We assessed both processes for the dominant species of six benthic categories  accounting for > 98% of the benthic cover of a central Red Sea coral reef. Rates were extrapolated to the relative benthic cover of the studied organisms in co-occurring coral- and algae-dominated areas of the same reef. In general, benthic categories with high N2 fixation exhibited low denitrification activity. Extrapolated to the respective reef area, turf algae and coral rubble accounted for > 90% of overall N2 fixation, whereas corals contributed to more than half of reef denitrification. Total N2 fixation was twice as high in algae- compared to coral-dominated areas, whereas denitrification levels were similar. We conclude that algae-dominated reefs promote new nitrogen input through enhanced N2 fixation and comparatively low denitrification. The subsequent increased nitrogen availability could support net productivity, resulting in a positive feedback loop that increases the competitive advantage of algae over corals in reefs that experienced a phase shift.Coral reefs experience phase shifts from coral- to algae-dominated benthic communities, which could affect the interplay between processes introducing and removing bioavailable nitrogen. However, the magnitude of such processes, i.e., dinitrogen (N Ironically, however, N2 gas is the least accessible for flora and fauna1. In oligotrophic marine ecosystems such as coral reefs, primary production is limited by low amounts of bioavailable N forms such as ammonium (NH4+) or nitrate (NO3-)5. Yet, coral reefs belong to the most productive ecosystems on earth and are regarded as oases in an oceanic desert8. In this context, microbial N cycling plays a key role by introducing, recycling and removing N from coral reefs9. Particularly, biological N2 fixation, i.e., the conversion of atmospheric N2 into bioavailable NH4+ by prokaryotic microbes (diazotrophs), can alleviate N limitation for coral reef primary producers10. In addition, the recycling of de novo bioavailable N via nitrification11 may serve as a mechanism to prevent the loss of N12. In contrast, denitrification  may remove bioavailable N in times of high environmental N availability14. Likewise, fixed N can be transformed into atmospheric N2 via anaerobic ammonium oxidation (ANAMMOX), a pathway functioning as an additional N removing mechanism in coral reef sponges15, and hypothetically in other coral reef associated organisms12. Whereas N influxes to coral reefs via N2 fixation are comparably well-studied17, knowledge about N efflux via denitrification is limited to some coral reef substrates (such as reef sediments)14, and is just starting to be generated for other coral reef organisms 21. Corals reefs and their main ecosystem engineers, scleractinian corals, are adapted to nutrient-poor environments23. Under these conditions, both the import of bioavailable N via N2 fixation as well as the removal via denitrification may essentially contribute to maintaining a stable, low N availability and, hence, ecosystem functioning22. Further N cycling processes have been detected or hypothesised in coral reef environments12. For example, nitrification, i.e., the oxidation of NH4+ to nitrite (NO2-) and NO3-, has been measured in coral reef environments24, and may function as an internal recycling mechanism with nitrate serving as a substrate for coupled denitrification12.Nitrogen (N) is vital for all living organisms and is required for primary production and the production of biomass. Among the key elements required for life 45, our knowledge about their functioning is still in its infancy. Additionally, functioning likely differs between coral- and algae-dominated communities47.Coral reefs not only belong to one of the most productive but also to the most threatened ecosystems on the planet. Global and local change associated stressors such as ocean warming and acidification2 fixation) and loss (via denitrification) terms of bioavailable N differ quantitatively between coral- and algae-dominated reef states. For this study, we hypothesised differences between coral- and algae-dominated reef states in the amount of total fixed and denitrified N, based on differences in N2 fixation and denitrification activities of different benthic categories49. Hypothetically, an altered reef community structure associated with phase-shifts could lead to different total N2 fixation and denitrification budgets in coral- and algae-dominated reef areas. Further, we hypothesised that N cycling processes may have the potential to amplify and catalyse phase-shifts through the proliferation of turf algae as prominent N2 fixers50. The role of denitrification in reef communities is mostly unknown, as well as the interplay of both N2 fixation and denitrification in coral- and algae-dominated reefs. Understanding N cycling patterns in baseline scenarios  and alternative reef states  is, hence, of paramount interest to gain a holistic understanding of these dynamic systems, which then can be used as a basis to address, elaborate, and expand future management strategies.N cycling is critical for the stability of coral reef ecosystems; however, it has not been investigated yet how gain (via N2 fixation and denitrification) in a comparative framework that covers the main species of six key benthic categories that together account for > 98% of the benthic cover on a central Red Sea coral reef with two distinct reef areas.In the present study, we carried out acetylene-based incubations (i) to identify the key players that import and/or remove nitrogenous compounds into/from the reef system; and (ii) to provide a relative budget for two counteracting N cycling processes . A detailed overview of the benthic communities can be found in Table Up = 0.007), whereas hard coral cover was threefold lower (Mann–Whitney Up < 0.001). Pre-defined differentiation between algae- and coral-dominated reef areas were confirmed visually by Principle Coordinate Analysis . Hard corals and turf algae were the major drivers of separation and explained 64.2% of the dissimilarities between reef areas (DistLM).Two distinct reef community states characterised by contrasting relative cover of benthic categories were identified Fig.  and pre-2 fixation rates per substrate surface area, being approximately 5 to 6-fold higher than those of biogenic rock, 10 to 12-fold higher than reef sands, 32 to 39-fold higher than soft coral, and approximately two orders of magnitude higher than hard corals . The soft coral displayed the highest denitrification activity, being 3- to 4-fold higher than that of reef sands, biogenic rock and coral rubble, and 6-fold higher than denitrification potentials of hard corals and turf algae , A. hemprichii showed the highest denitrification potential that was 5-fold higher than that of P. verrucosa  and 26-fold higher than S. pistillata .Due to NOgae Fig.  and S2. 2 fixation and denitrification from all measured organisms and substrates (see Table p = 0.24), whereas denitrification was similar  and coral-dominated areas (79.8%), followed by coral rubble . Slightly lower N2 fixation rates in the present study may a) be due to an underestimation caused by an initial lag phase associated with acetylene-based assays61 (see limitations), which was omitted from rate calculations of other studies59 but included here; or b) due to varying sampling times: benthic categories of the present study were incubated in March 2018, which is the winter season. It has been demonstrated that N2 fixation activity in winter is generally lower than in summer62, which could explain lower N2 fixation rates of the present study compared to previously reported rates , reef sands solely cover a minor fraction of the benthic cover.Our results suggest a clear distinction between key benthic categories, in which the most active N33 and opportunists67, which can form extensive mats even under oligotrophic conditions69. Furthermore, they can rapidly take over bare substrate due to high growth rates71. The high N demand needed to fuel metabolism and biomass production in filamentous turf algae can, to a large extent, be satisfied by high N2-fixing activities73. A recent study showed that accumulated N in the form of turf algal biomass can be exported to the wider reef33. N2 fixation activities of coral rubble were similar to those of turf algae, which confirms findings of a recent study74. Coral rubble N2 fixation activity measured here is in the range of previous studies76 and may, thus, be driven by microbial communities inhabiting coral rubble surfaces, as suggested by Davey and others75, who observed significantly higher N2 fixation activity in coral rubble compared to living hard corals.From an ecological perspective, turf algae are pioneers2 fixation activities, being in a similar range77 or significantly lower59 than rates measured previously with acetylene reduction techniques. Lower N2 fixation rates for hard corals of the present study may have occurred due to a phosphate limitation of N2 fixation79, as the estimated N:P ratio of 83:1 in the incubation water (see Methods) ranged above the canonical Redfield ratio of 16:180. Additionally, discrepancies could also result from differing surface area determination techniques used here and in other studies. Previous studies determined the surface area of investigated benthic categories, such as hard corals, using the aluminium foil method81 or advanced geometry58, but potentially lack accuracy82 and, hence, potentially underestimate the surface area of hard corals and, thus, overestimate N fluxes. The soft coral displayed highest denitrification activity. The interplay of N2 fixation and denitrification, favouring low internal N availability, may be vital for the stability between the coral host and the associated photosynthetic algal endosymbiont of the family Symbiodiniaceae (sensu Rädecker and others12). Low N2 fixation and comparatively high denitrification activity may promote the host’s control over symbiotic algae83 by keeping N availability limited84. As such, seasonal fluctuations 85 or environmental stressors, like eutrophication or ocean warming, may influence both processes12, leading to shifts from N to P or another micronutrient  limitation88, which can result in a breakdown of the coral-Symbiodiniaceae symbiosis87. Furthermore, Tilstra and others20 hypothesised a negative correlation between heterotrophic capacity and denitrification activity in coral holobionts, as previously suggested for diazotrophs77. The hard coral species used in the present study are all on the autotrophic end of the mixotrophic spectrum92. As such, these coral species rely mostly on the Symbiodiniaceae for their energy. As denitrifying microbes are heterotrophic94, it is likely that photosynthates translocated from the Symbiodiniaceae are their main source of energy. Thus, a differing heterotrophic capacity of the coral could potentially influence denitrification potentials. This hypothesised link may also explain the high denitrification activity found in the investigated soft coral of the family Xeniidae, which is a functional autotroph95.Among all benthic categories, corals  showed lowest NXenia sp. occurred due to their different capacity in releasing and producing mucus97, with thick mucus layers favouring high anaerobic potentials that might facilitate denitrification96. It has been demonstrated recently that soft coral mucus does not provide a favourable habitat for associated diazotrophs97, which in return could explain observed comparatively low N2 fixation rates.Finally, denitrification is an anaerobic process. Potentially, observed denitrification potential differences among the hard coral species and 2 fixation of both coral- and algae-dominated reef areas  and contributed equally to the 78% of overall denitrification. This is surprising, as both benthic categories showed lowest  or highest  denitrification activity. While all investigated hard coral species showed similar N2 fixation patterns, findings regarding their denitrifying activity showed a large variability  display higher capacities to remove bioavailable N via denitrification and could, thus, be more resilient to higher N availability than those of S. pistillata or P. verrucosa dominance. However, we have considered only a small selection of hard corals with a branching morphology that are considered as autotrophs92. It remains speculative how other hard coral species, such as those of mounding and plating morphologies, or heterotrophic corals98 with different mass transfer characteristics100 contribute to potential reef resilience.At the community level, the relative contribution of key benthic categories varied when compared to N fluxes related to substrate surface area. Together, turf algae and coral rubble represent 91% of overall N103, which increases the relative importance of hard corals for N2 fixation and particularly denitrification in both reef areas in the present study. A reduction of hard coral cover and, thus, spatial complexity  also leads to a reduced contribution to overall denitrification . Nevertheless, a higher N availability  in algae-dominated reefs could have multiple consequences resulting in a positive feedback loop. Just as eutrophication promotes turf algae growth on coral reefs112, higher N accumulation from N2 fixation could relieve N limitation and cause algae to proliferate in nutrient-poor waters114. This can result in high abundances of benthic algae that in turn deter herbivorous fish that successively control algal proliferation by grazing115. Jessen and Wild116 have described this feedback loop before, and we here append that higher N availability (via N2 fixation) in algae-dominated reefs can be further utilised for algal growth or metabolism. Subsequently, increased N availability could facilitate the release of algal exudates such as dissolved organic nitrogen (DON)117 from benthic algae during active growth or decomposition. Ultimately, this feedback loop could turn a reef from a previously net sink of DON into a DON source, which similarly occurs during eutrophication events118.Besides being most abundant in coral-dominated areas, hard corals  contribute most to the three-dimensional structure  of coral reef ecosystemsion Fig. , even thion Fig. , despite119, but also between investigated benthic categories122. Although the microbial community composition was not considered in this study (see limitations), varying microbial communities and their interactions might have implications for N2 fixation and denitrification activities and should be investigated in future studies. Discontinuous shifts123, shifts of varying intensity124, or community shifts from reefs dominated by corals to assemblages other than benthic (turf) algae have been reported (reviewed in Norström and others45). Aside from algae-dominated reefs, alternative reef states can be dominated by corallimorphia, sponges, ascidians, or soft corals45. Particularly, soft coral dominance is common in the Red Sea126 and other regions such as Taiwan, East Pacific127 and at the Great Barrier Reef, Australia128, where the soft coral genus Xenia attains as much as 80% of benthic cover after disturbance129. Moreover, climate change associated stressors such as ocean acidification might induce community shifts from hard to soft coral dominance130. Bednarz and others48 propose that soft corals may become an important player in N cycling due to their increasing dominance in benthic cover in the northern Red Sea. Based on the results of the present study, we carefully speculate that a high soft coral cover may alleviate degraded reefs, or reefs in a transitional state, from excessive N. The extent to which Xenia sp., as the main denitrifying organism, can decelerate coral reef degradation remains to be determined in future studies. Hypothetically, N limitation could be exacerbated in Xenia sp. dominated reef areas, as more N is removed via denitrification than in hard coral or algae-reef dominated areas. This hypothesis is supported by findings of Pupier and others97, who suggest a significant decrease in N2 fixation and subsequent N limitation in soft coral-dominated reefs.In the present study, we evaluated two distinct reef communities and the implications of their varying benthic composition. Microbial communities associated with the benthic categories likely not only vary between coral- and algae-dominated reefs131. Findings of the present study confirm previous hypotheses, in which the potential of coral rubble as highly active N2-fixers can aggravate N influxes to a destroyed or vulnerable reef75. At the same time, our findings indicate that the denitrifying capacity of rubble-dominated reefs is presumably lower than in intact coral-dominated areas , which suggests that this reef state could compound N influxes, resulting in N accumulation at the ecosystem scale.Coral rubble-dominated areas, particularly reef flats, can be the result of fragmentation and erosion processes of nearby reef areas such as leeward slopes, resulting in mobile fragments that are unsuitable for coral colonisation2 fixation could lead to an aggregation of N in algae-dominated communities, while differences regarding the bioavailable N removal via denitrification were not observed between coral- and algae-dominated reef areas. Potentially, N2 fixation rates58 as well as denitrification potentials (85) experience seasonal fluctuations that might cause feedback responses in the extrapolated fixed or removed N. The range of these feedback responses remains to be determined.We demonstrated that N influxes via N4+ and NO2− to elemental N2), that potentially remove fixed N from the system133 have been identified in coral microbiomes134 and coral-reef sponges15. The extent to which ANAMMOX can serve as a N removal process in shifting reefs remains to be determined. Further, cryptic habitats in coral reefs harbouring high abundances of sponges135 may reduce bioavailable N via ANAMMOX and should be prioritised in future studies, as they were not considered in the present study (see limitations). The biogeochemical significance of stressor-induced phase shifts and the resulting loss of structural complexity  in reef N cycling remain unknown and should be the subject of future studies.N cycling processes in coral reefs, including anaerobic ammonium oxidation  and were solely used as a base for relating the respective N cycling rates to the reef area. Specimens were sampled from the total reef area (see next paragraph). The selected reef displays a small-scale heterogeneity of communities and varying degrees of community composition with both target reef areas being less than 30 m apart from each other.The Abu Shosha reef in the Jeddah Region  on the west coast of Saudi Arabia in the central Red Sea was chosen due to the co-occurrence of both coral-  and algae-  dominated areas within the same reef Fig. 51. Both 51 by photo quadrats136, providing a two-dimensional (2D) planar reef coverage of each benthic category. Briefly, a PVC quadrat  was randomly placed on the reef surface , and a photograph was taken from approx. 1 m distance to the substrate. Photographs were then analysed with the software Coral Point Count with Excel extension (CPCe) 4.1137. With the help of the software, 48 randomly located points were overlaid on the photographs, resulting in 576 and 480, respectively, data points per study area. The underlying benthos for each data point was determined to the lowest possible taxon. The major benthic categories of the investigated reef were , biogenic coral rock (hereafter termed biogenic rock), carbonate reef sands (hereafter termed reef sands), hard corals, macroalgae, and the giant clams (Tridacna sp.). Hard corals were identified to the genus level. Turf communities consisted of a heterogeneous assemblage of different filamentous algae and cyanobacteria. Examples from the Northern Red Sea have shown that turf algae, as defined for the present study, account for the highest fraction (up to 90%) of benthic algal cover138. Areas of bare coral rock, that were not covered with any of the other benthic categories but associated with endolithic algae and crustose coralline algae were defined as biogenic coral rock139 (hereafter termed biogenic rock). Coral rubble was defined as dislodged parts of framework builders with its associated microbial community according to Rasser and Riegl131.Benthic community composition of the Abu Shosha reef was determined for an earlier studyPocillopora verrucosa (n = 5), Acropora hemprichii (n = 4), Stylophora pistillata (n = 4), soft coral of the Xenia genus (n = 5), biogenic rock (n = 5), coral rubble (n = 4), reef sands (n = 5) and turf algae (n = 5), were collected randomly from the overall reef area  were approx. 10 cm long. Hard coral fragments were sampled from different coral colonies (> 10 m distance between each other) to account for genetic diversity. Individual coral colonies of Xenia sp. were collected with a small piece of anchoring rock (< 0.5 cm diameter) to prevent tissue damage. Reef sands were sampled using a Petri dish  which was pushed carefully into the sand. Reef sands were then fixed to the dish from underneath so that upper sand “cores” with a max. sediment depth of 14 mm were sampled, covering a similar depth as reported previously58. All fragments and Petri dishes containing reef sand samples were immediately transferred to recirculation aquaria on the boat after sampling, each filled with ambient seawater. Fragments of P. verrucosa, Xenia sp., turf algae, coral rubble, biogenic rock as well as sediment samples were kept at ambient water temperature and light conditions until the experimental incubations started within 3 h after sampling. For P. verrucosa, it has been demonstrated successfully that freshly collected fragments can be utilised for physiological quantifications140. Fragments of A. hemprichii and S. pistillata were sampled two weeks prior all other specimens. After being transferred to the wet lab facilities of the Coastal and Marine Resources (CMOR) Core Lab at KAUST, fragments were distributed randomly into four independent replicate 150 L flow-through tanks (flow-through rate 300 L h−1) for two weeks to allow for acclimation and healing of tissue damage. Each aquarium was constantly supplied with ambient, sediment-filtered reef water from inshore reefs located 1.5 km off KAUST, and ambient light conditions, i.e., a photon flux of ~ 200 µM quanta m−2 s−1, representing the daytime average photon flux of the studied reef and water depth during this period of the year.All benthic categories, i.e. hard corals cosa n = , AcroporCOmbined Blockage/Reduction Acetylene assay . As acetylene inhibits the production of NO3- via nitrification142, seawater (ambient NO3- concentrations ranged between 0.09 and 0.34 µM)112 was supplemented with nitrate to a final concentration of 5 µM as a substrate for the denitrification pathway to counteract substrate limitation 80. However, persistent N2 fixation rates in the presence of nitrate of up to 30 µM have been reported149. Furthermore, El-Khaled and others74 conclude that the technique provides sufficient information about the relative importance of different benthic categories by accounting for relative changes in N cycling rates (both N2 fixation and denitrification). COBRA provides denitrification “potentials” as artificially provided nitrate during the incubations drives denitrification above natural levels74. Acetylene was added to both incubation water and headspace at a concentration of 10%. This saturated acetylene concentration in the gastight incubation chambers leads to the preferential reduction of acetylene to ethylene (C2H4) instead of N2 to NH4+ by the key enzyme nitrogenase151. Moreover, acetylene blocks the nitrous oxide (N2O) reductase activity in the denitrification pathway leading to an accumulation of N2O153. Replicate samples were incubated and two additional chambers without specimens served as controls to correct for planktonic background activity. All incubations lasted for 24 h with a 12:12 h dark/light cycle and a photon flux of ~ 200 µM quanta m−2 s−1, representing the daytime average photon flux of the studied reef and water depth during this period of the year. Incubation chambers were submerged in a temperature-controlled water bath at 27 °C (resembling the ambient seawater temperature measured at the reef in 5 m depth during sampling) and constantly stirred (500 rpm) to ensure sufficient exchange between the water body and headspace. Gas samples were taken at the start (t0) and the end (t24) of each incubation, and analysed targeting C2H4 (as a proxy for N2 fixation) and N2O (as a proxy for denitrification) by gas chromatography and helium pulsed discharge detector . A detailed description of N2 fixation and denitrification rate/potential calculation can be found in the supplementary . Notably, sediment depth and, hence, oxygenation status as well as pore-water movement through the sediment matrix affect the biogeochemical cycling, with potentially higher N cycling activity due to anaerobic milieus provided in deeper sand layers63. Oxygen fluxes were quantified parallel with identical benthic categories to validate that neither hypoxia nor hyperoxia  conditions occurred during N cycling incubations156. We refer to supplementary material SM Incubations were performed using a 2H4 and N2O were converted to N fluxes using conservative molar ratios of N2O:N2 = 1 and C2H4:N2 = 4157. Extrapolations for total fixed or removed N  were performed according to formulas in supplementary material SM 10). Then, these benthic category-specific rates were used to account for the relative cover  of each benthic category in the respective reef area , which provides cumulative N fluxes related to 3D reef area .Production rates of C158 with the PERMANOVA + extension159. Differences in the N cycling processes among benthic categories were tested for significance using permutational analysis of variance (PERMANOVA) on a Bray–Curtis similarity matrix of square-root transformed data. In case significant differences occurred, pairwise t-tests with parallel Monte Carlo tests were performed. Type III  sum of squares was used with an unrestricted permutation of raw data (999 permutations). Unless mentioned otherwise, hard coral data consists of pooled replicates of the three investigated hard coral species  of which mean rates and standard error of means were calculated.Statistical analyses were performed using Primer-E v6160 with the interface Rstudio v1.0.153161). A one-way analysis of similarities  was used to describe the dissimilarities between both reef areas. Furthermore, a distance-based linear model  using a step-wise selection procedure with AICc as a selection criterion was used to calculate which benthic category(ies) coverage explained visualised dissimilarities best159.Normality (Shapiro–Wilk test) and differences between benthic category coverage in both reef areas  were tested using SigmaPlot (Version 12.0). Two-tailed t-tests were used if data were distributed normally whereas Mann–Whitney-Rank-sum tests were used if data were not normally distributed. Differences in the benthic composition among reef areas  were visualised using a principal coordinate analysis (PCO). Total fixed and removed N in both reef areas were calculated based on the sum of means of extrapolated rates/potentials of individual benthic categories and the respective standard propagated error, with Friedman’s aligned rank test checking for significant differences among respective reef areas (using R v4.0.42O:N2 and C2H4:N2) in different benthic categories (Wilson and others (2012) and references therein162), ii) methodological underestimation of N cycle processes164, iii) environmental alterations by benthic categories as an effect of benthic primary productivity119, iv) underestimations of N cycling rates for benthic categories that could not be assessed in their entirety such as reef sands, and v) reef-wide underestimations/omission of metabolic processes in cryptic habitats, such as cracks and crevices within the natural reef matrix, that harbour specific organisms . These organisms are generally not included in ex situ budget derivations. Nevertheless, the results of the present study are comparable to reefs of similar character and structural complexity. However, N cycling activity may vary substantially in reefs of differing structure, with more/fewer cracks and crevices in the reef matrix with inhabiting species that can remarkably contribute to metabolic processes in coral reefs166.Typical budget uncertainties include i) deviations from theoretical molar ratios (i.e., N119, and may influence N cycling processes. Potential effects of these differences, however, are rather insignificant as they would not allow for identification of differences in N cycling activities between benthic categories. Hence, we assume that shifts in the community composition are likely more relevant for the overall N fluxes than changes of N cycling activities within single benthic categories.Furthermore, all specimens were sampled randomly from the overall reef area, thus, disregarding potential differences in the microbial communities of benthic categories between reef areas. These differences are likely to occur between coral- or algae-dominated reef areas2H474, and from potential incomplete blockages of the denitrification pathway163. Due to potential underestimations of both N2 fixation and denitrification, we, thus, refrained from directly comparing both pathways.We, thus, consider the major results of the present study as solid and reliable, especially as the investigated benthic categories of investigated species cover > 98% in both reef areas. Nevertheless, we consider discussed and presented data as conservative estimates. Furthermore, aforementioned underestimation of N fluxes result from initial lag phases in the evolution of CSupplementary Information.


Lactobacillus agilis (YZ050) was selected as a model and its epitranscriptome was profiled and compared by using mass spectrometry.Ribonucleic acids (RNA) are involved in many cellular functions. In general, RNA is made up by only four different ribonucleotides. The modifications of RNA (epitranscriptome) can greatly enhance the structural diversity of RNA, which in turn support some of the RNA functions. To determine whether the epitranscriptome of a specific probiotic is associated with its adaptation to the source of energy, L. agilis epitranscriptome (minus rRNA modifications) consists of 17 different RNA modifications. By capturing the L. agilis cells during exponential growth, reproducible profiling was achieved. In a comparative study, the standard source of energy (glucose) in the medium was substituted by a prebiotic inulin, and a downward trend in the L. agilis epitranscriptome was detected. This marks the first report on a system-wide variation of a bacterial epitranscriptome that resulted from adapting to an alternative energy source. No correlation was found between the down-regulated RNA modifications and the expression level of corresponding writer genes. Whereas, the expression level of a specific exonuclease gene, RNase J1, was detected to be higher in cells grown on inulin.The  Collectively, all the RNA molecules in a specific group of cells are referred as a transcriptome. In order to achieve some of the RNA functionalities, the RNA structure can be altered by more than 170 different RNA modifications . The preLactobacillus species are common constituents of gastrointestinal tracts [L. agilis epitranscriptome, and subsequently determine whether the L. agilis epitranscriptome is involved in the adaptation to inulin.l tracts , and havl tracts . Prebiotl tracts . One of l tracts . Since il tracts . In thisE. coli alkaline phosphatase, Benzonase nuclease and bovine serum albumin (BSA) were purchased from Sigma-Aldrich . The venom exonuclease phosphodiesterase I was purchased from Worthington Biochemical Corp. . All other solvents were purchased from Thermo Fisher Scientific .Lactobacillus agilis strain named YZ050 was previously isolated from dairy cow fecal samples in our lab and showed the capability to ferment inulin [A t inulin . The stoCells were pelleted and resuspended in 1 mL RNAprotect Bacteria Reagent . The cells were washed twice with 1X PBS and pre-lysed with 250 μL 50 g/L lysozyme and 120 μL 1000 units/mL mutanolysin. Total RNA was extracted using the RNeasy mini kit . Total RNA samples were DNase-treated twice, and the absence of genomic DNA was confirmed by PCR.Ribosomal RNA was removed using the RiboMinus Transcriptome Isolation Kit, . The integrity of RNA was assayed using the 2100 Bioanalyzer .2 and 0.1 mg/mL BSA [g for 15 min , the digested RNA sample was diluted in deionized water to 50 ng/µL.Each RNA sample was digested in an enzymatic reaction of 25 µL at 37 °C for 3 h, which contained 5 µg rRNA-depleted RNA, 0.05 units phosphodiesterase I, 0.5 units alkaline phosphatase, 5 units benzonase, 50 mM Tris–HCl (pH 8.0), 1 mM MgClg/mL BSA . After rAn Acquity ultra-high performance liquid chromatography (UPLC) system  which was equipped with an Acquity HSS T3 column  and a HSS T3 VanGuard pre-column  at 30 °C was used. After injecting 10 µL of sample, the elution was carried out with a binary solvent system, in which solvent A contained water and 0.01% (v/v) formic acid, and solvent B contained 50% acetonitrile and 0.01% (v/v) formic acid at a flowrate of 0.4 mL/min. The gradient elution profile initiated at 100:0 (A:B) from 0.0 to 0.5 min., ramping to 70:30 from 0.5 to 9 min, followed by 50:50 from 9 to 10 min, and ended with 0:100 from 10 to 17 min. Randomized injections were used. The negative control was prepared without any RNA sample.Tandem mass spectrometry (MS/MS) was performed on a Q Exactive Plus  in the positive mode with ESI at 425 °C and 3.5 kV. Sheath and auxiliary gas flow were at 50 and 13 arbitrary units, respectively. Data was acquired with an inclusion list of calculated m/z of all known RNA modifications. The mass calibration was performed using a canonical ribonucleoside standard mixture (3 ng/µL). Data analysis was carried out with Xcalibur  restricting the precursor ion to ≤ 5 ppm accuracy and its retention time to ≤ 0.1 min.Each library was generated from 20 ng rRNA-depleted RNA sample using the Kapa Hyper Stranded RNA-seq kit . The consistency of the libraries was verified by 2100 Bioanalyzer. The libraries were quantified by fluorometry and sequenced on a NextSeq 500  with paired-end 75p reads. The sequence files were processed using the CLC-Bio Genomics Workbench .L. agilis epitranscriptome. Among various types of RNA, ribosomal RNA (rRNA) makes up ~ 80% of total RNA [The notions for epitranscriptome to be a standalone investigation include a single RNA modification can potentially alter the RNA interactions . There aotal RNA . To bettL. agilis sample with a signal-to-noise ratio of ≥ 2 are shown in Table L. agilis epitranscriptome (minus the rRNA modifications) is reported.The results obtained from analyzing all the detectable ribonucleosides in a Before determining whether there were any variations on the level of each specific RNA modification, the use of our method to perform accurate quantitative analysis was evaluated. Specifically, a calibration experiment with a series of standard dilutions was performed. The results indicate the linearity and the dynamic range of the four canonical ribonucleoside standards match or exceed the earlier reports with < 6% relative standard deviation (n = 3) , 20.L. agilis epitranscriptome. This indicates the L. agilis epitranscriptome reaches an equilibrium state when the cells were harvested during the exponential growth.As shown by the error bars in Fig. L. agilis epitranscriptomic profile prompted us to investigate whether the L. agilis epitranscriptome would become different when different prebiotic was used. As shown in Fig. L. agilis epitranscriptome match with those listed in Table L. agilis transcriptome, it would allow the L. agilis transcriptome to be turned over more effectively via the RNase digestion, which could be one way to rearrange the composition of the L. agilis transcriptome.The reproducibility of the L. agilis epitranscriptome, six of them were down regulated more than the average fold change of 0.65. The top six down-regulated RNA modifications include dihydrouridine (D), 1-methyladenosine (m1A), 4-acetylcytidine (ac4C), 2′-O-methyladenosine (Am), N6-methyladenosine (m6A) and N6-threonylcarbamoyl-adenosine (t6A). In the case of D modification, the hydrogenation at the 5 and 6 positions of uridine eliminate the only π bonding, thus weakening the effects of base stacking [Among all seventeen RNA modifications witnessed in the stacking . WhereasL. agilis epitranscriptome, we performed an untargeted gene expression analysis and compared the expression levels in the cell cultures. First, we focused on the writer and eraser genes that correspond to the top six down-regulated RNA modifications (Fig. L. agilis is not known; and no transcript corresponding to the m6A writer gene could be detected. An alternative mechanism to lower the level of specific RNA modifications could be due to an increased cellular activity on degrading the modified RNA molecules. For this reason, the expression levels of all detectable ribonuclease in L. agilis were compared, which included RNase 3, RNase HI, RNase HII, J1, RNase R, RNase Y and RNase Z. In the case of RNase J1, a significant increase on its expression level was found among the inulin samples (Fig. L. agilis epitranscriptome could be linked to the higher expression level of RNase J1 when inulin was used instead of glucose to cultivate the cells.To investigate the underlying reason for the down regulation of ons Fig. . Howeverles Fig. . WhereasL. agilis cells were cultivated with glucose being the sole source of energy, the L. agilis epitranscriptome consists of seventeen different RNA modifications at variable abundancy. There was a downward trend across the entire L. agilis epitranscriptome when the cells were exposed to inulin instead of glucose. To the best of our knowledge, this marks the first report on a system-wide variation of a bacterial epitranscriptome that resulted from adapting to an alternative source of energy. Based on our comparative study on gene expression, the down-regulated inulin-associated L. agilis epitranscriptome could be linked to an elevated RNase J1 activity. Overall, these results further strengthen the association of a unique epitranscriptome to a specific cellular activity [When activity .L. agilis, the experimental approach is applicable to study the other strains. For the MS analysis, due to the lack of available standards, the identification of each RNA modification was limited to the intrinsic accuracy from using high resolution mass spectrometry. Furthermore, the RNA modifications below the limit of detection would not be detectable and missed out from the reported profile.Although all the above observations were limited to the selected strain of


Metastasis remains the greatest cause of fatalities in breast cancer patients world-wide. The process of metastases is highly complex, and the current research efforts in this area are still rather fragmented. The revolution of genomic profiling methods to analyze samples from human and animal models dramatically improved our understanding of breast cancer metastasis. This article summarizes the recent breakthroughs in genomic analyses of breast cancer metastasis and discusses their implications for prognostic and therapeutic applications.Breast cancer (BC) is one of the most diagnosed cancers worldwide and is the second cause of cancer related death in women. The most frequent cause of BC-related deaths, like many cancers, is metastasis. However, metastasis is a complicated and poorly understood process for which there is a shortage of accurate prognostic indicators and effective treatments. With the rapid and ever-evolving development and application of genomic sequencing technologies, many novel molecules were identified that play previously unappreciated and important roles in the various stages of metastasis. In this review, we summarize current advancements in the functional genomic analysis of BC metastasis and discuss about the potential prognostic and therapeutic implications from the recent genomic findings.  Breast cancer (BC) is the most common tumor worldwide with around 2,260,000 new diagnoses worldwide in 2020, accounting for approximately 11.7% of all cancers . The 5-yThe metastatic localization is not a random process but rather at preferred sites under the control of a multitude of microenvironmental, cellular, and molecular factors . The patDifferent hypotheses of organ-specific metastasis were put forward in the past years, and the most widely accepted model of metastasis is the “seed and soil” theory. It essentially stipulates that the intrinsic properties of tumor cells and their supportive microenvironment of target tissues cooperate to determine a successful second-organ-colonization . Ample cThe parallel progression or early dissemination model, put forward especially by C. Klein  and postOverall, these two models depict similar but not identical perspectives that genetic and nongenetic alterations as well as selection pressures from the microenvironment give rise to heterogeneous cellular populations and metastatic potential . From thWith the rapid and ever-evolving genomic sequencing technology-related development, a number of molecules were found to play important roles in different steps of metastasis; for example, alterations in the expression of E-cadherin and metalloproteinase 9 (MMP9), which are epithelial-mesenchymal transition (EMT) markers that play important roles in mediating tumor invasion and metastasis ,41,42; cTraditionally, prediction of BC metastasis relies on standard descriptors and physical characteristics, such as patient age, tumor size, histological features (tumor grade), and number of involved axillary lymph nodes . HoweverTherefore, advances in the understanding of molecular signaling pathways and genetic signatures of BC are helpful to identify more accurate prognostic markers capable of recognizing patients at risk of relapse following local therapy. Genomic profiling technology enables the identification of gene signatures to predict prognosis for BC metastasis and guide the use of adjuvant therapy. Numerous studies were carried out and described the classification and prognosis based on genomic profiling in various cancers, such as BC ,54,55,56In addition to the apparent value of this technique in clinical practice, a provocative implication of these studies was that all or most cells in the primary tumor have met-astatic potential, since the signature that predicts metastasis could be identified in the bulk of the tumor. BC is a heterogeneous disease; several studies of the genomic landscape of invasive BC clearly show that each BC is genomically distinct, with a high level of diversity in single nucleotide variants (SNVs), small insertions and deletions (indels), structural variants (SVs), and copy number alterations (CNAs) ,68,69,70Circulating tumor cells (CTCs) are the tumor cells that are released from the formation and growth of primary tumor and/or metastatic sites into the bloodstream. Analyzing CTCs as the link between the primary tumor and metastatic sites, therefore, would give insights into the biology of the metastatic cascade. Moreover, it may serve as a valid counterpart for the assessment of prognostic and predictive factors in patients with met-astatic BC (MBC) . The prop < 0.001) and shorter overall survival . The number of CTCs is an independent predictor of progression-free survival and overall survival in patients with MBC [The time of CTCs in the bloodstream is short  . This iswith MBC . Persistwith MBC . Moreovewith MBC ,100. Howwith MBC , and a hwith MBC . These cThe molecular characterization of CTCs could provide the information on phenotypic identification of malignant cells and genetic alteration that may change according to disease progression and therapy resistance  . RemodelThe complex reciprocal effects between tumor cells and the bone stomal cells contribute to tumor cells metastatic homing and outgrowth. To identify relevant factors, a study of microarray gene-expression analysis of a cohort of metastasis samples that were surgically removed from BC patients, including 16 metastases from bone, 18 from lung, 19 from brain, and 5 from liver  identifiOnly a small percentage of tumor cells that disseminate via circulation can survive at distant sites and form micrometastases . Most inAfter evasion from apoptosis, the mutual regulation between tumor cells and other cells in the lung parenchyma facilitate their proliferation and the formation of de novo niches that support metastatic outgrowth. Tumor cells could educate lung fibroblasts to produce the extracellular matrix (ECM) component periostin (POSTN)  and tenaIn a recent work that analyzed the targeted sequencing results of the Memorial Sloan–Kettering Cancer Center (MSKCC) dataset of liver metastasis and primary BC extracted from the MSK-IMPACT Clinical Sequencing Cohort, mutations specific to the metastasis were enriched within the PI3K-AKT pathway molecules . The impThe motility and invasiveness of cancer cells that undergo EMT may favor their dispersion to distant organs. Oskarsson et al. surmised that cancer cells that underwent an EMT for metastatic dissemination must traverse the reverse process, a mesenchymal-epithelial transition (MET), to initiate metastatic colonization . Recent Metastatic cells invading the CNS parenchyma must pass the blood-brain barrier (BBB), a semipermeable barrier to metastasis, which is comprised of endothelial cells, astrocytes, and pericytes forming the neurovascular unit . One of Once infiltrated into the brain parenchyma, cancer cells encounter a number of host cell types, including pericytes, reactive glia, neural progenitor cells, neurons, and oligodendrocytes . AstrocyIn the past decade, significant efforts were made to characterize the genetic drivers in BC metastasis using modern sequencing techniques. Better understanding of the genomic complexity and heterogeneity of BC metastasis will lead to improved treatment strategies and research directions. Moreover, the extent of response and potential resistance to treatments varies among different metastatic types and patients. Therefore, more effective and targeted treatments that build on the molecular mechanism of meta-static BC are needed.Given that MTDH mediates the adhesion of cancer cells to lung endothelium, many ways against MTDH were developed to inhibit lung metastasis of BC, e.g., the antibodies reacting to the LHD of MTDH, the multiple tyrosine kinase inhibitor (TKI) SU6668, and DNA vaccines. Denosumab, a mAb directed against RANKL, reduces the SRE risk through inhibiting bone destruction caused by RANKL ,174. LapMoreover, metastasis is a multigenic process, establishing the functional role of candidate metastasis genes may not be easily accomplished by introducing individual genes into weakly metastatic cells to enhance their metastatic phenotype. With the development of whole genome sequencing, more metastasis-related microRNAs (MiRNAs) were identified. MiRNAs, 20–22 short nucleotide sequences that often negatively regulate gene expression, can regulate multiple genes and hence multiple processes simultaneously. Since miRNA can target multiple sets of genes, it is an excellent clinical choice for cancer metastasis, a process mediated by multiple deregulated genes. For example, miR-7 was shown to prevent BC cell spreading but also to inhibit tumor-associated angiogenesis in the metastatic BC by downregulating EGFR . MiR-7 aIdentification of genomic alterations specific to different metastases and targeted therapies against these mutations represent an essential research area to potentially im-prove survival outcomes for BC patients who develop metastases. One apparent disadvantage of DNA array- and RNA-seq based gene expression profiling is the limitation at the transcription level. Since protein expression and function are influenced by post-transcriptional regulations, DNA/RNA sequencing cannot provide a full view of the process of metastases. Current proteomic technologies were used to identify and characterize the molecular components of the invadopodia linked to the metastatic progression of BC cells . High thThe systematic discovery of specific changes contributing to metastases at the genome level enables a deeper understanding of metastasis evolution and new ways for metastasis prognosis and therapy.


Nomograms are currently used in predicting individualized outcomes in clinical oncology of several cancers. However, nomograms for evaluating occult nodal metastasis of patients with squamous cell carcinoma of lateral tongue (SCCLT) have not been widely investigated for their functionality. This retrospective cohort study was designed to address this question.This study was divided into primary and validation cohorts. The primary cohort comprised 120 patients diagnosed between 2012 and 2017, whereas the validation cohort included 41 patients diagnosed thereafter. The diagnostic value of multiparametric MRI, including radiologic tumor thickness threshold (rTTT) in three-dimensions, paralingual distance, and sublingual distance were investigated. A nomogram was developed based on stepwise logistic regression of potential predictors associated with nodal metastasis in the primary cohort and then tested for predictive accuracy in the validation cohort using area under the curve (AUC) and goodness-of-fit tests.P = 0.024), rTTT , paralingual distance , and tumor location  were included in the nomogram to predict the likelihood of having cervical metastasis. A nomogram cutoff value of 210 points  was significantly different to classify the patients metastasis risk group (P < 0.001). Nomogram showed predictive accuracy with AUC 0.881  and good calibration after the validation.Multivariate analysis, tumor size (odd ratio [OR] 15.175, 95% confidence interval [CI] 1.436–160.329, A preoperative nomogram incorporating multiparametric MRI demonstrated good prediction and performed adequately in our study. Three-dimensional assessment of occult metastasis risk value obtained from this nomogram can assist in preoperative decision making for individual patients with early-stage SCCLT. The probability of nodal metastasis tended to be greater than 20% in patients with high metastasis risk or nomogram total score > 210 points. Management of patients with clinically node-negative (cN0) early-stage oral cancer remains controversial –6. EarlyThere are several imaging methods available for preoperative evaluation. Recent studies suggest that the high resolution magnetic resonance imaging (MRI) reliably depicts soft tissue tumor extension, and can be used to predict cervical lymph node metastasis by assessing primary tumor thickness –13. PrevNomograms are currently the most reliable discriminating tools for predicting individualized outcomes in clinical oncology to develop a treatment plan and follow-up strategies in several cancers –25. PrevSolid cancer cells typically spread in different planes to invade surrounding structures as three-dimensional features. Kwon et al.  conducteThe present study is designed with two cohort series and aimed to (1) evaluate if the identified optimal cutoff value of multiparametric MRI in three-dimensions can predict the presence of cervical lymph node involvement, (2) establish an accurate nomogram based on MRI for preoperative assessment of the individual patient for occult metastasis risk and (3) determine the validity of a proposed MRI-based nomogram.n = 120 was determined after a literature review of similar studies, most of which had less than 100 patients were evaluated . The eighth edition of the AJCC proposed incorporating pDOI into three groups  [Recently, pDOI has become an essential predictor of occult nodal metastasis –35. Seve> 10 mm) . This st> 10 mm)  that rep> 10 mm) , 17, 34.Other MRI predictors describing tumor extension included SLD and PLD. SLD did not seem useful for prediction of the existence of lymph node metastasis. Multivariate analysis showed PLD with a cutoff value of 5 mm was a more reliable predictor of nodal metastasis than SLD, and this was included in the nomogram. Another valuable finding was that the risk of nodal metastasis was > 20% in patients with PLD ≤5 mm. This may be due to increased tumor extension to the lingual lymph nodes and lingual vessels on the lateral aspect of tongue may have a greater chance to develop metastasis. Lingual lymph node metastasis have been reported in oral squamous cell carcinoma . SimilarThis study has multiple limitations. First, the nomograms were constructed using retrospective data, which might introduce the risk of treatment selection bias. Also, sample size in our study was limited to the oral tongue sub-site and single center analysis. Therefore, these nomograms must be further validated in a larger prospective cohort in other sub-sites, and accurate risk estimates are required for the clinical trial design. A prospective study is ongoing to evaluate the effectiveness of the proposed nomogram and determine other potential predictive variables. The follow-up period in this study should have been longer to provide more accurate in predictions. Standardized technique and resolution of imaging to measure MRI thickness should be clarified and used to identify the precise cutoff value necessitating further study to confirm our findings.In summary, the nomogram demonstrated predictive accuracy of AUC 0.952 in the primary and AUC 0.881in the validation cohorts. The effect of three-dimensional evaluation of MRI predictors impacted the predictive accuracy of the preoperative nomogram. Assessment of occult metastasis risk value obtained from the MRI-based nomogram can assist in preoperative decision making of whether to perform neck surgery for individual patients with early-stage SCCLT. The probability of nodal metastasis tended to be greater than 20% in patients with high metastasis risk, or nomogram total score > 210 points, and the nomogram suggests that these patients should be treated with prophylactic neck dissection. It was concluded that the multiparametric MRI-based nomogram displayed reasonable accuracy and discrimination was generated and externally validated to predict individualized metastasis outcome.


We present RNA sequencing data sets and their genome sequence assembly for dengue virus that was isolated from a patient with dengue hemorrhagic fever and serially propagated in Vero cells. RNA sequencing data obtained from the first, third, and fifth passages and their corresponding whole-genome sequences are provided in this work. We present RNA sequencing data sets and their genome sequence assembly for dengue virus that was isolated from a patient with dengue hemorrhagic fever and serially propagated in Vero cells. RNA sequencing data obtained from the first, third, and fifth passages and their corresponding whole-genome sequences are provided in this work. Flaviviridae, genus Flavivirus. DENV consists of four serotypes, DENV1 to DENV4. All four serotypes are the cause of dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). DENV is an RNA virus that uses RNA-dependent RNA polymerase (RdRp) for replication. RdRp has poor proofreading capability, which results in high error rates during replication (Dengue virus (DENV) belongs to the family lication .EDTA-treated plasma was collected in 2005 in southern Thailand from a patient with grade 2 DHF who was infected with DENV1. The patient was enrolled in a cohort study that had been approved by the ethical committee of the Faculty of Medicine Siriraj Hospital, Mahidol University, and the Ministry of Public Health in Thailand. The disease severity was classified according to the 1997 WHO guidelines . The DENg for 1.5 h at 4°C. The supernatant was carefully removed. The pellet was resuspended in 140 μl of 1× phosphate-buffered saline (n = 1), P3 (n = 3), and P5 (n = 3) were selected for sequencing. The samples were sent to Macrogen  for the sequencing process. Briefly, each sample was used for library preparation with the TruSeq RNA sample preparation kit version 2. Then, each library was sequenced on the Illumina NovaSeq platform with 151-bp paired-end reads. The quality of the sequencing data was explored using FastQC version 0.11.8  database under the BioProject accession number


Flowering locus T (FT) mRNA despite the continuous debate about its mobility and biological relevance to the control of flowering time in plants. Nevertheless, accumulating evidence supports the notion of the long-distance movement of FT mRNA from leaf to shoot apex meristem and its role in flowering. In this review, we discuss the discovery of florigenic FT, the initial debate on long-distance movement of FT mRNA, emerging evidence to prove its mobility, and the use of mobile FT mRNA to generate heritable transgenerational gene editing in plants. We elaborate on evidence from virus-based RNA mobility assay, plant grafting, RNA with fluorescent protein labeling, and CRISPR/Cas9 gene-editing technology, to demonstrate that the FT mRNA besides the FT protein can move systemically and function as an integral component of the florigenic signal in flowering. We also propose a model to prompt further research on the molecular mechanism underlying the long-distance movement of this important mobile signaling RNA in plants.Many systemically mobile mRNAs have been revealed in phloem. However, very few of them have been found to be of clear signaling functions. One of such rare examples is the mobile  Wheat, rice, and maize are the three most important crops which produce seeds as food to feed people globally . To prodFlowering Locus T (FT), the initial debate on long-distance movement of FT mRNA and its biological relevance to flowering, emerging evidence to prove FT mRNA mobility, and the application of mobile FT mRNA to generate heritable transgenerational gene editing. We also discuss ideas to prompt further investigation into the molecular mechanisms underlying the long-distance movement of this important mobile signaling RNA in plants.To flower, plants perceive the day-length changes in leaves and synthesize a flowering messenger. This signal molecule, dubbed florigen, a theoretical flowering initiation switch, moves long-distance from leave to shoot apical meristem (SAM) through the phloem vascular system to induce flowering . HoweverFlowering Locus T encodes mobile florigen to induce plant flowering  mapping of the recombinant inbred line populations, FT coding sequence. Tissue-specific expression assays by dissecting the FT promoter activities also reveal that FT transcription is under the control of CONSTANS, and this occurs only in leaf veins but not the shoot meristem (FT transcript level increases under long-day (LD) but decreases under the short-day (SD), consistent with that Arabidopsis plants flowered much earlier in LD than SD growth conditions  can spread from cell to cell and over long-distance in plants. For instance, plant RNA and DNA viruses are long known to move their RNA and DNA genomes intercellular and systemically. Moreover, viruses express movement proteins that are required to promote the intercellular and systemic spread of viral RNA or DNA in plants  by virus-encoded movement proteins. Thus, defects in viral movement proteins can rid viruses of intercellular and systemic mobility whilst such movement-deficient viruses can still replicate in single infected cells. Based on these, two plant RNA viruses, i.e., s X PVX,  and Turnrus TCV; , were morus TCV; . By engig leaves . Secondl - Nicotiana benthamiana (as scion) system  system . However studies . To avoijunction . Furthererminant , consisterminant .FD-GFP was much longer than MS2SV40-GFP. FD-GFP, and chimeric SL-FT mRNA. Through fluorescent imaging, the SL-FT mRNA was found to move intracellularly and mainly accumulated at the plasmodesmata sites; however, the dynamic process of the SL-FT mRNA moving from one cell to another was not observed (The bacteriophage coat protein MS2 can bind its target RNAs “stem-loop repeats (SL).” The MS2-GFP fusion protein is often used to label and image RNAs in different organisms . Howeverobserved .Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISRP/Cas9) gene editing system has revolutionized targeted gene editing . This geFT RNA can facilitate RNA virus entering SAM (Tobacco rattle virus (TRV) to deliver sgRNA-tagged with the mobile FT RNA into SAM. In the way, the mutant progeny of Nicotiana benthamiana were recovered in next-generation at frequencies ranging from 65 to 100%; and due to sgRNA-targeting of PDS gene, the transgenerational seedlings with albino phenotype resulted from the PDS gene editing via TRV/(m)FT-sgRNA were statistically different compared with the mock control -mediated ViGE system was also developed. In this case, sgRNAs were fused to the 102-nt V genome . TogetheFlowering Locus T is one of six phosphatidyl ethanolamine-binding protein (PEBP) family members and the other five are TERMINAL FLOWER1 (TFL1) LIKE, MOTHER OF FT AND TFL1 (MFT), BROTHER OF FT AND TFL1 (BFT), ARABIDOPSIS THALIANA CENTRORADIALIS (ATC), and TWIN SISTER OF FT (TSF) in Arabidopsis  does not change the FT protein amino acid sequence but alters the RNA sequence. ft-1 with an expression cassette in which synFT contains 171 (of 175) codon substitutions. In grafting experiments where ft-1 was used as a recipient stock and transgenic synFT/ft-1 as a donor scion, the synFT mRNA was not detectable in the ft-1 shoot apical region. These experiments also suggest that changes in the FT RNA sequence did not affect the FT protein movement . Among these mobile tRNAs, their distributions are uneven. For example, no Ile-tRNA or very few Arg-tRNA but a few Asp-tRNA molecules were detected; however, Cys, Leu, Phe, Try, Trp, and Ser tRNAs were predominantly present in the phloem sap  family member, AtSRBP1, was found to mediate small RNA movement. AtSRBP1, a glycine-rich (GR) RNA-binding protein, also named AtGRP7, can bind to single-stranded siRNA    and a vifficking . In Arabed siRNA . It is potein(s) .6A) and 5-methylcytosine (m5C) play crucial and dynamic roles in embryo development, leaf morphogenesis, and root development (5C have been found to be linked with RNA mobility and m5C RNAs are predominant in the phloem (5C methylation-deficient mutants, mobile TRANSLATIONALLY CONTROLLED TUMOR PROTEIN 1 and HEAT SHOCK COGNATE PROTEIN 70.1 mRNAs become immobile (5C or other types of epigenetic modifications may play a role in FT mRNA mobility.Numerous RNA modifications have been reported  and someelopment . Recentle phloem . Interesimmobile . We specvia plasmodesmata (via the phloem-transportation highway, emerging evidence demonstrates that FT RNA can also undergo the same voyage en route to SAM. Therefore, it is possible that both FT mRNA and FT protein contribute to the florigen signal. Based on recent findings on the relevance of epigenetic RNA modifications, primary ribonucleotide sequences, secondary structures, and RNA binding proteins to RNA mobility, we propose a model for FT mRNA signaling in flowering (FT mRNAs is produced in companion cells, FT mRNAs may be epigenetically modified and form specific structures such as tRNA-like structures. Structured FT RNAs may then be recognized by RNA-binding proteins and transported through plasmodesmata into sieve tube. Along with the FT protein, FT mRNAs will move across sieve plates through phloem to germline cells in shoot apical meristem to induce flowering together with other floral induction factors. This model explains the possible movement of FT mRNA from specific companion cells to sieve tubes, then to distal SAM where they coordinate with other flowering induction factors to induce flowering (Specificized xylem and phloem are two conduits of the plant transportation system. They not only provide physical support for plants, but also are crucial to transport nutrients, minerals, and various signaling molecules in plants . Phloem odesmata . While llowering . Once FTlowering . This moZY and WC conceived the idea and wrote the draft of the manuscript. YH revised and finalized the manuscript. YW, PZ, and NS were involved in the discussion and helped to wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Epitranscriptomics is the study of RNA base modifications involving functionally relevant changes to the transcriptome. In recent years, epitranscriptomics has been an active area of research. However, a major issue has been the development of sequencing methods to map transcriptome-wide RNA base modifications. We have proposed a single-molecule quantum sequencer for mapping RNA base modifications in microRNAs (miRNAs), such as N6-methyladenosine (m6A) or 5-methylcytidine (5mC), which are related to cancer cell propagation and suppression. Here, we investigated 5mC and m6A in hsa-miR-200c-5p extracted from colorectal cancer cells and determined their methylation sites and rates; the data were comparable to those determined by mass spectrometry. Furthermore, we evaluated the methylation ratio of cytidine and adenosine at each site in the sequences and its relationship. These results suggest that the methylation ratio of cytidine and adenosine is facilitated by the presence of vicinal methylation. Our work provides a robust new tool for sequencing various types of RNA base modifications in their RNA context. There are about 130 types of known RNA base modifications in eukaryotic cells2, most of which occur in transfer and ribosomal RNA4. These RNA modifications play various important roles in the structures of transfer and ribosomal RNA. Recently, RNA base modifications have been identified in messenger and microRNA ; these modifications include N6-methyl-adenosine (m6A), 5-methyl-cytosine (5mC), inocine, pseudouridine, 2′-O-methyl-base, and N6,2′-O-methyl-adenosine11. Some of these RNA base modifications are known to enhance the stability and translation efficiency of mRNA7.The epitranscriptome refers to RNA base modifications that occur after transcription8, resulting in functional changes. Therefore, information about the types and quantities of RNA base modifications is important. Some RNA base modifications have been detected using RNA immunoprecipitation coupled with sequencing12. This method uses antibodies specific for particular base modifications. Therefore, only one type of RNA base modification can be detected in a single sequence. Actually, there are currently very few technologies for multiple types of base modifications present on a single RNA strand by MASS-spectroscopy and chemical sequencing method including bisulfite sequencing13. Therefore, the development of a comprehensive analytical technology to simultaneously detect various base modifications in a single RNA strand will be an important tool for enhancing our understanding of the epitranscriptome15.In miRNA, RNA base modifications play roles in miRNA processing and target suppression efficiency20. We have previously reported a single-molecule electrical resequencing method using nano-gap devices26. This methodology is based on sequentially reading the tunneling currents across individual single nucleotides in the sequence, resulting in high-speed electrical discrimination between individual nucleotides without chemical probes and PCR amplifications. Each base conductance value is determined by the individual molecular energy level of each of DNA/RNA nucleotide. Therefore, this method could identify any kind of known and/or unknown modified nucleotide, allowing comprehensive epigenetic analysis of the genome and transcriptome.Single-molecule sequencing is emerging as a method for understanding the RNA epitranscriptome because it can detect the physical properties of nucleobases in a sample nucleotide; thus, it has the potential to detect the location of any base modifications without PCR amplification, including methylations such as 5mCIn this study, we investigated multiple types of RNA modifications in miRNA by using single-molecule electrical resequencing of miRNAs extracted from colorectal cancer cells Fig. a. We foc28 was used for each of the conductance–time profiles based on the conductivity of mono-nucleotides (SI: S5–S7) and determined the sequences of the oligonucleotides being translocated through the gap electrodes  and 92 pS, respectively  > rGMP (87 pS) > m6A (92 pS) > rAMP (67 pS) > rCMP (60 pS) > rUMP (36 pS)  Table . These vides SI: –S7 and dS) Table . Based o6. In this study, we applied this method for estimation of the methylation rate in sample miRNAs extracted from cells of a typical colorectal cancer cell line (DLD-1). Of the DLD-1 miRNAs, miR-200c-5p (5′-CGUCUUACCCAGCAGUGUUUGG-3′) is strongly associated with cancer progression and metastasis29. To measure RNA base modification levels in miR-200c-5p  coexisted with the conductance of cytidine around 0.6 relative G at the cytidine sites Fig. b. This s1.Similarly, we found larger conductive signals around 0.9 relative G at the adenosine sites Fig. d, which We evaluated differences in the methylation ratios (5mC/C) of the cytidine sites  in the sample miR-200c-5p nucleotide by signal assembly of the right length of read sequence before and after the cytidine base number to be evaluated. The 5mC methylation ratio was the ratio of the number of methylated nucleotides to the number of non-methylated nucleotides for a given site. In the captured miR-200c-5p, 5mC/C was 0.6% for #4 (10/1606), 1.3% for #8 (28/2084), 1.4% for #9 (43/3137), 3.7% for #10 (72/1952), and 18.5% for #13 (302/1633) Fig. . Therefo30. Of the cytidine methylation sites, #4 (CUU), #8 (CCC), and #9 (CCA) match the CHH consensus sequence, and #10 (CAG) and #13 (CAG) match the CHG consensus sequence. The methylation ratios for the CHH and CHG sites were 1.2% (81/6827) and 10.4% (374/3585), respectively. These results suggest that the methylation in the miR-200c-5p sample extracted from colorectal cancer cells was induced by the NSUN2 methyltransferase.The 5mC methylation of RNA is carried out by methyltransferases, such as NSUN2. The consensus sequences targeted by NSUN2 are CHG, CHH, and CG We also evaluated the differences in methylation ratios (m6A/A) between the adenosine sites . In the captured miR-200c-5p, the methylation ratios (m6A/A) were found to be 10.9% (227/2074) for #7, 7.2% (118/1629) for #11, and 3.8% (34/905) for #14 Fig. , Fig. S231, and the consensus sequence that it recognizes is RACH . A three-base match (matching rate: 75%) to the RACH consensus sequence was found in the sequence neighboring the methylation site of #7 (UACC), and a two-base match (matching rate: 50%) was found in those of #11 (CAGC) and #14 (CAGU). The similarities to the RACH consensus sequence of the sequences neighboring the methylated adenosines suggest that miR-200c-5p methylation was induced by a METTL3 methyltransferase complex.It has previously been reported that the m6A methylation of RNA is caused by methyltransferases such as METTL3 complexFinally, we evaluated the signals of A and C methylations coexisting on a single molecule. In this study, we focused on correlating the 5mC methylation of site #13 with m6A methylation (sites #7 and #11) because the 5mC methylation was highest at site #13 compared with the other 5mC modification positions  in the miR-200c-5p sample, as shown in Fig. Importantly, both m6A and 5mC modified signal to total ratios were 4.8% (92/1936). This was the first time that simultaneous detection of m6A and 5mC in the same miRNA molecule had been achieved. These results suggest there is crosstalk between m6A and 5mC methylation. For instance, the ratio of 5mC methylation among m6A methylated signals was 30.4% (92/302), which was much larger than 18.5% of the ratio of 5mC methylated signals to the non-methylated signals (302/1634), and 20.3% of the 5mC modification to the total signal number (394/1936) . Oligonucleotide concentrations were determined by UV absorbance at 260 nm using the NanoDrop ND-1000 UV–Vis Spectrophotometer (ThermoFisher Scientific). No buffer was added to the solutions of single nucleotides. A 1-mM phosphate buffer was used for preparation of all aqueous sample oligomer solutions.Reagents and solvents were purchased from standard suppliers and used without further purification. Synthesized miRNAs were purchased from GeneDesign, Inc. Purification of oligonucleotides was performed on the Prominence High Performance Liquid Chromatograph (Shimadzu) using a COSMOSIL 5C2 atmosphere. Total RNA was extracted from cultured cells using the ISOGEN reagent  according to the manufacturer’s instructions.DLD-1 cells were purchased from the American Type Culture Collection (Manassas). DLD-1 cells were cultured in Dulbecco’s Modified Eagle Medium  supplemented with 10% fetal bovine serum  at 37 ℃ in a humidified 5% CO34. In this study, we utilized a nanochannel integrated nano-gap device and the detail device procedure are shown in the previous reports24. A polydimethylsiloxane (PDMS) cover was fused to the device substrate. The PDMS cover had a channel that connected the four hole for introducing the sample solution and the channel of the gap sensor. PDMS was purchased from Dow Corning Toray Co., Ltd. The electrophoresis electrodes were prepared by electrochemical oxidation of silver wires. A silver wire (The Nilaco Corporation) was electrochemically oxidized in 1 M NaCl using an electrochemical analyzer , and the resistance of the prepared Ag/AgCl electrode was around 20 kΩ. The formed gold nano-junction was broken by the home-made MCBJ systems24, and the sensing distance was set to 0.6–0.7 nm by the piezo element. During the measurement, the gap distance was maintained by feedback control of the piezo actuators.The nano-gap electrodes were constructed from nanofabricated mechanically controllable break-junctions (MCBJs) and the procedures for MCBJ fabrication are detailed elsewhereI–t measurement, we replaced the MCBJ sample with a new one. The measurements were carried out more than three times using different gold gap sensors.We formed a 0.8-nm electrode gap in a 0.10-μM target nucleotide solution in Milli-Q-purified water . The current across the electrodes was recorded at 10 kHz using a custom-built logarithmic current amplifier and a PXI-4071 Digital Multimeter  under a DC voltage bias of 0.4 V. The applied voltage of the electrophoresis is +/-0.6V for each of the electrophoresis chambers in the device. After every 1 h of Small RNAs (< 100 nt) including miRNA were isolated from total RNA using the High Pure miRNA Isolation Kit  according to the manufacturer’s instructions. Immunoprecipitation of m6A-containing small RNA was performed using an anti-m6A antibody (200 µg/ml)  at 4 ℃ for 2 h. The m6A-containing small RNA–anti-m6A-antibody complexes were mixed with Dynabeads Protein G  at 4 °C for 2 h. The mixture was isolated by magnetic separation. The m6A-containing small RNA was eluted from the mixture using 6.7 mM N6-methyladenosine 5-monophosphate sodium salt  at 4 °C for 2 h. The RNA not recovered by magnetic separation was designated as small RNA not containing m6A modifications.Immunoprecipitation of NSUN2 binding small RNA was performed using an anti-NSUN2 antibody  at 4 ℃ for 2 h. The m6A-containing small RNA–anti-m6A-antibody complexes were mixed with Protein A/G PLUS-Agarose  at 4 °C for 2 h. The mixture was isolated by centrifugation at 12,000 rpm for 20 s. The NSUN2 binding RNA was reverse cross-linked by incubating tubes in a 67 °C water bath, mixing occasionally over two hours. Remove beads by centrifugation and continue incubating supernatant at 67 °C overnight. The RNA not recovered by centrifugation was designated as small RNA not binding to NSUN2.Homology between the amino acid sequences of NSUN2, a cytosine methyltransferase, and YTHDF1, YTHDF2, and YTHDF3, which recognize m6A, was determined. The amino acid sequences of the proteins were obtained from NCBI Protein . For NSUN2, we used the sequence including amino acids 397–732; the RsmB domain was excluded from the analysis. The YTH domains of YTHDF1, YTHDF2, and YTHDF3  were selected from the entire amino acid sequence for analysis. The homology analysis was performed using GENETYX-MAC Ver. 18 (GENETYX CORPORATION).18 cartridge column  according to the manufacturer’s protocol. Purified miR-200c-5p was mixed with an aqueous solution of 3-hydroxypicolinic acid  in a 1:1 (v/v) ratio, and 1 µl of the mixture was applied to an MTP AnchorChip 384 target plate  and air-dried at room temperature. MALDI–TOF MS/MS analysis was performed using an ultrafleXtreme MALDI–TOF mass spectrometer  operated in negative-ion and reflectron modes. Spectra were manually acquired by FlexControl software v. 3.3.108.0 .Total RNA was hybridized with single-strand DNA oligonucleotides complementary to miR-200c-5p (5′-CCA AAC ACT GCT GGG TAA GAC G-3′) that were adenosine-methylated at the 5′ end via a C6 linker purchased from Hokkaido System Science Co., Ltd. The mixture was heated to 95 °C, then gradually cooled to 30 °C to anneal miR-200c-5p and the complementary DNA. The miR-200c-5p–DNA complex was incubated with Dynabeads M-270 Amine  at 4 °C for 1 h. The mixture was heat-eluted and the supernatant obtained by magnetic separation. Lyophilized samples were used for subsequent experiments. Captured miR-200c-5p was purified using a ZipTip CSupplementary Information.


Extreme disturbances such as hurricanes can cause reductions in coral cover and three-dimensional (3D) structural complexity of coral reefs. We examined changes in structural complexity utilizing 3D reconstruction of a coral-reef site before and after Hurricane Walaka passed through Lalo of the Northwestern Hawaiian Islands. This event resulted in complete destruction of the coral-reef habitat, with dramatic changes in benthic cover from pre-hurricane tabulate coral to post-hurricane rubble. Rugosity and mean slope decreased after the hurricane, while structural complexity, captured by vector ruggedness measure (VRM), showed resolution-specific responses. This metric captured the structural complexity of rubble at a high raster resolution of 1 cm and that of tabulate coral at lower resolutions, resulting in decreases in mean VRM values at 2- and 4-cm resolutions but an increase at 1-cm resolution. Variability in profile and planform curvature was reduced after the hurricane due to a disappearance of extreme curvature values created by the tabulate coral after the hurricane. This study highlights the varying responses of habitat complexity metrics to the complete destruction of a coral reef and provides us with insights into how choices of habitat complexity metrics can affect quantitative assessments of 3D habitat structure. For example, Hurricane Allen was one of the strongest recorded Category 5 hurricanes in the Caribbean and produced waves up to 12-m high causing significant damage to shallow-water coral reefs2. Loss of live coral cover and habitat structural complexity caused by such disturbance events can lead to detrimental losses in the abundance and diversity of reef organisms, which in turn impact the health and function of coral reef ecosystems7. Long-term monitoring of coral reefs allows for pre- and post-disturbance comparisons and can be used to assess reductions in the abundance of live coral cover and resulting declines in the three-dimensional (3D) structural complexity of coral reefs8.Extreme natural disturbance events, such as hurricanes and cyclones, are projected to increase in frequency and severity in the future10. Structurally complex branching or tabulate corals are generally more vulnerable to wave damage than corals with more robust and stable growth forms, such as mounding and encrusting corals11. In addition, coral communities that exhibit high diversity and richness often show a greater resistance to physical disturbance than monotypic communities12. This is especially concerning for areas with low species richness and diversity, such as the Hawaiian archipelago. Due to the isolation of the Hawaiian Islands, coral reefs in this area show lower species richness and higher endemism than those found in Indo-Pacific or Caribbean13. Thus, Hawai ‘i’s monotypic reef habitats that are comprised primarily of coral colonies with delicate morphologies are of particular interest when assessing the potential impacts of storm disturbances.The vulnerability of corals to storms differs among species, with delicate morphologies typically becoming increasingly vulnerable to dislodgment and mortality as they grow in size13. In October 2018, Hurricane Walaka, which is ranked as the second strongest tropical cyclone in the Central Pacific to date, passed through the NWHI reaching and travelling along a high latitude of 23° North15. Walaka originated from an area of low pressure south-southeast of Hawai‘i Island and strengthened as it entered the Central Pacific, eventually becoming a Category 5 hurricane on the Saffir-Simpson Hurricane Scale. Hurricane Walaka produced maximum high winds of 205 km/h, and the wave heights associated with the hurricane while it passed through Lalo  in the NWHI on 3 October 2018 are estimated to have been 11–15 m . The hurricane caused severe damage to coral reefs on the southern end of the shoal and destroyed a unpopulated island of Lalo named East Island15.Historically, coral reef ecosystems in the Northwestern Hawaiian Islands (NWHI), contained within the Papahānaumokuākea Marine National Monument, were rarely in the track of tropical storms and hurricanes17. The main objective of this study was to examine how different habitat metrics responded to the complete destruction of the study site. The photogrammetry and data processing techniques presented here are valuable to any marine ecologists requiring detailed quantitative analyses of changes occurring to 3D habitat complexity and can be easily adapted into existing coral reef monitoring efforts.We applied photogrammetric techniques to quantify structural changes caused by Hurricane Walaka to an iconic coral-reef study site referred to as Rapture Reef . Images were taken from a planar angle approximately 1 m above the substrata in a boustrophedonic (lawn mower) pattern with 70 ~ 80% overlap between images  photogrammetry methods were used to create 3D reconstructions of the coral-reef plot before and after the hurricane using Agisoft Photoscan/Metashape Professional software  following the methods described in Burns et al.Two-dimensional orthophotomosaics were imported into CoralNet website to compute the percent cover of corals, other invertebrates, algae and abiotic features. For each orthophotomoasic, 1000 random points were generated for manual annotation without any assistance from CoralNet’s auto-annotation function. All live coral were identified down to genus and morphology. Percent cover was obtained for each survey by dividing the number of points for each category by the total annotation points. Annotation points that landed on a transect tape, scale bars and mobile fauna were removed from total number of annotation points.22 and rgeos23 packages following the procedure of Fukunaga et al.24 to obtain the following habitat metrics  due to the computational difficulties associated with quantifying 3D mesh surfaces. Analyzing DEMs is a conventional approach for geospatial analyses of topographic features, and our recent research has found the structural metrics used in this study to be highly correlated when extracted from either a DEM or DSM17.DEMs were exported at 1-cm raster resolution, which was determined to be the smallest possible cell size while ensuring to be reasonably well within the range of model accuracy (i.e. millimeter-level accuracy) as reported in the results by the ground sampling distance and Root Mean Squared Error (RMSE) values obtained from ground control points (i.e. objects/features of known distances/dimensions) in the models. Both DEMs were processed in R using rasterics Data : surface25. Slope measures an elevational change in degree (i.e. steepness) for each cell of a DEM using 3 × 3 raster cell windows 27. Vector ruggedness measure is a computation of surface ruggedness based on the variability in the surface directions of DEM cells, which are determined by a combination of slope and aspect (face direction), and is calculated for each cell using 3 × 3 cell windows28. Curvature measures the rate of change in slope; profile curvature looks at the direction parallel to slope and planform curvature looks at the direction perpendicular to slope29. Similar to slope and VRM, profile and planform curvature are calculated for each cell of a DEM using 3 × 3 cell windows.Surface complexity is analogous to reef rugosity measured by the classic chain-and-tape method and is calculated for each DEM as the ratio of the total 3D surface area to 2D planar area17. For example, this metric captures the structural complexity of branching corals at a high resolution of 1 cm as the resolution is fine enough to capture coral branches17. The structural complexity of mounding corals is, on the other hand, better captured at a low resolution of 4 cm, as this resolution can capture the smooth convex surface of mounding morphology well and is course enough not to be affected by finer structures 17. The habitat metrics computed in the present study were, therefore, reef rugosity at 1-cm resolution, slope at 1-cm resolution, VRM at 1-cm, 2-cm and 4-cm resolutions and profile and planform curvature at 1-cm resolution. We aimed to capture the architectural complexity of branching and encrusting corals with VRM at 1- or 2-cm resolution and the complexity of mounding and tabulate corals with VRM at 4-cm resolution16. Curvature was included as this metric has the potential to capture the structural complexity of the survey plot created by surface topography such as holes and small ledge-like structure17.All habitat metrics were computed at 1-cm DEM resolution. Additionally, the aggregate function in the raster package was used to calculate VRM at 2- and 4-cm resolutions as VRM at these resolutions have varying capacity to capture the structural complexity of certain coral morphologies, other sessile benthic organisms or topographic featuresThe use of DEMs allowed us to utilize the entire DEM cells to calculate habitat metrics for the given area (i.e. the reef plot), thus the entire distribution of each habitat metric could be compared before and after the hurricane. We did not use any statistical tests to compare these values as we obtained the habitat metrics utilizing the entire population (i.e. every single cell of the DEMs) within the reef plot, not random draws of samples from the population. The mean and standard deviation values reported in the present study are the true mean and standard deviation values of the population, not their estimates based on sample mean and standard deviation values, thus any changes in these values before and after the hurricane are real changes that occurred within the reef plot.Acropora coral on the benthos before the hurricane, while no live corals are evident after the hurricane. Numerically, the survey plot was comprised of 69.7% tabulate Acropora (mostly A. cytherea), 0.8% encrusting Porites, 0.1% encrusting Montipora, 1.7% crustose coralline algae, 0.7% sand and 27.0% turf algae on hard substrata before the hurricane. Benthic cover after the hurricane was 67.9% turf algae on rubble and 31.8% sand. There were no other invertebrates detected in the survey year 2017 or 2019.The change in the benthic community of Rapture Reef before and after the hurricane was striking and visually apparent in site photographs Fig.  and orthGround sampling distance (GSD) values (resolution/pixel) for the 3D reconstructions generated for survey years 2017 and 2019 were 0.00128 m/pix and 0.00039 m/pix, with errors of 0.003 pixels and 0.073 pixels, respectively. Root mean standard error (RMSE) values for ground control points for the 2017 and 2019 survey years were 0.00143 m and 0.00136 m, respectively. Reef rugosity obtained at 1-cm DEM resolution decreased from 1.72 to 1.16 following Hurricane Walaka  turning into rubble as slope is the measure of steepness27  to 1 (highest variation), with most natural environments exhibiting VRM values of less than 0.40ric Fig. b was con17 Table . The incgy Table .29. In coral-reef habitats, the juxtaposition of concavity and convexity makes interpretation of mean curvature values difficult. The overall distribution of curvature values obtained from the DEM offers more meaningful information for interpreting the complexity of coral-reef habitats17  angle in the present study meant that the habitat created under the tabulate Acropora at the reef site (mostly A. cytherea) would not be effectively captured in the DEMs. Nevertheless, the presence of Acropora in the pre-hurricane plot and its loss in the post-hurricane plot were sufficiently captured by the changes in mean slope, mean VRM at 4-cm resolution and the range in curvature values. The varying (i.e. resolution-specific) responses of VRM also highlights the importance of understanding the unique properties of different habitat metrics; if VRM at 1-cm resolution was the only metric to be used to quantify the changes in the structural complexity before and after the hurricane, we would have reached, counterintuitively, a conclusion of an increase in the structural complexity of the reef site. This study illustrates the value of examining metrics of 3D habitat complexity across a range of scales and resolutions to accurately measure how changes in benthic composition will impact the architectural complexity of coral reef habitats, and in turn, affect reef biodiversity. Table The present study quantified structural damage caused by Hurricane Walaka at a single site of Lalo (i.e. Rapture Reef) and was not designed to assess the overall impacts of the hurricane. Rather, with the presence of pre-hurricane 3D reconstruction from a long-term monitoring project, it utilized the unique opportunity to determine how the complete destruction of the living coral community and entire loss of aggregate carbonate reef structure affected metrics of 3D structural complexity. The entire loss of aggregate carbonate habitat presents a novel scenario as other studies examining changes in 3D habitat structure following large-scale coral mortality studied habitats that retained the carbonate reef structure from the coral skeletons33. Acropora cytherea creates structurally complex habitats due to the distinct tabulate morphology and associated overhangs where reef fishes are often found in high abundance20. Despite the high abundance and diversity of reef fish at Rapture Reef prior to the hurricane19, no reef fish was observed at the site during the 2019 survey with the exception of a single shark , highlighting the potentially devastating impact of the loss of structural complexity and microhabitat created by tabulate Acropora on the reef ecosystem. The post-hurricane data in the present study can now serve as baseline data to document the potential recovery of iconic Rapture Reef in coming years, being contingent upon successful coral recruitment onto the unstable substratum consisting of unconsolidated rubble. Proper understanding of unique properties of different 3D habitat metrics, with varying capacity to capture the structural complexity of different morphologies and topographic features, is vital when quantifying the structural changes in coral-reef habitats over time. As extreme weather events are expected to increase in frequency and severity due to climate change, such understanding is essential to continuous long-term monitoring and assessment of ecologically, economically, and culturally important coral reef ecosystems.The importance of reef rugosity or surface complexity to the health and function of coral-reef ecosystems has been known for decades, with many studies documenting positive associations between the structural complexity of habitats and reef fish assemblagesSupplementary Information.