Strong linkage between benthic oxygen uptake and bacterial tetraether lipids in deep-sea trench regions

Domain: earth_science
Published: 2024-04-23
Editorial outcome: minor_revision

Abstract
Oxygen in marine sediments regulates many key biogeochemical processes, playing a crucial role in shaping Earth’s climate and benthic ecosystems. In this context, branched glycerol dialkyl glycerol tetraethers (brGDGTs), essential biomarkers in paleoenvironmental research, exhibit an as-yet-unresolved association with sediment oxygen conditions. Here, we investigated brGDGTs in sediments from three deep-sea regions (4045 to 10,100 m water depth) dominated by three respective trench systems and integrated the results with in situ oxygen microprofile data. Our results demonstrate robust correlations between diffusive oxygen uptake (DOU) obtained from microprofiles and brGDGT methylation and isomerization degrees, indicating their primary production within sediments and their strong linkage with microbial diagenetic activity. We establish a quantitative relationship between the Isomerization and Methylation index of Branched Tetraethers (IMBT) and DOU, suggesting its potential validity across deep-sea environments. Increased brGDGT methylation and isomerization likely enhance the fitness of source organisms in deep-sea habitats. Our study positions brGDGTs as a promising tool for quantifying benthic DOU in deep-sea settings, where DOU is a key metric for assessing sedimentary organic carbon degradation and microbial activity.

Introduction
Marine sediments constitute the largest repository of reactive organic carbon on Earth and serve as crucial archives for reconstructing climate history1. In sediments, the oxygen exchange rate is a critical metric for assessing the balance between the preservation and degradation of sedimentary organic matter. This balance directly impacts global atmospheric CO2 levels, thereby influencing long-term climate patterns2. Additionally, benthic oxygen availability plays a vital role in regulating numerous biogeochemical processes and profoundly affects the biology and ecology of benthic communities3,4. Despite its importance, current methodologies for quantitatively assessing benthic oxygen distribution and availability, especially in deep-sea environments, remain notably constrained3,5. This limitation underscores the need for innovative indicators like biomarkers, which are preserved in sediments and provide valuable insights into environmental conditions and biogeochemical processes6.

Among these biomarkers, branched glycerol dialkyl glycerol tetraethers (brGDGTs) are particularly notable for their utility in paleoclimate reconstructions7–9. Recent advancements in brGDGT research have unveiled potential connections between these biomarkers and benthic oxygen conditions in sediments10–12. Originating from bacteria, brGDGTs consist of two alkyl chains ether-linked to glycerol-3-phosphate (G3P). They exhibit 15 common unique structures, characterized by variations in methylation and cyclization degrees, as well as by their presence in different isomeric forms (e.g., 5- and 6-methyl brGDGTs; Fig. S1)13–15. These structural variations are captured by indexes such as the Methylation, Cyclization, and Isomerization indexes of Branched Tetraethers (MBT, CBT, and IR, respectively). Notably, these indexes and their derivatives have demonstrated robust empirical relationships with environmental factors like temperature and pH on both regional and global scales13,14,16.

One pertinent advancement lies in the expanded knowledge of diverse environmental origins of brGDGTs17–20. Initially, brGDGTs were thought to be specific for terrestrial environments, forming the basis for their use as proxies in studying terrestrial paleoclimate14,21. However, mounting evidence indicates that brGDGTs also originate from marine environments18, including estuaries19, continental shelves22, the deep ocean23, and the hadal zone24. Marine-derived brGDGTs can come from both planktonic and benthic bacteria10,25. While the extent to which these sources contribute to the sedimentary brGDGT pool remains debated, growing evidence supports that marine-derived brGDGTs preserved in sediments, especially in deep-ocean contexts10,23, are primarily biosynthesized by sediment-dwelling bacteria. These findings present opportunities for utilizing brGDGTs to explore marine benthic environments10. However, the environmental factors governing the distribution of marine-derived brGDGTs largely remain to be elucidated.

Another advancement is the growing recognition of the impact of oxygen on the production and distribution of brGDGTs26. Oxygen availability plays a vital role in microbial processing and in shaping microbial communities27, presumably including bacteria responsible for brGDGT biosynthesis15,28. Early investigations revealed substantially elevated brGDGT concentrations in the anoxic zones of peats, indicating anaerobic or facultative anaerobic bacteria as the primary producers of brGDGTs15. Further studies have examined brGDGTs across oxygen gradients in various ecosystems, including soils29, peats30, as well as in both the water column and sediments of lakes11,12,20 and oceans25, but provided divergent perceptions. Some studies suggest that oxygen depletion stimulates brGDGT production, while others argue that brGDGT production is favored by oxygen, and that certain brGDGT compounds are produced by aerobic or facultative aerobic bacteria11,12,30. Conflicting observations regarding the association of brGDGTs in low-oxygen conditions with either more or less methylated compounds have also been reported11,20,25. Recent culture-based studies have not established a clear consensus either28,31–34. The intricate relationships between brGDGTs and oxygen observed in both cultural and environmental samples strongly highlight the need for further investigation into the role of oxygen in brGDGT compositions and distributions.

It is reasonable to surmise that benthic oxygen conditions may impact the activity and composition of benthic bacteria, thereby influencing the in-situ production of brGDGTs. However, any specific linkage between benthic oxygen and sedimentary brGDGTs remains unresolved. Quantifying their linkage could be of great importance, as it may reveal the specific oxygen conditions favorable for brGDGT biosynthesis, enhance our understanding of the ecophysiological behavior of marine brGDGT-producing bacteria, and offer a potential molecular approach to resolve benthic oxygen conditions in marine sediments at both modern and geological timescales.

In this study, we investigated brGDGT distributions in dozens of sediment cores collected from the Atacama, Kermadec, and Mariana trench regions, with water depths ranging from 4045 to 10,100 m (Fig. 1A). Notably, each targeted trench region lies beneath water columns with varying levels of productivity, ranging from the oligotrophic Mariana, to the mesotrophic Kermadec, and to the eutrophic Atacama regions35. Sediments in these deep-sea trench regions are characterized by extremely high pressure (>40 MPa) and consistent bottom water temperature (ca. 2°C)36. Owing to their relatively long distance from major landmasses, their sedimentary organic carbon exhibits minimal terrestrial influence, predominantly originating from marine sources24,37. Additionally, these sites present varied oxygen microprofiles, encompassing a diffusive oxygen uptake (DOU) range of over one order of magnitude (Fig. 1B)38,39. These characteristics make our targeted trench systems ideal for investigating the linkage between benthic oxygen conditions and marine-derived brGDGTs.

Results
Distribution and origin of brGDGTs in trench regions
All supporting data are detailed in Supplementary Data 1–4, with the principal data summarized in Table S1. Despite the considerable water depths, our sediment cores exhibit relatively high sedimentation rates attributed to the trench’s V-shaped topography, ranging from 0.03–0.08 cm yr−1 in the Atacama Trench (AT), 0.03–0.04 cm yr−1 in the Kermadec Trench (KT), and 0.04 cm yr−1 in the Mariana Trench (MT)39–41. Consequently, the sediment cores from these sites, with lengths <40 cm, are estimated to represent a depositional age of <1.2 kyr.

The concentrations of brGDGTs at all depths in sediment cores were 215±170 ng g−1 (mean±standard deviation; same hereafter) for the AT, 12±7 ng g−1 for the KT, and 15±3 ng g−1 for the MT, respectively. When normalized to the total organic carbon (TOC) content, the concentrations were 36±29, 4±1, and 5±1 μg g−1 TOC for the AT, KT, and MT, respectively. Notably, the distribution of brGDGTs exhibited relatively small variations across different sediment depths in all three hadal trenches (Fig. 2A), implying that the proportion of individual brGDGT compounds, along with brGDGT-based proxies, remained largely consistent irrespective of whether the values were from the surface, bottom, or averaged across the core.

In all three trench regions, the non-cyclized brGDGT compounds (IIIa, IIIa’, IIa, IIa’, and Ia) were predominant. They constituted 96±1% in the MT, 78±8% in the KT, and 76±7% in the AT (Fig. 2A; Supplementary Data 2). In contrast, the mono-cyclized (IIb, IIb’, and Ib) and di-cyclized brGDGTs (IIc, IIc’, and Ic) were much less prevalent, comprising only 2±1% and 1±0% in the MT, 16±6% and 6±2% in the KT, and 17±5% and 7±2% in the AT, respectively. The Principal Coordinate Analysis (PCoA) of Bray Curtis dissimilarities in the brGDGT data revealed compositional and distributional variations at both inter- and intra-trench scales (Fig. 2B). These variations predominantly mirrored the methylation and isomerization degrees of brGDGTs. Specifically, at the inter-trench scale, the MT exhibited significantly higher abundances of 6-methyl brGDGTs (MT, 100%; KT, 73±15%; AT, 56±19%) and hexamethylated brGDGTs (MT, 73±2%; KT, 37±14%; AT, 26±7%), paired with higher IR values (MT, 1.0±0.0%; KT, 0.7±0.1%; AT, 0.6±0.2%), relative to the KT and AT (p<0.001) (Fig. 2A; Supplementary Data 2). At the intra-trench scale, notable differences were observed between non-hadal sites (depth <6000 m) and hadal sites (depth >6000 m42). The non-hadal sites displayed higher abundances of 6-methyl brGDGTs (KT, 95±4%; AT, 82±5%) and hexamethylated brGDGTs (KT, 59±6%; AT, 36±7%), accompanied by higher IR values (KT, 0.9±0.0%; AT, 0.8±0.1%). Whereas the hadal sites showed significantly lower abundances of 6-methyl brGDGTs (KT, 67±10%; AT, 48±15%) and hexamethylated brGDGTs (KT, 30±7%; AT, 23±3%), along with decreased IR values (KT, 0.7±0.1%; AT, 0.5±0.1%) (p<0.001). The variations in major brGDGT compounds, especially regarding the number of methyl groups and isomeric forms, are closely associated with DOU variations (Figs. 2A, 3A), hinting at a tight interrelationship. A comprehensive exploration of this connection will be delineated in the following section.

The branched isoprenoid tetraether (BIT) index21, a proxy signifying terrestrial influence, generally displays values <0.15 for open marine sediments and approaches 1 for soils7,21. For our trench sites, BIT values ranged from 0.02 to 0.05 (0.03±0.01) in the MT, 0.02 to 0.24 (0.07±0.05) in the KT, and 0.02 to 0.26 (0.07±0.05) in the AT. The ΣIIIa/ΣIIa index, another widely used tool for assessing the origin of brGDGTs10,18, ranged from 5.58 to 8.35 (7.14±0.98) in the MT, 1.00 to 4.16 (2.00±1.03%) in the KT, and 0.55 to 3.69 (1.45±0.91) in the AT (Fig. S2A; Supplementary Data 2). The ΣIIIa/ΣIIa index generally yields values <0.59 in soils; while in marine sediments, values are typically 0.59–0.92 for sites with terrestrial influence and typically >0.92 for sites lacking terrestrial influence10,24. Thus, both the BIT and ΣIIIa/ΣIIa indexes imply a predominantly marine origin for the brGDGTs in most trench sediments, although some AT sediments may demonstrate a slight terrestrial influence. These results are consistent with those obtained from the ternary diagram reflecting the fractional abundance of tetra-, penta-, and hexamethylated brGDGTs (Fig. 3B)22, as well as the ΣIIIa/ΣIIa vs. IIIa’ diagram (Fig. S2B)24, both of which support that brGDGTs in our settings are primarily of marine origin. Notably, in-situ production of brGDGTs in marine environments is prevalent18, a phenomenon we contend that is particular pronounced within our trench regions, distanced from terrestrial sources. This is also supported by the elemental and isotopic signatures of sediment organic carbon37,43.

In our study, given the close geographic proximity of the different sites within each trench (e.g., KT6 vs. KT7, AT9 vs. AT10, and AT3 vs. AT7; all < 150 km; Fig. 1A), the biogeochemical/physical factors like temperature, salinity, dissolved oxygen concentration, and pH in the water column exhibited minimal differences44,45. However, we note striking variations in brGDGT compositions and distributions across sediments (Fig. 2A). Such findings imply that brGDGTs in the trench sites are likely primarily produced within the sediments; and the variability in brGDGTs likely reflect the conditions of benthic environments, such as benthic DOU, a topic that will be discussed in the following section. This inference aligns with a growing body of research suggesting that marine-derived brGDGTs present in sediments predominantly originates from benthic bacteria inhabiting the sediments, particularly in deep-sea settings10,23.

Relation between benthic oxygen uptake and brGDGTs
The prevailing concept posits temperature and pH are the key factors influencing the composition and distribution of brGDGTs in terrestrial environments13,14. However, in hadal trench sites, where bottom water temperatures are consistently around 2°C, temperature is not likely the principal determinant affecting brGDGTs. This viewpoint is supported by substantial derivations in reconstructed temperatures using the MBT’5ME index (AT, 4–16°C, 10±3°C; KT, 8–19°C, 13±3°C; MT, 23°C)13. Despite the absence of in situ sediment porewater pH measurements, pH estimates derived from the CBT5ME index (AT, 5.9–7.2, 6.6±0.3; KT, 6.2–7.2, 6.9±0.3; MT, 6.1–6.1, 6.4±0.2) show an acidic deviation from the typically alkaline pH of hadal bottom seawater and sediment porewater44,46,47, suggesting that pH might not be the main influence on brGDGTs. To pinpoint the primary determinant of brGDGT variability, we performed correlation analyses comparing both the fractional abundance and concentration of brGDGTs with multiple parameters. These included surface and bottom water temperatures, geographic variables (latitude, longitude, water depth, and sediment depth), bottom water and sediment porewater oxygen concentrations, diffusive oxygen uptake rate (DOU), concentrations of organic matter (TOC) and total nitrogen (TN), the TOC/TN ratio, and surface net primary productivity (NPP) (Fig. 4 and S3; Supplementary Data 3). Our results unequivocally underscore DOU as the most significant parameter influencing the composition and distribution of brGDGTs across both inter- and intra-trench scales.

DOU denotes the consumption rate of dissolved oxygen within sediment porewater, especially in deep-sea cohesive sediments with minimal fauna activities. This oxygen consumption encompasses aerobic microbial respiration and the reoxidation of reduced products (e.g., NH4+, H2S, Fe2+, Mn2+, FeS, and FeS2) produced from underlying anaerobic mineralization processes3,5. Thus, DOU serves as a crucial metric for assessing the intensity of microbial-mediated diagenetic activity, the degradation rate of sedimentary organic carbon, and the activity levels of benthic communities3,39. DOU is influenced by many factors including water depth, TOC, NPP, temperature, bottom water oxygen concentration, faunal activities, and the physical characteristics of the sediment5. Our correlation analysis reveals relationships between DOU, NPP, TOC, and brGDGT concentrations. Moreover, beyond DOU, factors like NPP, TOC/TN, and bottom water oxygen concentration, also exhibit correlations with brGDGT fractional abundances (Fig. 4 and S3). However, regardless of the inter-trench or intra-trench scale, the relationship between DOU and brGDGTs stands out as markedly more robustness than the other parameters. While previous studies have primarily focused on oxygen concentration and its influence on the abundance and composition of brGDGTs11,28, our study reveals that with shifts in sediment depth and the accompanying pronounced oxygen concentration decline, the brGDGT compositions see only minor alternations (Fig. 2A). This points to the idea that oxygen concentration may not be the primary determinant affecting brGDGTs in deep-sea sediments. Instead, the role of DOU, which potentially controls the intensity of microbial-driven early diagenesis, emerges as pivotal. These findings may offer insights into the conflicting reports concerning the role of oxygen concentration on brGDGT compositions and distributions as noted in both environmental and cultural studies11,20,25,28,31–33.

Variability in DOU spans across different sampling sites, showing values of 355–1793 μmol m−2 d−1 in the AT, 152–538 μmol m−2 d−1 in the KT, and 154–165 μmol m−2 d−1 in the MT38,39. Overall, trench axis sites display heightened DOU levels and intensified microbial activities than their adjacent abyssal counterparts38,39. Correspondingly, trench axis sites demonstrate markedly lower methylation and isomerization degrees of brGDGTs. In low DOU sites (e.g., MT1 and KT7), brGDGTs are predominantly composed of IIIa’ (>50%). Moderate DOU sites (e.g., AT9 and KT3) exhibit a prevalence of IIIa’ and Ia, while high DOU sites (e.g., AT3 and AT4) feature Ia and IIa as the primary brGDGTs (Fig. S4). Regression analysis across the three trench regions uncovers a robust positive correlation between DOU and Ia, IIa, and IIIa compounds (r=0.86, 0.72, and 0.94, respectively; p<0.001; Fig. 3A). Conversely, IIa’ and IIIa’ display a strong negative correlation with DOU (r=−0.91 and −0.86, respectively; p<0.001). These compounds, primarily reflecting the degree of methylation and isomerization, constitute over 70% of total brGDGTs. The cyclic compounds like Ib, Ic, IIb and IIc are much less abundant and exhibit no significant correlation with DOU (Fig. 3A), suggesting that the cyclization degree of brGDGTs is weakly related to DOU. The robust relationship observed between DOU and major brGDGT compounds implies that brGDGTs are primarily produced in situ within sediments and are significantly influenced by the intensity of benthic oxygen consumption or the microbial diagenetic activity.

A brGDGT-derived index for benthic oxygen uptake
Based on the strong positive correlation between DOU and Ia, IIa, and IIIa compounds, as well as the strong negative correlation between DOU and IIa’ and IIIa’ compounds, we established the Isomerization and Methylation index of Branched Tetraethers (IMBT) as a quantitative indicator of DOU (Eq. 1).

IMBT = log[(IIIa’ + IIa’) / (IIIa + IIIa’ + IIa + IIa’ + Ia)] (1)

log[DOU] = 1.5 * IMBT + 2.1 (r=0.88, RMSE=400 μmol m−2 d−1, p<0.001) (2)

The IMBT index represents the degree of isomerization and methylation of the acyclic brGDGTs, with lower values indicating a higher abundance of 6-methy penta- and hexamethylated compounds, and vice versa. The IMBT index shows a significant positive correlation with DOU (r=0.88, RMSE=400 μmol m−2 d−1, p<0.001, Fig. 5A, Eq. 2). Note that both linear and logarithmic forms of the IMBT yield analogous correlation coefficients with DOU within the observed DOU range for the trench sites (100 to 2000 μmol m−2 d−1). However, we opted for the logarithmic form of IMBT as the linear model would confine the proxy values between 0 and 1. Such a linear model would inherently suggest that the corresponding DOU values are restricted to <4000 μmol m−2 d−1. Our study, while centered on sediments from deep-sea trench regions, encompasses three distinct trench areas and multiple stations across diverse geographical settings and varied water depths. This breadth reinforces the observed relationship between IMBT and DOU, hinting at its potential universality in deep-sea settings, which are typically characterized by DOU values ranging from 50 to 4000 μmol m−2 d−15. Collecting additional data from abyssal and bathyal sites would solidify these findings in the future.

We conducted a sensitivity analysis to examine the susceptibility of brGDGT compositions to variations in DOU (Fig. 5B). The results highlight that the brGDGT compositions are especially variable under lower DOU values. For instance, within the DOU range of 100 to 2000 μmol m−2 d−1, there is a considerable shift in the proportion of IIIa’ and IIa’ compounds among the acyclic brGDGTs, ranging from 100% to 20% (Fig. 5B). Generally, deep-sea sediments exhibit lower DOU levels (50–4000 μmol m−2 d−1), while coastal sediments tend to have higher DOU levels (2000–100,000 μmol m−2 d−1)5. Therefore, deep-sea sediments would exhibit a broader diversity in their brGDGT distribution patterns, as evidenced by observations from the deep sea mount sediments of the Western Pacific Ocean (at depths of 4400 to 5800 m)48 and the South China Sea (at depths of 700 to 3100 m)49. Notably, the variation in brGDGT compositions can become even more pronounced in the deepest hadal trenches, which are characterized by highly heterogeneous environments (Fig. 2A)42. It is important to acknowledge that DOU values in our trench regions sites spanned from 100 to 2000 μmol m−2 d−1, and further investigation is warranted to determine the continued validity of the empirical formula between IMBT and DOU in shallow regions with higher DOU values. However, in shallow marine regions, DOU is frequently impacted by benthic fauna activities3,5, while simultaneously, brGDGTs in these regions tend to be more affected by terrestrial influences and other environmental parameters, like temperature. Consequently, investigating the quantitative correlation between DOU and IMBT in shallow marine settings is likely to be more complicated.

Furthermore, we compared the IMBT index with other commonly used brGDGT indexes, including MBT’5ME, CBT5ME, DC’ (degree of cyclization)50, IR, and CBT’13 (Fig. S5 and S6). The analysis revealed that IMBT strongly correlates with indexes related to brGDGT methylation and isomerization (e.g., MBT’5ME and IR; absolute r values, |r|>0.85), while showing much weaker correlations with cyclization indexes (e.g., CBT5ME and DC’; |r|<0.35). This pattern extends to DOU, which exhibits strong correlations with methylation and isomerization indexes (|r|>0.70), but only minimal correlations with cyclization indexes (|r|<0.30) (Figs. S5, S6). Notably, the correlation between DOU and IMBT stands out as the most pronounced among these indexes. Considering the established association of methylation indexes with temperature and isomerization indexes with pH13,14, the influence of DOU is crucial in evaluating the reliability of methylation-based temperature and isomerization-based pH indexes, especially in marine settings characterized by predominant in-situ brGDGT production.

Supporting evidence for the IMBT
To our knowledge, no prior research has simultaneously examined both brGDGTs and DOU. This leaves us dependent on indirect insights from existing literature to gauge the applicability and validity of the IMBT index. In a regional case study of the southeastern Brazilian continental margin, where brGDGTs in 46 core-top sediments have been reported along cross-margin transects spanning water depths from 25 to 3000 m51, the region demonstrated minimal terrestrial influence and predominantly in-situ marine brGDGT production51. As water depth increases and distance from the coastline grows, it would be reasonable to conclude that benthic DOU diminishes (Fig. 6A). Correspondingly, the IMBT index consistently demonstrates a clear declining trend. Furthermore, on a global scale, a systematic decrease in benthic DOU is observed with increasing water depth5, aligning with the decreasing values of the IMBT index (Fig. 6B).

Thus, the parallel decrease in both the IMBT index and DOU with increasing water depth, observed at both the regional and global scales, hints at a strong linkage between the IMBT index and benthic DOU in marine settings. Notably, data from trench sediments exhibit a deviation from the global correlation between IMBT and water depth (Fig. 6B), owing to the relatively heightened microbial dynamics of hadal trenches which exhibit elevated DOU levels compared to adjacent abyssal plains38,39. These observations bolster the credibility of the IMBT index, underscoring its value as an indicator of DOU variations and suggesting its broad applicability across different spatial scales.

The global correlation between IMBT and water depth (Fig. 6B) hints at a potential role of hydrostatic pressure on IMBT. However, the elevated IMBT values in trench sediments, which experience significantly higher hydrostatic pressures compared to nearby abyssal sediments (e.g., KT6 vs. KT7, and AT3 vs. AT7; Supplementary Data 2), cast doubt on this notion. The paucity of research on how pressure influences brGDGTs hinders a clear assessment of its impact on IMBT.

Potential mechanism underlying the IMBT
The empirical relationships between brGDGTs and environmental parameters, whether driven by the direct physiological adaptations of source bacteria to changing environments, and/or the indirect restructuring of bacterial communities, remain an open question52. Several biogeochemical and microbial studies have investigated the sites examined in this study38,53–55. Our trench core sediments display redox stratification into oxic, nitrogenous, and ferruginous zones53,54. Despite bathymetric and depositional heterogeneity, microbial communities exhibit high similarities among sediments sharing similar redox stratifications within each trench, while vary strongly with sediment depth following redox gradients55. In contrast, our examination of brGDGT compositions reveals minor variations along vertical redox gradients but distinct differences between different trenches and sites (Fig. 2A). These findings prompt speculation that brGDGT variations might not be primarily driven by bacterial community shifts within trench sediments.

Molecular dynamics simulations suggest that increased methylation in brGDGTs can enhance membrane fluidity56. While terrestrial brGDGT-producing bacteria have been shown to adapt to temperature by synthesizing brGDGTs with varied methyl branches14,31,32, there is limited insight into the ecophysiological behaviors of marine brGDGT-producing bacteria. In trench region sediments, despite consistently cold bottom water temperatures (ca. 2°C), notable variations in methylation and isomerization degrees of brGDGTs primarily correspond to DOU rather than temperature, suggesting that temperature is not the predominant influencer of IMBT in these settings, as discussed above. In the deep ocean, DOU levels typically reflect microbial diagenetic intensity3,39. The correlations observed across our study sites between NPP, TOC, DOU, and brGDGT concentrations (Fig. 4 and S3) suggest a likely connection between a decreased supply of organic carbon and lower concentration of brGDGTs, alongside reduced DOU levels—indicative of diminished microbial diagenetic activity3,5. Further, there is evidence indicating that methylation in membrane molecules aids organisms to cope under nutrient or energy constraints57. For example, 3-methylhopanoids promote cell viability under nutrient scarcity58, and increased backbone methylation appears in archaeal GDGT lipids during stationary phases and in nutrient-deprived sediments59. Hence, we propose that increased methylation and isomerization of brGDGTs may enhance the fitness of source organisms in deep-sea habitats under nutritional limitations, which usually coincide with reduced microbial activity and lower DOU levels3,5. Compared to methylation, isomerization of brGDGTs may be even more influential, as evidenced by the opposing trends observed in IIIa and IIIa’ with respect to DOU, while consistent trends are observed in IIIa’ and IIa’ (Fig. 3A). However, our understanding of how brGDGT isomerization affects membrane properties remains limited. To comprehensively discern how marine brGDGT-producing bacteria modulate their methylation and isomerization in response to microbial diagenetic intensity, further investigations involving environmental experiments, incubation tests, and molecular simulations are essential.

Implications and significance of the IMBT
The observed correlation between brGDGTs and DOU within our trench region sites implies that marine-derived brGDGTs preserved in deep-sea sediments are primarily produced by benthic bacteria within sediments and are strongly related to benthic oxygen consumption or microbial diagenetic activity. Our results challenge the conventional view that brGDGTs are mainly produced by anaerobic or facultatively anaerobic bacteria15,60. Instead, our study indicates that aerobic or facultatively aerobic bacteria in marine sediments can also produce brGDGTs. This insight aligns with recent studies conducted in lakes and pure cultures11,31,32, expanding our knowledge on brGDGT production across diverse environments. Our findings underscore the pivotal role of DOU in modulating brGDGT methylation and isomerization patterns, which are typically associated with temperature and pH13,14, respectively. In marine settings where in-situ brGDGT production is predominant, accounting for the effect of DOU becomes essential for evaluating methylation-based temperature and isomerization-based pH indexes13,61 (Fig. S5 and S6). This research advances our understanding of brGDGTs in marine environments and promotes their application in paleoclimate reconstructions.

Measuring DOU in benthic oceans involves three primary methodologies: sediment incubations, flux calculations derived from oxygen profiles, and the eddy covariance technique16,49. These methodologies are commonly constrained by their reliance on specialized and costly in situ analytical instrumentation, which limits the scope and frequency of global ocean measurements. Moreover, they provide only insights into current conditions and are not applicable in studying geological DOU variations. Our study presents an approach using brGDGTs from sediment archives as a deep-sea DOU indicator. The practicality of collecting sediments followed by laboratory lipid analysis is particularly beneficial for broad deep-sea investigations. Furthermore, with brGDGTs traceable back at least millions of years62, they provide potential for exploring geological DOU variations. In summary, this study pioneers the innovative IMBT index, based on brGDGTs, to quantitatively assess benthic DOU in deep-sea settings, which serve as a key metric for evaluating the degradation and preservation of sedimentary organic matter and for gauging the activity levels of benthic communities.

Methods
Study area
The AT is the deepest sector of the Peru-Chile Trench that is formed by the subduction of the Nazca Plate underneath the South American Plate and has a maximum depth over 8000 m63. Geographically, it is in close proximity to the Atacama Desert and is characterized by a surface ocean with relatively high net primary productivity (NPP, 300–450 g C m−2 yr−1). This elevated productivity is primarily attributed to the intense upwelling phenomena occurring in the area. Notably, the Atacama Desert is one of the driest regions globally, leading to the predominantly wind-driven transport of terrestrial materials rather than significant contributions from riverine run-off64. The KT is recognized as the fifth deepest trench globally and is formed by the subduction of the Pacific Plate underneath the Indo-Australian Plate42. It has a maximum water depth exceeding 10,000 m and extends from approximately 26° S to 36° S near the North Island of New Zealand. The southern end of the trench is about 160 km from New Zealand, and receives low inputs of terrestrial materials65. The KT is characterized by oligotrophic to moderately productive waters (NPP, 100–150 g C m−2 yr−1). The MT is formed as the subduction of the Pacific plate beneath the eastern edge of the Philippine Sea plate66. It has a total length of ca. 2500 km and a mean width of 70 km. The Challenger Deep, as the deepest point in the world’s oceans, is located on the southern rim of the MT and has a water depth of ca. 11,000 m. The MT is overlain by extremely oligotrophic waters (NPP, <60 g C m−2 yr−1).

Sample collection
Waters, sediments, and benthic organisms were collected from the KT, AT, and MT regions during three research cruises aboard the R/V Tangaroa (November to December 2017), R/V Sonne (March 2018), and R/V Zhangjian (December 2016 to February 2017), respectively. A total of 13 sediment cores were selected for GDGT measurements. These cores included four from the KT region (K3, K4, K6 and K7; water depth, 6080–9560 m; core length, 25–40 cm), eight from the AT region (A2–7, A9 and A10; water depth, 4045–8090 m; core length, 10–35 cm), and one from the MT region (M1; water depth, 10,840 m; core length, 11 cm) (Fig. 1A; Supplementary Data 1). For sediment samples from the KT region, the sediment cores were sliced at 1 cm intervals for the top 2 cm, 2 cm intervals for the depth range of 2–10 cm, and 5 cm intervals for depths greater than 10 cm. For sediment samples from the AT region, the sediment cores were sliced at 1 cm intervals for the top 10 cm, 2.5 cm intervals for the depth range of 10–20 cm, and 5 cm intervals for depths greater than 20 cm. For sediment samples from the MT region, the sediment cores were sliced at 1 cm intervals throughout the core. All collected samples were immediately placed in freezers set at −20°C until further analysis. The detailed information on the samples has been summarized and documented in the Supplementary Data 1.

Lipid extraction
Sediment samples were freeze-dried and homogenized for GDGT analysis. About 2–3 g of sediment was subjected to ultrasonic extraction using a 3:1 (v:v) mixture of dichloromethane and methanol, with three extraction cycles lasting 15 minutes each. A known amount of C46-GTGT was added as an internal standard prior to extraction. The resulting extracts were centrifuged at 1500g for 5 min. The supernatants were transferred to pre-combusted glass bottles and dried under a stream of nitrogen. Subsequently, the extracts were separated into non-polar and polar fractions using silica gel columns (60–100 mesh) with n-hexane and dichloromethane:methanol (1:1, v-v), respectively. The polar fraction containing the GDGTs was purified with a 0.45 μm PTFE filter to remove any remaining particles.

Lipid analysis
GDGTs were analyzed using an Agilent 1260 series High-Performance Liquid Chromatography (HPLC) system coupled with an Agilent 6135B quadrupole Mass Spectrometer (MS) with an Atmospheric Pressure Chemical Ionization (APCI) source. The separation of GDGT compounds followed a modified method proposed by Hopmans et al.67. For this purpose, two UPLC columns (BEH HILIC columns, 2.1 × 150 mm, 1.7 μm, Waters) were connected in series. The mobile phase consisted of hexane as solvent A and hexana:isopropanol (9:1, v-v) as solvent B. A 25-min wash using 0% A was initially performed, followed by an elution gradient. The elution gradient involved a transition from 82% A to 65% A over 50 min, followed by a 10-min transition to 100% B, which was maintained for 20 min. Subsequently, a 10-min gradient change of the B component to 18% was implemented and maintained for 30 min to achieve equilibrium. The flow rate was set at 0.2 ml min−1, and the column temperature was maintained at 30°C. In terms of mass spectrometry, the selected ion monitoring (SIM) mode included C46-GTGT (m/z=743.6), Ia (1022.0), Ib (1020.0), Ic (1018.0), IIa and IIa’ (1036.0), IIb and IIb’ (1034.0), IIc and IIc’ (1032.0), IIIa and IIIa’ (1050.0), IIIb and IIIb’ (1048.0), IIIc and IIIc’ (1046.0), and crenarchaeol (1292.3). Following data acquisition, manual integration using Agilent MassHunter Qualitative Analysis software (version 10.0) was performed, and compound identification was carried out based on retention time and peak order. Quantification of compounds was accomplished by comparing the peak areas of the internal standard C46-GTGT with those of the target compounds. Note that compounds IIIb, IIIb’, IIIc, and IIIc’ were not reported in this study due to their extremely low abundance or being below the detection limit. The resulting quantification values were reported as dry weight of sediment (ng g−1 dws).

Data compilation
The in situ oxygen microprofile data, which are used to calculate bottom water and sediment dissolved oxygen concentrations, as well as DOU values, are referenced from Glud et al.39 and Glud et al.38. The KT and AT samples analyzed in this study are obtained from the same location as the in situ oxygen measurements. However, the MT samples were collected from a different location (11.43°N, 142.36°E, 10,840 m) that differs from the in situ oxygen measurement site (11.34°N, 142.43°E, 10,850 m). Nevertheless, both sampling sites are geographically close to each other and situated within the Challenger Deep. The data on TOC, TN and the TOC/TN ratio are obtained from Xu et al.37 and Xiao et al.24. Surface and bottom water temperature data are extracted from the WOA18 0.25 degree data68. Note that the time periods considered are annual, and the time span encompasses all the data utilized in WOA18, irrespective of the year. The NPP data for the surface waters above the station sites are derived from the standard Vertically Generalized Production Model, using remote sensing data spanning from 2004 to 201869. To explore the relationship between the IMBT index and water depth, we compiled brGDGT data from various studies, including Cao et al.70, Cao et al.71, Ceccopieri et al.51, Crampton-Flood72, Crampton-Flood73, Crampton-Flood et al.74, De Jonge et al.19, De Jonge et al.16, Li et al.75, Sinninghe Damsté22, Soelen et al.76, Wang et al.49, Warden et al.77, Zell et al.78, and the present study. Note that brGDGTs in the surface sediments of the KT and AT have been reported in Xu et al.79, and brGDGTs in the core sediments of the MT have been reported in Xiao et al.24. All the aforementioned data have been documented in Supplementary Data 4.

Proxy calculation
The BIT index was calculated according to Hopmans et al.21. The ΣIIIa/ΣIIa index was calculated following the definition of the IIIa/IIa ratio by Xiao et al.18, which combined the 5- and 6-methyl isomers to correspond to traditional chromatographic approaches13,14. Note that the calculation of ΣIIIa/ΣIIa values excludes the 7-methyl isomers80. The IR index was determined based on the approach outlined by De Jonge et al.19. The MBT’5ME and CBT5ME were calculated following the approach outlined by De Jonge et al.13. The IMBT index was calculated according to this study (see Eq. 1). These calculations involve utilizing the fractional abundance of brGDGTs, represented by roman numerals, and the isoprenoid GDGT crenarchaeol (Cren), which is a specific GDGT associated with Thaumarchaeota81. The structures of these GDGTs can be found in Fig. S1. The resulting values of these indexes, along with reconstructed values of environmental parameters (if applicable), have been documented in Supplementary Data 2 and 3.

BIT = (Ia + IIa + IIIa + IIa’ + IIIa’) / (Ia + IIa + IIIa + IIa’ + IIIa’ + Cren) (3)

ΣIIIa/ΣIIa = (IIIa + IIIa’) / (IIa + IIa’) (4)

IR = (IIa’ + IIb’ + IIc’ + IIIa’ + IIIb’ + IIIc’) / (IIa + IIa’ + IIb + IIb’ + IIc + IIc’ + IIIa + IIIa’ + IIIb + IIIb’ + IIIc + IIIc’) (5)

MBT’5ME = (Ia + Ib + Ic) / (Ia + Ib + Ic + IIa + IIb + IIc + IIIa) (6)

CBT5ME = −log[(Ib + IIb) / (Ia + IIa)] (7)

Statistical analysis
The maps in this study were created utilizing Ocean Data View (ODV version 5.6.3) and ArcMap version 10.7 software. Principal Coordinates Analysis (PCoA) was conducted using the vegan package in R version 4.2.1, with the Bray Curtis method employed to generate the distance matrix. To investigate variations in brGDGT compositions and related indexes across different trench sites, one-way analysis of variance (one-way ANOVA) was performed using SPSS version 22.0 software. The significance level for determining statistical significance was set at p<0.05, unless otherwise specified. Pearson correlation analysis was employed to assess the associations between variables, with Pearson correlation coefficients (r values) reported to quantify the magnitude and direction of linear correlations. The molecular structures of brGDGTs were generated using ChemDraw version 19.0 software, while other graphical representations were generated using OriginPro version 9.8.0.200 software.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript fitled “Strong linkage between benthic oxygen uptake and bacterial tetraether lipids in\ndeep-sea trench regions” presents data on the distribufion of branched glycerol dialkyl glycerol\ntetraethers (brGDGTs) in sediment cores from the Atacama, Kermadec, and Mariana trench regions.\nWithin these regions, terrestrial input is limited, pressure is high, and boftom waters are consistently\nsimilar temperatures, which allows the authors to make general arguments in the manuscript regarding\nthe relafionship between oxygen and brGDGTs in marine sediments. The authors idenfify a strong\nrelafionship between diffusive oxygen uptake, which measures the microbial diagenefic intensity.\nThe manuscript is well wriften, and the sample and data collecfion methods follow the typical\nmethodologies used to obtain this type of data. The data presented is novel, and the implicafions are\nintriguing as the data may explain why previous studies of brGDGTs distribufion in sedimentary\nenvironments have yielded conflicfing results and inferences about the favorable condifions for bacterial\nsynthesis of brGDGTs and the role oxygen availability plays on the producfion and distribufion of these\nbiomarkers. The paper should be published; however, I suggest a few improvements to the manuscript\nbelow.\nSuggested Edits:\n1. Several figures are overcomplicated, making them difficult to read. I also struggled to see how the\ndata presented applied to what was discussed in the text. For example, Fig. 2A is visually appealing, but\nit was difficult to read and make interpretafions from the heat maps. As Fig. 2A is organized, the insfinct\nis to read the heat maps as though they represent increasing DOU across some horizontal confinuum,\nlike along a cross-secfion. Instead, the two rows are unrelated to each other (the boftom row shows data\nfrom the AT collected at different locafions in that trench region, whereas, the top row displays the data\nfrom one sample from the MT and 4 samples from the KT that were collected from different locafions in\nthat trench region). The data are unrelated and not meant to be correlated, nor do they represent\nchange across one cross-secfion.\nIt was also difficult to see that the sediment depth arrows represent depth into the core. After looking at\nthe figure for a while, I rotated the paper so that the brGDGT labels were at the top of the maps and the\narrow indicafing the sediment thickness pointed down as it would when reading data from cores. It\nmight be easier for an audience to read if the heat maps are rearranged to read from top to boftom as\nyou would with data in a core sample. There should also be a way to indicate that these maps are not\nmeant to correlate with each other (as you would when creafing a fence diagram or correlafing strata).\nUnfortunately, I am sfill unable to idenfify the relafionship you are describing when you reference the\nfigure in line 143. There may not be a befter way to convey this informafion in a figure, which can be\nchallenging. I frequently referred to the data chart in the SI material to gain an understanding of what\nwas being displayed in the figure.\nThere is a similar issue with the correlafion maps in SI Fig. 3. The figure is responsible for displaying too\nmuch informafion and requires an extended amount of fime to decipher what is being displayed. I found\nthe SI table with the environmental data helpful as I looked through this figure.\n2. The figures currently in the supplemental informafion should be included in the main manuscript\nbecause they were crucial to understanding the other images in your paper, and they are cited as\nevidence used as support for the manuscript’s conclusions. This is especially true of SI Figs. 2 and 3. I\nreferred to the figures (and tables) in the SI PDF as much, if not more, than I did to those in the\nmanuscript. Although the figures are overcomplicated, each figure created for this manuscript, including\nthose in the SI, is important for reaching the conclusions of the manuscript. I recognize there may be a\nlimit on the number of figures allowed in an arficle for this journal. However, the manuscript would be\nbefter served if all the figures were included as part of the main manuscript.\n3. The environmental data presented on sheet 3 of the SI Excel file was extremely helpful when reading\nthrough the manuscript because it answered all the quesfions about the consistency of the environment\nthat I was asking as I read through the text.\n4. Lines 168-173: If the biogeochemical/physical factors are relafively consistent with each other, what\nheterogeneity are you referring to in the benthic environments that would cause the “significant\nvariafions” observed in the composifion and distribufion of brGDGTs in the sediment? Adding discussion\non this may be helpful for your argument by providing a guide for your audience to follow as you walk\nthem through your conclusions.\n5. Results and Discussion Secfion - this secfion of the manuscript blends the results and discussion of\nyour interpretafions so well that I often reread paragraphs to find the raw data you were presenfing. I\nsuggest adding a data table to the manuscript summarizing the data you want the audience to track as\nyou walk through the discussion, even if it is the mean and standard deviafion in the chart (i.e., lines\n111-119). Doing so will allow the audience to reference your data easily while reading through the\ndiscussion.", "reviewer_2": "In this manuscript Xiao et al. present a dataset of sediments from three deep-sea regions where\nbrGDGTs were measured. Through a series of correlafion analyses between environmental parameters\nmeasured on site, or from previously published studies, the authors show that the diffusive oxygen\nuptake (DOU) parameter best correlates with changes in the brGDGT concentrafions, and suggest a\ncorrelafion between this parameter and the acfivity from the brGDGT producing organisms. The authors\npropose the Isomerizafion and Methylafion index of Branched Tetraethers (IMBT) as a metric to esfimate\nDOU in sediments. This correlafion between DOU and IMBT is then shown to be maintained when the\nstudy is expanded to previously published and globally distributed marine sediments.\nThe authors present an interesfing and compelling argument about the influence of DOU on the\nproducfion of brGDGTs in deep-sea environments, where parameters usually associated with GDGTs\nremain stable (i.e. temperature). I think this is a well wriften and compelling manuscript that is suited for\nthis journal. I think that only some relafively minor issues need to be tackled first.\nMy main concern with the manuscript is regarding the introducfion of the IMBT index, which the authors\nshow to have a correlafion with DOU. While the correlafion between brGDGTs and DOU is consistent\nwith the data, the formulafion of IMBT strongly resembles that of the Isomer Rafio (IR). Since IR=(IIa’+\nIIb’+IIc’+IIa’+IIIb’+IIIc’)/(Ia+IIa’+IIb+ IIb’+IIc+IIc’+IIIa+IIIa’+IIIb+IIIb’+IIIc+IIIc’) and the presented\nenvironments already have low abundances of the brGDGT with cyclopentane rings, the equafion ends\nup resembling a lot the proposed IMBT index IMBT=-log10((IIIa’ +IIa’)/(IIIa+IIIa’+IIa+IIa’+I)) which mostly\nadds Ia to the denominator, parficularly since the authors show that the non-logarithmic formulafion of\nIMBT shows comparable results. Although I think it is possible that the IMBT index does provide new\ninformafion compared with IR, or any other index, I think that a proper comparison between the\nperformance of IMBT with previously established indices would be important, parficularly when the\nindices are formulated based on correlafions and not mechanisfic principles.\nDetailed comments\nLine 53: Feels like a citafion is missing here from the sentence.\nLine 148 (and others): Why is the index presented as ∑IIIa/∑IIa? Xiao et al., 2016 presents the index as\nIII/IIa.", "reviewer_3": "Dear editor,\nI have completed my review of the manuscript “Strong linkage between benthic oxygen uptake and\nbacterial tetraether lipids in deep-sea trench regions”. It is an interesfing manuscript, aiming to explain\nvariafion in brGDGTs in marine sediments with contrasfing sediment oxygen properfies. The manuscript\nencompasses an interesfing dataset, is well wriften, well-referenced and presents clear figure.\nFurthermore, the development of a proxy that is mechanisfically linked to DOU, would be very valuable\nfor the paleoclimate community. While I support the empirical link between DOU and brGDGT fracfional\nabundances, the interpretafion of this mechanism is currently not strong, which I aftribute to the lack of\nconcentrafion data presented in the manuscript. I have outlined several comments below that can\nimprove the manuscript.\nMajor comments:\nWhile the distribufion (i.e. fracfional abundance changes) is linked to DOU, the proposed mechanism\nthat causes this is poorly constrained. This is caused in part, by the lack of use of concentrafion data. The\ncomplete discussion is currently built up on correlafions between fracfional abundance and DOU, which\nmeans that we don’t known whether we are observing an increase in 5-methyl brGDGTs, or instead a\ndecrease in 6-methyl brGDGTs with increasing DOU values. Determining this would be a necessary step\ntowards making the discussion on mechanisms more clear. Importantly, the method secfions describes\nthat quanfificafion was done, but no concentrafions are reported. Using concentrafion data will also\nallow to evaluate whether DOU is really the main driving factor, or whether TOC/TN, NPP and boftom\nwater oxygen concentrafion perhaps play a more significant role explaining brGDGT concentrafions.\nA second major comment is, that if a formula is proposed to link brGDGT distribufion to DOU, this\nformula should include an esfimate of error. Also, is the log transformafion necessary? The performance\nof this novel rafio in comparison with exisfing rafios (DC’, IR) should be compared. A figure that plots the\nmost common rafios (MBT’5ME, DC’, IR) against DOU would be helpful for the community to interpret\nmanuscripts that report these data.\nFrom fime to fime, the authors make a statement that is not backed up by data or references. For\ninstance at L 53 (“recent advancements … marine sediments), L 168 (…exhibited minimal differences), L\n296 (… casts no doubt on this nofion))\nMinor comments:\nL 55. Isomerizafion degree is not a valid term (in the end all 15 brGDGTs are ‘isomers’), this needs to be\nexplained as a change from 5-methyl to 6-methyl forms (or vice versa) of penta- and hexamethylated\nbrGDGTs.\nL 124. 0-ring brGDGT compound is not a correct term.\nL 136. As far as I saw the definifion of hadal and non-hadal sites at your sefting was not explained yet.\nPlease introduce these terms before.\nL 163-165, is repefifion, can be removed or fied in with the end of the paragraph (as part of the\nconclusion).\nAt L 182-185 the discussion on CBT5ME, reconstructed pH and boftom water pH is very unclear. The\npoint that the acidic bias between reconstructed and measured pH is supposed to make is not clear to\nme?\nL 185. Specify that this is fracfional abundance of brGDGTs.\nL 192. Before reaching this conclusion, changes in concentrafion of brGDGTs with DOU and other\nparameters should also be evaluated.\nL 312. Here the authors discuss the mechanism as being related to increased methylafion, but what is\nthe correlafion between MBT’5ME (degree of methylafions) and DOU?\nL 325. If nutrient limitafions are the proposed mechanism, the link between nutrient availability and\nDOU needs to be described befter.\nL 453. The ΣIIIa/ΣIIa rafio somefimes also includes the late elufing isomers of IIIa and IIa (so-called IIIa’’’\nand IIa’’’ or IIIa7ME and IIa7ME). Can the authors specify that their calculafion, and that of the compiled\ndata of course, both didn’t include these late elufing isomers?"}, "author_response": "Responses to Reviewers\nReviewer #1 (Remarks to the Author):\nComments:\nThe manuscript titled “Strong linkage between benthic oxygen uptake and bacterial tetraether\nlipids in deep-sea trench regions” presents data on the distribution of branched glycerol\ndialkyl glycerol tetraethers (brGDGTs) in sediment cores from the Atacama, Kermadec, and\nMariana trench regions. Within these regions, terrestrial input is limited, pressure is high, and\nbottom waters are consistently similar temperatures, which allows the authors to make\ngeneral arguments in the manuscript regarding the relationship between oxygen and\nbrGDGTs in marine sediments. The authors identify a strong relationship between diffusive\noxygen uptake, which measures the microbial diagenetic intensity.\nThe manuscript is well written, and the sample and data collection methods follow the typical\nmethodologies used to obtain this type of data. The data presented is novel, and the\nimplications are intriguing as the data may explain why previous studies of brGDGTs\ndistribution in sedimentary environments have yielded conflicting results and inferences\nabout the favorable conditions for bacterial synthesis of brGDGTs and the role oxygen\navailability plays on the production and distribution of these biomarkers. The paper should be\npublished; however, I suggest a few improvements to the manuscript below.\nResponse: We greatly appreciate your constructive feedback and the positive evaluation,\nwhich have significantly enhanced the clarity and readability of our manuscript. In response\nto your suggestions, we have 1) revised Fig. 2 to make it more intuitive and easier to interpret;\n2) transferred the correlation analysis plot from the supplementary materials to the main text\nto provide readers with more information; 3) added a new table to the supplementary\nmaterials, summarizing the key data to facilitate an easier navigation through our discussion;\nand 4) addressed all other feedback provided. We believe these revisions thoroughly address\nyour concerns and fulfill the publication criteria.\nSuggested Edits:\n1. Several figures are overcomplicated, making them difficult to read. I also struggled to see\nhow the data presented applied to what was discussed in the text. For example, Fig. 2A is\nvisually appealing, but it was difficult to read and make interpretations from the heat maps.\nAs Fig. 2A is organized, the instinct is to read the heat maps as though they represent\nincreasing DOU across some horizontal continuum, like along a cross-section. Instead, the\ntwo rows are unrelated to each other (the bottom row shows data from the AT collected at\ndifferent locations in that trench region, whereas, the top row displays the data from one\nsample from the MT and 4 samples from the KT that were collected from different locations\nin that trench region). The data are unrelated and not meant to be correlated, nor do they\nrepresent change across one cross-section.\nIt was also difficult to see that the sediment depth arrows represent depth into the core. After\nlooking at the figure for a while, I rotated the paper so that the brGDGT labels were at the top\nof the maps and the arrow indicating the sediment thickness pointed down as it would when\nreading data from cores. It might be easier for an audience to read if the heat maps are\nrearranged to read from top to bottom as you would with data in a core sample. There should\nalso be a way to indicate that these maps are not meant to correlate with each other (as you\nwould when creating a fence diagram or correlating strata).\nResponse: Thank you for your insightful suggestion. We have made two revisions to improve\nthe clarity of Fig. 2. 1) Initially, the horizontal arrangement of different images was based on\nthe DOU levels, but this arrangement corresponded to three different trenches separately. In\nthe revised figure, we have reorganized the figure to present the sampling sites from the three\ntrenches in a unified manner that aligns with DOU gradients, to more clearly show how\nbrGDGT compositions vary with DOU. 2) The original figure's horizontal axis represented\nsediment depth, which contradicts the common intuition that the vertical axis should\nrepresent sediment depth. Therefore, we have rotated the images to make the vertical axis\nrepresent sediment depth. Additionally, we have refined the legend to more clearly state that\ndifferent color blocks visualize the fractional abundance of brGDGTs.\nRevision:\nRevised Figure 2A: Heat maps showing the fractional abundance of brGDGT compounds in\nsediment cores from the Mariana, Kermadec and Atacama trench regions. The colormap\nvisualizes the fractional abundance of brGDGTs in each sample. DOU values are labeled for\neach station site.\nUnfortunately, I am still unable to identify the relationship you are describing when you\nreference the figure in line 143. There may not be a better way to convey this information in a\nfigure, which can be challenging. I frequently referred to the data chart in the SI material to\ngain an understanding of what was being displayed in the figure.\nResponse: Thank you for highlighting this issue. Indeed, Fig. 2 may not have effectively\ncaptured the changes in methylation and isomerization degrees of brGDGTs, since it\nprimarily showcased variations in the fractional abundance of different brGDGT compounds.\nRecognizing this, we have revised the text from \"brGDGT methylation and isomerization\ndegrees\" to \"brGDGT compounds, especially regarding the number of methyl groups and\nisomeric forms…\" Figures 2A and 3A detail the changes in the fractional abundance of\nbrGDGTs and their relationship with DOU. We believe that by combining these two figures,\nwe can more clearly convey the interrelationship between DOU and brGDGT compounds.\nRevision:\nLines 145 – 148: The variations in major brGDGT compounds, especially regarding the\nnumber of methyl groups and isomeric forms, are closely associated with DOU variations\n(Fig. 2A and 3A), hinting at a tight interrelationship.\nThere is a similar issue with the correlation maps in SI Fig. 3. The figure is responsible for\ndisplaying too much information and requires an extended amount of time to decipher what is\nbeing displayed. I found the SI table with the environmental data helpful as I looked through\nthis figure.\nResponse: Thank you for your valuable suggestion. We acknowledge that Fig. S3 presented a\ndense compilation of information, including a array of correlation analyses across different\ntrenches and depth levels. Our intention was to provide detailed evidence to support the\nrobustness of our findings. In response to your suggestion, we have divided Fig. S3 into two\nparts: one part has been integrated into the main text to complement our discussion, while the\nother part remains in the supplementary materials. This adjustment helps to prevent\ninformation overload. Furthermore, as you pointed out, the Supplementary Dataset is\nimportant for understanding the figures, so we have highlighted references to the\nSupplementary Dataset at key points in the text.\nRevision:\nRevised Figure 4. Correlation maps between brGDGTs and environmental variables.\nPearson correlation analysis was utilized to assess the relationships between brGDGTs, both\nin terms of fractional abundances and concentrations (conc.), and a range of environmental\nvariables. These variables include latitude, longitude, water depth, sediment depth, DOU,\ndissolved oxygen concentrations in bottom water and sediment, annual sea surface and\nbottom temperatures, NPP, TOC, TN, and TOC/TN ratio (Supplementary Dataset). Notice a\nlogarithmic scale of DOU. The colormap indicates the correlation coefficients (r values), with\nred indicating positive correlations and blue indicating negative correlations. Statistical\nsignificance is denoted as *p < 0.05. Due to the limited number of cores from the KT (n = 4)\nand MT (n = 1), conducting separate correlation analyses for these trenches was impractical.\nAlternatively, we performed correlation analyses on samples from the AT, combined samples\nfrom the AT and KT, and combined samples from all the trenches. While analyses for surface\nsamples are included here, those for the average values of each core and for the entire core\nsample dataset are presented in Fig. S3.\nRevised Figure S3:\n2. The figures currently in the supplemental information should be included in the main\nmanuscript because they were crucial to understanding the other images in your paper, and\nthey are cited as evidence used as support for the manuscript’s conclusions. This is especially\ntrue of SI Figs. 2 and 3. I referred to the figures (and tables) in the SI PDF as much, if not\nmore, than I did to those in the manuscript. Although the figures are overcomplicated, each\nfigure created for this manuscript, including those in the SI, is important for reaching the\nconclusions of the manuscript. I recognize there may be a limit on the number of figures\nallowed in an article for this journal. However, the manuscript would be better served if all\nthe figures were included as part of the main manuscript.\nResponse: Thank you for pointing this out. The figures in the supplementary materials are\nindeed valuable in supporting the manuscript's conclusions. Following your suggestion and\nconsidering the journal's general format, we have strategically relocated a portion of Fig. S3\nto the main text. This aims to make critical data, which directly supports our findings, more\nreadily accessible to readers within the main narrative. As a result, the total number of figures\nin the main text has reached six, which we believe is a suitable number that conveys\nnecessary information while avoiding an excess of figures.\nRevision: Please refer to the revised Fig. 4 and S3 to see the changes.\n3. The environmental data presented on sheet 3 of the SI Excel file was extremely helpful\nwhen reading through the manuscript because it answered all the questions about the\nconsistency of the environment that I was asking as I read through the text.\nResponse: We appreciate your positive feedback. We have added references to the\nSupplementary Dataset at strategic points within the main text, aiming to guide readers\ntowards these additional resources and facilitating a better engagement with the manuscript's\ncontent.\nRevision:\nLines 113 – 114: All supporting data are detailed in the Supplementary Dataset, with the\nprincipal data summarized in Table S1.\n4. Lines 168-173: If the biogeochemical/physical factors are relatively consistent with each\nother, what heterogeneity are you referring to in the benthic environments that would cause\nthe “significant variations” observed in the composition and distribution of brGDGTs in the\nsediment? Adding discussion on this may be helpful for your argument by providing a guide\nfor your audience to follow as you walk them through your conclusions.\nResponse: Thank you for bringing this issue to our attention. In the revised manuscript, we\nhave omitted the term \"significant heterogeneity\" to avoid any confusion. Also, we have\nspecified that it is the DOU that we pinpoint as a critical driver of the observed significant\nvariations in the composition and distribution of brGDGTs. This specificity helps to clarify\nour argument and guide readers a clearer pathway through our discussion.\nRevision:\nLines 172 – 175: Such findings imply that brGDGTs in the trench sites are likely primarily\nproduced within the sediments; and the variability in brGDGTs likely reflect the conditions of\nbenthic environments, such as benthic DOU, a topic that will be discussed in the following\nsection.\n5. Results and Discussion Section - this section of the manuscript blends the results and\ndiscussion of your interpretations so well that I often reread paragraphs to find the raw data\nyou were presenting. I suggest adding a data table to the manuscript summarizing the data\nyou want the audience to track as you walk through the discussion, even if it is the mean and\nstandard deviation in the chart (i.e., lines 111-119). Doing so will allow the audience to\nreference your data easily while reading through the discussion.\nResponse: We have carefully considered your valuable suggestion. In the revised manuscript,\nwe have added a table into the supplementary materials, summarizing the main data results.\nThis table is designed to simplify the reader's navigation through our findings. Additionally,\nwe have referenced this table and the Supplementary Dataset at strategic points in the\n\"Results and Discussion\" section.\nRevision:\nLines 113 – 114: All supporting data are detailed in the Supplementary Dataset, with the\nprincipal data summarized in Table S1.\nTable S1. Summary of main data presented in the \"Results and discussion\" section of\nthe main text. Main data including sedimentation rates, DOU values, concentrations and\nfractional abundances of brGDGTs, along with related brGDGT proxies, from sites in the\nMariana Trench (MT), Kermadec Trench (KT) and Atacama Trench (AT) regions.\nSedimentation rate data are cited from Glud et al. (2013)5, Oguri et al. (2022)6, and Zabel et\nal. (2022)7. DOU data are cited from Glud et al. (2013)5 and Glud et al. (2021)8. Data on\nbrGDGT concentrations, fractional abundances, and related proxies were generated in this\nstudy, which have been detailed in the Supplementary Dataset.\nMT site KT sites AT sites\nParameter\n(n = 1) (n = 4) (n = 8)\nSedimentation rate (cm yr-1) 0.04 0.03 – 0.04 0.03 – 0.08\nDOU (μmol m-2 d-1) 154 152 – 538 355 – 1793\nBrGDGT concentration (ng g-1) 15±3 12±7 215±170\nBrGDGT concentration normalized by TOC (μg g-1TOC) 5±1 4±1 36±29\nBrGDGT-IIIa (%) 0±0 5±3 10±3\nBrGDGT-IIIa' (%) 73±2 32±17 15±9\nBrGDGT-IIa (%) 0±0 8±4 14±8\nBrGDGT-IIa' (%) 10±1 11±2 8±1\nBrGDGT-IIb (%) 0±0 3±2 2±1\nBrGDGT-IIb' (%) 1±0 6±2 9±5\nBrGDGT-IIc (%) 0±0 1±0 1±0\nBrGDGT-IIc' (%) 0±0 2±1 3±2\nBrGDGT-Ia (%) 12±1 21±5 29±4\nBrGDGT-Ib (%) 2±0 6±3 5±1\nBrGDGT-Ic (%) 1±0 3±1 3±1\nNon-cyclized brGDGTs (%) 96±1 78±8 76±7\nMono-cyclized brGDGTs (%) 2±1 16±6 17±5\nDi-cyclized brGDGTs (%) 1±0 6±2 7±2\n6-methyl brGDGTs (%) 100±0 73±15 56±19\n5-methyl brGDGTs (%) 0±0 27±15 44±19\nHexamethylated brGDGTs (%) 73±2 37±14 26±7\nPentamethylated brGDGTs (%) 11±1 32±6 38±4\nTetramethylated brGDGTs (%) 15±2 31±8 37±4\nBIT 0.03±0.01 0.07±0.05 0.07±0.05\nΣIIIa/ΣIIa 7.14±0.98 2.00±1.03 1.45±0.91\nIR 1.00±0.00 0.73±0.15 0.56±0.19\nCBT' 0.84±0.04 0.21±0.29 -0.16±0.29\nMBT' 1.00±0.00 0.67±0.10 0.59±0.10\n5ME\nCBT 0.81±0.10 0.55±0.15 0.73±0.15\n5ME\nDC' 0.10±0.02 0.27±0.06 0.26±0.10\nIMBT 0.06±0.01 0.30±0.14 0.55±0.19\nReviewer #2 (Remarks to the Author):\nIn this manuscript Xiao et al. present a dataset of sediments from three deep-sea regions\nwhere brGDGTs were measured. Through a series of correlation analyses between\nenvironmental parameters measured on site, or from previously published studies, the authors\nshow that the diffusive oxygen uptake (DOU) parameter best correlates with changes in the\nbrGDGT concentrations, and suggest a correlation between this parameter and the activity\nfrom the brGDGT producing organisms. The authors propose the Isomerization and\nMethylation index of Branched Tetraethers (IMBT) as a metric to estimate DOU in sediments.\nThis correlation between DOU and IMBT is then shown to be maintained when the study is\nexpanded to previously published and globally distributed marine sediments.\nThe authors present an interesting and compelling argument about the influence of DOU on\nthe production of brGDGTs in deep-sea environments, where parameters usually associated\nwith GDGTs remain stable (i.e. temperature). I think this is a well written and compelling\nmanuscript that is suited for this journal. I think that only some relatively minor issues need\nto be tackled first.\nResponse: We sincerely appreciate your encouraging comments and constructive feedback\non our manuscript. Your suggestion to compare IMBT with other major indexes is incredibly\nconstructive. It has not only deepened our discussion but also offered a richer context for\nother studies utilizing these classic indexes. We have made revisions based on all your\nsuggestions. We trust that these revisions have improved the manuscript’s quality and align\nwith the publication criteria.\nMy main concern with the manuscript is regarding the introduction of the IMBT index, which\nthe authors show to have a correlation with DOU. While the correlation between brGDGTs\nand DOU is consistent with the data, the formulation of IMBT strongly resembles that of the\nIsomer Ratio (IR). Since IR=(IIa’+ IIb’+IIc’+IIa’+IIIb’+IIIc’)/(IIa+IIa’+IIb+\nIIb’+IIc+IIc’+IIIa+IIIa’+IIIb+IIIb’+IIIc+IIIc’) and the presented environments already have\nlow abundances of the brGDGT with cyclopentane rings, the equation ends up resembling a\nlot the proposed IMBT index IMBT=-log10((IIIa’ +IIa’)/(IIIa+IIIa’+IIa+IIa’+I)) which\nmostly adds Ia to the denominator, particularly since the authors show that the\nnon-logarithmic formulation of IMBT shows comparable results. Although I think it is\npossible that the IMBT index does provide new information compared with IR, or any other\nindex, I think that a proper comparison between the performance of IMBT with previously\nestablished indices would be important, particularly when the indices are formulated based on\ncorrelations and not mechanistic principles.\nResponse: We appreciate your insightful suggestion regarding the comparison between\nIMBT and other indexes. In the revised manuscript, we have conducted a comprehensive\ncomparison between IMBT with other widely used brGDGT indexes, including MBT’ ,\n5ME\nCBT , DC’ (degree of cyclization), IR, and CBT’. Since IMBT reflects both methylation\n5ME\nand isomerization degrees of brGDGTs, it naturally shares similarities and exhibits strong\ncorrelations with these traditional isomerization and methylation indexes (e.g., MBT’ and\n5ME\nIR). However, it is important to highlight that IMBT uniquely captures both methylation and\nisomerization aspects and shows the strongest correlation with DOU. We have also compared\nIMBT with cyclization indexes (e.g., CBT and DC’). These discussions aim to clarify\n5ME\nIMBT’s utility in reflecting DOU and assist the academic community in better interpreting\nour results.\nRevision:\nRevised Figure S5. Correlation maps between brGDGT indexes and DOU. Pearson\ncorrelation analysis was employed to assess the relationships between multiple brGDGT\nindexes and DOU. The examined indexes include IMBT, MBT’ , CBT , DC’, IR, and\n5ME 5ME\nCBT’. The calculations for DC’ and CBT’ were based on equations from De Jonge et al.\n(2021)3 and De Jonge et al. (2014)4, respectively. Descriptions of the other indexes are\nprovided in the \"Methods\" section of the main text. Notice a logarithmic scale of DOU. The\ncolormap indicates the correlation coefficients (r values), with red indicating positive\ncorrelations and blue indicating negative correlations. Correlation analyses were performed\nindividually for surface samples, the average values of each core, and the entire core sample\ndataset. Notably, IMBT, MBT’ , IR, and CBT’ show strong correlations with DOU, while\n5ME\nCBT and DC’ exhibit much weaker correlations.\n5ME\nLines 280 – 291: Furthermore, we compared the IMBT index with other commonly used\nbrGDGT indexes, including MBT’ , CBT , DC’ (degree of cyclization)50, IR, and\n5ME 5ME\nCBT’13 (Fig. S5). The analysis revealed that IMBT strongly correlates with indexes related to\nbrGDGT methylation and isomerization (e.g., MBT’ and IR; absolute r values, |r| > 0.85),\n5ME\nwhile showing much weaker correlations with cyclization indexes (e.g., CBT and DC’; |r|\n5ME\n< 0.35). This pattern extends to DOU, which exhibits strong correlations with methylation\nand isomerization indexes (|r| > 0.70), but only minimal correlations with cyclization indexes\n(|r| < 0.30). Notably, the correlation between DOU and IMBT stands out as the most\npronounced among these indexes. Considering the established association of methylation\nindexes with temperature and isomerization indexes with pH13,14, the influence of DOU is\ncrucial in evaluating the reliability of methylation-based temperature and isomerization-based\npH indexes, especially in marine settings characterized by predominant in-situ brGDGT\nproduction.\nLines 366 – 370: Our findings underscore the pivotal role of DOU in modulating brGDGT\nmethylation and isomerization patterns, which are typically associated with temperature and\npH13,14, respectively. In marine settings where in-situ brGDGT production is predominant,\naccounting for the effect of DOU becomes essential for evaluating methylation-based\ntemperature and isomerization-based pH indexes13,61.\nDetailed comments\nLine 53: Feels like a citation is missing here from the sentence.\nResponse: We have included citations to studies by Xiao et al. (2022), Wu et al. (2021), and\nWeber et al. (2018) in the revised manuscript.\nRevision:\nLines 52 – 54: Recent advancements in brGDGT research have unveiled potential\nconnections between these biomarkers and benthic oxygen conditions in sediments10-12.\nLine 148 (and others): Why is the index presented as ∑IIIa/∑IIa? Xiao et al., 2016 presents\nthe index as III/IIa.\nResponse: Thank you for pointing out this confusion. The original IIIa/IIa ratio by Xiao et al.\n(2016) indeed included both 5- and 6-methyl brGDGTs. However, at the time of their study,\nthe distinction between 5- and 6-methyl brGDGTs was not commonly made in the literature.\nSubsequent research adopted the notation ΣIIIa/ΣIIa to differentiate between 5- and 6-methyl\nbrGDGTs more clearly. We have provided an explanation of this in the revised manuscript.\nRevision:\nLines 476 – 479: The ΣIIIa/ΣIIa index was calculated following the definition of the IIIa/IIa\nratio by Xiao et al. (2016)18, which combined the 5- and 6-methyl isomers to correspond to\ntraditional chromatographic approaches13,14.\nReferences: All references cited can be found in the main text.\nReviewer #3 (Remarks to the Author):\nI have completed my review of the manuscript “Strong linkage between benthic oxygen\nuptake and bacterial tetraether lipids in deep-sea trench regions”. It is an interesting\nmanuscript, aiming to explain variation in brGDGTs in marine sediments with contrasting\nsediment oxygen properties. The manuscript encompasses an interesting dataset, is well\nwritten, well-referenced and presents clear figure. Furthermore, the development of a proxy\nthat is mechanistically linked to DOU, would be very valuable for the paleoclimate\ncommunity. While I support the empirical link between DOU and brGDGT fractional\nabundances, the interpretation of this mechanism is currently not strong, which I attribute to\nthe lack of concentration data presented in the manuscript. I have outlined several comments\nbelow that can improve the manuscript.\nResponse: We sincerely appreciate your insightful review and positive feedback. Your\ncomments have been instrumental in refining our manuscript. In response to your suggestions,\nwe have 1) incorporated detailed discussion on the correlations between brGDGT\nconcentrations and environmental factors (including DOU) and expanded the discussion on\nthe mechanisms of interaction between IMBT and DOU; 2) compared IMBT with other\ncommonly used brGDGT indexes; 3) added references at strategic points to support our\narguments; and 4) carefully addressed all the minor comments. We believe that these\nrevisions improve the manuscript's quality and align with the publication criteria.\nMajor comments:\nWhile the distribution (i.e. fractional abundance changes) is linked to DOU, the proposed\nmechanism that causes this is poorly constrained. This is caused in part, by the lack of use of\nconcentration data. The complete discussion is currently built up on correlations between\nfractional abundance and DOU, which means that we don’t known whether we are observing\nan increase in 5-methyl brGDGTs, or instead a decrease in 6-methyl brGDGTs with\nincreasing DOU values. Determining this would be a necessary step towards making the\ndiscussion on mechanisms more clear. Importantly, the method sections describes that\nquantification was done, but no concentrations are reported. Using concentration data will\nalso allow to evaluate whether DOU is really the main driving factor, or whether TOC/TN,\nNPP and bottom water oxygen concentration perhaps play a more significant role explaining\nbrGDGT concentrations.\nResponse: Thank you for your constructive suggestion. We have actually measured the\nbrGDGT concentrations, briefly mentioned the concentration data early in the \"Results and\nDiscussion\" section and included the corresponding data in the Supplementary Dataset.\nHowever, our initial discussion focused on exploring the relationship between the fractional\nabundance of brGDGTs and environmental parameters, without discussing the concentration\nof brGDGTs. In the revised manuscript, we have included a comprehensive correlation\nanalysis that includes brGDGT concentrations. This analysis revealed relationships between\nDOU, NPP, TOC, and brGDGT concentrations. We further explained these relationships in\nour discussion on mechanisms: lower NPP and TOC may indicate a scarcity of organic\ncarbon supply, which corresponds to lower brGDGT concentrations; simultaneously, a\nreduction in organic carbon supply could be associated with decreased microbial activity,\nthereby leading to lower DOU levels. This links lower DOU with lower brGDGT\nconcentrations. These new findings enhance the discussion and bolster the manuscript's\narguments. We hope that this more analysis addresses your suggestions.\nRevision:\nLines 207 – 208: Our correlation analysis reveals relationships between DOU, NPP, TOC and\nbrGDGT concentrations.\nLines 339 – 343: In the deep ocean, DOU levels typically reflect microbial diagenetic\nintensity3,39. The correlations observed across our study sites between NPP, TOC, DOU and\nbrGDGT concentrations (Fig. 4 and S3) suggest a likely connection between a decreased\nsupply of organic carbon and lower concentration of brGDGTs, alongside reduced DOU\nlevels—indicative of diminished microbial diagenetic activity.\nRevised Figure 4. Correlation maps between brGDGTs and environmental variables.\nRevised Figure S3:\nA second major comment is, that if a formula is proposed to link brGDGT distribution to\nDOU, this formula should include an estimate of error. Also, is the log transformation\nnecessary? The performance of this novel ratio in comparison with existing ratios (DC’, IR)\nshould be compared. A figure that plots the most common ratios (MBT’5ME, DC’, IR)\nagainst DOU would be helpful for the community to interpret manuscripts that report these\ndata.\nResponse: Thank you for this valuable comment. In the revised manuscript, we have made\nthe following improvements: 1) We have included the estimated error associated with the\nIMBT calculation; 2) We have expanded the discussion comparing IMBT with other\ncommonly used indexes, including MBT’ , CBT , DC’ (degree of cyclization), IR, and\n5ME 5ME\nCBT’. Since IMBT reflects both methylation and isomerization degrees of brGDGTs, it\nnaturally exhibits strong correlations with these traditional isomerization and methylation\nindexes (e.g., MBT’ and IR). Accordingly, DOU also shows strong correlations with these\n5ME\nindexes. We also compared IMBT with cyclization indexes (e.g., CBT and DC’). These\n5ME\ndiscussions will assist readers in better interpreting our results. 3) We have explained the\nrationale behind opting for logarithmic transformation. While our data showed that both\nlogarithmic and linear analyses yielded highly similar results, the choice to use logarithmic\nrepresentation was deemed more appropriate across a wider range of DOU values.\nRevision:\nLines 249 – 250: The IMBT index shows a significant positive correlation with DOU (r =\n0.88, RMSE = 400 μmol m-2 d-1, p < 0.001, Fig. 5A, equation 2).\nLines 280 – 291: Furthermore, we compared the IMBT index with other commonly used\nbrGDGT indexes, including MBT’ , CBT , DC’ (degree of cyclization)50, IR, and\n5ME 5ME\nCBT’13 (Fig. S5). The analysis revealed that IMBT strongly correlates with indexes related to\nbrGDGT methylation and isomerization (e.g., MBT’ and IR; absolute r values, |r| > 0.85),\n5ME\nwhile showing much weaker correlations with cyclization indexes (e.g., CBT and DC’; |r|\n5ME\n< 0.35). This pattern extends to DOU, which exhibits strong correlations with methylation\nand isomerization indexes (|r| > 0.70), but only minimal correlations with cyclization indexes\n(|r| < 0.30). Notably, the correlation between DOU and IMBT stands out as the most\npronounced among these indexes. Considering the established association of methylation\nindexes with temperature and isomerization indexes with pH13,14, the influence of DOU is\ncrucial in evaluating the reliability of methylation-based temperature and isomerization-based\npH indexes, especially in marine settings characterized by predominant in-situ brGDGT\nproduction.\nLines 366 – 370: Our findings underscore the pivotal role of DOU in modulating brGDGT\nmethylation and isomerization patterns, which are typically associated with temperature and\npH13,14, respectively. In marine settings where in-situ brGDGT production is predominant,\naccounting for the effect of DOU becomes essential for evaluating methylation-based\ntemperature and isomerization-based pH indexes13,61.\nRevised Figure S5. Correlation maps between brGDGT indexes and DOU. Pearson\ncorrelation analysis was employed to assess the relationships between multiple brGDGT\nindexes and DOU. The examined indexes include IMBT, MBT’ , CBT , DC’, IR, and\n5ME 5ME\nCBT’. The calculations for DC’ and CBT’ were based on equations from De Jonge et al.\n(2021)3 and De Jonge et al. (2014)4, respectively. Descriptions of the other indexes are\nprovided in the \"Methods\" section of the main text. Notice a logarithmic scale of DOU. The\ncolormap indicates the correlation coefficients (r values), with red indicating positive\ncorrelations and blue indicating negative correlations. Correlation analyses were performed\nindividually for surface samples, the average values of each core, and the entire core sample\ndataset. Notably, IMBT, MBT’ , IR, and CBT’ show strong correlations with DOU, while\n5ME\nCBT and DC’ exhibit much weaker correlations.\n5ME\nFrom time to time, the authors make a statement that is not backed up by data or references.\nFor instance at L 53 (“recent advancements … marine sediments), L 168 (…exhibited\nminimal differences), L 296 (… casts no doubt on this notion)).\nResponse: Thank you for pointing out these matters. We have carefully reviewed our\nmanuscript and revised it by incorporating relevant references at the corresponding points to\nsupport our arguments. Additionally, we have included additional references to our\nSupplementary Dataset.\nRevision:\nLines 52 – 54: Recent advancements in brGDGT research have unveiled potential\nconnections between these biomarkers and benthic oxygen conditions in sediments10-12.\nLines 169 – 171: …the biogeochemical/physical factors like temperature, salinity, dissolved\noxygen concentration, and pH in the water column exhibited minimal differences44,45.\nLines 313 – 316: However, the elevated IMBT values in trench sediments, which experience\nsignificantly higher hydrostatic pressures compared to nearby abyssal sediments (e.g., KT6 vs.\nKT7, and AT3 vs. AT7; Supplementary Dataset), cast doubt on this notion.\nMinor comments:\nL 55. Isomerization degree is not a valid term (in the end all 15 brGDGTs are ‘isomers’), this\nneeds to be explained as a change from 5-methyl to 6-methyl forms (or vice versa) of penta-\nand hexamethylated brGDGTs.\nResponse: We have adjusted the phrasing accordingly.\nRevision:\nLines 55 – 57: They exhibit 15 common unique structures, characterized by variances in\nmethylation and cyclization degrees, as well as by their presence in different isomeric forms\n(e.g., 5- and 6-methyl brGDGTs; Fig. S1)13-15.\nL 124. 0-ring brGDGT compound is not a correct term.\nResponse: We have corrected the term \"0-ring brGDGTs\" to \"non-cyclized brGDGTs\" and\nadjusted the relevant descriptions.\nRevision:\nLines 127 – 130: In all three trench regions, the non-cyclized brGDGT compounds (IIIa, IIIa',\nIIa, IIa', and Ia) were predominant. They constituted 96±1% in the MT, 78±8% in the KT, and\n76±7% in the AT (Fig. 2A; Supplementary Dataset). In contrast, the mono-cyclized (IIb, IIb',\nand Ib) and di-cyclized brGDGTs (IIc, IIc', and Ic)…\nL 136. As far as I saw the definition of hadal and non-hadal sites at your setting was not\nexplained yet. Please introduce these terms before.\nResponse: In the revised manuscript, we have clarified that \"non-hadal sites\" refer to sites\nwith water depths less than 6000 m, while \"hadal sites\" refer to sites with water depth\nexceeds 6000 m. We have also provided the appropriate references for support. Furthermore,\nthe Supplementary Dataset have indicated which sites are hadal sites and which are non-hadal\nsites.\nRevision:\nLines 139 – 140: At the intra-trench scale, notable differences were observed between\nnon-hadal sites (depth < 6000 m) and hadal sites (depth > 6000 m42).\nL 163-165, is repetition, can be removed or tied in with the end of the paragraph (as part of\nthe conclusion).\nResponse: We appreciate your guidance on this matter. We have removed this sentence to the\nend of the paragraph and closely integrated it with our arguments.\nRevision:\nLines 175 – 178: …This inference aligns with a growing body of research suggesting that\nmarine-derived brGDGTs present in sediments predominantly originates from benthic\nbacteria inhabiting the sediments, particularly in deep-sea settings10,23.\nAt L 182-185 the discussion on CBT5ME, reconstructed pH and bottom water pH is very\nunclear. The point that the acidic bias between reconstructed and measured pH is supposed to\nmake is not clear to me?\nResponse: Thank you for the comment. We have revised the relevant sentences and adjusted\nthe way the discussion is presented.\nRevision:\nLines 186 – 190: Despite the absence of in-situ sediment porewater pH measurements, pH\nestimates derived from the CBT index (AT, 5.9 – 7.2, 6.6±0.3; KT, 6.2 – 7.2, 6.9±0.3; MT,\n5ME\n6.1 – 6.1, 6.4±0.2) show an acidic deviation from the typically alkaline pH of hadal bottom\nseawater and sediment porewater44,46,47, suggesting that pH might not be the main influence\non brGDGTs.\nL 185. Specify that this is fractional abundance of brGDGTs.\nResponse: We have revised it accordingly.\nRevision:\nLines 190 – 192: …we performed correlation analyses comparing both the fractional\nabundance and concentration of brGDGTs with multiple parameters.\nL 192. Before reaching this conclusion, changes in concentration of brGDGTs with DOU and\nother parameters should also be evaluated.\nResponse: Thank you for emphasizing this point. In the revised manuscript, we have\nexpanded our correlation analysis to incorporate brGDGT concentrations. Please refer to our\nresponse to major comment [1] for a more detailed explanation.\nL 312. Here the authors discuss the mechanism as being related to increased methylation, but\nwhat is the correlation between MBT’5ME (degree of methylations) and DOU?\nResponse: Thank you for emphasizing this point. In the revised manuscript, we have\nthoroughly compared the relationships between DOU and other commonly used brGDGT\nindexes. Please refer to our response to major comment [2] for a more detailed explanation.\nL 325. If nutrient limitations are the proposed mechanism, the link between nutrient\navailability and DOU needs to be described better.\nResponse: Thank you for highlighting this confusion. We have further refined our discussion\nto elucidate the link between nutritional limitations and DOU more clearly. Please note that\nwe used the term \"nutritional\" which refers to the bioavailability and utilization of nutrients\nby organisms, rather than \"nutrient\".\nRevision:\nLines 339 – 343: In the deep ocean, DOU levels typically reflect microbial diagenetic\nintensity3,39. The correlations observed across our study sites between NPP, TOC, DOU and\nbrGDGT concentrations (Fig. 4 and S3) suggest a likely connection between a decreased\nsupply of organic carbon and lower concentration of brGDGTs, alongside reduced DOU\nlevels—indicative of diminished microbial diagenetic activity.\nLines 347 – 350: Hence, we propose that increased methylation and isomerization of\nbrGDGTs may enhance the fitness of source organisms in deep-sea habitats under nutritional\nlimitations, which usually coincide with reduced microbial activity and lower DOU levels.\nL 453. The ΣIIIa/ΣIIa ratio sometimes also includes the late eluting isomers of IIIa and IIa\n(so-called IIIa’’’ and IIa’’’ or IIIa7ME and IIa7ME). Can the authors specify that their\ncalculation, and that of the compiled data of course, both didn’t include these late eluting\nisomers?\nResponse: Yes, we only included 5- and 6-methyl compounds when calculating the\nΣIIIa/ΣIIa ratio and did not include 7-methyl compounds. We have made this clear in the\nrevised manuscript.\nRevision:\nLines 476 – 480: The ΣIIIa/ΣIIa index was calculated following the definition of the IIIa/IIa\nratio by Xiao et al. (2016)18, which combined the 5- and 6-methyl isomers to correspond to\ntraditional chromatographic approaches13,14. Note that the calculation of ΣIIIa/ΣIIa values\nexcludes the 7-methyl isomers80.\nReferences: All references cited can be found in the main text."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I agree with the authors that all of my concerns from the first review have been addressed in their\nresponses and the final manuscript.", "reviewer_2": "Upon reading the modified version of the manuscript by Xiao et al. I find that all the minor revisions have\nbeen successfully addressed by the authors.\nI appreciate the efforts of the authors to address my comments regarding the comparison between the\npreviously established proxies and IMBT. However I think that the new Figure S5 highlights, I believe,\nReviewer #3 and my comment about comparing the advantages of IMBT over older indices. Figure S5\nshows a strong correlafion between IMBT and both IR, CBT’, like the authors discuss in the paper, and\nthis is reflected in similar absolute relafionships between these indices and DOU (presented on log\nscale). What I think is truly missing is a figure akin to figure 5, but with both IR and CBT’, comparing the\nregression with these indices. If IMBT does improve in a stafisfically significant way, I think just adding\nthese plots as supplementary figures would be enough and I would be happy to recommend the\nmanuscript for publicafion. I think even if this analysis shows that IMBT does not improve over IR or CBT’,\nthis is by no means of detriment to the manuscript, which shows a strong correlafion between brGDGTs\nand DOU, it may just require reconsidering if the IMBT is a necessary index or if IR or CBT’ provide the\nsame informafion.\nI want to stress that I think this is a very good and publicafion-worthy manuscript, I just think that this\nrelafively simple test will strengthen the author’s point and either highlight the importance of IMBT or\nstreamline the use of brGDGTs to invesfigate DOU in these seftings."}, "author_response": "Responses to Reviewers\nReviewer #1 (Remarks to the Author):\nI agree with the authors that all of my concerns from the first review have been addressed in\ntheir responses and the final manuscript.\nResponse: We appreciate your feedback and recommendation for publication. Thank you for\ndedicating your time to review our work.\nReviewer #2 (Remarks to the Author):\nUpon reading the modified version of the manuscript by Xiao et al. I find that all the minor\nrevisions have been successfully addressed by the authors.\nI appreciate the efforts of the authors to address my comments regarding the comparison\nbetween the previously established proxies and IMBT. However I think that the new Figure\nS5 highlights, I believe, Reviewer #3 and my comment about comparing the advantages of\nIMBT over older indices. Figure S5 shows a strong correlation between IMBT and both IR,\nCBT’, like the authors discuss in the paper, and this is reflected in similar absolute\nrelationships between these indices and DOU (presented on log scale). What I think is truly\nmissing is a figure akin to figure 5, but with both IR and CBT’, comparing the regression\nwith these indices. If IMBT does improve in a statistically significant way, I think just adding\nthese plots as supplementary figures would be enough and I would be happy to recommend\nthe manuscript for publication. I think even if this analysis shows that IMBT does not\nimprove over IR or CBT’, this is by no means of detriment to the manuscript, which shows a\nstrong correlation between brGDGTs and DOU, it may just require reconsidering if the IMBT\nis a necessary index or if IR or CBT’ provide the same information.\nI want to stress that I think this is a very good and publication-worthy manuscript, I just think\nthat this relatively simple test will strengthen the author’s point and either highlight the\nimportance of IMBT or streamline the use of brGDGTs to investigate DOU in these settings.\nResponse: We sincerely appreciate your continued engagement and constructive guidance\nregarding our manuscript. Your recommendation for publication is greatly valued, and in\naccordance with your latest suggestions, we have carefully revised our work. Following your\ninsights, we have performed additional analyses to assess the correlation of DOU with\ncommonly used brGDGT-based indexes such as IR, CBT’, MBT’ and CBT . Notably,\n5ME 5ME\nthe correlation between DOU and IMBT stands out as the most pronounced among the\nindexes examined. These additional analyses have been included in a new figure, Fig. S6, as\nyou suggested. We have also enhanced the referencing of Fig. S5 and S6 within the main text.\nWe believe these updates comprehensively address your comments.\nRevision:\nNewly added Figure S6. Correlation between DOU and commonly used brGDGT-based\nindexes. Scatterplot comparing the A IR, B CBT’, C MBT’ , and D CBT indexes with\n5ME 5ME\nDOU. Notice a logarithmic scale of DOU. Linear regression line (black) and 95% confidence\nintervals (gray band) are shown. Statistical significance is denoted as ***p < 0.001 and **p <\n0.01. The circle, triangle and pentagon symbols with error bars represent the average values\nwith standard deviation of variables for sediment cores from the Mariana, Kermadec, and\nAtacama trench regions, respectively. The colormap indicates the DOU values of the hadal\nsamples.\nLines 280 – 281: Furthermore, we compared the IMBT index with other commonly used\nbrGDGT indexes, including MBT’ , CBT , DC’ (degree of cyclization)50, IR, and\n5ME 5ME\nCBT’13 (Fig. S5 and S6).\nLines 285 – 288: This pattern extends to DOU, which exhibits strong correlations with\nmethylation and isomerization indexes (|r| > 0.70), but only minimal correlations with\ncyclization indexes (|r| < 0.30) (Fig. S5 and S6). Notably, the correlation between DOU and\nIMBT stands out as the most pronounced among these indexes.\nLines 368 – 371: In marine settings where in-situ brGDGT production is predominant,\naccounting for the effect of DOU becomes essential for evaluating methylation-based\ntemperature and isomerization-based pH indexes13,61 (Fig. S5 and S6)."}]

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