the destabilized titin-V15P mutant.\nReviewer #3 (Remarks to the Author):\nUsing FRET-based single-molecule analysis, López-Alfonzo et al. examined six Pore-1\nloop mutants, where the conserved Tyr residues in the Pore-1 loop were substituted with\nAla, revealing that the Pore-1 loops of Rpt6 and Rpt4 play unique and distinct roles\ncompared to other subunits. They developed an algorithm to improve the analysis of the\npreviously established smFRET method, enabling unbiased assessment of structural\nfluctuations. Structural analysis using Cryo-EM demonstrated that the Rpt6 Pore-1 loop,\nwhose mutation resulted in defects in both ATPase activity and substrate degradation\nassays, forms an α-helix in the s1 state, accompanied by a unique Arg finger orientation.\nOverall, the experiments were well-designed, with the structural dynamics derived from\ntheir FRET analysis aligning with those observed in Cryo-EM. The established smFRET\nanalysis provides significant and unique insights into the mechanical function of the\nproteasome. While a few minor questions remain, the study is well-suited for publication\nin Nature Communications.\nWe thank this reviewer for the overall very positive evaluation of our study.\n1. YA6 increases the non-s1 conformation in the presence of ATP, while no significant\nchanges are observed in YA1 and YA4. The escape rate, representing the rate of\nconformational switching, is notably faster than the ATPase hydrolysis rate, implying that\nthe conformational switch is independent of hydrolysis.\nWhat, then, triggers the conformational switch? Additionally, how does hydrolysis\ninfluence this process?\nThe reviewer is correct about the conformational switching occurring potentially\nspontaneously. In fact, we now postulate that the resting s1 state does not hydrolyze ATP\nat all, and the basal ATPase rate may originate solely from the spontaneous switching to\nhydrolysis-active non-s1 states. This assumption is not only consistent with the single,\napparently static spiral staircase orientation observed in structures of the s1-state\nproteasome, but also supported by the undetectably low ATPase activity of the human\nproteasome in the absence of substrate, which does not show significant spontaneous\nswitching to processing non-s1 states in cryo-EM particle distributions. We now\nreference those recent studies of the human proteasome.\nThe molecular reason for the conformational switching remains unknown. It could just be\na stochastic thermal crossing of the energy barrier between s1 and non-s1 states in this\nconformational equilibrium, or switching could be triggered by an ATP hydrolysis event in\nthe s1 state. Regarding the latter, it is interesting that ATPgS induces and stabilizes the\nnon-s1 states, indicating that nucleotide identity in some of the ATPase subunits strongly\naffects the global conformational equilibrium.\nSubstrate engagement appears to drive the conformational switch or at least stabilize the\nnon-s1 states, likely by bridging 4-5 ATPase subunits through pore-1 loop contacts and\ncoordinating or synchronizing their conformational changes and ATP hydrolysis. The\nobservation that the human proteasome quickly engages substrate despite the absence\nof spontaneous switching to non-s1states suggests that there are trigger mechanisms\nthrough substrate interactions in the s1 state, and engagement is independent of ATP\nhydrolysis or spontaneous switching.\n2. In Cryo-EM analysis, it is important to show the density map to validate whether the\nside-chain structures are accurately modeled.\nWe apologize for not including such density maps with docked atomic models in the\noriginal paper. The new Supp. Fig. 4-2 now includes those examples for density maps.\n3. Among the structures of the yeast 26S proteasome, s2 and s5 exhibit similar\nconfigurations to the s1 state, with Rpt6 positioned as the seam subunit. Do these\nstructures share loops that form a helix with Tyr222 oriented inward? Additionally, can\nthis helix formation of the pore-1 loop be observed when other subunits occupy the seam\nposition? A comparison would be interesting.\nOnly the s1 state shows this Rpt6-3 interaction with a helical conformation for Rpt6’s pore-\n1 loop. None of the other interfaces, neither in s1 nor in non-s1 states, including seam\nsubunits, show similar conformations and interactions. We are trying to highlight this in\nthe Supp. Fig. 4-3, depicting an example non-seam interface (Rpt2/Rpt6) in the s1 state\nand a seam as well as non-seam interface (Rpt4/Rpt5 and Rpt6/Rpt3) in a non-s1 state.\n4. smFRET data showed that the YA4 mutant significantly increases the s1 conformation\nin the presence of substrate, presumably due to substrate slip. The reviewer questions\nwhether a single mis-capture could indeed lead to entire substrate release. What is the\nprobability that a mis-capture of the substrate causes its release? Would it be feasible to\nanalyze the frequency of substrate release to investigate this further?\nThe reviewer raises an interesting question: Is a slip in front of the unfolding barrier\nsufficient for allowing the entire tail to slide out of the central channel and make a\nsubstrate escape degradation. In Fig. 7B we show the substrate release frequency after\nunsuccessful unfolding attempts and in Fig. 7C we show the time spent trying to unfold\n(successfully and unsuccessfully). Based on these results, a single slip does not seem\nsufficient for release. We see a lot of s1 transitions for YA4 during substrate processing,\nmeaning it can slip and maintain the substrate bound. Based on Fig. 5J, YA4 slips and\nswitches to s1 with a time constant of 1.8 s, yet based on Fig. 7C it spends on average\n15 s trying to unfold a substrate before giving up and releasing. A single slip consequently\ndoes not lead to release, and it takes several slips until a substrate escapes. We now\ndiscuss this at the end of the results section and thank the reviewer for bringing this up.\n5. A more detailed discussion on the dysfunction of YA4 would be valuable, as the data\nplausibly suggest that Rpt4 acts as a barrier to switching motion. In Cryo-EM analyses,\ns1-like and s4-like conformations are frequently observed in the absence and presence\nof substrate, respectively. This may result from the instability of other seam configurations.\nHowever, it remains unclear how the Rpt4 loop actively facilitates the transition from the\nbottom position to the seam.\nOur recent structural studies of the substrate-processing human proteasome agree with\nthe findings here and in previous cryo-EM analyses that Rpt4 frequently resides at the\nbottom or the seam of the staircase when the proteasome is dealing with an unfolding or\ntranslocation barrier Arkinson et al., bioRxiv 2024 .11.08.622731). We observed\nreproducibly more than 50% of proteasome particles with Rpt4 at the bottom or the seam,\nwhich we now include in the revised manuscript.\nTogether with the detected nucleotide occupancies and transitions between states, we\nproposed a burst-like mechanism in which some subunits move in rapid succession or\neven simultaneously, whereas other subunits, i.e. Rpt4, progress more slowly. Although\nwe do not have concrete proof, it is conceivable that staircase conformations with Rpt4\nat the seam or the bottom of the staircase represent pre-power stroke states, in\nagreement with our findings here that Rpt4’s pore-1 loop plays a particularly important\nrole for substrate unfolding. However, the molecular origins for this asymmetry in burst-\nlike subunit movements and their contributions to unfolding remain unknown.\nReviewer #4 (Remarks to the Author):\n# Kinetics analysis for single-molecule FRET traces\n> To analyze the FRET transition kinetics, authors used the Hidden Markov Model, a well-\nestablished model for single-molecule analysis. They used \"ebFRET\" software for this,\nand transition density plots show the transition between two dominant FRET states for\nthe proteasome construct. They also used Bayesian nonparametric FRET-analysis\nalgorithm based BNP-FRET which does not assume the number of states.\nThe authors were to better explain how transition rates were obtained and if the BNP-\nFRET result was different from the ebFRET result.\nWe thank the reviewer for this comment. In response to another reviewer’s comment, we\nhave elaborated upon the procedure for generating rates. Briefly, ebFRET and BNP-\nFRET do not contradict each other, rather they complement each other. BNP-FRET\ngenerates Monte Carlo samples for all parameters of interest from all FRET traces, which\nare then combined to produce the probability distributions over rates, trajectories, and\nFRET efficiencies. At the ensemble level, trace-to-trace kinetic heterogeneity causes the\ndistribution over rates to be wide, making it difficult to identify states. At the individual\ntrace level, ebFRET estimates lie within the high probability regions of distributions\nestimated by BNP-FRET.\n# Comments on the transition rate analysis\nThey were to clearly specify the used fitting model (single or double-exponential) and\noverlay the fitting curve with the dwell time data in Supp. Fig.2-2 or elsewhere to show if\ntheir model actually fits. It seems that they used double exponential fitting to get the \"fast\"\nand \"slow\" rates.\nWe specify in the figure legends (e.g. Fig. 2E, Fig. 3G,H, and new Supp. Fig. 3-3) that\ntransition rates were determined by double exponential fitting of the dwell time\ndistributions. The new Supp. Fig. 3-3 show the dwell time distributions for the s1 and non-\ns1 states of WT proteasomes as well as the YA4 and YA6 mutants, and their fits to double\nexponentials to determine the fast and slow phases of transition rates (shown in Fig.\n3G,H).\nBecause we expect the single-exponential distribution (with a tail...) in the simple two-\nstate system (assuming one dominant rate-limiting step) and double exponential fitting\nusually fits many types of data, we need some justification for the double exponential\nfitting. Is it due to the limited temporal resolution or another technical limitation? Or, is a\ntwo-step reaction actually expected here?\nWe assume that these deviations from ideal behavior are due to the complexity of the\nmultifaceted system, including a not completely uniform substrate pool, slight differences\nin ubiquitination, or compromised activity of immobilized proteasomes. Some molecules\nmay not be as active. We do not assume a 2-step reaction, although it cannot be\ncompletely ruled out.\n# Comments on each line\n220: with rates of 0.34 - 4.22 s-1 ... 0.66 - 7.22 s-1\n> What does the range mean? Confidence interval? The range is not very clear or\ninformative for a data set with an intrinsic wide distribution...\nWe thank the reviewer for this comment. We have now clarified in the text that the range\nin the ensemble heatmap indicates kinetic heterogeneity rather than uncertainty in rates\nfor a given trace.\n222: According to the ebFRET analysis (Fig. 2E)\n> Fig. 2E legend says the data is Bivariate probability distribution (not ebFRET). Which\none is correct?\nThank you for pointing out this mistake. The legends for Fig. 2 C-E were wrong and have\nbeen corrected.\n> Describe what three dots represent, here. t1/t2 of double exponential fitting of each data\nset? How can we get that from Fig. 2D?\nThe 3 dots represent the values determined in 3 technical replicates with separate\nebFRET analyses, which is now much clearer with the correct figure legend.\nFig. 2D/2E: The data should be ATP vs ATPrS, but there is only one graph for each\nsubplot.\nAgain, this was our mistake with an incorrect figure legend. The data for ATPgS are shown\nin the supplement (Supp. Fig. 3-4).\n225: The rates determined by ebFRET and BNP-FRET show overall similar trends and\nthe observed differences ... using camera calibration frames to avoid overfitting.\n> I believe the author should find a better analysis (may depend on the parameter we\nwant to see) and provide a fair justification for using the method over the other one. If the\ndifference is from the various noises, we cannot trust the data for the analysis.\nWe thank the reviewer for this comment. In response to an earlier comment and this one,\nwe have added more clarification points in the text. We use ebFRET and BNP-FRET as\ncomplementary tools that confirm each other’s conclusions, although one is more general\nand newer than the other. Furthermore, we now emphasize further in the text that all\nmicroscopy data are corrupted by noise, including photon shot noise, camera noise, and\nspectral crosstalk. By calibrating our camera and other sources of noise, BNP-FRET\nprovides accurate uncertainty estimates for rates to complement deterministic estimates\nby ebFRET.\nIn my opinion, because BNP-FRET does not assume the number of states, the result can\nbe less clear. If we can confirm that there are only two states based on the traces, the\nebFRET result can be more clear. BNP-FRET can be used to confirm if there are 3rd or\nmore states.\nWe appreciate this observation by the reviewer. We have now clarified further in the text\nthat, although we observe two FRET efficiencies at the individual trace level, it may not\nimmediately imply the existence of only two states. We do observe trace-to-trace kinetic-\nheterogeneity indicating the possibility of a rugged energy landscape for conformational\nchanges. In other words, more than two conformations likely exist, but are degenerate in\nFRET efficiency. Furthermore, existence of rarely visited intermediate FRET efficiency\nstate would manifest itself as higher uncertainty/wider distribution in BNP-FRET\nestimated rate vs FRET efficiency heatmaps, regardless of whether the intermediate state\nshows up in an individual HMM trajectory.\n238: This was confirmed in the BNP-FRET analysis by a redistribution of the s1–to–non-\ns1 escape towards higher rates that extend beyond 6 s-1 (Fig. 3E..\n> IT seems that both states got longer escape times in Fig. 3E, which means that the\ntransition got slower which does not necessarily mean that the high FRET state is more\npopulated. We'd better check the numbers or the bar graph.\nThe single-molecule distribution of dwell time (escape time or rate) is informative. It is\nhard to follow the distribution in the 2D density plot for me.\nThe reviewer is correct that there is an increase in the distribution of both escape rates\nfor the YA4 mutant (Fig. 3E), meaning that some population appears to switch more\nrapidly. However, the mean values for switching rates determined by ebFRET, shown in\nthe bar graph in Fig. 3G + H, indicate that YA4 changes conformations with similar rates\nas the wild-type proteasome.\nFig3\n> Labeling non-S1 or S1 on each FRET peak would help.\nWe thank the reviewer for this suggestion. This has been done.\nFig 3G/H\n> a color legend for WT/YA6/YA4 would help.\nThis makes sense. Done.\nmutant in the absence of substrate is also consistent with its higher basal ATPase rate.\n> As mentioned at 251, YA1 is not like this. It is not convincing... we may need a better\nexplanation or insight on the structure.\nWe agree with the reviewer that it is necessary to better explain the potential scenarios\nthat could lead to this differential behavior of the YA1 and YA6 mutants. In the revised\nmanuscript we discuss in more detail that the removal of Rpt1’s pore-1 loop tyrosine may\nincrease the flexibility of the s1 state and allow ATP hydrolysis in some subunits without\na global conformational switch to non-s1 states. The faster substrate processing by the\nYA1 mutant may be explained by a reduction of crowding in the central channel that\nallows other subunits to move more rapidly, yet does not affect the grip or pulling force\non a substrate. The increase in productive ATP hydrolysis and degradation velocity when\nin non-s1 states will be hard to study structurally. Solving a cryo-EM structure of the YA1\nmutant in the s1 state may provide some insights into the increased basal ATPase rate\n(possibly due to a partial disruption of the network of hydrogen bonds formed by the pore-\n1 loop Tyr of Rpt1, Rpt2, Rpt6, and Rpt3 with Rpt3), but such a structure is unlikely to\nreveal the reasons for increased substrate processing in non-s1 states and is therefore\nnot really worth pursuing. We hope that this reviewer agrees that the present study should\nprimarily focus on the Rpt subunits with the strongest contributions to proteasomal\nsubstrate processing, i.e. Rpt6 and Rpt4. We think that through the combination of in vitro\nbiochemistry, single-molecule measurements, and cryo-EM structure determination, we\ncould provide a reasonable model for AAA+ motor mechanisms that is well supported by\nthe experimental data, even though some questions, for instance about the stimulated\nATPase activity of the YA1 mutant, remain unanswered.\n285: We previously found that upon substrate engagement ... high-FRET non-s1 states\nthat are maintained until substrate unfolding and threading through the ATPase\n> Based on this, we will assume that high-FRET state dwell is the sum of intrinsic high\nFRET, substrate folding time (after binding), and threading time.\nTheoretically yes. But it is tricky, because numbers come from conclusions drawn using\n2 different assays, each with their shortcomings (peptide release from 20S holds things\nup in the processing assay, whereas spontaneous switching may make processing look\nshorter in the conformational switching assay).\n288: With the new instrumental setup\n> The author mentioned this multiple times. Need to specify what was improved\ntechnically (eg. temporal resolution?) and what information authors additionally obtained.\nOr remove it.\nWe removed it.\n289: high-FRET phases, i.e. substrate-processing dwells\n> unfolding and threading time (285)\nFollowing the reviewer’s suggestion this has been changed to be more specific: “high-\nFRET phases, i.e. substrate-processing dwells that include unfolding and complete\nthreading”.\n299: we were previously unable to use ebFRET for reliably measuring the ...\n> I do not get the difference between ebFRET and BNP here. Both measure the dwell\ntime of each state. It seems that the bivariate probability distribution of BNP-FRET shows\nthe distribution of the \"rate\" (the inverse of \"dwell time\") of each event. If so, there should\nbe no significant difference between the two methods in principle. If not, bivariate\nprobability distribution should be better explained.\nWe have clarified these points in response to previous comments.\n> It is not easy to compare bivariate probability distributions. In this figure. The sum of all\npixels should be 1, but Fig 5I has much more bright pixels compared to 5G. It seems that\nthey are not normalized equally or the color scale is not showing the proper region.\nWe thank the reviewer for bringing up this observation. We double checked, and the plots\nindeed represent the correct probability densities, shown in log space in order to make\nlow-density regions more visible. Due to the log space representation, normalization is\nnot trivial and intensities appear not additive.\n306: higher rates of 0.38 - 8.72 s-1, compared to 0.55 - 6.61 s-1 for WT\n> not a good way to represent the data\nWe have addressed this in response to this and another reviewer’s comment.\n309: correspondingly wider range of rates\n> \"wider\" what does it mean? Is the rate more heterogeneous or higher?\nThe rates are overall higher, and we changed the text accordingly.\n315:To more specifically analyze how\n> need to specifically explain the benefit of the manual scoring...\n> Was the manual scoring result different from the ebFRET or BNP? With the slower\nrates, both software may find the state better, too.\nIn particular the analyses by ebFRET benefitted from the lower substrate concentration\nthat allowed a better distinction between degradation events and phases of spontaneous\nconformational switching without substrate. In the revised text we added the following\nsentence: “This lower substrate concentration reduced the frequency of degradation\nevents and made it easier to distinguish between phases of degradation and idling without\na bound substrate.”\n320: shorter high-FRET phases, with tYA4 = 3.2 ± 0.3 s and tYA6 = 3.1 ± 0.3 s\n> Specify the representative numbers. Are they mean?\nYes, these values are the mean ± standard error of the mean, which we now specify in\nthe revised text and it is also mentioned in suppl. table 8.\n> I suggest the author show the distribution of dwell time (frequency vs dwell-time) as\nmany conventional single-molecule data and discuss the distribution more. It seems that\nWT has a more Gaussian distribution which implies that the high FRET dwell time is the\nresult of multiple reactions, or threading. YA6 and YA4 are not. It seems that the result is\na mixture of failing (single or double exponential) and some threading.\nThis is a very good suggestion. We now included a new Supp. figure 5-4 that shows the\ncumulative frequencies of high-FRET dwell times for WT and all YA-mutant proteasomes\nand reveals a clear deviation for YA4 and YA6, whose majority of high-FRET phases\nduring degradation last less than 2 s.\n327: Rpt4’s pore-1 loop affects the stable maintenance\n> Specify how it was affected\nThis sentence was rephrased to now read: “…mutation of either Rpt6’s or Rpt4’s pore-1\nloop compromise the stable maintenance of the processing-competent, non-s1 states\nduring substrate unfolding and cause more frequent returns to the s1 state, potentially\ndue to slippage.”\nFig. 5C-E\n> labeling (WT, YA6, YA4) would be nice.\nDone.\n353: slower substrate insertion into the YA6 mutant can be explained by its shift of the\nconformational equilibrium\n> YA4 showed the slower insertion, but its shift of the conformational equilibrium is the\nopposite.\nWe changed the text to now say that the slower substrate insertion into the YA6 mutant\ncan “to some extent” be explained by the shift of the conformational equilibrium, and we\nfurther discuss that the YA-mutation-induced dislodging of Rpt6’s pore-1 loop from Rpt3\nmay sterically interfere with the diffusive substrate insertion into the central channel. The\nslower substrate insertion into the YA4 mutant may have other reasons, for instance a\nless stable commitment to substrate degradation at a slightly later stage, for instance due\nto failed power strokes that drive substrate translocation after engagement, as discussed\nat the end of the results section on capture success.\n360: suggesting that substrates either do not fully enter the ATPase ring or fail to stay\nstably inserted\n> If so, oPA does not work for mutants and we cannot assume the single-turnover\nscenario. Is it still fair to accept the measured time constant?\nWe can still consider this as a single-turnover scenario regarding successful substrate\nengagement, even if this engagement takes several attempts and not all proteasomes\nend up with a stably engaged substrate. oPA does still work, as it prevents the\ndegradation process to proceed beyond engagement. It is therefore fair to accept the\nmeasured time constant, for the same reasons why we can determine degradation time\nconstants for the proteasome, despite substrate capture by the motor being successful in\njust ~ 50% or less of interaction events and requiring re-binding of the substrate.\n1072: Traces were filtered for visualization using Matlab R2019b.\n> Specify the filtering criteria instead of the software.\nWe used the MATLAB R2019b moving average filter, which is MATLAB’s default smooth\nfunction with a heuristically determined averaging window of five frames (equivalent to\n250 ms). We now provided additional information in the legend for Fig. 6.\n# More minor points\n184: Phe2\n> What is Phe2?\nPhe2 stands for phenylalanine 2. Depending on the context, we use single-letter code\n(for mutations), three-letter code (specifying certain residues), and the full name for amino\nacids, but we will adhere to the journal style if a certain code is preferred.\n592: 5,50-dithiobis-2-nitrobenzoic acid\n> 5,5-thiobis?\nThank you for catching it. This has been corrected.\n627: 300 uM LD555 (Lumidyne Technologies)\n> DBCO? Cat No. Can be added to all reagents. Specify dyes and their functional group\nas possible.\nWe now explain that DBCO-LD555 and DBCO-LD655 are dibenzocyclooctyne-\nconjugated sulfo-Cy3 and sulfo-Cy5 derivatives, respectively, from Lumidyne\nTechnologies, with the DBCO modification being custom synthesis. Due to the custom\nsynthesis there is no Cat.No.\n680: Excess dye was quenched\n> The dye was not quenched here. The reaction was.\nThis was corrected.\n742: built on an ultrastable single molecule stage\n> There are many words for optical tables. Single-molecule stage sounds a bit weird.\nWe changed this to “ultrastable optical table”.\n746: at 5mW and 2mW power\n2mW laser (from the laser head) is usually not good enough for single-molecule imaging\nin general. Better specify the information.\nThank you for pointing this out. This information has been corrected. We used 40% power\nfor the 532 nm laser and 25% power for the 640 nm laser. The output power at the laser\nhad / fiber optics is ~ 20 mW, meaning that at the sample stage we had ~ 8 mW for 532\nnm and 5 mW for 640 nm.\n793 but with a higher EM gain of 40\n> The 40 cannot be a real gain of iXon for smF...\nWe double checked, and this was indeed the gain value we consistently used for the EM\nGain, together with a preamp setting of 1 and a readout rate of 17MHz\nSupp. Fig.2-1:\n> The camera model number is wrong.\nThank you for pointing this out. The number has been corrected to iXon 897.\nSupp. Fig.2-2: \"hmm-mcmc\"\n> \"hmm-mcmc\" was not mentioned before. It should be a BNP-FRET-related one. Please\nuse consistent terminology.\nWe corrected this mistake. Thank you.\n\"DTNB was added to the purified base after concentrating\"\nIs it to minimize the non-specific interaction of DBCO? Does blocking thiol affect the\nprotein function?\nThe reviewer is correct that the reaction of exposed Cys with DTNB protects them from\nthe undesired modification with DBCO. Blocking thiols this way may have effects on\nprotein function, and we therefore reverse this modification by subsequent incubation with\nDTT, which restores free thiols. We now explain this in the revised methods section.\nQ. The construct shows the transition between two states (S1 or non-S1). Do substrates\nbind to both states?\nBoth states bind substrate through the interaction of substrate-attached ubiquitin chains\nwith proteasomal ubiquitin receptors, but only the s1 state allows a substrate to enter the\ncentral channel and be engaged by the ATPase motor.\nNon-S1 states process a substrate after successful engagement, but do not allow efficient\nsubstrate insertion due to steric occlusion of the pore by Rpn11. We added a sentence in\nthe introduction to further clarify this.\nResponse to reviewers’ comments:\nWe thank all 4 reviewers again for their constructive criticism that helped us to significantly\nimprove our manuscript for publication in Nature Communications.\nOur response to reviewer #4’s concern about experimental repeats is below.\nReviewer #1 (Remarks to the Author):\nAuthors have addressed all my concerns and questions.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed all of my concerns. I have no further suggestions and recommend\nthe manuscript for publication.\nReviewer #3 (Remarks to the Author):\nBy responding thoughtfully to my comments and that of the other reviewers, the authors have\ngreatly strengthened and improved the manuscript. This paper is exceptional in both its\nbiophysical approaches and its analysis of proteasome functions, and it is fully deserving of\nacceptance in Nature Communications.\nReviewer #4 (Remarks to the Author):\nThe authors’ response and the new revision are acceptable.\nOne remaining minor concern is related to Fig. 2E.\nThe statement, “Three technical replicates with separate ebFRET analyses, contributing to N =\n289 particles,” could be interpreted as indicating that the main figure is based on a single\nexperiment whose dataset was divided and analyzed three times, rather than on three\nindependent biological experiments. If this is the case, the data may not be sufficiently robust for\ninclusion as a main figure. If the authors indeed performed three independent experiments, it\nwould be clearer and more appropriate to state this explicitly."}, "author_response": ""}, {"round": 2, "reviewer_comments": {"reviewer_1": "authors have addressed all my concerns and questions.", "reviewer_2": "The authors have addressed all of my concerns. I have no further suggestions and recommend the\nmanuscript for publication.", "reviewer_3": "By responding thoughtfully to my comments and that of the other reviewers, the authors have greatly strengthened and\nimproved the manuscript. This paper is exceptional in both its biophysical approaches and its analysis of proteasome\nfunctions, and it is fully deserving of acceptance in Nature Communications.", "reviewer_4": "The authors’ response and the new revision are acceptable.\nOne remaining minor concern is related to Fig. 2E.\nThe statement, “Three technical replicates with separate ebFRET analyses, contributing to N = 289 particles,” could be\ninterpreted as indicating that the main figure is based on a single experiment whose dataset was divided and analyzed three\ntimes, rather than on three independent biological experiments. If this is the case, the data may not be sufficiently robust for\ninclusion as a main figure. If the authors indeed performed three independent experiments, it\nwould be clearer and more appropriate to state this explicitly."}, "author_response": "We would like to thank the reviewers for their detailed review of our manuscript and their\nconstructive criticism that helped us improve our study with additional experiments and\nanalyses. Our responses to individual comments are pasted below in blue and\ncorresponding changes to the manuscript are highlighted in red.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe paper by Lopez-Alfonzo et al describes new mechanistic insights into the unfolding\nand degradation of proteins by the proteasome. Upon recognition of ubiquitinated\nproteins, the pore loops of the proteasomal AAA-ATPase ring engage with the substrate’s\ninitiation region thereby facilitating the unfolding and translocation of substrates into the\nCP. The authors identify the loop of Rpt6 to be critical in initiation. Interestingly, in the\nengagement competent state (s1) this loop interacts with Rpt3 arginine fingers, which\ncontributes to stabilizing this s1 state. So, the Rpt6 loop is a critical component of the\ninitiation of degradation. A second loop that was identified as important is the Rpt4 loop,\nhowever, the logic and mechanistic unique feature here remains less well defined.\nWe thank the reviewer for this positive assessment of our findings. Regarding the\ncontributions of Rpt4, our data show that a lack its pore-1 loop Tyr leads to ~ 2-fold\nreduced success in capturing a substrate and a ~ 2-fold increased release of substrate\ndue to unsuccessful unfolding attempts. Together with the strongly skewed cryo-EM\nparticle distributions observed in numerous studies, where spiral-staircase states of the\nATPase motor with Rpt4 at the bottom or the seam position are 4 to 5-fold more prevalent\nthan expected for an equal distribution of all staircase states, these data indicate a critical\nrole of Rpt4 in the mechanical power stroke for substrate unfolding.\nThe authors also observed some unique properties for Rpt1 loop mutants, however, no\nrational or detailed follow up for that was provided.\nGiven the lack of substrate-degradation defects for the Rpt1 pore-1 loop mutant, we\ndecided to not further pursue the studies of this variant, despite its increased ATP\nhydrolysis rate. The complexity of the proteasomal ATPase motor and its regulation for\ncoordinated ATP-hydrolysis, nucleotide exchange, and conformational changes make it\nextremely difficult to reveal the mechanistic details of this stimulated hydrolysis activity.\nIn light of our cryo-EM structural insights for the s1-state proteasome, where Rpt1’s pore-\n1 loop shows previously missed interactions with Rpt3 that may stabilize the s1 state with\nlow (or no) ATPase activity, we have included in the revised manuscript a brief discussion\nabout the potential roles of Rpt1 and the consequent effects of a Rpt1 YA mutation on\nthe ATPase activity.\nAlso, in the section on how pore loops affect the conformational dynamics of the\nproteasome, we now state: “It is possible that removal of Rpt1’s Tyr allows for a less static\ns1 state that hydrolyzes ATP at a considerable rate without globally switching to non-s1\nconformations.”\nOverall, the strengths of the paper are the elegant molecular dissection with powerful\nbiophysical assays such as the 26S conformational state with a single molecule FRET-\nbased assay and the substrate translocation with another FRET based assay. These\nassays have been used in the past and have been further improved upon in this\nmanuscript. These assays are further supported with a cryoEM structure that is of higher\nresolution as previous structures. This was important to identify the Rpt6 pore loop-Rpt3\nArg finger interactions.\nThe manuscript is well written and provides strong support for the proposed models and\ncompelling and relevant new\ninsights into the mechanism of proteasome substrate\nengagement and unfolding. One weakness is that the Rpt1 loop mutant data are largely\nnot explained and show in part phenotypes similar to the Rpt6 loop mutations, suggesting\nthat some of the data can be interpreted differently as Rpt1 loop clearly must be acting\ndifferently from the Rpt6 loop.\nIn contrast to the Rpt6 mutant, the Rpt1 pore-loop mutant showed no degradation defects.\nThe reason for its elevated ATP-hydrolysis activity that does not get further stimulated\nupon substrate engagement must therefore be distinct from that of the Rpt6 YA mutant.\nRpt1’s hydrolysis activity is productive, leading to 50% faster degradation of the I27V15P\nmodel substrate compared to the wild-type proteasome. While its increased basal\nATPase rate may originate from a partial disruption of the s1 state that could allow ATP\nhydrolysis in some subunits without global conformational transitions to non-s1 states,\nthe elevated ATPase rate and faster substrate degradation by the YA1 mutant in non-s1\nstates may stem from a reduced bulk in the central channel that allows other subunits to\nmove more quickly. We now mention these hypotheses in the revised manuscript.\nAnother point of concern is that the general phenomenon that are deduced from these in\nvitro studies are all based on one model substrate.\nAlthough we agree that it would be insightful to eventually perform similar experiments\nwith a variety of proteins, and ideally endogenous substrates, it was important to conduct\nour fundamental studies with well-defined model substrates that allow a reliable and\nreproducible readout. For identifying defects in substrate engagement, unfolding, and\ntranslocation, it is critical to know exactly where initiation occurs on a substrate, meaning\nthat there should be no intrinsically flexible or disordered regions other than the\nunstructured tail. Since the number and location of ubiquitin modifications may influence\nsubstrate engagement and degradation rates, we needed a model protein containing a\nsingle Lys with a nearby E3 ligase recognition motif that allows efficient ubiquitination in\none spot. Also, using the well-characterized titin I27 domain allowed us to generate model\nsubstrates with defined thermodynamic stabilities in order to assess how the height of the\nunfolding barrier affects different proteasome variants in their degradation rates. The titin\nI27 domain with a cyclin-B-derived tail for engagement is an ideal substrate, and findings\nregarding different ATPase motor defects should be generally applicable. We do not think\nthat the number and identity of folded domains, or the sequence and location of the\nunstructured initiation region would fundamentally change the defects observed for the\ndifferent pore-1 loop mutations.\nWhile the structure of the engagement competent 26S supports the Rpt6 role as gate\nkeeper and thus likely is substrate independent, for some of the other loops that is less\nclear to me. E.g., the described important role of Rpt4; could there be substrate\ndependance or other differences where certain loops might play a more dominant role in\none case compared to another? Different initiation regions have different efficiencies of\ndegradation, so maybe the length and/or composition of the tail can show more\ndependence on different loops? So, how can the author be sure the data for Fig. 1D, e.g.,\nis more universal and not specific for this Titin substrate? I think it would be helpful if the\nauthors could explain why this is universal or state the constrains of their study in this\nregard.\nThe reviewer is correct that different flexible tails may affect the insertion, engagement,\nand unfolding, but we don’t think that the differential roles of individual Rpt pore loops will\nchange, for 2 reasons. 1) We see defects not just at one particular stage, e.g. initiation,\nbut throughout substrate processing, during which the motor interacts with different\nsegments of the substrate. 2) Our findings about the particular importance of Rpt6 and\nRpt4 are nicely supported by structural data and the prominent positioning of these\nsubunits in critical spiral-staircase states. There is just a single engagement-competent\ns1 state, such that Rpt6 is always at the seam when a substrate lands, it is the first subunit\nto move in the staircase after substrate insertion, and it is the first subunit to form new\ncontacts with the substrate polypeptide. Similarly, the vast majority of cryo-EM structures\nfor the proteasome (both yeast and human) with stalled substrates or during active\nunfolding of a stable domain show Rpt4 at the seam or bottom position, which suggests\nthat this subunit has a special role in overcoming an unfolding barrier. Importantly, this is\ntrue for various distinct substrates that were used for these structural studies by different\ngroups. Furthermore, previous studies in yeast showed that the Rpt4 pore-1 loop mutant\nshowed the highest accumulation of ubiquitinated proteins in whole-cell lysates, again\nindicating defects that are independent of the particular substrate identify.\nWe therefore do not think that the use of titin-I27-tail model substrates represents a major\nlimitation of our study or restricts the conclusions that can be drawn from it.\nThe Rpt1 mutant shows unique and interesting ATPase activity with and without\nsubstrate. It is not clear to me how does this mutant fits with the authors’ model? Rpt1\nmutant has increased ATPase activity for 26S by itself (like Rpt6 loop mutant) without an\nshift in the population of s1 to non-s1. So, what is going on with Rpt1 mutant and how can\nauthors be sure their interpretation for Rpt6 mutant is correct as there can apparently be\ndifferent causes of increased ATPase activity? If the higher rate of Rpt1 mutant is for\nincreased activity in the non-S1 state, then combining Rpt1 and Rpt6 mutation should be\nadditive regarding ATPase activity and help distinguish in mechanism between these\nmutants on 26S by itself?\nWe currently do not know the exact reason for the increased ATP-hydrolysis and\ndegradation activities of the Rpt1 YA mutant. As mentioned above, it is possible that the\nYA mutation partially relaxes the s1 state and allows increased ATP hydrolysis without a\nglobal conformational shift to non-s1 states that could be detected in our FRET-based\nassays. The molecular origin for the increased and productive ATP-hydrolysis in non-s1\nstates during substrate processing remains unclear as well. Removing the pore-1 loop\nTyr from Rpt1 may reduce the bulk in the central channel and allow other subunits to\nmove more quickly, yet have no significant effect on the grip and pulling force of the motor.\nOur findings from recent cryo-EM studies of the substrate-processing human proteasome\nwould be consistent with this hypothesis (Arkinson et al., bioRxiv 2024 .11.08.622731).\nIn these structures, we observed that Rpt1 and Rpt2 apparently move together from the\nbottom to the top of the staircase for Rpt2 to re-engage the substrate. During this Rpt2\nre-engagement, Rpt5 next to Rpt1 already moves up to the top of the staircase and\nexchanges ADP for ATP, such that in the subsequent step when Rpt1 re-engages the\nsubstrate polypeptide, Rpt5 is nearby and ready to engage. A lack of Rpt1’s pore-1 loop\nTyr may therefore have no major effects on substrate translocation or unfolding, as\nneighboring subunits can readily compensate.\nCombining the Rpt1 YA and Rpt6 YA mutations, as suggested by this reviewer, will likely\nnot provide further insights, because these mutations affect different stages of\ndegradation and are therefore expected to not be truly additive in their effects. The\nengagement defects of Rpt6 YA would also apply to the combined mutant and dominate\nthe phenotype. Furthermore, given the interactions of pore loops with each other in the\ncentral channel, eliminating more than one Tyr may lead to other global effects that are\nhard to interpret.\nOur new data for mutations at the Rpt6/Rpt3 interface that destabilize the s1 state and\nincrease ATPase activity nicely support our conclusions about Rpt6’s pore-1 loop. We\nare therefore more confident in our interpretations for Rpt6, even if there remain open\nquestions about Rpt1 that may be answered in future studies.\nLine 274-275. I like this conclusion by the authors. However, doesn’t the Rpt1 mutant\nsuggest this might be too simplistic, as there is higher activity without increased non-s1\nstate?\nIn response to reviewers’ comments, we mutated E140 and K141 in Rpt6 to disrupt the\napparent contacts at the Rpt6/Rpt3 interface that we identified in our new structure of the\ns1-state proteasome. Indeed, these mutations increased the ATPase activity and the\nE140A mutation also shifted the conformational equilibrium in our single-molecule assay\ntoward non-s1 states, further supporting our conclusion that the s1 state likely does not\nhydrolyze ATP. In agreement with this, in our recently solved structure of the resting-state\nhuman proteasome, we observed the same Rpt6/Rpt3 contacts as well as pore-1 loops\nof Rpt1, Rpt2, and Rpt3 held in “parked” positions. The human 26S proteasome has\nundetectable ATPase activity in the absence of substrate, and cryo-EM particle\ndistributions indicate that it rarely switches to the non-s1 processing states. We now\ndiscuss these parallels between the yeast and human proteasomes in the revised\nmanuscript and show the structural overlay in a new Supp. Fig. 4-3.\nMutating the loop of Rpt6 leads to increase non-s1 conformations, which are less suitable\nfor engagement with initiation region. Based on cryoEM the loop of Rpt6 interacts with\nRpt3 arginine fingers. The complementary mutations of Rpt3 should thus also change the\nequilibrium from more s1 to more non-s1, which could be a nice confirmation of their data,\nassuming the mutated arginine fingers don’t interfere too much with ATP binding and\nATPase ring formation. Did the authors attempt or consider this mutation?\nThe reviewer is correct that mutations of the Arg fingers would compromise ATPase\nactivity and are therefore not suited to address this question. Instead, we introduced the\nE140A and K141A mutations in Rpt6, and indeed observed the expected effects: both\nmutants show an increase in ATP hydrolysis activity, and our single-molecule\nconformational change measurements for the E140A mutant showed a corresponding\nshift from the s1 to non-s1 states (new Supp. Fig. 4-4). As mentioned above, we also\npresent in the revised manuscript a direct structural comparison with the s1 state of the\nhuman proteasome, which shows the same Rpt6/Rpt3 contacts and interactions with the\npore-1 loops of Rpt1, Rpt2, and Rpt3 that likely help stabilizing a static, ATPase deficient\ns1 state.\nThe supplementary Fig 7-2 C provides for nice complementary data to the other type of\nassays. However, looking at the figure the impact seems rather modest compared to the\ndescribed impact of the mutations from the other assays. Wouldn’t it be expected that\nmore of the substrate would be degraded in the wild type versus Rpt6 and Rpt4 mutants,\nthis is not apparent to me from this assay. Also, would all the released substrates be truncated or could some be full length and only be\ndeubiquitinated?\nThe reviewer is correct about these SDS-PAGE results being not as clear as expected\nbased on our other assays. We were also disappointed to not see a stronger accumulation\nof partially degraded product. In part this may be due to a lack of tail clipping when the\nmotor fails to unfold titin I27, leading to the release of deubiquitinated full-length substrate,\nrather than a truncated product (see our response to the next point below). Furthermore,\nit is possible that a small amount of free 20S core particle from dissociated 26S\nproteasomes truncates the tail of released substrates, generating non-uniform products\nthat spread over a wider range of the gel.\nRegarding the extend of substrate degradation for wild-type versus Rpt6 and Rpt4, this\nis always hard to assess by SDS-PAGE, since there is a broad distribution of ubiquitinated\nsubstrate species, and wild-type titin I27 is turned over very slowly. The single-turnover\nbulk degradation measurements (Supp. Fig. 6-2) and the single-molecule analyses of WT\ntitin I27 degradation (Fig. 6, Fig. 7, Supp. Fig. 6-3) are therefore more reliable in\ndetermining differences in degradation kinetics for WT proteasome versus its YA mutants,\nand WT proteasomes show faster turnover there. It is indeed possible that the less\nfrequent substrate release during or following an unfolding attempt hold up WT\nproteasomes, such that YA4 and YA6 mutants may more quickly move on to the next\nsubstrate and thereby generate more truncated as well as deubiquitinated substrate\nspecies. This is indeed what the gel in Supp. Fig. 7-2 C seems to show: YA4 and YA6\nappear to turn over more ubiquitinated substrate, and the bands for deubiquitinated and\ndeubiquitinated + truncated titin are more intense than for WT proteasomes. We briefly\ndiscuss this in the revised manuscript and thank the reviewer for pointing this out.\nAlso, would all the released substrates be truncated or could some be full length and only\nbe deubiquitinated?\nThe reviewer is absolutely correct. Only if the C-terminal unstructured tail of 59 is\nreasonably extended within the degradation chamber of the 20S CP by the time the motor\nreaches the titin I27 folded domain, one would expect clipping prior to release. Failure to\nunfold may therefore also lead to deubiquitination and release of full-length substrate.\nAlthough this is harder to quantify, as there is some unmodified substrate in our initial\nsample due to incomplete ubiquitination, the gel in Supp. Fig. 7.2 C indeed appears to\nshow a more intense unmodified titin band for YA4 and YA6 mutants compared to the WT\nproteasome, which we now briefly discuss at the end of the results section.\nReviewer #2 (Remarks to the Author):\nThis manuscript by López-Alfonzo, Erika M., et al., presents a comprehensive study using\nsingle-molecule FRET and cryo-EM techniques to elucidate the role of pore loops in the\nRpt6 and Rpt4 ATPase subunits of the 26S proteasome. The authors provide valuable\ninsights into how these structural elements affect the protein degradation process,\ndemonstrating that the Rpt6 pore loop is crucial for substrate handling and initiation of\ndegradation, whereas the Rpt4 loop aids in substrate unraveling and sustains proteasome\nefficiency. Although the experiments are well-executed and the findings presented are\nintriguing, I have the following major concerns:\n1. The study explores the Rpt6 pore-1 loop’s role via the YA6 mutation, positing that it\naffects substrate capture. Could you detail whether this mutation alters the interaction\nbetween Rpt3 and Rpt6?\nThe reviewer is correct, the YA6 mutation indeed weakens the s1-conformation-specific\ninteraction between Rpt6 and Rpt3, leading to a shift in the conformational equilibrium\ntoward non-s1 states. Our new mutations E140A and K141A in Rpt6 confirm this finding\nby also weakening the interaction with Rpt3, leading to an increase in ATPase activity\nand, as tested for the E140A mutant at the single-molecule level, to a shift in the\nconformational equilibrium. Depending on the mutation, destabilizing this interface may\nalso have effects on proteasome assembly, as alternative Rpt3 mutants, D304A and\nD325A, showed significantly reduced yields and were therefore not further pursued for\nthe revision of this manuscript.\nFurthermore, how does the helical conformation of the Rpt6 pore-1 loop interact with the\narginine finger of Rpt3 to facilitate substrate capture and the conformational state\ntransition?\nThe helical conformation of Rpt6’s pore-1 region and its interaction with the neighboring\nRpt3, including the pore-2 loop and the second region of homology with its Arg fingers,\nseems to stabilize the s1 state and hold the proteasome in a resting state until substrate\narrival. Based on our observations for both the yeast and the human 26S proteasomes,\nwe assume that in the s1 state the spiral staircase is static and there is very little or no\nATP hydrolysis. In the revised manuscript we now present that yeast and human\nproteasomes share the same interactions that “park” the ATPase motor. Those\ninteractions involve not just the Rpt6/Rpt3 interface, but there also appear to be stabilizing\ninteractions (mostly hydrogen bonds) between the Rpt2’s pore-1 loop Tyr and Rpt3,\nbetween the Rpt1 pore-1 loop Tyr and Rpt3, as well as between the Rpt3 pore-1 loop Tyr\nand the N-domain. It remains to be determined by what mechanisms substrate insertion\ninto the central channel breaks those interactions, leading to engagement and a transition\nof the motor form a static s1 to dynamic non-s1 states with actively hydrolyzing subunits.\nBased on our single-molecule conformational change assay, the yeast proteasome\nspontaneously samples non-s1 states, which may allow Rpt6 and other subunits to grab\na substrate that inserted itself in the channel. Although there are no similar single-\nmolecule studies for the human proteasome, particle distributions for cryo-EM data sets\nand undetectably low ATPase activity in the absence of substrate indicate that the human\nproteasome does not frequently switch to non-s1 states, and a specific mechanism may\ntrigger this transition upon substrate insertion.\n2. The manuscript references data on ATPγS in Figure 2's legend that appears absent\nfrom the figure itself. Could you include a supplementary explanation or correct the figure\nto reflect this data?\nThe reviewer is right about the incorrect legend for Fig. 2 C-E. This has been corrected.\nThe ATPgS data are shown in the supplement (Supp. Fig. 3-4).\n3. You mention kinetic parameters from BNP-FRET analysis for transition rates; however,\nthe methodology to derive these figures is unclear. The visual distinction in Figure 2D\nbetween states is not evident. Could you elaborate on the criteria used for determining\nthese rates?\nWe thank the reviewer for pointing this out. We have now clarified the procedure for\ngenerating the figures in the text. Briefly, BNP-FRET works in the Bayesian paradigm\nwhere it generates a collection of Monte Carlo samples to estimate probability\ndistributions for each parameter of interest, including rates and trajectories. The heatmap\nin Fig. 2D has contributions from the whole ensemble of FRET traces and a wide\ndistribution reflects the kinetic heterogeneity among traces. This, in turn, makes it\nchallenging to identify states at the ensemble level.\n4. In Figure 2E, the fitting of kfast and kslow for the escape rate of the low-FRET s1 state\nsuggests two kinetic processes. If these rates are not indicative of separate processes,\nplease clarify their relevance.\nThe fast transition rates are dominant, which is why we largely disregard the slow rates,\nwhose molecular origin remains unknown. We now mention this explicitly in the revised\ntext.\n5. The authors have excluded static fluorescence traces from the population analysis. It\nwould be beneficial for the study if the reasons for these traces exhibiting static\ncharacteristics were discussed. Specifically, it should be clarified whether these\nstatic traces originate from denatured samples, which could potentially exhibit different\nfluorescence behaviors. If the static nature is not due to denaturation, an explanation\nshould be provided regarding why these samples exhibit such characteristics. This\ndiscussion could help validate the exclusion of these traces and ensure that the analysis\naccurately reflects the behavior of functional protein complexes.\nWe appreciate this reviewer’s critical assessment of this issue, which represents a\ncommon challenge in single-molecule analyses. We disregarded static traces based on\nthe more consistent behavior we observed for dynamically switching proteasomes,\ncombined with results from bulk measurements and with cryo-EM data showing certain\ndistributions of s1 and non-s1 states for substrate-free yeast proteasomes. It seems not\nsurprising that some of the immobilized molecules are “sick” and not behaving as expect.\nAs suggested by the reviewer, denaturation, partial unfolding, or sticking may play a role.\nBased on the fluorescence signal we can rule out oligomerization or aggregation of\nseveral labeled particles, but otherwise it is impossible to say why some proteasomes\nappear stuck in a certain state. We now explain in the text why we focus on the\ndynamically switching molecules and disregard the static ones.\n6. The Rpt1 mutant YA1 shows enhanced ATPase and degradation activities. Could\nfurther insights into the mechanistic implications of this observation be provided,\nparticularly regarding the pore loop's role as a potential rate-limiting factor?\nWe do not know what is rate limiting for the motor movements during substrate unfolding\nand translocation, but it is possible that the YA1 mutation removes bulk from the central\nchannel in non-s1 states and makes the motor overall move more quickly. Importantly,\nthe increased ATPase activity also leads to increased degradation velocity for all the\nsubstrate variants, indicating that this mutant can hydrolyze and move faster, with no\napparent negative consequences on substrate processing, which makes this distinct from\nRpt6. We now discuss in the revised manuscript the potential origins for the increased\nATPase activity of the YA1 mutant in the s1 and non-s1 states.\n7. The role of the YA6 mutation in facilitating transitions to non-s1 states lacks direct\nevidence linking substrate interaction directly with Rpt6.\nThe effect of the YA6 mutation may be direct, through Rpt6’s pore-1 loop contacting\nsubstrate, or indirect, through a compromised interface with Rpt3. It is hard to assess\nwhat contributes what. From structures during active processing it is clear that Rpt6\nmakes direct physical contact with the substrate, but when and how Rpt6’s pore-1 loop is\nreleased from its “parked” position against Rpt3 remains unclear. The yeast proteasome\nspontaneously switches from s1 to non-s1 states more than twice per second, such that\nRpt6’s pore-1 loop may grab an inserted substrate for engagement. The resting (s1)\nstate of the human proteasome is much more static and rarely switching to non-s1 states,\nsuch that substrate insertion into the central channel may trigger a conformational transition\nand release of Rpt6’s pore-1 loop from Rpt3, yet elucidating the underlying mechanism\nis beyond the scope of this paper.\nStructural data in Figure 4 imply dependency on Rpt3. Could the mutation’s effects be\ndue to destabilizing Rpt3/Rpt6 interactions?\nYes, the reviewer is correct about this destabilization of the s1-specific Rpt6/Rpt3\ninterface by the YA6 mutation. We were able to further support this model by\ncharacterizing two other interface mutations, Rpt6 E140A and K141A. Both show\nincreased ATPase activity, and the E140A mutation tested in our single-molecule assay\nleads to a shift of the conformational equilibrium towards non-s1 states, similar to the YA6\nmutation. We also attempted to mutate the Rpt3 side of this interface by replacing D304\nor D325 with Ala, yet these mutations led to significantly reduced yields of the base\nsubcomplex (possibly due to assembly defects), and were not further pursued for this\nrevision.\nDirect structural evidence of substrate engagement with Rpt6 would strengthen this claim.\nAlthough there is structural evidence for Rpt6 physically interacting with substrate at later\nstages of processing, it seems impossible to catch this subunit in the process of initial\nengagement.\n8. The observation of increased substrate releases due to mutations in the Rpt4 pore-1\nloop suggests a gripping defect. Could an additional mechanism explain this loop's role\nin substrate processing?\nIssues with stably gripping the substrate during mechanical unfolding seem to best\nexplain the phenotypes we observed for the YA4 mutation. Our single-molecule\nmeasurements provide unprecedented insights that go far beyond of previous bulk\nbiochemistry or in vivo data for the contributions of individual ATPase subunits to\nproteasomal substrate degradation, but of course we cannot rule out alternative or\nadditional mechanisms.\n9. You propose a \"burst-like\" mechanism contrasting with the traditional hand-over-hand\nmodel. How does this align with the asymmetric arrangement of Rpt subunits and the\nstructure of individual subunits? More data would bolster this novel hypothesis.\nThe hypothesis of the “burst-like” mechanism is based on our functional data, combined\nwith strongly asymmetric distributions of proteasome particles in different spiral staircase\nstates that were observed in various cryo-EM data sets. Our recent structural studies of\nthe human proteasome during active substrate degradation strongly support this model,\nas they indicate that movement of Rpt4 from the bottom to the top of the spiral staircase\nis the slow step during the ATPase cycle of the motor hexamer and is linked to ATP\nhydrolysis in two Rpt subunit, Rpt2 and Rpt1. This movement of Rpt4 may therefore\nrepresent the power stroke of the proteasomal motor for substrate unfolding.\nWe cite this work now in the revised manuscript.\n10. The use of singly fluorescently labeled substrates could potentially influence\ndegradation rates. Have comparisons been made between rates of ATP hydrolysis and\nprotein degradation in fluorescently labeled versus non-labeled substrates?\nThe reviewer brings up a very valid concern. For previous bulk and single-molecule\nstudies (Bard et al., 2019; Jonsson et al., 2022) we tried to compare labeled and\nunlabeled substrates. The rate-limiting step of substrate degradation was not affected,\nbut translocation through the proteasome central channel may have been somewhat\nslowed by pulling through a bulky fluorescent dye. However, direct comparisons are\ndifficult, because unlabeled substrates cannot be analyzed regarding the individual\nphases of their degradation. Importantly, we observed robust and rapid turnover of the\nfluorescently labeled substrates, and by using identical substrate batches for the\ncharacterization of different proteasome mutants we assured that the measured effects\nare reporting true functional differences.\n11. To substantiate the claim that mutants YA4 and YA6 destabilize the non-S1 state with\nthe substrate (Figure 5J), could you provide dwell-time distributions for high-FRET states\nacross other mutants?\nWe now include in the new Fig.5J the High-FRET dwell time distributions for all YA\nmutants, showing that only the YA4 and YA6 mutations lead to significantly shorter times\ncontinuously spent in non-s1 states during substrate processing.\n12. In Figure 6, the definition of FRET states shows significant fluctuations, especially in\nthe unfolded state (Figure 6D). Could you provide a detailed methodology for how these\nFRET states were determined and assigned?\nThe pre-unfolding FRET state was assigned based on comparing WT and YA mutants\nand comparing WT titin and the titin V15P mutant, with the latter not showing much of the\npre-unfolding intermediate FRET phase. Also, Supp. Fig. 6-5 shows slips out of the pre-\nunfolding intermediate FRET to a higher FRET state and back. Overall, we think that there\nis reasonably solid evidence for the lower FRET state being a pre-unfolding dwell. We\nnow mention in the revised manuscript that this assignment as a pre-unfolding dwell was\nmade based on the distinct presence for the thermodynamically much more stable wild-\ntype titin, while being much shorter or absent for the destabilized titin-V15P mutant.\nReviewer #3 (Remarks to the Author):\nUsing FRET-based single-molecule analysis, López-Alfonzo et al. examined six Pore-1\nloop mutants, where the conserved Tyr residues in the Pore-1 loop were substituted with\nAla, revealing that the Pore-1 loops of Rpt6 and Rpt4 play unique and distinct roles\ncompared to other subunits. They developed an algorithm to improve the analysis of the\npreviously established smFRET method, enabling unbiased assessment of structural\nfluctuations. Structural analysis using Cryo-EM demonstrated that the Rpt6 Pore-1 loop,\nwhose mutation resulted in defects in both ATPase activity and substrate degradation\nassays, forms an α-helix in the s1 state, accompanied by a unique Arg finger orientation.\nOverall, the experiments were well-designed, with the structural dynamics derived from\ntheir FRET analysis aligning with those observed in Cryo-EM. The established smFRET\nanalysis provides significant and unique insights into the mechanical function of the\nproteasome. While a few minor questions remain, the study is well-suited for publication\nin Nature Communications.\nWe thank this reviewer for the overall very positive evaluation of our study.\n1. YA6 increases the non-s1 conformation in the presence of ATP, while no significant\nchanges are observed in YA1 and YA4. The escape rate, representing the rate of\nconformational switching, is notably faster than the ATPase hydrolysis rate, implying that\nthe conformational switch is independent of hydrolysis.\nWhat, then, triggers the conformational switch? Additionally, how does hydrolysis\ninfluence this process?\nThe reviewer is correct about the conformational switching occurring potentially\nspontaneously. In fact, we now postulate that the resting s1 state does not hydrolyze ATP\nat all, and the basal ATPase rate may originate solely from the spontaneous switching to\nhydrolysis-active non-s1 states. This assumption is not only consistent with the single,\napparently static spiral staircase orientation observed in structures of the s1-state\nproteasome, but also supported by the undetectably low ATPase activity of the human\nproteasome in the absence of substrate, which does not show significant spontaneous\nswitching to processing non-s1 states in cryo-EM particle distributions. We now\nreference those recent studies of the human proteasome.\nThe molecular reason for the conformational switching remains unknown. It could just be\na stochastic thermal crossing of the energy barrier between s1 and non-s1 states in this\nconformational equilibrium, or switching could be triggered by an ATP hydrolysis event in\nthe s1 state. Regarding the latter, it is interesting that ATPgS induces and stabilizes the\nnon-s1 states, indicating that nucleotide identity in some of the ATPase subunits strongly\naffects the global conformational equilibrium.\nSubstrate engagement appears to drive the conformational switch or at least stabilize the\nnon-s1 states, likely by bridging 4-5 ATPase subunits through pore-1 loop contacts and\ncoordinating or synchronizing their conformational changes and ATP hydrolysis. The\nobservation that the human proteasome quickly engages substrate despite the absence\nof spontaneous switching to non-s1states suggests that there are trigger mechanisms\nthrough substrate interactions in the s1 state, and engagement is independent of ATP\nhydrolysis or spontaneous switching.\n2. In Cryo-EM analysis, it is important to show the density map to validate whether the\nside-chain structures are accurately modeled.\nWe apologize for not including such density maps with docked atomic models in the\noriginal paper. The new Supp. Fig. 4-2 now includes those examples for density maps.\n3. Among the structures of the yeast 26S proteasome, s2 and s5 exhibit similar\nconfigurations to the s1 state, with Rpt6 positioned as the seam subunit. Do these\nstructures share loops that form a helix with Tyr222 oriented inward? Additionally, can\nthis helix formation of the pore-1 loop be observed when other subunits occupy the seam\nposition? A comparison would be interesting.\nOnly the s1 state shows this Rpt6-3 interaction with a helical conformation for Rpt6’s pore-\n1 loop. None of the other interfaces, neither in s1 nor in non-s1 states, including seam\nsubunits, show similar conformations and interactions. We are trying to highlight this in\nthe Supp. Fig. 4-3, depicting an example non-seam interface (Rpt2/Rpt6) in the s1 state\nand a seam as well as non-seam interface (Rpt4/Rpt5 and Rpt6/Rpt3) in a non-s1 state.\n4. smFRET data showed that the YA4 mutant significantly increases the s1 conformation\nin the presence of substrate, presumably due to substrate slip. The reviewer questions\nwhether a single mis-capture could indeed lead to entire substrate release. What is the\nprobability that a mis-capture of the substrate causes its release? Would it be feasible to\nanalyze the frequency of substrate release to investigate this further?\nThe reviewer raises an interesting question: Is a slip in front of the unfolding barrier\nsufficient for allowing the entire tail to slide out of the central channel and make a\nsubstrate escape degradation. In Fig. 7B we show the substrate release frequency after\nunsuccessful unfolding attempts and in Fig. 7C we show the time spent trying to unfold\n(successfully and unsuccessfully). Based on these results, a single slip does not seem\nsufficient for release. We see a lot of s1 transitions for YA4 during substrate processing,\nmeaning it can slip and maintain the substrate bound. Based on Fig. 5J, YA4 slips and\nswitches to s1 with a time constant of 1.8 s, yet based on Fig. 7C it spends on average\n15 s trying to unfold a substrate before giving up and releasing. A single slip consequently\ndoes not lead to release, and it takes several slips until a substrate escapes. We now\ndiscuss this at the end of the results section and thank the reviewer for bringing this up.\n5. A more detailed discussion on the dysfunction of YA4 would be valuable, as the data\nplausibly suggest that Rpt4 acts as a barrier to switching motion. In Cryo-EM analyses,\ns1-like and s4-like conformations are frequently observed in the absence and presence\nof substrate, respectively. This may result from the instability of other seam configurations.\nHowever, it remains unclear how the Rpt4 loop actively facilitates the transition from the\nbottom position to the seam.\nOur recent structural studies of the substrate-processing human proteasome agree with\nthe findings here and in previous cryo-EM analyses that Rpt4 frequently resides at the\nbottom or the seam of the staircase when the proteasome is dealing with an unfolding or\ntranslocation barrier Arkinson et al., bioRxiv 2024 .11.08.622731). We observed\nreproducibly more than 50% of proteasome particles with Rpt4 at the bottom or the seam,\nwhich we now include in the revised manuscript.\nTogether with the detected nucleotide occupancies and transitions between states, we\nproposed a burst-like mechanism in which some subunits move in rapid succession or\neven simultaneously, whereas other subunits, i.e. Rpt4, progress more slowly. Although\nwe do not have concrete proof, it is conceivable that staircase conformations with Rpt4\nat the seam or the bottom of the staircase represent pre-power stroke states, in\nagreement with our findings here that Rpt4’s pore-1 loop plays a particularly important\nrole for substrate unfolding. However, the molecular origins for this asymmetry in burst-\nlike subunit movements and their contributions to unfolding remain unknown.\nReviewer #4 (Remarks to the Author):\n# Kinetics analysis for single-molecule FRET traces\n> To analyze the FRET transition kinetics, authors used the Hidden Markov Model, a well-\nestablished model for single-molecule analysis. They used \"ebFRET\" software for this,\nand transition density plots show the transition between two dominant FRET states for\nthe proteasome construct. They also used Bayesian nonparametric FRET-analysis\nalgorithm based BNP-FRET which does not assume the number of states.\nThe authors were to better explain how transition rates were obtained and if the BNP-\nFRET result was different from the ebFRET result.\nWe thank the reviewer for this comment. In response to another reviewer’s comment, we\nhave elaborated upon the procedure for generating rates. Briefly, ebFRET and BNP-\nFRET do not contradict each other, rather they complement each other. BNP-FRET\ngenerates Monte Carlo samples for all parameters of interest from all FRET traces, which\nare then combined to produce the probability distributions over rates, trajectories, and\nFRET efficiencies. At the ensemble level, trace-to-trace kinetic heterogeneity causes the\ndistribution over rates to be wide, making it difficult to identify states. At the individual\ntrace level, ebFRET estimates lie within the high probability regions of distributions\nestimated by BNP-FRET.\n# Comments on the transition rate analysis\nThey were to clearly specify the used fitting model (single or double-exponential) and\noverlay the fitting curve with the dwell time data in Supp. Fig.2-2 or elsewhere to show if\ntheir model actually fits. It seems that they used double exponential fitting to get the \"fast\"\nand \"slow\" rates.\nWe specify in the figure legends (e.g. Fig. 2E, Fig. 3G,H, and new Supp. Fig. 3-3) that\ntransition rates were determined by double exponential fitting of the dwell time\ndistributions. The new Supp. Fig. 3-3 show the dwell time distributions for the s1 and non-\ns1 states of WT proteasomes as well as the YA4 and YA6 mutants, and their fits to double\nexponentials to determine the fast and slow phases of transition rates (shown in Fig.\n3G,H).\nBecause we expect the single-exponential distribution (with a tail...) in the simple two-\nstate system (assuming one dominant rate-limiting step) and double exponential fitting\nusually fits many types of data, we need some justification for the double exponential\nfitting. Is it due to the limited temporal resolution or another technical limitation? Or, is a\ntwo-step reaction actually expected here?\nWe assume that these deviations from ideal behavior are due to the complexity of the\nmultifaceted system, including a not completely uniform substrate pool, slight differences\nin ubiquitination, or compromised activity of immobilized proteasomes. Some molecules\nmay not be as active. We do not assume a 2-step reaction, although it cannot be\ncompletely ruled out.\n# Comments on each line\n220: with rates of 0.34 - 4.22 s-1 ... 0.66 - 7.22 s-1\n> What does the range mean? Confidence interval? The range is not very clear or\ninformative for a data set with an intrinsic wide distribution...\nWe thank the reviewer for this comment. We have now clarified in the text that the range\nin the ensemble heatmap indicates kinetic heterogeneity rather than uncertainty in rates\nfor a given trace.\n222: According to the ebFRET analysis (Fig. 2E)\n> Fig. 2E legend says the data is Bivariate probability distribution (not ebFRET). Which\none is correct?\nThank you for pointing out this mistake. The legends for Fig. 2 C-E were wrong and have\nbeen corrected.\n> Describe what three dots represent, here. t1/t2 of double exponential fitting of each data\nset? How can we get that from Fig. 2D?\nThe 3 dots represent the values determined in 3 technical replicates with separate\nebFRET analyses, which is now much clearer with the correct figure legend.\nFig. 2D/2E: The data should be ATP vs ATPrS, but there is only one graph for each\nsubplot.\nAgain, this was our mistake with an incorrect figure legend. The data for ATPgS are shown\nin the supplement (Supp. Fig. 3-4).\n225: The rates determined by ebFRET and BNP-FRET show overall similar trends and\nthe observed differences ... using camera calibration frames to avoid overfitting.\n> I believe the author should find a better analysis (may depend on the parameter we\nwant to see) and provide a fair justification for using the method over the other one. If the\ndifference is from the various noises, we cannot trust the data for the analysis.\nWe thank the reviewer for this comment. In response to an earlier comment and this one,\nwe have added more clarification points in the text. We use ebFRET and BNP-FRET as\ncomplementary tools that confirm each other’s conclusions, although one is more general\nand newer than the other. Furthermore, we now emphasize further in the text that all\nmicroscopy data are corrupted by noise, including photon shot noise, camera noise, and\nspectral crosstalk. By calibrating our camera and other sources of noise, BNP-FRET\nprovides accurate uncertainty estimates for rates to complement deterministic estimates\nby ebFRET.\nIn my opinion, because BNP-FRET does not assume the number of states, the result can\nbe less clear. If we can confirm that there are only two states based on the traces, the\nebFRET result can be more clear. BNP-FRET can be used to confirm if there are 3rd or\nmore states.\nWe appreciate this observation by the reviewer. We have now clarified further in the text\nthat, although we observe two FRET efficiencies at the individual trace level, it may not\nimmediately imply the existence of only two states. We do observe trace-to-trace kinetic-\nheterogeneity indicating the possibility of a rugged energy landscape for conformational\nchanges. In other words, more than two conformations likely exist, but are degenerate in\nFRET efficiency. Furthermore, existence of rarely visited intermediate FRET efficiency\nstate would manifest itself as higher uncertainty/wider distribution in BNP-FRET\nestimated rate vs FRET efficiency heatmaps, regardless of whether the intermediate state\nshows up in an individual HMM trajectory.\n238: This was confirmed in the BNP-FRET analysis by a redistribution of the s1–to–non-\ns1 escape towards higher rates that extend beyond 6 s-1 (Fig. 3E..\n> IT seems that both states got longer escape times in Fig. 3E, which means that the\ntransition got slower which does not necessarily mean that the high FRET state is more\npopulated. We'd better check the numbers or the bar graph.\nThe single-molecule distribution of dwell time (escape time or rate) is informative. It is\nhard to follow the distribution in the 2D density plot for me.\nThe reviewer is correct that there is an increase in the distribution of both escape rates\nfor the YA4 mutant (Fig. 3E), meaning that some population appears to switch more\nrapidly. However, the mean values for switching rates determined by ebFRET, shown in\nthe bar graph in Fig. 3G + H, indicate that YA4 changes conformations with similar rates\nas the wild-type proteasome.\nFig3\n> Labeling non-S1 or S1 on each FRET peak would help.\nWe thank the reviewer for this suggestion. This has been done.\nFig 3G/H\n> a color legend for WT/YA6/YA4 would help.\nThis makes sense. Done.\nmutant in the absence of substrate is also consistent with its higher basal ATPase rate.\n> As mentioned at 251, YA1 is not like this. It is not convincing... we may need a better\nexplanation or insight on the structure.\nWe agree with the reviewer that it is necessary to better explain the potential scenarios\nthat could lead to this differential behavior of the YA1 and YA6 mutants. In the revised\nmanuscript we discuss in more detail that the removal of Rpt1’s pore-1 loop tyrosine may\nincrease the flexibility of the s1 state and allow ATP hydrolysis in some subunits without\na global conformational switch to non-s1 states. The faster substrate processing by the\nYA1 mutant may be explained by a reduction of crowding in the central channel that\nallows other subunits to move more rapidly, yet does not affect the grip or pulling force\non a substrate. The increase in productive ATP hydrolysis and degradation velocity when\nin non-s1 states will be hard to study structurally. Solving a cryo-EM structure of the YA1\nmutant in the s1 state may provide some insights into the increased basal ATPase rate\n(possibly due to a partial disruption of the network of hydrogen bonds formed by the pore-\n1 loop Tyr of Rpt1, Rpt2, Rpt6, and Rpt3 with Rpt3), but such a structure is unlikely to\nreveal the reasons for increased substrate processing in non-s1 states and is therefore\nnot really worth pursuing. We hope that this reviewer agrees that the present study should\nprimarily focus on the Rpt subunits with the strongest contributions to proteasomal\nsubstrate processing, i.e. Rpt6 and Rpt4. We think that through the combination of in vitro\nbiochemistry, single-molecule measurements, and cryo-EM structure determination, we\ncould provide a reasonable model for AAA+ motor mechanisms that is well supported by\nthe experimental data, even though some questions, for instance about the stimulated\nATPase activity of the YA1 mutant, remain unanswered.\n285: We previously found that upon substrate engagement ... high-FRET non-s1 states\nthat are maintained until substrate unfolding and threading through the ATPase\n> Based on this, we will assume that high-FRET state dwell is the sum of intrinsic high\nFRET, substrate folding time (after binding), and threading time.\nTheoretically yes. But it is tricky, because numbers come from conclusions drawn using\n2 different assays, each with their shortcomings (peptide release from 20S holds things\nup in the processing assay, whereas spontaneous switching may make processing look\nshorter in the conformational switching assay).\n288: With the new instrumental setup\n> The author mentioned this multiple times. Need to specify what was improved\ntechnically (eg. temporal resolution?) and what information authors additionally obtained.\nOr remove it.\nWe removed it.\n289: high-FRET phases, i.e. substrate-processing dwells\n> unfolding and threading time (285)\nFollowing the reviewer’s suggestion this has been changed to be more specific: “high-\nFRET phases, i.e. substrate-processing dwells that include unfolding and complete\nthreading”.\n299: we were previously unable to use ebFRET for reliably measuring the ...\n> I do not get the difference between ebFRET and BNP here. Both measure the dwell\ntime of each state. It seems that the bivariate probability distribution of BNP-FRET shows\nthe distribution of the \"rate\" (the inverse of \"dwell time\") of each event. If so, there should\nbe no significant difference between the two methods in principle. If not, bivariate\nprobability distribution should be better explained.\nWe have clarified these points in response to previous comments.\n> It is not easy to compare bivariate probability distributions. In this figure. The sum of all\npixels should be 1, but Fig 5I has much more bright pixels compared to 5G. It seems that\nthey are not normalized equally or the color scale is not showing the proper region.\nWe thank the reviewer for bringing up this observation. We double checked, and the plots\nindeed represent the correct probability densities, shown in log space in order to make\nlow-density regions more visible. Due to the log space representation, normalization is\nnot trivial and intensities appear not additive.\n306: higher rates of 0.38 - 8.72 s-1, compared to 0.55 - 6.61 s-1 for WT\n> not a good way to represent the data\nWe have addressed this in response to this and another reviewer’s comment.\n309: correspondingly wider range of rates\n> \"wider\" what does it mean? Is the rate more heterogeneous or higher?\nThe rates are overall higher, and we changed the text accordingly.\n315:To more specifically analyze how\n> need to specifically explain the benefit of the manual scoring...\n> Was the manual scoring result different from the ebFRET or BNP? With the slower\nrates, both software may find the state better, too.\nIn particular the analyses by ebFRET benefitted from the lower substrate concentration\nthat allowed a better distinction between degradation events and phases of spontaneous\nconformational switching without substrate. In the revised text we added the following\nsentence: “This lower substrate concentration reduced the frequency of degradation\nevents and made it easier to distinguish between phases of degradation and idling without\na bound substrate.”\n320: shorter high-FRET phases, with tYA4 = 3.2 ± 0.3 s and tYA6 = 3.1 ± 0.3 s\n> Specify the representative numbers. Are they mean?\nYes, these values are the mean ± standard error of the mean, which we now specify in\nthe revised text and it is also mentioned in suppl. table 8.\n> I suggest the author show the distribution of dwell time (frequency vs dwell-time) as\nmany conventional single-molecule data and discuss the distribution more. It seems that\nWT has a more Gaussian distribution which implies that the high FRET dwell time is the\nresult of multiple reactions, or threading. YA6 and YA4 are not. It seems that the result is\na mixture of failing (single or double exponential) and some threading.\nThis is a very good suggestion. We now included a new Supp. figure 5-4 that shows the\ncumulative frequencies of high-FRET dwell times for WT and all YA-mutant proteasomes\nand reveals a clear deviation for YA4 and YA6, whose majority of high-FRET phases\nduring degradation last less than 2 s.\n327: Rpt4’s pore-1 loop affects the stable maintenance\n> Specify how it was affected\nThis sentence was rephrased to now read: “…mutation of either Rpt6’s or Rpt4’s pore-1\nloop compromise the stable maintenance of the processing-competent, non-s1 states\nduring substrate unfolding and cause more frequent returns to the s1 state, potentially\ndue to slippage.”\nFig. 5C-E\n> labeling (WT, YA6, YA4) would be nice.\nDone.\n353: slower substrate insertion into the YA6 mutant can be explained by its shift of the\nconformational equilibrium\n> YA4 showed the slower insertion, but its shift of the conformational equilibrium is the\nopposite.\nWe changed the text to now say that the slower substrate insertion into the YA6 mutant\ncan “to some extent” be explained by the shift of the conformational equilibrium, and we\nfurther discuss that the YA-mutation-induced dislodging of Rpt6’s pore-1 loop from Rpt3\nmay sterically interfere with the diffusive substrate insertion into the central channel. The\nslower substrate insertion into the YA4 mutant may have other reasons, for instance a\nless stable commitment to substrate degradation at a slightly later stage, for instance due\nto failed power strokes that drive substrate translocation after engagement, as discussed\nat the end of the results section on capture success.\n360: suggesting that substrates either do not fully enter the ATPase ring or fail to stay\nstably inserted\n> If so, oPA does not work for mutants and we cannot assume the single-turnover\nscenario. Is it still fair to accept the measured time constant?\nWe can still consider this as a single-turnover scenario regarding successful substrate\nengagement, even if this engagement takes several attempts and not all proteasomes\nend up with a stably engaged substrate. oPA does still work, as it prevents the\ndegradation process to proceed beyond engagement. It is therefore fair to accept the\nmeasured time constant, for the same reasons why we can determine degradation time\nconstants for the proteasome, despite substrate capture by the motor being successful in\njust ~ 50% or less of interaction events and requiring re-binding of the substrate.\n1072: Traces were filtered for visualization using Matlab R2019b.\n> Specify the filtering criteria instead of the software.\nWe used the MATLAB R2019b moving average filter, which is MATLAB’s default smooth\nfunction with a heuristically determined averaging window of five frames (equivalent to\n250 ms). We now provided additional information in the legend for Fig. 6.\n# More minor points\n184: Phe2\n> What is Phe2?\nPhe2 stands for phenylalanine 2. Depending on the context, we use single-letter code\n(for mutations), three-letter code (specifying certain residues), and the full name for amino\nacids, but we will adhere to the journal style if a certain code is preferred.\n592: 5,50-dithiobis-2-nitrobenzoic acid\n> 5,5-thiobis?\nThank you for catching it. This has been corrected.\n627: 300 uM LD555 (Lumidyne Technologies)\n> DBCO? Cat No. Can be added to all reagents. Specify dyes and their functional group\nas possible.\nWe now explain that DBCO-LD555 and DBCO-LD655 are dibenzocyclooctyne-\nconjugated sulfo-Cy3 and sulfo-Cy5 derivatives, respectively, from Lumidyne\nTechnologies, with the DBCO modification being custom synthesis. Due to the custom\nsynthesis there is no Cat.No.\n680: Excess dye was quenched\n> The dye was not quenched here. The reaction was.\nThis was corrected.\n742: built on an ultrastable single molecule stage\n> There are many words for optical tables. Single-molecule stage sounds a bit weird.\nWe changed this to “ultrastable optical table”.\n746: at 5mW and 2mW power\n2mW laser (from the laser head) is usually not good enough for single-molecule imaging\nin general. Better specify the information.\nThank you for pointing this out. This information has been corrected. We used 40% power\nfor the 532 nm laser and 25% power for the 640 nm laser. The output power at the laser\nhad / fiber optics is ~ 20 mW, meaning that at the sample stage we had ~ 8 mW for 532\nnm and 5 mW for 640 nm.\n793 but with a higher EM gain of 40\n> The 40 cannot be a real gain of iXon for smF...\nWe double checked, and this was indeed the gain value we consistently used for the EM\nGain, together with a preamp setting of 1 and a readout rate of 17MHz\nSupp. Fig.2-1:\n> The camera model number is wrong.\nThank you for pointing this out. The number has been corrected to iXon 897.\nSupp. Fig.2-2: \"hmm-mcmc\"\n> \"hmm-mcmc\" was not mentioned before. It should be a BNP-FRET-related one. Please\nuse consistent terminology.\nWe corrected this mistake. Thank you.\n\"DTNB was added to the purified base after concentrating\"\nIs it to minimize the non-specific interaction of DBCO? Does blocking thiol affect the\nprotein function?\nThe reviewer is correct that the reaction of exposed Cys with DTNB protects them from\nthe undesired modification with DBCO. Blocking thiols this way may have effects on\nprotein function, and we therefore reverse this modification by subsequent incubation with\nDTT, which restores free thiols. We now explain this in the revised methods section.\nQ. The construct shows the transition between two states (S1 or non-S1). Do substrates\nbind to both states?\nBoth states bind substrate through the interaction of substrate-attached ubiquitin chains\nwith proteasomal ubiquitin receptors, but only the s1 state allows a substrate to enter the\ncentral channel and be engaged by the ATPase motor.\nNon-S1 states process a substrate after successful engagement, but do not allow efficient\nsubstrate insertion due to steric occlusion of the pore by Rpn11. We added a sentence in\nthe introduction to further clarify this.\nResponse to reviewers’ comments:\nWe thank all 4 reviewers again for their constructive criticism that helped us to significantly\nimprove our manuscript for publication in Nature Communications.\nOur response to reviewer #4’s concern about experimental repeats is below.\nReviewer #1 (Remarks to the Author):\nAuthors have addressed all my concerns and questions.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed all of my concerns. I have no further suggestions and recommend\nthe manuscript for publication.\nReviewer #3 (Remarks to the Author):\nBy responding thoughtfully to my comments and that of the other reviewers, the authors have\ngreatly strengthened and improved the manuscript. This paper is exceptional in both its\nbiophysical approaches and its analysis of proteasome functions, and it is fully deserving of\nacceptance in Nature Communications.\nReviewer #4 (Remarks to the Author):\nThe authors’ response and the new revision are acceptable.\nOne remaining minor concern is related to Fig. 2E.\nThe statement, “Three technical replicates with separate ebFRET analyses, contributing to N =\n289 particles,” could be interpreted as indicating that the main figure is based on a single\nexperiment whose dataset was divided and analyzed three times, rather than on three\nindependent biological experiments. If this is the case, the data may not be sufficiently robust for\ninclusion as a main figure. If the authors indeed performed three independent experiments, it\nwould be clearer and more appropriate to state this explicitly.\nResponse:\nWe apologize for not presenting this more clearly. The data presented in Fig. 2E were not just\nfrom a single experiments or from technical repeats, but from biological repeats, using\nreconstituted proteasome subcomplexes from different purifications. This has been clarified in the\nrevised figure legend:\n“E) Rates for the s1 – to – non-s1 and non-s1 – to – s1 transitions determined using ebFRET,\nperformed as previously described 38, and fitting the survival plots to a double exponential.\n(n = 3 biological replicates with separate ebFRET analyses, contributing to N = 289 particles;\nerror bars represent the SD).”"}]

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