High-resolution mapping reveals features of bacterial NAD-capped RNAs and stress-responsive transcription initiation

Domain: chemistry
Published: 2026-04-07
Editorial outcome: major_revision

Abstract
The NAD+ cap has been discovered in RNAs across prokaryotes and eukaryotes, suggesting a
possible role of NAD capping in gene regulation. Current NAD-capped RNA (NAD-RNA)
profiling methods lack precision in 5’-end mapping or bias against small NAD-RNAs. Here, we
introduce precision NAD-RNA sequencing (pNAD-seq), which combines a two-step enrichment
strategy with high-throughput sequencing to achieve single-nucleotide resolution of 5’-ends and
unprecedented sensitivity for identifying small NAD-RNAs. We further develop NAD-linkSeq to
determine full-length NAD-RNA sequences. Applying these methods to E. coli, we uncover a vast
repertoire of NAD-RNAs, including tRNAs, rRNAs, intragenic transcripts, and antisense RNAs,
many of which are significantly shorter than regular mRNAs, implying specialized biogenesis.
High-resolution mapping reveals conserved promoter architectures driving NAD-RNA production
and condition-dependent initiation dynamics: under nitrogen limitation, some NAD-RNA undergo
TSS switching, alternative promoter usage, and coordinated expression shifts, correlating with
metabolic stress responses. This report presents findings that offer a comprehensive view of NAD-
RNAs in E. coli and introduces reliable methods for genome-wide profiling of NAD-RNAs across
different organisms, which will facilitate the functional characterization of NAD-capping.

Introduction
Eukaryotic messenger RNAs (mRNAs) typically feature a 7-methylguanylate (m⁷G) cap at their
5’-end, a critical modification that protects them from 5’-3’ exonucleolytic degradation and
promotes essential processes such as mRNA processing, nuclear export, and translation initiation
via interactions with cap-binding proteins1, 2, 3. In contrast, prokaryotic RNAs were long thought
to possess only a 5’-triphosphate terminus derived from the initiating nucleotide of
transcription4.However, recent studies have revealed the presence of nicotinamide adenine
dinucleotide at the 5’-end of certain bacterial transcripts5, 6. Intriguingly, NAD-capped RNAs
(NAD-RNAs) are not restricted to prokaryotes; they have also been identified in diverse
eukaryotes, including yeast7, mammals8, 9, and plant10, 11, suggesting a broader biological
significance of this modification.

The NAD captureSeq technique5 was the first method developed for transcriptome-wide
profiling of NAD-RNAs. In this approach, the nicotinamide moiety of NAD is enzymatically
modified with an alkyne group using ADP-ribosyl cyclase (ADPRC). The alkyne-labeled NAD-
RNAs are then biotinylated via copper-catalyzed azide-alkyne cycloaddition (CuAAC), enabling
their selective enrichment with streptavidin-coated beads. The purified RNAs are subsequently
converted into cDNA libraries for high-throughput sequencing. This method has successfully
identified NAD-RNAs in diverse organisms, including bacteria5, yeast7, mammalian cells8, and
the plants Arabidopsis10 and rice12.

Alternative methods for transcriptome-wide identification of NAD-RNAs include NAD
tagSeq11 and NAD tagSeq II13. Both techniques use ADP-ribosyl cyclase (ADPRC) to label NAD
caps, but differ in their downstream chemistry: NAD tagSeq employs copper-catalyzed azide-
alkyne cycloaddition (CuAAC) to attach an RNA tag for Oxford Nanopore sequencing, while
NAD tagSeq II replaces CuAAC with copper-free strain-promoted azide-alkyne cycloaddition
(SPAAC) to minimize copper-induced RNA fragmentation. Unlike enrichment-based approaches,
these methods enable direct quantification of both NAD-RNAs and untagged transcripts in the
same sequencing run. The SPAAC chemistry has also been adapted into SPAAC-NAD-seq for
profiling NAD-RNAs in Arabidopsis and a similar method, NADcapPro14, has been applied in
yeast.

Current methods for NAD-RNA detection face significant challenges in precisely mapping the
5’-ends of NAD-capped transcripts. This limitation impedes both mechanistic studies of NAD
capping and functional characterization of NAD-RNAs. In the original NAD captureSeq protocol5,
first-strand cDNA synthesis occurs while NAD-RNAs remain immobilized on streptavidin resin,
where the bulky biotin moiety at the 5’-end can interfere with reverse transcriptase processivity,
preventing full-length cDNA synthesis. Modified versions of NAD captureSeq7, 8, 10 and ONE-
Seq15 employ standard RNA-seq library preparation strategies (random priming or template
switching) to improve transcript coverage, but these approaches compromise accurate 5’-end
mapping16, 17. Similarly, while NAD tagSeq11 and NAD tagSeq II13 enable direct sequencing of
NAD-RNAs without enrichment, the non-canonical nucleotides introduced during click chemistry
prevent precise identification of the native 5’-terminus.

Current NAD-RNA detection methods also struggle to effectively identify short NAD-capped
transcripts. Standard cDNA library preparation protocols, optimized for typical mRNAs, and the
original NAD captureSeq protocol5 that omits RNA fragmentation, both introduce biases against
shorter RNAs through size selection, adapter ligation, and PCR amplification steps. This results in
inefficient capture and underrepresentation of small NAD-RNAs in sequencing libraries. While
NAD tagSeq11 and NAD tagSeq II13 offer direct sequencing capabilities, they are similarly limited
by Nanopore technology’s inherent bias against small transcripts. These technical constraints
create a significant gap in our ability to comprehensively profile the NAD-capped transcriptome,
as shorter but potentially important NAD-RNA species are frequently lost or underrepresented in
current analyses.

NAD-RNAs are primarily formed when RNA polymerase initiates transcription using NAD+
instead of ATP as the starting nucleotide. This co-transcriptional capping occurs at specific
transcription start sites (TSS) and is influenced by promoter sequences18, 19. However, evidence
suggests that NAD+ may also be incorporated post-transcriptionally in some instances8, 14. Using
NAD tagSeq, Zhang et al. demonstrated that while NAD-capped RNAs represent only ~0.5% of
non-rRNA transcripts in E. coli overall, certain genes produce predominantly NAD-RNAs under
specific growth conditions13. This finding indicates that NAD-capping may be a regulated process
with potential biological significance.

To overcome existing limitations in NAD-RNA profiling, we developed precision NAD-RNA
sequencing (pNAD-seq) and its modified version, NAD-linkSeq, which combine SPAAC-
mediated biotinylation for specific NAD-RNA enrichment, NudC processing to convert NAD-
capped RNAs to 5’-monophosphate RNAs for selective amplification, and a linker-based cDNA
library construction strategy for high-resolution sequencing. When applied to E. coli, pNAD-seq
demonstrated superior sensitivity, accuracy, and 5’-end resolution compared to existing methods,
enabling full-length NAD-RNA characterization. Our analysis revealed an unanticipated diversity
of NAD-capped transcripts, including small intragenic and antisense RNAs. Our findings indicate
that NAD-RNAs represent a diverse class of RNAs that may play significant regulatory roles.
These findings not only expand the known repertoire of NAD-RNAs but also establish a robust
framework for investigating the biological significance of NAD-capping.

Results
High-efficiency biotinylation of NAD-RNA through SPAAC tagging
Our previous work established SPAAC-based tagging for NAD-RNA labeling in methods such as
NAD tagSeq II13 and SPAAC-NAD-seq20. Building on this, we developed precision NAD-RNA
sequencing (pNAD-seq), which relies on ADPRC-mediated transglycosylation of the 5’-NAD
moiety in the presence of azide to generate clickable azide-NAD-RNA. This product is then
conjugated to biotin via SPAAC reaction with biotin-DBCO (Fig. 1a). To optimize the SPAAC
tagging efficiency in pNAD-seq, we first tested the system using an in vitro-transcribed NAD-
capped 24mer RNA. Following ADPRC treatment and biotin-DBCO conjugation, we observed a
slow-running band in urea-PAGE, absent in the no-ADPRC control (Fig. 1b), confirming
successful biotinylation. Quantification of the biotinylated and unbiotinylated bands revealed a
tagging efficiency of ~94%. Next, we determined the optimal ADPRC concentration by titrating
the enzyme and monitoring substrate conversion. After incubating NAD-RNA with varying
ADPRC concentrations and subsequent biotin-DBCO labeling, urea-PAGE separation allowed
quantification of biotinylated vs. unbiotinylated RNA. The resulting titration curve (Fig. 1c)
indicated that 42 nM ADPRC was sufficient to achieve 96% conversion efficiency. Our tests
showed that the amount of ADPRC enzyme used in previous studies can be significantly reduced
while still working effectively. We used the original, high concentration5 in this study to
guarantee reliable results, but this finding means future studies can achieve the same outcome at a
much lower cost. We further compared SPAAC tagging with the one-step biotinylation approach,
where NAD-RNA is directly labeled using biotin-PEG-OH via ADPRC15. Under identical
conditions, SPAAC tagging achieved 92% efficiency, whereas the one-step method reached only
50% (Fig. 1d), demonstrating the superior efficiency of SPAAC-based biotinylation.

Specificity of SPAAC tagging for NAD-RNA
Having validated the high efficiency of SPAAC tagging, we assessed its specificity using RNAs
with diverse 5’-ends, including NAD-capped 25mer RNA (NAD+24nt), uncapped A-RNA, and
RNAs with various biologically relevant 5’-modifications (pppA4, ppRNA21, pRNA22, Ap3A-
RNA23, Ap4A-RNA24, 5’-OH RNA25, and dpCoA-RNA26). While NAD-RNA showed near-
complete biotinylation (98%), none of the other tested RNAs were labeled, confirming high
specificity (Supplementary Fig. 1a–c). NADH-RNA, though recognized by ADPRC, exhibited
significantly lower biotinylation efficiency (~20%) compared to NAD-RNA (Supplementary Fig.
1d), suggesting that ADPRC-mediated tagging selectively enriches NAD-RNAs with minimal
cross-reactivity toward NADH-RNA.

NudC efficiently hydrolyzes the pyrophosphate bond of biotinylated NAD-RNA The E. coli
Nudix hydrolase NudC5, a known NAD-RNA decapping enzyme, cleaves the pyrophosphate bond
of NAD-RNA. Using purified recombinant NudC (Supplementary Fig. 2), we confirmed that
NudC also hydrolyzes biotinylated NAD-RNA generated via SPAAC tagging, producing a biotin-
modified riboside moiety and 5’-monophosphorylated RNA (pA-RNA) (Fig. 1e). Urea-PAGE
analysis revealed faster migration of the NudC-treated product (Fig. 1f), and mass spectrometry
identified the expected biotin-containing fragment (m/z=1063.421) (Supplementary Fig. 3),
confirming pyrophosphate bond cleavage. Time-course experiments showed complete decapping
of biotinylated NAD-RNA within 4 min (Fig. 1g). We further examined how 5’-secondary
structures affect decapping efficiency 27 by testing linear, extended, blunt, and recessed ends.
While linear and extended structures required lower NudC concentrations, complete decapping of
blunt or recessed ends needed ≥500 nM enzyme (Fig. 1h), demonstrating that 5’-end accessibility
influences NudC activity. These results establish that NudC efficiently processes biotinylated
NAD-RNA for downstream applications while being sensitive to RNA structural context.

Precision NAD-RNA sequencing (pNAD-seq) method
We developed pNAD-seq as a two-step enrichment strategy for high-specificity NAD-RNA
identification (Fig. 1i). The method proceeds as follows: (1) Total RNA is fragmented to ~200 nt
and treated with phosphatase to remove 5’ phosphates (preventing non-NAD-RNA ligation in later
steps) while preserving 3’-OH groups for adapter ligation; (2) SPAAC tagging biotinylates NAD-
capped RNAs (with ADPRC- control); (3) Streptavidin bead enrichment isolates NAD-RNAs; (4)
A 3’-RNA adapter is ligated to bead-bound RNAs; (5) After elution, NudC decapping generates
5’-monophosphate ends (5’-pA-RNA); (6) A 5’-RNA adapter is ligated to the decapped ends; (7)
cDNA synthesis and PCR amplification are performed using adapter-specific primers (forward
primer complementary to 5’-adapter and reverse primer complementary to 3’-adapter); (8) Final
libraries are indexed and sequenced. NAD-RNAs are identified by: precise 5’-end adenosine
mapping and ADPRC+ enrichment over control. Compared to NAD captureSeq, pNAD-seq
provides nucleotide-resolution 5’-end mapping and enhanced specificity through both streptavidin
enrichment and selective PCR amplification of properly adapter-ligated, decapped NAD-RNAs.

Profiling the NAD-capped transcriptome in E. coli by pNAD-seq
We validated pNAD-seq using stationary-phase E. coli total RNA spiked with a synthetic NAD-
RNA standard (Supplementary Fig. 4). Three technical replicates demonstrated excellent
reproducibility (Supplementary Fig. 5), with 55.8-fold enrichment of standard in ADPRC+ versus
ADPRC- samples. The intentional depletion of non-NAD-capped RNAs during the ADPRC+
treatment was highly effective, as evidenced by the dramatically higher levels of rRNA and tRNA
retained in the ADPRC- controls (Supplementary Fig. 6). Due to this significant and intentional
difference in library composition, standard differential expression tools like DESeq2 were
unsuitable for our enrichment analysis. Instead, we identified high-confidence NAD-RNAs by
applying stringent thresholds (>20-fold enrichment in Reads Per Million (RPM), p < 0.05, and a
count > 150), yielding a final set of 820 NAD-RNAs (Fig. 2a). The full pNAD‑seq results for all
detected transcripts are provided in Supplementary Data 1, and the curated list of the 820
high‑confidence NAD‑RNAs (with counts, enrichment values, and statistics) is provided in
Supplementary Data 2.

The (+1) A-read ratio (proportion of reads starting with NAD-derived adenosine) served as a
key specificity metric. While background signals from incomplete dephosphorylation or RNA
degradation showed the expected ~25% probability of A-starts (matching random nucleotide
distribution), ADPRC+ samples exhibited strong 5’-A preference (71-100% A-read ratios) (Fig.
2b). High-confidence NAD-RNAs showed exceptional specificity with > 94% (+1) A-read ratios,
demonstrating pNAD-seq’s ability to distinguish true NAD-capped transcripts from background.
pNAD-seq specifically captures 5’-terminal fragments of NAD-capped RNAs through selective
streptavidin enrichment following fragmentation, enabling precise 5’-end mapping as
demonstrated by the synthetic NAD-RNA standard, gcvB, ssrA, and raiA (Fig. 2c–f).
Approximately 50% of the NAD-RNAs originated from canonical transcription start sites (TSSs),
consistent with NAD+ serving as an initiating nucleotide, while the remaining transcripts revealed
unexpected NAD-capping events: one-third of protein-coding NAD-RNAs (e.g., prmB, Fig. 2g)
mapped to intragenic regions, suggesting internal alternative promoters; 118 antisense RNAs (e.g.,
glpF, Fig. 2h) implied NAD-dependent initiation on the opposite strand; and structured ncRNAs,
including tRNA glyW (Fig. 2i) and 16S rRNA rrsA fragments (Fig. 2j), expanded the diversity of
NAD-capped transcripts beyond mRNA and noncoding sRNA. In contrast, 5S rRNA, previously
reported to lack an NAD cap5, showed neither enrichment nor a +1A profile (Fig. 2k), serving as
a negative control.

pNAD-seq significantly outperformed previous methods, identifying 42 of the 47 E. coli NAD-
RNAs reported by NAD captureSeq and all 279 previously detected by NAD tagSeq II (Fig. 2l),
demonstrating superior sensitivity and expanding the known catalog of NAD-capped transcripts.
Beyond increased detection, the method’s precision revealed unexpected complexity in NAD
capping—including widespread intragenic transcription and antisense NAD-RNAs—suggesting
regulatory mechanisms more diverse than previously recognized.

To validate the NAD-RNAs identified by pNAD-seq, we selected 14 candidates for
confirmation: six previously reported NAD-RNAs and eight candidates uniquely detected by our
method (Fig. 2m and Supplementary Fig. 7). Using biotinylated oligonucleotides, we affinity-
purified these transcripts from E. coli total RNA and analyzed their 5’-caps by nuclease P1
digestion followed by LC-MS. All 14 RNAs showed a clear NAD+ peak (m/z = 664.1), confirming
their NAD-capped status. The eight pNAD-seq specific targets included both non-coding RNAs
(glmZ sRNA, tRNAs glyW/metZ/glyU, and tmRNA ssrA) and protein-coding transcripts (spy,
glpF, and phoH) (Fig. 2k). In contrast, no NAD⁺ peak was detected in 5S rRNA, which was also
negative by pNAD-seq. Notably, we detected no NADH (m/z=666.1) in these samples
(Supplementary Fig. 8), suggesting either minimal abundance of NADH-capped RNAs or
technical limitations in their detection.

Classification of NAD-RNAs
Among the 820 NAD-RNAs identified, 35 originated from noncoding genes, including the 16S
rRNA gene (Fig. 2j), 22 sRNAs (Fig. 3a), 11 tRNAs, and one tmRNA. Gene‑body coverage of the
NAD‑sRNA reads showed that they closely matched their annotated sequences (Fig. 3b). Notably,
9 of the 11 NAD‑tRNAs were transcribed from alternative TSSs, suggesting regulatory variants
(Fig. 3c). The remaining 785 NAD-RNAs derived from protein-coding genes were classified into
three subgroups based on TSS position and strand orientation (Fig. 3d, Supplementary Data 3): 5’-
Region (n=401): canonical 5’-UTR sense transcripts; Internal (n=268): intragenic sense transcripts;
Antisense (n=116): antisense-strand transcripts, implicating potential regulatory roles. Gene
Ontology (GO) enrichment analysis of NAD-RNA-producing genes revealed associations with
metabolic regulation, particularly nucleobase-containing compound metabolism, and negative
regulation of macromolecular processes (Fig. 3e).

Identification of promoter elements associated with NAD capping
To elucidate the mechanism of NAD capping, we analyzed the promoter sequences of NAD-RNA
genes using the precise transcription start sites mapped by pNAD-seq. We focused on the top 199
NAD-RNA genes (representing > 76% of total NAD-RNA reads), grouping their promoters as
5’‑region, intragenic, or antisense (Supplementary Data 4). Sequence alignment revealed
significant enrichment of a -10 TATA box and a -35 TT element in both promoter classes (Fig.
3f). Furthermore, we identified a conserved RDAY motif (positions -2 to +2) in a subset of 75
promoters (Fig. 3g). The RDAY motif includes a +1 A, which is necessary for NAD incorporation;
however, +1 A alone is not sufficient; the corresponding sequences are listed in Supplementary
Data 5. Promoters lacking RDAY also show a strong preference for +1 A transcription start sites
(Fig. 3h), and only a subset of +1 A promoters yield NAD-RNAs. Accordingly, RDAY is enriched
among promoters that produce NAD-capped transcripts but is not exclusive to them; it should be
viewed as a predictive feature rather than a unique signature of NAD capping.

To test whether the RDAY motif affects transcriptional output of NAD‑RNA‑producing genes,
we compared total RNA levels between promoters with and without the motif and observed no
significant difference (Fig. 3i). We then assessed NAD incorporation efficiency by comparing the
ADPRC+ / ADPRC- read count ratio for transcripts arising from RDAY versus non RDAY
promoters. Because ADPRC- broadly reflects total transcript abundance while ADPRC+
corresponds to NAD-RNA levels, this ratio serves as a proxy for NAD-capping efficiency. A
statistically significant difference was observed between the two groups (Fig. 3i), suggesting a
potential association between the RDAY motif and higher NAD capping efficiency, which appears
to be independent of transcriptional activity. Together, these results define distinct promoter
features linked to NAD capping: a core architecture, comprising a -10 TATA box, an extended -
10 element, and a +1 A start site, accounts for most NAD-RNAs, whereas the RDAY motif marks
a smaller subset. These conserved sequences could contribute to the recruitment or orientation of
transcription machinery to facilitate co‑transcriptional NAD incorporation.

NAD-linkSeq demonstrates that most of NAD-RNAs are shorter than their regular mRNA
counterparts
The pNAD-seq results indicated that NAD-RNAs are predominantly small (Supplementary Fig.
9). However, because pNAD-seq identifies only the 5’ regions of NAD-RNAs, it cannot resolve
full-length sequences. Our previous method, NAD tagSeq II13, enables direct analysis of full-
length NAD-RNAs by Oxford Nanopore direct RNA sequencing, but the SPR bead–based
purification step removes short RNAs, potentially biasing size representation. To overcome these
limitations, we developed a modified pNAD-seq workflow, termed NAD-linkSeq, for full-length
NAD-RNA sequencing (Fig. 4a).

In NAD-linkSeq, total RNA is spiked with four NAD-RNA standards (see Methods) and left
unfragmented. As in pNAD-seq, NAD-RNAs are biotinylated via SPAAC tagging and enriched.
Following ligation of a 3’ adaptor, full-length RNAs undergo NudC-mediated decapping and are
subsequently ligated to an extended 5’ adaptor. The resulting RNAs are then reverse transcribed
to generate full-length cDNAs, which are directly sequenced. Because Nanopore DNA (cDNA)
sequencing more efficiently captures shorter fragments than direct RNA sequencing, cDNAs are
analyzed using Oxford Nanopore direct cDNA sequencing. Following adaptor trimming, clean
cDNA reads with A as the first nucleotide were mapped to the E. coli reference genome.
This analysis showed that NAD-RNAs originating from non-coding genes generally matched
the annotated full transcript lengths (Fig. 3b), whereas NAD-RNAs derived from protein-coding
genes typically ranged from 50 to 450 nt, with an average length of ~ 200 nt; the four internal
standards were recovered at their expected sizes (Fig. 4b, Supplementary Data 6). These findings
are consistent with previous reports that, even in the absence of RNA fragmentation, specific 5’
terminal fragments, rather than full length mRNAs, are preferentially enriched in E. coli NAD
RNAs5. Comparing gene-body coverage for NAD-RNAs (NAD-linkSeq) with their mRNA
counterparts (RNA-seq) further revealed that NAD-RNAs predominantly occupy the 5’ regions of
protein-coding loci (Fig. 4c), as exemplified by read mapping to trmJ (Fig. 4d).

To validate the observed size differences between NAD‑RNAs and their cognate mRNAs, total
RNA was subjected to SPAAC‑mediated biotinylation and streptavidin pull‑down to enrich
NAD‑RNAs. The enriched fraction and the input RNA were then analyzed by Northern blot using
a trmJ‑specific probe. The trmJ NAD‑RNA size determined by Northern blot (Fig. 4e) matched
the NAD‑linkSeq result. Notably, gene‑coverage analysis identified 40 cases in which NAD‑RNAs
correspond to full‑length mRNAs (Fig. 4g). Among these, NAD‑acpP was previously reported by
NAD tagSeq II13; consistent with that, Northern analysis confirmed that NAD‑acpP and acpP
mRNA are similar in size (Fig. 4h). A complete list of these NAD‑RNAs is provided in
Supplementary Data 7.

Dynamic remodeling of the NAD-RNA landscape in response to metabolic stress
We investigated the dynamic remodeling of the NAD-RNA landscape in response to nitrogen
deficiency by comparing E. coli cells grown in nitrogen-reduced M9 medium versus standard M9
conditions. Using pNAD-seq with spike-in NAD-RNA standards for normalization, we identified
811 NAD-RNAs, including 178 that showed significant expression changes (160 upregulated and
18 downregulated, p < 0.05) under nitrogen limitation (Fig. 5a; dataset in Supplementary Data 8).
To validate these findings, we developed a NAD-PEGylation method using ADPRC and SPAAC
to selectively label NAD-RNAs with a 10 kDa PEG tag, enabling their separation from regular
transcripts by gel electrophoresis (Fig. 5b). Northern blot analysis of PEGylated RNAs confirmed
the pNAD-seq results, showing increased NAD-gcvB and decreased NAD-gadY levels under
nitrogen stress (Fig. 5c-d; see Supplementary Fig. 10 for lower-contrast versions of the blots). We
then asked whether the observed shifts in NAD‑RNA levels could be attributed primarily to
transcriptional changes. To address this, we performed RNA‑seq to assess the differential
expression of total RNA between the two growth conditions (Supplementary Data 9). Comparison
of log₂ fold changes for NAD‑RNA and total RNA under the two conditions revealed a positive
overall correlation (R² = 0.35; Fig. 5e), suggesting that changes in NAD‑RNA abundance often
parallel changes in transcript levels. However, a notable subset of genes departed from this trend,
displaying marked changes in NAD‑RNA with little shift in total RNA, or vice versa. This pattern
implies that, alongside transcriptional co‑variation, NAD‑capping efficiency may be subject to
additional gene‑specific modulation.

Conventional RNA-seq analysis indicated a metabolic shift under nitrogen stress, with
upregulation of nitrogen scavenging genes and downregulation of core energy metabolism genes
(Supplementary Fig. 11). In contrast, Gene Ontology (GO) enrichment analysis of genes with
upregulated NAD-RNAs showed significant enrichment for transcriptional regulatory processes,
including RNA biosynthetic process and regulation of DNA-templated transcription
(Supplementary Fig. 12). The distinct functional categories associated with total mRNA changes
versus NAD-RNA changes suggest these RNA populations may participate in different aspects of
the nitrogen stress response.

Beyond expression-level changes, we identified significant condition-dependent alterations in
transcriptional initiation patterns. Under nutrient stress conditions, several genes exhibited striking
shifts in their transcription start site (TSS) selection. Notably, mqsR and sibD transitioned from
utilizing their annotated TSSs in nutrient-rich LB medium to preferentially initiating at
downstream TSSs in minimal media. This redistribution was particularly pronounced for sibD,
which showed 46% downstream TSS usage in standard M9 medium, increasing to near-exclusive
downstream initiation under nitrogen-limited conditions (Fig. 5f-i). A parallel phenomenon
occurred with promoter selection, as demonstrated by ftnB’s switch from its annotated LB-medium
promoter to a downstream promoter in minimal media conditions (Fig. 5j).

Methods
E. coli strain, culture conditions and RNA extraction
E. coli K-12 strain MG1655 was grown aerobically at 37°C in Luria-Bertani (LB) broth. Overnight
cultures were diluted 1:100 into fresh medium and grown until stationary phase (OD = 2.4). For
nitrogen reduction experiments, cells were initially grown in M9 minimal medium at 37°C to mid-
log phase (OD = 0.5), harvested by centrifugation (2,500 ×g), and resuspended in either:
standard M9 medium (18.7 mM NH Cl), or nitrogen-reduced M9 medium (5.6 mM NH Cl).
4 4
Resuspended cultures were incubated for 3.5 h in their respective media before harvesting. Total
RNA was extracted using the hot phenol method13.

In vitro Transcription
A double-stranded DNA template was generated by annealing oligonucleotides φ2.5-24mer_F and
φ2.5-24mer_R (Supplementary Data 10). Transcription reactions contained 40 mM Tris-Cl (pH
8.1), 1 mM spermidine, 22 mM MgCl₂, 0.01% Triton X-100, 5 mM DTT, 5% DMSO, 1 mM each
of GTP, CTP and UTP, plus 4 mM of either NAD (for NAD-RNA), AMP (for 5’-pA-RNA), ADP
(for 5’-ppA-RNA), ATP (for 5’ pppA-RNA), Ap3A (for 5’-ApppA-RNA), Ap4A (for 5’-Ap4A-
RNA), dpCoA (for 5’-dpCoA-RNA), or NADH (for 5’-NADH-RNA), along with 0.1 μM DNA
template and 5.2 U/μL T7 RNA polymerase. To generate longer NAD-RNA standards, we
performed in vitro transcription reactions using 2 μg of double-stranded DNA template
(Supplementary Table 1) for two NAD-RNA spike-in controls (Standard 1 and Standard 2) and a
90-nt NAD-RNA for PEGylation analysis (Standard 3). All transcription reactions were conducted
under identical buffer conditions in the presence of 4 mM NAD. All reactions were incubated at
37°C for 4 h, treated with 50 U of DNase I (Takara, 2270B) at 37°C for 20 min, and products were
resolved on 8-10% polyacrylamide/8 M urea gels (1× TBE, 40 mA). RNA bands were excised and
eluted in 0.3 M NaOAc (pH 5.5), followed by ethanol precipitation. To generate 5’-OH-A-RNA,
5’-pA-RNA was treated with 0.1 U/μL calf intestinal alkaline phosphatase (Invitrogen, 18009019)
in 1× CutSmart buffer for 20 min, then purified by acid phenol/chloroform extraction and ethanol
precipitation, with concentrations measured using a Qubit fluorometer (Thermo Scientific).

SPAAC biotinylation
Each 25-mer RNA oligonucleotide (30 pmol) with a distinct 5’ end was incubated in a 50 μL
reaction containing 50 mM Na-HEPES (pH 7.0), 5 mM MgCl₂, 4.25 μM ADPRC (Sigma, A9106),
and 5 μL of 3-azido-1-propanol (Sigma, 776130) at 37°C for 30 min. Enzyme-free reactions were
included as negative controls. Following incubation, all RNA samples were purified by acid
phenol/chloroform extraction and ethanol precipitation. The purified RNAs were then resuspended
in 10 μL of PBS (pH 7.4) containing 1 mM biotin-PEG4-DBCO (BroadPharm, BP-22295) and
incubated at 37°C for 1 h to facilitate biotinylation. Reactions were halted by adding 10 μL of
RNA loading dye (Thermo Scientific, R0641). The samples were resolved on a 12% TBE-urea
polyacrylamide gel (containing 8 M urea), and the biotinylated RNA bands were excised and
eluted in 0.3 M NaOAc (pH 5.5), followed by ethanol precipitation.

One-step biotinylation
NAD-24mer RNA (30 pmol) was biotinylated by incubating with 100 mM HEEB (Amatek, B-
1328) and 4.25 μM ADPRC (Sigma) in 100 μL of 50 mM Na-HEPES (pH 7.0), 5 mM MgCl₂ at
37°C for 30 min, with parallel enzyme-free reactions serving as negative controls. Reactions were
terminated and purified by acid phenol/chloroform extraction, followed by ethanol precipitation.

Recombinant NudC purification
The E. coli nudC gene was amplified by PCR from K12 MG1655 genomic DNA using primers
NudC_BamHI and NudC_SalI (Supplementary Data 10). The resulting PCR product was digested
with BamHI and SalI and cloned into the pET28a vector (Novagen, 69864). The constructed
plasmid, pET28a-NudC, was transformed into E. coli Rosetta (DE3) cells (Novagen, 70954) for
protein expression. Expression of NudC was induced by adding 0.3 mM IPTG when the culture
reached an OD₆₀₀ of ~0.6, followed by incubation at 16°C for 12 h. Cells were harvested by
centrifugation and lysed via sonication in Lysis Buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl,
10 mM imidazole). The lysate was clarified by centrifugation at 12,500 g for 20 min at 4°C. The
supernatant was applied to Ni-NTA resin (Thermo Scientific, 88222) and washed with Wash
Buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, 50 mM imidazole). The His-tagged NudC protein
was eluted with Elution Buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, 250 mM imidazole).
The eluted protein was buffer-exchanged into 50 mM Tris-HCl (pH 8.0) using a 10-kDa centrifugal
filter (Millipore, UFC501008) and further purified by FPLCS (Bio-Rad, 7880003) on a MonoQ
column (Cytiva, 29275878) with a linear 0 to 1 M NaCl gradient. Fractions containing pure NudC,
as confirmed by SDS-PAGE, were pooled, concentrated, and buffer-exchanged into Storage
Buffer (25 mM Tris-HCl, pH 8.0, 50 mM NaCl, 1 mM MgCl₂, 1 mM DTT, 50% glycerol) using a
10-kDa centrifugal filter. The final protein concentration was determined using a Qubit
fluorometer (Thermo Scientific, Q33216).

NudC decapping assay
To assess the impact of 5’-end secondary structure on decapping, biotinylated NAD-24mer RNA
was annealed to complementary oligonucleotides (Supplementary Data 10) to generate substrates
with extended, blunt, or recessed ends. For the decapping assay, 30 pmol of either the linear RNA
substrate or the structured substrates were incubated in a 10 µL reaction buffer containing 10 mM
Tris-HCl (pH 8.0), 100 mM KCl, 2 mM MgCl₂, 1 mM MnCl₂, and 2 mM DTT, along with specified
concentrations of NudC (typically 0.58 µM, unless otherwise indicated for titration) at 37°C for
10 min. Reactions were terminated by adding 10 µL of 2× RNA loading dye (Thermo Scientific;
R0641), followed by denaturation, separation on a 12% denaturing urea-polyacrylamide gel, and
visualization with RedSafe (INTRON, 21141) staining.

pNAD-seq library preparation
A 600 μg aliquot of RNA was spiked with either 5 ng of standard 1 RNA (for normal conditions)
or 6 ng of standard 1 plus 3 ng of standard 2 RNA (for nitrogen reduction experiments). RNA
fragmentation was performed in 600 μL of 10 mM Tris-HCl (pH 7.4) and 10 mM ZnCl₂ at 75°C
for 2.5 min, immediately quenched with 20 μL of 0.5 M EDTA (pH 8.0), and purified by acid
phenol:chloroform:isoamyl alcohol (PCI, Invitrogen) extraction followed by ethanol precipitation.
Dephosphorylation was carried out with 25 U of calf intestinal alkaline phosphatase (NEB, M0290)
in 1× CutSmart Buffer (NEB, B6004) at 37°C for 20 min, followed by purification as above. For
NAD-RNA capture, the sample was divided into two equal halves. One half was incubated in a
150 μL reaction containing 50 mM Na-HEPES (pH 7.0), 5 mM MgCl₂, 8.5 μM ADPRC, and 15
μL of (Sigma, 776130) at 37°C for 30 min. The other half underwent the same treatment but
without ADPRC, serving as a negative control. Both RNA samples were then purified by
phenol/chloroform extraction and ethanol precipitation. The resulting RNA pellets were
resuspended in 30 μL of 1 mM biotin-PEG4-DBCO (BroadPharm, BP-22295) in 1× PBS (pH 7.4)
and incubated at 37°C for 1 h. Streptavidin capture was performed by incubating the RNA in 200
μL of binding buffer (50 mM Tris-Cl, pH 7.5, 500 mM NaCl, 5 mM EDTA) with 600 μg of MyOne
T1 beads (Thermo Scientifc, 65601) at 37°C for 20 min. Beads were subsequently washed twice
with 200 μL of nuclease-free water and once with 200 μL of T4 RNA ligation buffer (50 mM Tris-
HCl, pH 7.5, 10 mM MgCl₂, 1 mM DTT). 3’-adapter ligation was performed in a 30 μL reaction
containing T4 RNA ligation buffer, 5 μM pre-adenylated adapter (Supplementary Data 10), 20%
PEG 8000, 30 U of murine RNase inhibitor (NEB, M0314S), and 30 U of T4 Rnl2tr K227Q (NEB,
M0351L) at 25°C for 4 h. Ligation products were then washed six times with 200 μL of 50 mM
Tris-Cl (pH 7.5), 8 M urea, 0.5% SDS, and 10 mM EDTA. Beads-bound RNA was eluted by
incubation in 80 μL of 50 mM Tris-Cl (pH 7.5), 95% formamide, 10 mM EDTA, and 2 mM biotin
at 65°C for 2.5 min. The supernatant was collected and combined with 320 μL of 0.3 M sodium
acetate (pH 5.5) and 50 μg of linear acrylamide (Thermo Scientific, AM9520), and the RNA was
ethanol-precipitated. To remove the biotin-labeled NAD cap, the RNA was incubated in a 40 μL
reaction containing 10 mM Tris-HCl (pH 8.0), 100 mM KCl, 2 mM MgCl₂, 1 mM MnCl₂, 2 mM
DTT, and 0.58 μM NudC at 37°C for 20 min. The decapped RNA was purified using a RNA Clean
& Concentrator kit (Zymo, R1016) and eluted in 11 μL of nuclease-free water. 5’-adapter ligation
was performed in a 30 μL reaction containing 1× T4 RNA ligase reaction buffer (NEB, B0216L),
the purified RNA, 3.3 μM 5’-adapter (Supplementary Data 10), 15% PEG 8000, 1 mM ATP, 30
U of murine RNase inhibitor, and 30 U of T4 RNA ligase 1 (NEB, M0204S) at 25°C for 3 h. The
ligation product was combined with 10 pmol of RT primer (Supplementary Data 10), heated to
70°C for 5 min, and immediately chilled on ice. Reverse transcription was performed in a 40 μL
reaction containing the primed RNA, 1× Maxima RT Buffer, 1 mM dNTPs, 40 U of murine RNase
inhibitor (NEB; M0314L), and 200 U of Maxima Reverse Transcriptase (Thermo Scientific,
EP0742) at 50°C for 30 min. The resulting cDNA was amplified by PCR for 12–13 cycles using
Q5 High-Fidelity DNA Polymerase (NEB; M0491L) and primers listed in Supplementary Data 10,
followed by a 5-cycle indexing PCR. The final library was purified with AMPure XP beads
(Beckman, A63880) at a 1.2:1 bead-to-sample ratio, and its quality was assessed on an Agilent
2100 Bioanalyzer. Sequencing was performed on an Illumina HiSeq 2000 platform (Novogene)
for 150 bp paired-end reads.

qPCR analysis
Relative transcript levels of selected tRNAs and rRNAs were measured by qPCR in pNAD-seq
libraries prepared with or without ADPRC treatment. Reactions were performed using SupRealQ
Ultra Hunter SYBR qPCR Master Mix (Vazyme, Q713-02) on a StepOne Plus RT-PCR system
(Applied Biosystems). Transcript levels were normalized to a synthetic NAD-RNA spike-in
control for each RNA species. Primer sequences are listed in Supplementary Data 10.

RNA-Seq and data analysis
For RNA sequencing, rRNA depletion was performed using the Ribo-Zero Plus rRNA Depletion
Kit for bacteria (Illumina, ILL20037135EA). Library preparation was then carried out using the
Next Ultra Directional RNA Library Prep Kit for Illumina (NEB, E7420). The prepared samples
were sequenced on an Illumina HiSeq 2000 platform, generating 150 bp paired-end reads
(Novogene). The raw reads were trimmed using fastp v0.22.031. The cleaned reads were then
aligned to the E. coli str. K-12 substr. MG1655 genome (ASM584v2) using HISAT232. Expression
levels of genes were calculated using featureCounts v2.0.133. Finally, differential gene expression
analysis was conducted on the count data using DESeq234. A Benjamini–Hochberg-adjusted p-
value of less than 0.05 was considered statistically significant. Data were visualized in GraphPad
Prism 10.

NAD-linkSeq library preparation
A 400 μg aliquot of total RNA from stationary phase E. coli was spiked with four NAD- RNA
standards: 150 pg of 50 nt, 420 pg of 150 nt, 800 pg of 277 nt, and 200 pg of 700 nt transcripts
(Supplementary Table 2). The mixture was incubated for 30 min at 37°C with 8.5 μM ADPRC
and 15 μL 3 azido 1 propanol in a 150 μL reaction containing 50 mM Na HEPES (pH 7.0) and 5
mM MgCl . RNA was purified by acid phenol–chloroform extraction followed by ethanol
2
precipitation. For biotinylation, the RNA was resuspended in 40 μL PBS (pH 7.4) with 1 mM
biotin‑PEG4‑DBCO (BroadPharm, BP-22295) and incubated at 37°C for 1 h, then
ethanol‑precipitated to remove excess reagent. Subsequent steps, from streptavidin bead capture
through reverse transcription, followed the pNAD-seq protocol, with the modification of using a
longer 5’ adapter and the linkSeq RT primer (Supplementary Data 10). After reverse transcription,
RNA templates were digested with 1 μL RNase A/T1 mix (Thermo Scientific, EN0551) at 37°C
for 10 min, and cDNA was purified using AMPure XP beads. The second cDNA strand was
synthesized with Q5 DNA polymerase after annealing 1 pmol linkSeq FP (Supplementary Data
10). Finally, the resulting double‑stranded cDNA was purified using AMPure XP beads (Beckman,
A63880).

Nanopore sequencing and data analysis
DNA library was prepared using Ligation sequencing DNA VS14 kit (ONT, SQK-LSK114) and
loaded on a flowcell (ONT, R10.1 version) and sequencing was run on a GridIon sequencer (ONT).
The adaptor sequences, 5’-CAGAGTTCTACAGTCCGACGATC-3’ present at 5’-end and 5’-
GATCGGAAGAGCACACGTCTG-3’ present at 3’-end of each read, were trimmed using
Cutadapt35. Sequencing reads were aligned to the reference using the minimap2 36. Length
distribution was analyzed using Samtools37. Candidate sequences were visualized in the Integrated
Genome Viewer38.

RNA pulldown and LC-MS/MS
RNA pulldown was performed by hybridizing 100 pmol biotin-DNA probe (Supplementary Data
10) with 1 mg total RNA in 400 μL solution (50 mM Tris pH 7.5, 500 mM LiCl, and 5 mM EDTA)
at 80°C for 5 min and slowly cooled to 25°C, followed by capture with 500 μg MyOne Streptavidin
T1 beads (Thermo Scientific, 65601) at 37°C for 20 min. After washing with 50 mM Tris (pH 7.5),
500 mM LiCl, 5 mM EDTA, and 0.05% Tween, elution was performed by incubating the beads-
bound RNA in 80 μL elution buffer (10 mM Tris-Cl pH 7.5, 95% formamide, 5 mM EDTA, and
2 mM biotin) at 65°C for 2.5 min, then ethanol-precipitated after mixing the supernatant with 320
μL of 0.3 M sodium acetate (pH 5.5) containing 30 μg linear acrylamide. The RNA was digested
with 50 U of nuclease P1 (NEB, M0660S) in 1× nuclease P1 buffer at 37°C for 1 h and analyzed
by LC-MS/MS using a TSQ Altis mass spectrometer (negative ion mode) with an ACQUITY
UPLC HSS T3 column (2.1 × 100 mm, 1.8 μm) at 0.1 mL/min flow rate. Separation was performed
at a flow rate of 0.1 mL/min with mobile phase A (0.3% formic acid) and B (80% acetonitrile)
using the following gradient: 18-21% B (0-2 min), 21-40% B (2-4 min), 40-60% B (4-14 min),
and 100% B (14-18 min), while monitoring m/z 428.001. The column was re-equilibrated by
returning to 18% B for 2 min between injections.

NAD PEGylation
Standard 90-nt NAD-RNA (200 ng) or E. coli total RNA (200 μg) was PEGylated by incubation
with 8.5 μM ADPRC and 15 μL of 3-azido-1-propanol (Sigma, 776130) in 150 μL reaction
containing 50 mM Na-HEPES, pH 7.0, 5 mM MgCl₂ at 37°C for 30 min, followed by
phenol/chloroform extraction and ethanol precipitation. The RNA was then reacted with 1 mM
DBCO-mPEG (10kDa) (BroadPharm, BP-22462) in 40 μL 1xPBS (pH 7.4) at 37°C for 1 h,
ethanol-precipitated, and analyzed by urea-PAGE or Northern blot.

Digoxigenin-labeled RNA probes
DNA template was generated by PCR amplification with primers (Supplementary Data 10) using
E. coli K-12 genomic DNA as template. Transcription mixture containing 2 μg DNA template in
40 μL transcription solution containing 40 mM Tris -Cl, pH 8.1, 1 mM spermidine, 22 mM MgCl ,
2
0.01% Triton-X-100, 5 mM DTT, 5% DMSO, and 2.5 mM of each of NTP and 0.1 mM
digoxigenin-11-UTP (Roche, 11209256910), along with 208 U T7 RNA polymerase was
incubated at 37 °C for 3 h. To the reaction 10 U DNase I (Takara, 2270B) was added to digest
DNA template by incubation at 37 °C for 30 min. Transcription products were resolved on 8%
polyacrylamide/8M urea gel. RNA probes were extracted from the gel for immediate use in
Northern blot.

Northern blot
20 μg aliquot of total RNA from the PEGylation step was denatured by incubation at 95°C for 2
min in 1× RNA gel loading dye. The RNA was then separated on a 6.5% polyacrylamide/8 M urea
gel in 1× TBE buffer at a constant current of 40 mA. Following electrophoresis, the RNA was
transferred onto a Hybond-N+ membrane (Cytiva, RPN303B) by electroblotting in 0.5× TBE
buffer at 250 mA for 30 min. The membrane was cross-linked using UV light at 120 mJ/cm². For
hybridization, the membrane was first prehybridized in DIG Easy Hyb solution (Roche,
11603558001) for 1 h. A digoxigenin-labeled RNA probe was then added, and hybridization was
carried out overnight at 62°C. The membrane was washed twice for 15 min each at 62°C, first with
2× SSC containing 0.1% SDS, followed by 0.5× SSC containing 0.1% SDS. The membrane was
subsequently washed for 5 min in maleic acid wash buffer (0.1 M maleic acid, 0.15 M NaCl, 0.3%
Tween-20, pH 7.5) and blocked with blocking solution (Roche, 11585762001) for 30 min. It was
then incubated with anti-digoxigenin-AP antibody (Roche,11093274910) diluted to 75 mU/mL in
blocking solution for 45 min. After incubation, the membrane was washed three times for 15 min
each in maleic acid wash buffer and equilibrated in detection buffer (0.1 M Tris, 0.1 M NaCl, pH
9.5). Signals were detected using the chemiluminescent substrate CSPD (Thermo Scientific,
T2142) and visualized on a ChemiDoc XRS+ system (Bio-Rad). Uncropped and unprocessed
scans of the most important blots are provided in the Source Data file.

Statistics and reproducibility
Statistical analyses and data visualization were performed using GraphPad Prism 10. Significance
thresholds were set at as a p-value of < 0.05 as [*] or < 0.01 as [**] as indicated in the respective
figure legends. All experiments were performed at least two times.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Zhang et al. report on RNA sequencing approaches to better map the 5’ ends of NAD-capped transcripts in E. coli (precision NAD-RNA seq = pRNA-seq for short transcrips and NAD-linkSeq for longer transcripts). Thus, this study adds to the list of transcripts reported to contain an NAD-cap. The authors compare the promoter sequences for transcripts with an NAD-cap and also report that the spectrum of NAD-capped transcripts is different without and with nitrogen limitation.\nI appreciate that this manuscript was very carefully prepared with appropriate controls and clear description and presentation of the data. However, a major limitation of this and other studies of NAD-capped transcripts is that there is no evidence of a physiological role. While the authors speculate “roles of NAD capping in gene regulation” (in abstract) and “roles in stress adaptation” (in discussion), there is no evidence of this. The authors should carry out additional experiments to test these hypotheses (for example what is the role of the truncated trmJ transcript) or dramatically “tone down” the speculation, especially since the fraction of capped transcript may be low as seen in Figure 5c and 5d).", "reviewer_2": "Zhang et al describe in this paper two novel methods for capturing and sequencing NAD-capped RNAs, combined with novel insight into transcription mechanims and RNA biochemistry in E. coli. The first developed sequencing method, Illumina-based pNAD-seq, achieves very accurate single-nucleotide resolution of the 5'-ends of NAD-RNAs. While the novelty of the method is limited (SPAAC tagging has already been described by the same authors, and NudC release + ligation was already implemented in the OneSeq protocol), the combination offers some interesting features and ultimately allows identifying most of the previously known RNA species, plus many new ones. It also allows identifying very interesting features regarding promoter architecture and the crosstalk with metabolism. I think that this is high-quality work, and I have only a few minor requests (see below).\nUnfortunately, the second method (NAD-linkSeq) produces results that are irreconcilable with published literature, including data from these authors' lab. In Fig. 6b-d the authors describe that for all (!) 882 genes identified as NAD-capped are much shorter (~130 nt, with 5 outliers at around 250 nt) than the non-NAD-RNAs (most around 800 - 1000 nt). This is essentially the opposite of what the same authors claim in in Figure 6 of their earlier NAD TagSeq II paper (ref. 13) and the associated text, namely that \"NAD-mRNAs and their non–NAD-mRNA counterparts generally contain similar overall sequence regions\". The only logical explanation I can come up with is that the bead-based purification procedure used in NAD-linkSeq afforded an unintended size selection that eliminated full-length mRNA sequences, and the PCR then amplified the fragments in the selection window. Furthermore, in terms of methodology, I think that NAD-linkSeq (indirect DNA sequencing) is a step back from NAD tagSeq II (direct RNA sequencing) and has many more biases and pitfalls. As Oxford Nanopore sequencing is a single-molecule method, I do not see the value of PCR amplifications.\nMinor issues:\n- in general, the non-specifically enriched transcripts in the ADPRC(–) group were sequenced at substantially lower levels compared to those in the ADPRC(+) group. Therefore, it is essential that the authors clarify the definition of “Counts” in Figure 2c–h—specifically, whether these refer to raw counts—and specify the normalization method used (e.g., TPM, RPM, etc.) prior to making such comparisons.\n- Additionally, when applying DESeq2 for differential enrichment analysis, highly expressed genes such as rRNAs and tRNAs could disproportionately influence the total read counts, potentially biasing the estimation of median-ratio size factors. The authors are encouraged to perform qRT-PCR validation of these high-count species using their spike-in controls (NAD-capped and non–NAD-capped RNAs) for reference.\n- To further support the authors’ conclusions regarding the high-quality 5′-A feature, it would also be valuable to profile the read mapping of the spike-in controls (NAD-capped and non–NAD-capped RNAs) using their current approach.\n- At many instances, the Materials and Methods section lacks detail essential to repeat these experiments, such as exact buffer or eluent compositions, exact number and volume of washes (e.g.: line 591: what is \"formamide-based buffer\", what volume, any whashes?.", "reviewer_3": "Comments for Zhang et al.:\nIn their manuscript entitled ‘High-resolution mapping of NAD-capped RNAs unveils novel features of bacterial NAD-RNA and stress-responsive transcription initiation’ the authors describe a new method for the identification and precise 5’-mapping of NAD-capped RNAs.\nHere, building on previous approaches from their own and other labs, they cleverly combine ADPRC-catalyzed conversion of NAD to an azide-handle, which is reacted with a strained alkyne in a strain-promoted click reaction, to attach biotin for purification on streptavidin. Following 3’-adapter ligation, they then decap the purified RNA using the NAD-RNA decapping enzyme NudC, generating a 5’-monophosphate to enable ligation of an adapter. They then continue library preparation to either subject libraries where RNA was sheared at the beginning of the protocol to short read deep sequencing, or libraries made from intact full-length RNA to long-read nanopore sequencing, thereby achieving precise mapping of 5’-ends, as well as (from long-read sequencing) information on the length of the NAD-capped RNAs.\nApplying this new methodology to E. coli, they identify hundreds of additional NAD-capped RNAs, of which they confirm 9 to indeed carry the NAD-cap using LC-MS/MS. Newly identified (and validated) NAD-capped RNAs include a specific 16S fragment, as well as specific tRNAs, including tmRNA. Applying the methodology to different growth conditions, the authors show that the abundance of many NAD-capped RNAs changes upon nitrogen starvation. They further identify shifts of initiation sites under these conditions, shifting to initiation at A, which enables NAD-capping. They also identify common features of transcription promotors from their hundreds of NAD-capped RNAs and argue that this common feature demonstrates capping to happen during initiation.\nOverall an interesting methodology, by combining known methods, with superior powers, which might be suitable for publication in Nature Communications - also because it could be adapted not only for bacteria but beyond. Also, some interesting biological findings, however, with some weaknesses, which should be amended prior to publication. I will discuss general strengths and weaknesses below:\nThe authors convincingly demonstrate the quality of their new approach, showing strong enrichment of NAD-capped RNA, also using a spike-in control.\nUsing LC-MS/MS, they provide further evidence of NAD-capping for a small subset of newly identified RNAs, importantly including the new classes of capped RNAs, (16S fragment, tRNAs, tmRNA). A weakness I found here was the general lack of y-axis labels (both, what is shown and what is the scaling is lacking) in the LC-MS/MS data (as well as other data), making it impossible to fairly assess the meaning and quality of the data. I assume equal scaling was used, but this is unclear from the figures themselves. If different scales were used, how was this chosen, e.g., for the negative control?\nConcerning potential roles of NAD-RNA, the authors infer functionality, e.g., in regulation, from the types of RNAs that are capped, and from changes in NAD-capped RNA levels upon nitrogen starvation, from their finding that some RNAs are more changed than others, and from switching of initiation sites. However, at this point, I find it hard to assess whether this functionality indeed exists, or whether these chances are coincidental. Also, from what I understood, it is possible that the NAD-capped RNAs change in abundance due to overall changes in abundance of the specific mRNA (capped and uncapped). I could not identify any data on how specific these changes are. To show that NAD-capping increases (beyond the examples where TSS-switching was shown), changes in NAD-capped RNA abundance should be normalized to overall changes in abundance. Otherwise, to show whether RNAs that are target of NAD-capping change more in abundance than RNAs that are never capped, changes in the abundance of NAD-capped RNAs could be compared to changes in the abundance of non-capped RNA (e.g., in total RNA samples), to find whether they are, e.g., more dynamic.\nI am also hesitant about the promoter sequence motifs identified, as at least some positions do not seem to show any strong signature, although one is claimed (e.g., K (C or G) is claimed at some positions, although C+G seems to be as abundant as A+T. Here, I think the analysis should be deepened. As one example, the authors could separate the data into sequences that follow the suggested pattern exactly, (e.g., sequences that exactly contain KYTKK and RDAY) and anayze patterns in the remaining sequences. Do those sequences contain just small deviations from those patterns, or are they entirely different? I think this is particularly important as the authors claim that the existence of a conserved promoter pattern excludes the possibility of post-transcriptional capping. However, since the conservation does not seem that high, this is questionable.\nThe authors also make additional claims of functionality which are not based on direct evidence. I think the authors should make it clearer where these claims are speculative, or should test some of them experimentally.\nOverall, for a methods-oriented manuscript, I believe the amount of evidence for functional importance will be sufficient if the issues mentioned above and below are addressed.\nSpecific remarks in order of appearance in the manuscript:\nl. 67: ADP-ribose cyclase should be ADP-ribosyl cyclase\nl.83: reference missing for NADcapPro at least in this line.\nl.102: actually the original NAD captureSeq if anything had a bias against long sequences, due to the absence of a shearing step\nl.140: use slower-running or similar instead of the term retarded\nl.144: it is unclear why this optimization had to be done. How much does the current approach differ from their previous method? Please discuss\nl.151: 50.4% - excessive number of digits for a gel quantification. 50% would be enough.\nl.161: suggesting that SPAAC-tagging selectively enriches NAD-RNAs (…) This makes it sound as if the SPAAC step brings the specificity. However, the specificity really should come from the ADPRC.\nl. 173-177: very similar results were already shown by Höfer et al (ref. 28). Please discuss that similarity, as now it sounds like this is entirely new.\nFig. 1 panel h: the extrapolation for the lower curves does not seem valid. 1. The extrapolation goes beyond 100%, 2. Too few data points. Higher quantities of enzyme should have been used or the extrapolation should not be done, especially considering the high error bars of the existing data points. If anything maybe do an extrapolation with confidence intervals?\nFig. 2, panel k: y-axis labels are missing (what and scale). Also, it would be good to show the negative control in the main figure for comparison. It does exist in the supplementary. Caption for panel k: l.281: RNA should be changed into RNAs.\nl.300-301 – the assumption of a broad involvement of NAD-RNAs in transcription and metabolic fine-tuning is too weak. There is no direct evidence of this. (as discussed above)\nFig. 3 e-f: Sequence Logo analysis not very convincing. Explanation of R is missing in the caption. The KYTKK ‘enrichment’ looks very small, in some cases even G+C seems to be less abundant than A+T especially in panel e, first and second K. Also, why is GT labelled in e, and GG in f. In total, there might be a motif GGT, but the sequences look near-identical in e and f.\nl. 361/362. The fact that NAD-capped mRNAs are shorter than their full-length mRNA counterparts was already demonstrated in the original NAD-captureSeq paper (for some mRNAs), both by the sequencing and by additional qPCR analyses targeting the 5’-ends and the middle of affected mRNAs, which should be cited here. Still, it is nice to show this transcriptome-wide.\nFig. 4 c: y-axis label missing\nFig. 5 b, c, d: please show less contrasted versions of this as well (in Supplementary?)\nFig. 5 g, i: y-axis labels missing. Also, the way the promotor As are shown could be better. It might be good to show the respective sequence and highlight the 2 promotor nucleotides, or it would be equally good to show a zoomed-in version of the respective region of the initiation, together with the sequence (in the direction of the gene).\nFig. 5 e,f, I think boxplots would be more instructive here. Now, we see assessments filtered by arbitrary thresholds. With boxplots, we could see a general trend. E.g., show 2 boxes for downregulated and upregulated NAD-RNA and show data points for RNA levels. Or separate the data into quantiles by log2FC in NAD-RNA levels, and then plot the data for total RNA Log2FC.\nAlso, it would be helpful to report the data in a normalized way (Log2FC in NAD-RNA normalized to Log2FC in total RNA)\nl. 445-446: Regulatory mechanisms are very hypothetical. It is not clear from which data exactly, an environmentally responsive mechanism can be deduced.\nl. 465 ‘critical RDAY motif’. To me, this does not look 100% conserved in the figure, so that I have doubts whether this is indeed critical.\nl. 500-502: a parallel is drawn to the RNAylation by T4phage. I do not quite see the analogy. This is very hypothetical.\nIn general, most of the discussion is still very hypothetical.\nMethods:\nl. 518. At which OD or at what point are the cells harvested? Are we looking at stationary phase cells or at exponential phase? This seems to only be stated for the nutrient deprivation experiment.\nl. 631/l.352. 18 cycles of PCR does not seem very little (it was stated earlier in the manuscript at l.352 that few cycles are needed). Why were 18 cycles used for NAD-linkSeq nanopore sequencing, but only 12-13 for pNAD-seq? This could still create size biases to lower sizes, despite the use of nanopore sequencing. Please discuss, or try again once with lower cycle number (maybe using more input material?)\nSupplementary: Fig. S1: It is not mentioned what is shown exactly: Urea-PAGE? Was it stained or was some label used?\nSame for Fig. S2\nFig. S3: y-axis labels missing\nFig. S4. Was this stained?\nFig. S5: the light blue is difficult to read. Maybe better on a dark background (for the light shade). Or no color code necessary, as we have the numbers.\nAlso, unclear what exactly is shown? Pearson correlation for data points (gene abundance in dataset?)\nFig. S6: y axis label and scale missing. Since there is a tiny signal in the 5S rRNA control, if the scale is not equal, we cannot assess if this is indeed negative, or if there is a relevant signal, which was put on a different scale.\nFig. S7: y-axis label and scale missing.\nFig. S8: are these genes really differentially expressed (on total RNA level?)? Or differentially abundant in pNAD seq?"}, "author_response": "We thank the reviewers and editor for the valuable comments and suggestions, which have greatly helped us improve our manuscript. We have conducted additional experiments and analyses and included new data to address the reviewers’ concerns. Furthermore, the text has been revised in accordance with the reviewers’ recommendations. We believe the revised manuscript is significantly strengthened. Our point-by-point responses to the reviewers’ comments are provided below (in blue).\nReviewer #1 (Remarks to the Author):\nZhang et al. report on RNA sequencing approaches to better map the 5’ ends of NAD-capped transcripts in E. coli (precision NAD-RNA seq = pRNA-seq for short transcrips and NAD-linkSeq for longer transcripts). Thus, this study adds to the list of transcripts reported to contain an NAD-cap. The authors compare the promoter sequences for transcripts with an NAD-cap and also report that the spectrum of NAD-capped transcripts is different without and with nitrogen limitation.\nI appreciate that this manuscript was very carefully prepared with appropriate controls and clear description and presentation of the data. However, a major limitation of this and other studies of NAD-capped transcripts is that there is no evidence of a physiological role. While the authors speculate “roles of NAD capping in gene regulation” (in abstract) and “roles in stress adaptation” (in discussion), there is no evidence of this. The authors should carry out additional experiments to test these hypotheses (for example what is the role of the truncated trmJ transcript) or dramatically “tone down” the speculation, especially since the fraction of capped transcript may be low as seen in Figure 5c and 5d).\nResponse: We thank the reviewer for this constructive feedback. We fully agree with the reviewer that there is an urgent need to clarify the molecular and physiological roles of NAD capping. Although some reports have shown that altering NAD capping leads to discernible phenotypes, the precise physiological functions and molecular mechanisms of NAD-RNAs in gene regulation remain unknown. Accordingly, we have toned down our speculation regarding the possible function of NAD-RNAs in the revised manuscript.\nWe have acknowledged that the functional significance of the identified NAD-RNAs, including truncated species like the trmJ NAD-RNA, remains an open question for future research.\nRegarding the fraction of capped transcripts, another method we previously developed, NAD tagSeq II, enabled the determination of the relative abundance of NAD-RNAs compared to the total transcripts. Using that method, we found that overall less than 1% of RNAs in E. coli (excluding rRNAs) are NAD-capped; however, some genes produced the majority of their transcripts as NAD-RNAs in stationary phase (Zhang et al., PNAS, 2021, 118(14): e2026183118). The gcvB and gadY genes selected for the modified Northern blotting analysis in Figures 5c–5d do not represent those with the highest fraction of NAD-capped transcripts. Instead, they were chosen as the examples that exhibited increase and decrease, respectively, in NAD-RNA abundance in response to nitrogen deficiency stress. Again, the biological significance of these changes remains to be determined. We have reframed our conclusions to highlight that the primary contribution of this work is to provide researchers with an improved tool for generating more precise and detailed information on the sequences and features of NAD-RNAs. Such information is essential for designing future experiments aimed at elucidating the molecular and physiological functions of NAD capping. Please see our related response to Reviewer 3 on this matter.\nReviewer #2 (Remarks to the Author):\nZhang et al describe in this paper two novel methods for capturing and sequencing NAD-capped RNAs, combined with novel insight into transcription mechanims and RNA biochemistry in E. coli. The first developed sequencing method, Illumina-based pNAD-seq, achieves very accurate single-nucleotide resolution of the 5'-ends of NAD-RNAs. While the novelty of the method is limited (SPAAC tagging has already been described by the same authors, and NudC release + ligation was already implemented in the OneSeq protocol), the combination offers some interesting features and ultimately allows identifying most of the previously known RNA species, plus many new ones. It also allows identifying very interesting features regarding promoter architecture and the crosstalk with metabolism. I think that this is high-quality work, and I have only a few minor requests (see below).\nUnfortunately, the second method (NAD-linkSeq) produces results that are irreconcilable with published literature, including data from these authors' lab. In Fig. 6b-d the authors describe that for all (!) 882 genes identified as NAD-capped are much shorter (~130 nt, with 5 outliers at around 250 nt) than the non-NAD-RNAs (most around 800 - 1000 nt). This is essentially the opposite of what the same authors claim in in Figure 6 of their earlier NAD TagSeq II paper (ref. 13) and the associated text, namely that \"NAD-mRNAs and their non–NAD-mRNA counterparts generally contain similar overall sequence regions\". The only logical explanation I can come up with is that the bead-based purification procedure used in NAD-linkSeq afforded an unintended size selection that eliminated full-length mRNA sequences, and the PCR then amplified the fragments in the selection window. Furthermore, in terms of methodology, I think that NAD-linkSeq (indirect DNA sequencing) is a step back from NAD tagSeq II (direct RNA sequencing) and has many more biases and pitfalls. As Oxford Nanopore sequencing is a single-molecule method, I do not see the value of PCR amplifications.\nResponse: We thank the reviewer for raising this point regarding the apparent discrepancy in NAD-RNA size distributions obtained from our new NAD-linkSeq method and our prior work with NAD tagSeq II. The reviewer’s observation allows us to clarify an important distinction between the two sequencing technologies.\nThe reviewer noted the difference and proposed a plausible technical explanation involving size selection during the NAD-linkSeq procedure. We have carefully considered this, and our data indicate that the observed size distribution is a genuine biological feature revealed by NAD-linkSeq, not an artifact of bead-based purification. The discrepancy stems from the inherent technical limitations of Oxford Nanopore direct RNA sequencing used in NAD tagSeq II, which is one of the reasons we decided to overcome it with the development of NAD-linkSeq.\nDirect RNA sequencing with Oxford Nanopore Technologies has poor efficiency for RNAs shorter than ~150 nucleotides. Consequently, our previous NAD tagSeq II study was inherently biased against short transcripts. Using pNAD-seq and NAD-linkSeq, we have now discovered that NAD-RNAs from protein-coding genes are mostly short transcripts (60-160nt) although those from sRNA genes tend to have similar sizes to their uncapped transcripts. This shortcoming in our NAD tagSeq II method led to the previous conclusion that NAD-mRNAs were generally full-length.\nOnce we realized that NAD-RNAs are mostly short, we started to develop NAD-linkSeq, which is designed to cover both long and short transcripts by introducing a cDNA synthesis step to add additional sequence to cDNA. As a result, cDNAs from short NAD-RNAs will not be missed during subsequent Nanopore sequencing to capture the full spectrum of RNA lengths. The data presented in Fig. 4b, showing a predominant population of short NAD-RNAs (~130 nt), therefore represents a more complete and accurate profile of the NAD-RNA landscape in E. coli. The longer transcripts observed previously are a minority population that was selectively detected by NAD tagSeq II. The vast majority of the NAD-RNAs identified in this study were not detected by NAD tagSeq II, likely because they were too short or of low abundance to be captured by that method. We acknowledge the reviewer's valid point that NAD-linkSeq involves PCR amplification, which can introduce biases. To minimize this, we used a low number (12) of PCR cycles. We have revised the manuscript to clearly explain this technical comparison and its biological implications, presenting NAD-linkSeq as an advancement that overcomes the limitations of prior methods to provide a more comprehensive picture of NAD-RNAs. At the same time, we agree with the reviewer that the Nanopore direct RNA sequencing approach has its own distinct advantages, such as avoiding PCR bias and offering more accurate quantification. We are also developing a modified NAD tagSeq II method that can detect small NAD-RNAs although it still has other limitations such as lower coverage and higher costs compared to 2nd generation sequencing. We believe these methods are complementary, and their combined availability will significantly advance the field.\nMinor issues:\n- in general, the non-specifically enriched transcripts in the ADPRC(–) group were sequenced at substantially lower levels compared to those in the ADPRC(+) group. Therefore, it is essential that the authors clarify the definition of “Counts” in Figure 2c–h—specifically, whether these refer to raw counts—and specify the normalization method used (e.g., TPM, RPM, etc.) prior to making such comparisons.\nResponse: We acknowledge the observation regarding the lower sequencing depth in the ADPRC (–) controls. To address any potential bias from library size disparities, we have re-analyzed the enrichment data in Figs. 2a and 5a using Reads Per Million (RPM)-normalized counts, as now indicated in the updated figure legends. We confirm that the core set of identified NAD-RNAs remains consistent with the initial analysis. The reported numbers of NAD-RNAs have been updated throughout the manuscript to reflect this normalized analysis.\nFor Figs. 2c-h, raw read counts are retained to accurately visualize the absolute enrichment levels of NAD-RNA 5’ fragments in ADPRC (+) samples, as annotated in the respective legends.\n- Additionally, when applying DESeq2 for differential enrichment analysis, highly expressed genes such as rRNAs and tRNAs could disproportionately influence the total read counts, potentially biasing the estimation of median-ratio size factors. The authors are encouraged to perform qRT-PCR validation of these high-count species using their spike-in controls (NAD-capped and non–NAD-capped RNAs) for reference.\nResponse: We agree that the extreme abundance of rRNAs and tRNAs could indeed bias normalization methods relying on total read counts, such as the median-ratio approach used by DESeq2. We clarify that DESeq2 was not used for our comparative analysis, as its median-ratio method is unsuitable for pNAD-seq data. When tested, we observed significant variation in size factors between ADPRC- and ADPRC+ samples because the method’s core assumption, that most genes are not differentially expressed, is violated by the intentional depletion of non-NAD-capped RNAs during ADPRC treatment. This would cause DESeq2 to misinterpret the treatment effect as a library size difference and incorrectly suppress true NAD-RNA signals as false negatives.\nAs suggested by the reviewer, we performed qRT-PCR validation using our NAD-capped spike-in control, which confirmed dramatically higher rRNA and tRNA levels in control samples (now shown in Fig. S6), illustrating the potential bias highlighted by the reviewer. Validating against non-NAD-capped controls was not feasible since those RNAs, such as 5S rRNA, are themselves highly abundant. Instead, we employed a spike-in normalization strategy where endogenous NAD-RNA counts are normalized to a synthetic NAD-RNA reference, effectively controlling for technical variation while remaining unaffected by endogenous RNA fluctuations. We have revised the manuscript to explicitly describe these approaches.\n- To further support the authors’ conclusions regarding the high-quality 5’-A feature, it would also be valuable to profile the read mapping of the spike-in controls (NAD-capped and non–NAD-capped RNAs) using their current approach.\nResponse: As suggested by the reviewer, we have included the read mapping profiles for the NAD-capped spike-in control (Fig. 2c) and the non-NAD-capped 5S rRNA fragment (Fig. 2k). The spike-in control data demonstrates a specific enrichment of reads exclusively in the ADPRC (+) sample. In contrast, the profile for the known non-NAD-capped 5S rRNA (Fig. 2k) shows neither enrichment of reads nor +1A profile.\n- At many instances, the Materials and Methods section lacks detail essential to repeat these experiments, such as exact buffer or eluent compositions, exact number and volume of washes (e.g.: line 591: what is “formamide-based buffer”, what volume, any whashes?.\nResponse: We have revised the Methods section to include all essential details. Specifically, we have now provided the exact composition and volumes for all key buffers and washing steps. For example, the elution step in line 591 has been updated to: “Elution was performed with 80 μL of elution buffer (95% formamide, 10 mM EDTA in 50 mM Tris-Cl, pH 7.5) at 65°C for 2.5 min, followed by six stringent washes each with 200 μL of wash buffer (50 mM urea, 0.5% SDS, 10 mM EDTA in 50 mM Tris-Cl, pH 7.5).” Similar revisions have been made throughout the section to specify the exact compositions, concentrations, volumes for all critical reagents and procedures.\n-\nReviewer #3 (Remarks to the Author):\nComments for Zhang et al.:\nIn their manuscript entitled ‘High-resolution mapping of NAD-capped RNAs unveils novel features of bacterial NAD-RNA and stress-responsive transcription initiation’ the authors describe a new method for the identification and precise 5’-mapping of NAD-capped RNAs.\nHere, building on previous approaches from their own and other labs, they cleverly combine ADPRC-catalyzed conversion of NAD to an azide-handle, which is reacted with a strained alkyne in a strain-promoted click reaction, to attach biotin for purification on streptavidin. Following 3’-adapter ligation, they then decap the purified RNA using the NAD-RNA decapping enzyme NudC, generating a 5’-monophosphate to enable ligation of an adapter. They then continue library preparation to either subject libraries where RNA was sheared at the beginning of the protocol to short read deep sequencing, or libraries made from intact full-length RNA to long-read nanopore sequencing, thereby achieving precise mapping of 5’-ends, as well as (from long-read sequencing) information on the length of the NAD-capped RNAs.\nApplying this new methodology to E. coli, they identify hundreds of additional NAD-capped RNAs, of which they confirm 9 to indeed carry the NAD-cap using LC-MS/MS. Newly identified (and validated) NAD-capped RNAs include a specific 16S fragment, as well as specific tRNAs, including tmRNA. Applying the methodology to different growth conditions, the authors show that the abundance of many NAD-capped RNAs changes upon nitrogen starvation. They further identify shifts of initiation sites under these conditions, shifting to initiation at A, which enables NAD-capping. They also identify common features of transcription promotors from their hundreds of NAD-capped RNAs and argue that this common feature demonstrates capping to happen during initiation.\nOverall an interesting methodology, by combining known methods, with superior powers, which might be suitable for publication in Nature Communications - also because it could be adapted not only for bacteria but beyond. Also, some interesting biological findings, however, with some weaknesses, which should be amended prior to publication. I will discuss general strengths and weaknesses below:\nThe authors convincingly demonstrate the quality of their new approach, showing strong enrichment of NAD-capped RNA, also using a spike-in control.\nUsing LC-MS/MS, they provide further evidence of NAD-capping for a small subset of newly identified RNAs, importantly including the new classes of capped RNAs, (16S fragment, tRNAs, tmRNA). A weakness I found here was the general lack of y-axis labels (both, what is shown and what is the scaling is lacking) in the LC-MS/MS data (as well as other data), making it impossible to fairly assess the meaning and quality of the data. I assume equal scaling was used, but this is unclear from the figures themselves. If different scales were used, how was this chosen, e.g., for the negative control?\nResponse: We thank the reviewer for raising these points regarding label clarity. We have carefully reviewed the manuscript and revised the relevant labels for clarity. Our detailed responses to each point are provided below.\nConcerning potential roles of NAD-RNA, the authors infer functionality, e.g., in regulation, from the types of RNAs that are capped, and from changes in NAD-capped RNA levels upon nitrogen starvation, from their finding that some RNAs are more changed than others, and from switching of initiation sites. However, at this point, I find it hard to assess whether this functionality indeed exists, or whether these chances are coincidental. Also, from what I understood, it is possible that the NAD-capped RNAs change in abundance due to overall changes in abundance of the specific mRNA (capped and uncapped). I could not identify any data on how specific these changes are. To show that NAD-capping increases (beyond the examples where TSS-switching was shown), changes in NAD-capped RNA abundance should be normalized to overall changes in abundance. Otherwise, to show whether RNAs that are target of NAD-capping change more in abundance than RNAs that are never capped, changes in the abundance of NAD-capped RNAs could be compared to changes in the abundance of non-capped RNA (e.g., in total RNA samples), to find whether they are, e.g., more dynamic.\nResponse: We agree that change in abundance of certain NAD-RNAs could be due to overall change of transcription. We performed the comparative analysis suggested by the reviewer. We analyzed the fold-changes of both NAD-RNA and total RNA (from the RNA-seq data) for each gene under nitrogen-reduced versus standard conditions. These analyses confirm that upregulation for a subset of NAD-RNA occurs independently of transcriptional changes. As shown in the revised Fig. 5e, while downregulated NAD-RNA genes show symmetric total RNA changes centered near zero (median log2FC ≈ 0), approximately 50% of upregulated NAD-RNA genes exhibit disproportionate changes where NAD-RNA increases significantly (median log2FC > 0) without corresponding total RNA elevation.\nI am also hesitant about the promoter sequence motifs identified, as at least some positions do not seem to show any strong signature, although one is claimed (e.g., K (C or G) is claimed at some positions, although C+G seems to be as abundant as A+T. Here, I think the analysis should be deepened. As one example, the authors could separate the data into sequences that follow the suggested pattern exactly, (e.g., sequences that exactly contain KYTKK and RDAY) and anayze patterns in the remaining sequences. Do those sequences contain just small deviations from those patterns, or are they entirely different? I think this is particularly important as the authors claim that the existence of a conserved promoter pattern excludes the possibility of post-transcriptional capping. However, since the conservation does not seem that high, this is questionable.\nResponse: At the reviewer’s suggestion, we performed further analysis on the promoter motifs. We agree that the initial sequence logos did not show strong conservation at all positions, and that a deeper analysis is necessary.\nWe separated the promoter sequences into distinct groups for analysis. We first classified promoters as either 5’-region promoters or intragenic region promoters, which revealed a core architecture enriched for the -10 TATA box and -35 “TT” element in both classes (Fig. 3e). We then specifically isolated promoters containing the exact “RDAY” motif at positions -2 to +2. The sequence logo for this subset (Fig. 3f) now shows a strong, clear consensus. In contrast, the sequence logo for promoters lacking the RDAY motif (Fig. 3g) shows a strong preference for a +1A start site.\nWe have therefore removed the less-conserved “KYTKK” description and focused our conclusions on these two data-supported categories. The presence of these specific promoter motifs, particularly the well-conserved RDAY sequence, provides strong evidence for a co-transcriptional capping mechanism. We have revised the text to reflect the strength of this evidence.\nThe authors also make additional claims of functionality which are not based on direct evidence. I think the authors should make it clearer where these claims are speculative, or should test some of them experimentally.\nOverall, for a methods-oriented manuscript, I believe the amount of evidence for functional importance will be sufficient if the issues mentioned above and below are addressed.\nResponse: We thank the reviewer for this important feedback. We agree that our initial claims regarding the functional importance of NAD-capping and the identified motifs were speculative without direct experimental validation. In accordance with the reviewer’s suggestion, we have revised the manuscript to temper these claims and clearly frame them as hypotheses for future investigation. We have reframed the manuscript to emphasize that its primary contribution is methodological—providing an improved tool for the robust characterization of NAD-RNAs, which we hope will enable future experimental studies of their function. Please also refer to our response to Reviewer 1’s comment.\nSpecific remarks in order of appearance in the manuscript:\nl. 67: ADP-ribose cyclase should be ADP-ribosyl cyclase\nResponse: The term has been corrected to “ADP-ribosyl cyclase” throughout the manuscript.\nl.83: reference missing for NADcapPro at least in this line.\nResponse: The reference for NADcapPro has now been added to line 83.\nl.102: actually the original NAD captureSeq if anything had a bias against long sequences, due to the absence of a shearing step\nResponse: We have revised the text to clarify that the original NAD captureSeq protocol was indeed biased against long transcripts due to the absence of an RNA fragmentation (shearing) step.\nl.140: use slower-running or similar instead of the term retarded\nResponse: The term “retarded” has been replaced with “slower-running” in the manuscript.\nl.144: it is unclear why this optimization had to be done. How much does the current approach differ from their previous method? Please discuss\nResponse: We have added a discussion to clarify the purpose of the optimization. Previously, NAD-RNA profiling used an empirical ADPRC concentration of 4.25 µM. Our titration demonstrated that a 100-fold lower concentration (42 nM) is sufficient for 96% efficiency (Fig. 1c). For this study, we used the higher concentration to ensure robust capture and dataset comparability. However, this optimization is meaningful as it suggests that future work can use less enzyme, yielding substantial cost savings.\nl.151: 50.4% - excessive number of digits for a gel quantification. 50% would be enough.\nResponse: The tagging efficiency has been revised from 50.4% to 50% in the manuscript. We have also reviewed the text and rounded other excessively precise values accordingly.\nl.161: suggesting that SPAAC-tagging selectively enriches NAD-RNAs (…) This makes it sound as if the SPAAC step brings the specificity. However, the specificity really should come from the ADPRC.\nResponse: We have revised the text to accurately reflect that the ADPRC enzymatic step provides the specificity for NAD-capped RNAs. The sentence now reads:\n“…suggesting that ADPRC-mediated tagging selectively enriches NAD-RNAs with minimal cross-reactivity toward NADH-RNA.”\nl. 173-177: very similar results were already shown by Höfer et al (ref. 28). Please discuss that similarity, as now it sounds like this is entirely new.\nResponse: We have discussed that similarity as follows: “This finding is consistent with a previous report demonstrating that specific 5’-terminal fragments, rather than full-length mRNAs, are preferentially enriched even in the absence of RNA fragmentation” in the text.\nFig. 1 panel h: the extrapolation for the lower curves does not seem valid. 1. The extrapolation goes beyond 100%, 2. Too few data points. Higher quantities of enzyme should have been used or the extrapolation should not be done, especially considering the high error bars of the existing data points. If anything maybe do an extrapolation with confidence intervals?\nResponse: To address the issue of extrapolation beyond 100%, we have re-plotted the data with a fitted curve that is constrained by a maximum plateau of 100% decapping efficiency, which is the physiologically meaningful limit. To improve the reliability of the curve fitting and address the concern about too few data points, we have included additional data points at higher enzyme concentrations. This provides a more robust dataset that clearly defines the saturation phase of the reaction kinetics. The revised Fig. 1h presents this improved dataset and analysis. The new curves are based on a more complete dataset and respect the logical boundary of 100% efficiency. We believe these changes have resolved the issues raised.\nFig. 2, panel k: y-axis labels are missing (what and scale). Also, it would be good to show the negative control in the main figure for comparison. It does exist in the supplementary. Caption for panel k: l.281: RNA should be changed into RNAs.\nResponse: As suggested, we have made the following revisions to Fig. 2k and its caption: y-axis label “Intensity (a.u.)” has been added to all chromatograms in the panel to clarify the data scale and units. As suggested, the negative control (5S rRNA) is now displayed within the main figure panel for direct visual comparison. In the figure caption (line 281), “RNA” has been replaced with ‘RNAs” for accuracy.\nl.300-301 – the assumption of a broad involvement of NAD-RNAs in transcription and metabolic fine-tuning is too weak. There is no direct evidence of this. (as discussed above)\nResponse: As suggested, we have revised the text to more accurately reflect the associative nature of the GO enrichment results. The sentence now reads: “Gene Ontology (GO) enrichment analysis of NAD-RNA-producing genes revealed associations with metabolic regulation, particularly nucleobase-containing compound metabolism, and negative regulation of macromolecular processes (Fig. 3d).”\nFig. 3 e-f: Sequence Logo analysis not very convincing. Explanation of R is missing in the caption. The KYTKK ‘enrichment’ looks very small, in some cases even G+C seems to be less abundant than A+T especially in panel e, first and second K. Also, why is GT labelled in e, and GG in f. In total, there might be a motif GGT, but the sequences look near-identical in e and f.\nResponse: We have conducted a more rigorous promoter analysis that has substantially strengthened our conclusions and improved the clarity of our presentation.\nOur updated analysis of the top 220 NAD-RNA genes reveals a core promoter architecture characterized by significant enrichment of both the -10 TATA box and -35 “TT” element across all promoters (Fig. 3e). Through investigation of regulatory motifs, we identified a conserved RDAY motif (positions -2 to +2) in a subset of promoters (Fig. 3f). Importantly, comparative analysis with promoters lacking the RDAY motif revealed a strong preference for a +1A transcription start site in the latter group (Fig. 3g), providing clear visualization of distinct nucleotide conservation patterns as suggested by the reviewer.\nTo assess functional relevance, we compared transcript abundance between promoters with and without the RDAY motif and found no significant difference in NAD-RNA levels (Fig. 3h), indicating that this motif does not serve as a primary determinant of transcriptional output.\nThese findings support a refined model where a core promoter architecture (-10 TATA box, extended -10 element, +1A) is associated with most NAD-RNAs, while the RDAY motif defines a distinct subset with potentially specialized functions in the NAD capping mechanism itself. We have updated all relevant figures, captions, and manuscript text to reflect these strengthened analyses, which we believe provide a more comprehensive and convincing characterization of promoter features associated with NAD capping.\nl. 361/362. The fact that NAD-capped mRNAs are shorter than their full-length mRNA counterparts was already demonstrated in the original NAD-captureSeq paper (for some mRNAs), both by the sequencing and by additional qPCR analyses targeting the 5’-ends and the middle of affected mRNAs, which should be cited here. Still, it is nice to show this transcriptome-wide.\nResponse: As suggested, we have now cited the original report using NAD-captureSeq (Cahová et al., 2015), which first demonstrated that NAD-capped mRNAs are shorter than their full-length counterparts for specific transcripts using both qPCR and Northern validation. The original text has been revised to: \"This finding is consistent with a previous report demonstrating that specific 5’-terminal fragments, rather than full-length mRNAs, are preferentially enriched even in the absence of RNA fragmentation.”\nFig. 4 c: y-axis label missing\nResponse: The y-axis label has been added to Fig. 4c and now clearly indicates “Counts’ with the corresponding scale values shown.\nFig. 5 b, c, d: please show less contrasted versions of this as well (in Supplementary?)\nResponse: We have now included less contrasted versions of the original gel images from Figure 5b, c, and d in the supplementary information as Supplementary Fig. S9a-c, respectively.\nFig. 5 g, i: y-axis labels missing. Also, the way the promotor As are shown could be better. It might be good to show the respective sequence and highlight the 2 promotor nucleotides, or it would be equally good to show a zoomed-in version of the respective region of the initiation, together with the sequence (in the direction of the gene).\nResponse: As suggested, we have added the missing y-axis labels (“Counts”) to the original panels g and I (now f, h). In addition, we have replaced the single “A” marker in both promoter regions with a zoomed-in inset which displays the nucleotide sequence surrounding the transcription start site of the gene.\nFig. 5 e,f, I think boxplots would be more instructive here. Now, we see assessments filtered by arbitrary thresholds. With boxplots, we could see a general trend. E.g., show 2 boxes for downregulated and upregulated NAD-RNA and show data points for RNA levels. Or separate the data into quantiles by log2FC in NAD-RNA levels, and then plot the data for total RNA Log2FC.\nAlso, it would be helpful to report the data in a normalized way (Log2FC in NAD-RNA normalized to Log2FC in total RNA)\nResponse: As suggested, we have replaced the original Venn diagram with a boxplot (Fig. 5e) to better visualize the relationship between changes in NAD-RNA levels and total RNA levels. The updated figure displays the distribution of total RNA fold changes for genes with significantly upregulated or downregulated NAD-RNA levels.\nThe analysis reveals that genes with downregulated NAD-RNAs exhibit symmetric total RNA changes centered near zero, indicating coordinated regulation. In contrast, approximately 50% of genes with upregulated NAD-RNAs show disproportionate changes, where NAD-RNA levels increase significantly without a corresponding elevation in total RNA. This pattern confirms that NAD-RNA upregulation frequently occurs independently of transcriptional changes.\nl. 445-446: Regulatory mechanisms are very hypothetical. It is not clear from which data exactly, an environmentally responsive mechanism can be deduced.\nResponse: We have revised the text to reflect the observational nature of our findings. The original text: “Strikingly, we identified 11 NAD-tRNAs originating from both monocistronic and polycistronic clusters, with most utilizing alternative promoters containing functional -10 TATA elements, suggesting NAD capping serves as an environmentally responsive regulatory mechanism.” has been revised to: “Strikingly, we identified 11 NAD-tRNAs originating from both monocistronic and polycistronic clusters, with most utilizing alternative promoters containing functional -10 TATA elements.”\nl. 465 ‘critical RDAY motif’. To me, this does not look 100% conserved in the figure, so that I have doubts whether this is indeed critical.\nResponse: We have revised the text to more accurately describe this as a “conserved RDAY motif” that is statistically enriched in a specific promoter subset (Fig. 3f) without overinterpreting its functional necessity.\nl. 500-502: a parallel is drawn to the RNAylation by T4phage. I do not quite see the analogy. This is very hypothetical.\nResponse: We have revised the text to remove the comparison to the T4 phage RNAylation system and to more cautiously frame our findings as a hypothesis for future investigation.\nIn general, most of the discussion is still very hypothetical.\nResponse: We have now revised the Discussion to separate observations from interpretations, so that speculative claims about mechanism and biological function are framed as hypotheses requiring future validation.\nMethods:\nl. 518. At which OD or at what point are the cells harvested? Are we looking at stationary phase cells or at exponential phase? This seems to only be stated for the nutrient deprivation experiment.\nResponse: As suggested, we have revised the Methods section to include details on culture conditions and duration. Specifically, for the standard condition, cells were grown to stationary phase. Overnight cultures were diluted 1:100 into fresh LB medium and incubated for 12 hours, reaching an OD600 of 3.4, before being harvested for RNA extraction.\nl. 631/l.352. 18 cycles of PCR does not seem very little (it was stated earlier in the manuscript at l.352 that few cycles are needed). Why were 18 cycles used for NAD-linkSeq nanopore sequencing, but only 12-13 for pNAD-seq? This could still create size biases to lower sizes, despite the use of nanopore sequencing. Please discuss, or try again once with lower cycle number (maybe using more input material?)\nResponse: As suggested, we have re-prepared the NAD-linkSeq library using a reduced number of 12 PCR cycles, consistent with the protocol used for pNAD-seq. The original Fig. 4b has been updated with the new results, which show a consistent size distribution of NAD-RNAs compared to the original data. The revised protocol have been updated in the Methods section.\nSupplementary: Fig. S1: It is not mentioned what is shown exactly: Urea-PAGE? Was it stained or was some label used?\nSame for Fig. S2\nResponse: We have revised the legends for Fig. S1 and S2 to state the method used for separation and detection.\nFig. S3: y-axis labels missing\nResponse: We have added y-axis labels “Intensity (a.u.)” in Supplementary Fig. S3 to specify the data scale for both the Total Ion Chromatogram (TIC) and Selected Reaction Monitoring (SRM) traces.\nFig. S4. Was this stained?\nResponse: We have revised the figure caption to clarify that the RNAs in the urea-polyacrylamide gel were visualized using RedSafe staining.\nFig. S5: the light blue is difficult to read. Maybe better on a dark background (for the light shade). Or no color code necessary, as we have the numbers.\nAlso, unclear what exactly is shown? Pearson correlation for data points (gene abundance in dataset?)\nResponse: As suggested, we have updated the original figure with a higher-contrast version to ensure numerical values are easily distinguishable. In addition, the legend has been revised to clarify that each value represents the pairwise Pearson correlation coefficient between global gene expression profiles derived from pNAD-seq data. These coefficients are calculated by comparing normalized read counts across all detected genes for each sample pair.\nFig. S6: y axis label and scale missing. Since there is a tiny signal in the 5S rRNA control, if the scale is not equal, we cannot assess if this is indeed negative, or if there is a relevant signal, which was put on a different scale.\nResponse: As suggested, we have revised the figure to ensure proper data representation. We have added y-axis labels “Intensity (a.u.)” and applied a linear scale across all panels in Fig. S6 (now Fig. S7). The scaling now enables direct comparison across samples, with the 5S rRNA negative control showing negligible intensity when viewed on the same scale as the positive signals from NAD-RNA samples.\nFig. S7: y-axis label and scale missing.\nResponse: As suggested, we have updated Fig. S7 (now Fig. S8) to include a y-axis label (“Intensity [a.u.]”) with a linear scale for all panels.\nFig. S8: are these genes really differentially expressed (on total RNA level?)? Or differentially abundant in pNAD seq?\nResponse: We believe the reviewer’s comment refers to Fig. S9 (now Fig. S11) rather than Fig. S8. The GO analysis in Fig. S9 (now Fig. S11) specifically reflects the differential expression of genes at the total RNA level, not their differential abundance in the NAD-RNA fraction (pNAD-seq). We have revised the figure caption to clarify that the analysis was performed on total RNA-seq data to eliminate potential ambiguity.\nWe thank the reviewers and the editor for their valuable comments and suggestions, which have substantially strengthened the manuscript. We performed additional experiments and analyses and incorporated new data to address the concerns. We also revised the text in line with the reviewers’ recommendations. We believe the manuscript is now significantly improved. Point-by-point responses to the reviewers’ comments are provided below (in blue).\nReviewer #1 (Remarks to the Author):\nOverall, I appreciate how thoughtfully the authors responded to the reviewers’ comments (though they failed to respond to one of my comments).\nThe authors acknowledge that there is “an urgent need to clarify the molecular and physiological roles of NAD capping”. In this context, I am left wondering about the broad appeal of improved approaches for detecting NAD capping.\nResponse: Thank you for the feedback. We believe these precision tools will accelerate discovery in this area.\nReviewer #2 (Remarks to the Author):\nThe authors have carried out a thorough revision of their work, improving the quality and scope of their manuscript. Specifically, they have satisfactorily addressed all the minor issues raised by this reviewer in the first round. However, while my main point - the striking discrepancy between the data from NAD-link seq and those from NAD tagSeq II (published by the same lab) has been addressed in the rebuttal letter, I did not find any mentioning of this discrepancy and the proposed explanation in the manuscript. It is my opinion that the reader should be made aware of this. I would also like to state that - while I find the proposed explanation plausible - I would prefer to see some hard proof for it, e.g., through side-by-side comparison of identical samples sequenced with the two protocols. As the ground truth (the real size and sequence distribution of RNAs in E. coli) is unknown, spike-ins of different sizes could provide valuable support for the explanation.\nResponse: Thank you for the constructive feedback. We agree that a side-by-side analysis of identical samples processed with both protocols would provide definitive confirmation. While such a comparison is beyond the scope of this revision, we have implemented an improved NAD-linkSeq to address this concern.\nWe strengthened NAD-linkSeq by adding four defined NAD-RNA spike-in standards (50, 150, 277, and 700 nt), eliminating PCR amplification, and sequencing full-length cDNAs generated from enriched, NudC-decapped, adaptor-ligated NAD-RNAs. This approach uses Oxford Nanopore direct cDNA sequencing, which captures shorter fragments more efficiently than direct RNA sequencing.\nWe now discuss in the Results and Discussion the technical differences between NAD-linkSeq and NAD tagSeq II and how these account for the observed size distributions. Briefly, NAD tagSeq II relies on Nanopore direct RNA sequencing and is less sensitive to short NAD-RNAs, whereas the improved NAD-linkSeq detects a broader spectrum, including short fragments underrepresented by direct RNA sequencing. The spike-in standards were recovered at their expected sizes, supporting platform-dependent capture biases.\nWe have added a dedicated paragraph addressing the discrepancy and its proposed explanation, and have updated the figures, Methods, and Supplementary Materials accordingly.\nReviewer #3 (Remarks to the Author):\nIn their revised version of the manuscript, the authors have addressed all of my concerns. I am satisfied with the majority of changes and feel the manuscript is much improved, especially since the claims of function have been toned down and labels and descriptions have been added for clarity. In general I would recommend the manuscript for publication, as long as the following two concerns are addressed, which I will outline below:\nThe discussion of the RDAY-containing promotors has been improved a lot. It is interesting to see that the motif does not influence strength of transcription itself. It would be ideal, however, to also comment on the efficiency of NAD-incorporation. E.g., is there any hint, e.g. in the NAD-RNA enrichment factors, or other data available whether there are differences between RNAs transcribed from the RDAY-containing promotors or others? If possible at all, please comment.\nResponse: Thank you for the suggestion. We compared NAD‑RNA enrichment—defined as the ADPRC+/ADPRC− read‑count ratio—for transcripts arising from RDAY versus non‑RDAY promoters. Because ADPRC− approximates total transcript abundance and ADPRC+ reflects NAD‑capped RNA levels, this ratio serves as an estimate of relative NAD‑incorporation efficiency. RDAY promoters showed significantly higher ratios than non‑RDAY promoters (p < 0.001). Thus, while RDAY does not measurably affect overall transcription strength, it is associated with increased NAD‑capping efficiency, possibly by creating a favorable context at the transcription start site for initiation factors or NAD‑incorporation machinery. This analysis has been added as Fig. 3i.\nIn addition, I am also missing a comment whether the RDAY motif is specific to promotors generating NAD-capped transcripts, or whether it also occurs for RNAs that have not been determined as NAD-capped. And if it does occur for non-capped RNAs (or RNAs not yet determined as capped), is it possibly enriched for NAD-capped ones? After all, otherwise this could only be one possible promotor among many others.\nResponse: We have clarified this point in the manuscript. The RDAY motif is enriched among promoters that produce NAD‑capped transcripts, but it is not exclusive to them. The motif includes a +1 A, which is necessary for NAD incorporation; however, +1A alone is not sufficient—only a subset of +1A promoters yield NAD‑capped RNAs. Accordingly, RDAY should be viewed as an enriched, predictive feature rather than a unique signature of NAD capping.\n2) More importantly, concerning the nitrogen shift experiment, the authors have taken up my suggestion of generating boxplots comparing mRNA levels (from total RNA sequencing) between NAD-capped RNAs that are upregulated on the NAD-RNA level, and those downregulated at the NAD-RNA level (Fig. 5e). They argue that 'The scatter plot reveals that changes in NAD-RNA abundance are not simply proportional to changes in total transcript levels, as indicated by the substantial overlap in the distribution of total RNA (Fig. 5e). This indicates that NAD capping may be regulated independently of transcription for a subset of genes.'\nHowever, I do not agree with the conclusion. Due to the fact that the 'upregulated' NAD-RNAs had on average much higher expression at the total RNA level than 'downregulated', I had a look at the log2FC data from datasets 2 (adjusted log2FC) and 3 (log2FC) myself. In general there seems to be a strong correlation between log2-fold changes at the NAD-RNA and at the total RNA levels for the majority of the NAD-RNAs, which can be fitted quite well with a linear correlation (I tried for all RNAs (R2=0.41), as well as upregulated (R^2=0.73) and downregulated (R2=0.44) separately). Although it is true that many of the 'upregulated' NAD-RNAs are not 'upregulated' at the total RNA level, I believe this may be misinterpreted, because, as far as I understand, all measures of up- or downregulation are based on the proportion that certain sequences take up in the sequencing library, and are not based on absolute expression/abundance value. This does not exclude that, for some examples, there is indeed an independent upregulation of NAD-capping and expecially the extreme cases are certainly worth a closer look. However, I would urge the authors to acknowledge the general correlation of changes on NAD-RNA and total RNA level and to tone down the claim of independent regulation of capping and transcription a lot more than currently. Also, I believe showing scatterplots (log2FC on total RNA level vs. log2FC on NAD-RNA level) would be more useful in this case than the boxplots currently shown. In any case, for better clarity of the plot itself, it should include 'total RNA' for the y-axis label and 'NAD-RNA' for the x-axis label.\nResponse: As suggested, we have replaced the boxplots with a scatterplot comparing the log₂ fold changes of total RNA versus NAD‑RNA levels (now presented in Fig. 5e). The plot indeed reveals a general positive correlation between the two datasets (R² = 0.35). We acknowledge this overall trend and have toned down our original claim regarding the “independent regulation” of capping and transcription. In the revised Results section, we now state that while changes in NAD‑RNA abundance are broadly correlated with transcriptional output, a subset of genes deviates from this trend, suggesting that NAD capping efficiency may be modulated by additional, gene‑specific regulatory layers superimposed on transcription.\n1\n0\n-4.5 -4 -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0\n-1\n-2\n-3\n-4\n-5\nCF2gol\nANR\nlatot\ndownregulated on NAD-RNA level\nNAD-RNA log2FC\n12\n8\n6\n4\n2\n0\n0 2 4 6 8 10 12\n-2\n-4\nCF2gol\nANR\nlatot\nupregulated on NAD-RNA level\nNAD-RNA log2FC\n12\n10\n6\n4\n2\n0\n-6 -4 -2 0 2 4 6 8 10 12\n-2\n-4\n-6\nCF2gol\nANR\nlatot\nall NAD-RNAs\nNAD-RNA log2FC"}, {"round": 2, "reviewer_comments": {"reviewer_3": "Comments to the authors:\nMy two concerns regarding the previous revision have been addressed well and to my full satisfaction. The figures and text added/modified in response improve the discussion and I especially found the analysis of the RDAY promotor motif very interesting.\nAs far as I can tell, the other referees' concerns have also been responded to well.\nI would now recommend the article for publication."}, "author_response": ""}]

Decision letter