From this overlap we identified 21 lead SNPs with 100% validation rate containing two clusters: one consisted of DGAT1 (chr14:1.8 M+), MGST1 (chr5:93 M+), PAEP (chr11:103 M+) and GPAT4 (chr27:36 M+) affecting protein, milk and fat yield and the other included CSN2 (chr6:87 M+), MUC1 (chr3:15.6 M), GHR (chr20:31.2 M+) and SDC2 (chr14:70 M+) affecting protein and milk yield. Combining beef cattle data identified correlated SNPs representing CAPN1 (chr29:44 M+) and CAST (chr 7:96 M+) loci affecting beef tenderness, showing pleiotropic effects in dairy cattle. Our findings show that SNPs with a large effect on one trait are likely to have small effects on other uncorrelated traits.While single nucleotide polymorphisms (SNPs) associated with multiple phenotype have been reported, the knowledge of pleiotropy of uncorrelated phenotype is minimal. Principal components (PCs) and uncorrelated Cholesky transformed traits (CT) were constructed using 25 raw traits (RTs) of 2841 dairy bulls. Multi-trait meta-analyses of single-trait genome-wide association studies for RT, PC and CT in bulls were validated in 6821 cows. Most PCs and CTs had substantial estimates of heritability, suggesting that genes affect phenotype via diverse pathways. Phenotypic orthogonalizations did not eliminate pleiotropy: the meta-analysis achieved an agreement of significant pleiotropic SNPs ( Most mammalian phenotypes are quantitative or complex traits, whose variation is controlled by many genomic mutations with small effects and by environmental effects. While thousands of single nucleotide polymorphisms (SNPs) have been found associated with individual complex traits by genome-wide association studies (GWAS), an important question is the extent to which the same causal variants affect multiple traits, i.e. the extent of pleiotropy4.Understanding genetic control of mammalian phenotype, including body growth, health outcomes and metabolic pathways can improve patient treatment5 and livestock7. However, it is also possible that uncorrelated traits share some causal variants. This possibility can be tested by transforming a set of correlated traits into uncorrelated traits, for instance, by principal components (PCs) analysis9. If genes influence a set of traits through a limited number of physiological pathways, it may result in that only the first few PCs showed strong genetic effects leading to a simple picture of pleiotropy. A previous study analysing simulated and a small amount of real human data showed that large genetic variances can exist in PCs explaining small amount of total phenotypic variances10.It is expected that correlated traits share some causal variants and this has been observed in humans6, an equivalent analysis of a large number of dairy traits has not been conducted, although some pleiotropic patterns were reported9. The 25 dairy traits included measures of milk production, fertility11, conformation and management traits12 which contribute to the profitability of dairy farming13. Secondly, we examined the effects in dairy cattle of SNPs significantly associated with quantitative traits in beef cattle7.To further describe the extent and nature of pleiotropy in large mammals, we used data on 2841 progeny-tested dairy bulls with phenotypes on 25 traits and high density genotypes of 632,002 SNPs. Whilst many pleiotropic SNPs have been found in beef cattle7 to analyse 25 raw traits (RTs), 25 PCs and a novel set of phenotypic orthogonalisation, Cholesky transformed traits (CTs)14 in the dairy cattle discovery population. This was followed by the selection of lead SNPs representing major dairy QTL, confirmed by conditional and joint analysis. Finally, SNPs associated with both dairy traits alone and those SNPs shared by dairy and beef traits were validated at both multi-trait (linear index approach) and single-trait (GWAS) level in a separate population of 6821 dairy cows.We used genome-wide meta-analysis modelling Chi-square distributions of SNP effect sizehttp://www.datagene.com.au/). Daughter trait deviations were the average trait deviations of a bull’s daughters and all phenotypes were pre-corrected for known fixed effects. Only those bulls’ phenotype which were based on records from more than 15 progenies were included. Complete phenotype data were from 9,662 dairy cattle from the breeds Holstein, Jersey, MIX (crosses between Holstein and Jersey) and Australian Red, a genetically distinct breed15  were discarded. 2,841 bulls were used as the discovery population due to the high accuracy of the phenotype which was the average of >15 daughter records. The 6,821 cows, who had individual phenotypic records and weak genetic relationships with the bulls  = D, a diagonal matrix of eigenvalues; gn was an k × 1 vector of RT for animal n. The 25 eigenvectors were shown in Supplementary Table n × k CT matrix was calculated based on Cholesky decomposition:cn was a k × 1 vector of Cholesky scores for the animal n; L was the k × k matrix of the Cholesky factor which satisfied LLt = COV, the k × k covariance matrix of raw scores after standardisation as z-scores14; gn was an k × 1 vector of RT for animal n. The kth CT can be interpreted as the kth raw trait corrected for the preceding k-1 traits. Consequently, 1st CT equals the 1st RT.The principal components (PCs) and Cholesky transformed traits (CTs) were calculated based on centered and z-score scaled raw traits (RTs) of the discovery population in R (v3.3.1)18:breedi = three breeds, Holstein, Jersey and Australian Red; bx = regression coefficient b on SNP genotypes x; a = polygenic random effects ~N where G = genomic relatedness matrix based on all SNPs19. The same model was applied to GWAS and, without including SNP in the model, calculations of SNP heritability for all RTs, PCs and CTs.25 RTs with the derived sets of 25 PCs and 25 CTs were analysed one trait at a time with linear mixed models using GEMMAps < 0.05) for both of a pair of traits were compared with the expected number using the Fisher’s exact test (pf) implemented in GeneOverlap20 in R.The count of SNPs that were significant  × 1 vector of the signed t-values of SNPi effects, i.e., beta/se, for the k traits; ti′ was a transpose of vector ti (1 × k); and V−1 was an inverse of the k × k correlation matrix where the correlation was calculated over the all estimated SNP effects  of the two traits. The χ2 value of each SNP was examined for significance based on a χ2 distribution with k degrees of freedom to test against the null hypothesis that the SNP had no significant effects on any one of the k traits. The false discovery rates of χ2 tests were calculated following Storey’s method21 by ‘qvalue’ package in R. An additional test of pleiotropy was performed by carrying out the multi-trait test separately for odd and even numbered PCs. This was to confirm the existence of pleiotropy using PCs’ orthogonality: if a SNP had strong pleiotropic effects on all PCs, the variances of which were randomly attributable to RTs, this SNP was then expected to have strong effects on any subsets of PCs. Following this logic, this pleiotropic SNP was expected to have consistently strong effects on randomly selected odd and even PCs. t values of single-trait GWA of odd PCs and of even PCs were combined to calculated odd PC χ2 and even PC χ2. We then tested whether or not the same SNPs were significant in both analyses.Multi-trait meta-analysis of 25 RTs or 25 PCs or 25 CTs followed previous procedurespm of RT, PC and CT at least <1 × 10−5) within non-overlapping 1-Mb intervals of a chromosome of the discovery population. For chromosomes with multiple significant SNPs, the 1-Mb interval started from the most significant SNP and approached to the distal ends. Such selected lead SNPs were refined by step-wise analyses . The most significant ones of these few SNPs one per 1 Mb interval were again selected, added to the list of existing lead SNPs and the process repeated until there were no additional SNPs significant after fitting the lead SNPs. Then, joint analyses22 fitting all lead SNPs in a regression was used to estimate their effects on traits. Those SNPs without significant effects (joint P < 0.05) on at least one trait were removed from the lead SNP list.The selection of lead SNPs representing major QTLs was based on the most significant SNP  that had the same direction of effect in both the discovery and validation (see below) were used to calculate the effect correlation matrix within RTs, PCs and CTs. The correlation matrices were used to perform hierarchical clustering.23 and previous publications including27. Published results overrode ensemble predicted annotation if both existed. If no genes from Ensembl or published results could be identified for the SNP, the closest gene within 1 Mb was assigned.Genes associated with SNPs were annotated by variant effect predictorpm < 1 × 10−5 in the meta-analysis were selected and compared with dairy cattle SNPs with pm < 0.05 in the meta-analysis of 25 dairy RTs. The significance of the overlap between SNPs significant in the dairy and beef analysis was tested with the GeneOverlap.Beef cattle traits with animal numbers >1900 from a previous study (Table 1 in ref. b′ was the transpose of a vector of the size effects (beta) of the SNP  on the 24 RT, PC and CTs; C−1 was an inverse of the 24 × 24 (co)variance matrix among the k traits calculated from the beta of all tested SNPs for RT, PC and CTs only in the discovery population. yRT was a 24 × 1 vector of the phenotype values for the 24 traits (matching 24 RTs in bulls) for each animal in the validation population. yPC and yCT in the validation population were calculated using the same formula for calculating 24 PCs (PC eigenvectors) and 24 CTs (Cholesky L matrix) as in the discovery population according to ref. yi) for each cow in the validation population was analysed as a new response variable for an association with only the lead SNPi used to define this linear index. Such linear index analysis was also applied to validate in dairy cows the SNPs that were significant in the analysis of beef cattle and the dairy bulls. Dairy lead SNPs and dairy-beef shared SNPs were also validated for individual RT by comparing SNP effect directions between GWAS of the discovery and validation populations.The phenotypes on the validation population (i.e. the cows) did not include one trait (‘Mamm’), so the multi-trait analysis on the bulls was repeated with 24 traits so that the results could be compared directly with results on the cows. Based on these results the linear index of 24 traits on which each lead SNP had the most significant effect was calculated by:15 and ref. The genotype data used in this study were included in published articlesAmong the RTs and CTs there was a tendency for the traits with the highest heritability to have the highest number of significant SNPs Table . Milk prThe single trait analysis of the PCs’ showed little relationship between the phenotypic variance explained by each PC, the number of significant SNPs and the heritability Table . PC1 wh accounteps < 0.05) effects on both traits than expected by chance   Fig. . Althoug05) Fig.  and CTs 05) Fig.  still ha05) Fig. .Figure 1DGAT1 locus which is strongly associated with milk and fat traits28, also had the largest number of significant SNPs segregating across single-trait GWAS for RTs, PCs and CTs  SNPs were 416 for RTs, 466 for PCs and 425 for CTs, each with a FDR < 0.01. These numbers are greater than the number of significant SNPs detected in any single trait analysis. Each of the three meta-analysis was an approximation to a full multi-trait analysis because they used summary statistics. However, they largely agreed with 368 SNPs being significant in all 3 meta-analyses 28, SDC2 15, GHR 15, CSN2 15, MGST1 25, PAEP 30 and GPAT4 29. The significance peak on chr18, 57 M+, detected in our study overlapped with reported CTU1 locus associated with calving difficulty27. The small peak detected on chr3 (15.6 M+) was associated with previously identified MUC1 locus26.Three multi-trait analyses were performed. The number of significant  or only on the even 2, 4, 6…) PCs again detected pleiotropic QTL on chromosome 14 and 18  from each chromosome of the dairy bulls , MGST1 , PAEP  and GPAT4  loci. These SNPs had an allele which increased fat yield but decreased protein and especially milk yield , MUC1 , GHR  and SDC2 , the clustering was stronger across PCs  of pleiotropic SNPs were detected between the 25 dairy cattle traits and 15 beef cattle traits which included body height, muscle and fat mass. Although these dairy-beef shared SNPs had small effects in the dairy cattle population, more than 86% had effects in the same direction in bulls and cows  and CAST , both associated with beef tenderness31 showed correlated effect patterns across dairy cattle RTs, PCs and CTs. Both of these two loci contained an allele which decreased RT udder texture (11.UdTex), rear attachment width (11.RearAw) and stature, but increased likeability (farmer’s preferences score)  Fig. . The likre) Fig. . In addi9, we identified the mid-to-high range of heritability estimates of bull’s RTs  identified many significant pleiotropy SNPs with 100% validation rates of 21 lead SNPs 26, MGST1 25, PAEP 26 and GPAT4 29, each of which has an allele that increases fat yield but decreases protein and milk yields. DGAT1, MGST1 and GPAT4 have an effect on fat synthesis but PAEP is the gene for the milk protein beta lactoglobulin. The simplest explanation for this clustering is competition for substrate within the mammary gland. That is, a mutation in DGAT1 that decreases fat synthesis causes more substrate to be available for lactose and protein synthesis. In human cell lines, DGAT1 and MGST1 were reported to show co-expression in a gene group regulating adipogenesis35.The lead SNPs representing the dairy cattle major pleiotropic loci in Holstein, Jersey and Australian Red, largely overlap with reported dairy production-traits related loci Fig. . Using cnd cluster contained CSN2 , MUC1 , GHR  and SDC2 . Each member has an allele that increases protein yield but decreases milk yield  and CAST . Previously, these two SNPs were reported for both independent7 and epistatic31 effects on beef tenderness and the CAST protein binds to CAPN1 to inhibit its activities38. The effects on tenderness are partially post-mortem but in live cattle these proteins probably affect protein turnover. However, we did not observe significant effects of these two loci on protein yield in dairy cattle. Instead, the majority of observed effects of these two SNPs were on conformation traits  on a wide range of body type traits appear to be consistent with its role in regulating muscle development and growth.Some SNPs with large effects on beef cattle traits were shown to have small effects on dairy traits. Fig. . The twoCAST 7, 9.1 M+. Prits Fig.  which maKIZ  and within PGBD5  and close to SASH1  with widespread pleiotropic effects on dairy RTs, PCs and CTs  had effects on somatic cell count but not on milk production traits42. However, we also identified its significant effects on milking speed (in both RT and CT). RT and CT milking speed are also associated with the SNP close to SASH1 which regulates cell proliferation and apoptosis in human (RefSeq). There is too limited knowledge of the function of the piggyBac transposable element derived gene PGBD5 for us to explain its pleiotropic effects, especially these effects on RT, PC and CT protein yield, in the dairy cattle. Interestingly, PGBD5 gene is highly conserved across invertebrates and its encoded protein affected many other genes’ actions by inducing DNA transposition and may contribute to complex traits by genome remodelling43. It may also have an important regulatory role in the ruminant species.We identified less characterised loci, including SNPs within gene CTs Fig. . ConsistWe conclude that SNPs with a large effect on one trait are likely to have much smaller effects on other traits. Transforming the correlated traits to uncorrelated PCs or CTs reduces but does not eliminate this pleiotropy at the single-trait GWAS level. We hypothesise that this is because each causal variant has a unique pattern of effects across traits and hence generates a set of correlated effects that is different to the average correlations caused by all the causal variants together. Consequently, when the average correlations are used to construct PCs or CTs, some causal variants still have effects on multiple uncorrelated traits. A previously less characterised locus CTU1  showed strong pleiotropic effects on production and non-production traits. We also identified SNPs with strong effects in beef cattle showing small but validated effects in dairy populations. Our findings are not only useful for the dairy industry to use multi-functional genetic markers to achieve efficient selection, also provide important information for other researchers to consider when conducting multi-trait genome-wide analysis.Supplementary TableSupplementary Figure


Δ17O values as low as −0.22‰ in irghizites, however, are incompatible with a CI-like impactor. We suggest that the observed 17O depletion in irghizites relative to the terrestrial range is caused by partial isotope exchange with atmospheric oxygen (Δ17O = −0.47‰) following material ejection. In contrast, combined Δ17O–ε54Cr data for central European tektites  fall into the terrestrial range and neither impactor fingerprint nor oxygen isotope exchange with the atmosphere are indicated.Chemical fingerprints of impacts are usually compromised by extreme conditions in the impact plume, and the contribution of projectile matter to impactites does not often exceed a fraction of per cent. Here we use chromium and oxygen isotopes to identify the impactor and impact-plume processes for Zhamanshin astrobleme, Kazakhstan. ε Identifying the original impactor from craters remains challenging. Here, the authors use chromium and oxygen isotopes to indicate that the Zhamanshin astrobleme impactor was a carbonaceous chrondrite by demonstrating that depleted 17O values are due to exchange with atmospheric oxygen. The identification of projectile types for impacts is thus central for tracing the origin and aftermath of collisions. In general, chondrites are regarded as the most frequent projectiles in larger impacts2 . High thermal energy that is released in impacts leads to almost complete melting and/or evaporation of the impactor as well as large amount of the target rocks, and may also change the behavior of the elements and their chemical compounds4, making the identification of the projectile difficult.Large-scale planetary collisions and smaller impacts are important processes that may add to the chemical makeup of the bodies in the Solar System and shape the planetary surfaces by forming variably sized craters, layers of impact ejecta, and shock deformation features. Some meteorites, in particular carbonaceous chondrites, contain high concentrations of organic matter and volatiles like water, and are considered to potentially bear on the emergence of oceans and life6. Tektites are found as variably shaped and sized objects; typically, they are of splash-form shapes with a size of few centimetres. They usually are interpreted as being formed from the uppermost layers of the target lithologies, i.e., unconsolidated sediments and soils, partly vaporized and partly melted and ejected with a high velocity from the boundary zone between the impactor and the Earth’s surface by jetting7. They are mostly silica-rich and with extremely low contents of volatile components . In fact, tektites belong to the most volatile-depleted natural materials on Earth, often with < 100 p.p.m. H2O10 and low contents of other volatiles (<30–40 p.p.m. C)11. There is not an agreement on the exact formation mechanisms of tektites and several concepts have been published14. A general model of tektite formation and volatile loss15 developed the original ideas16 considering possible mechanisms of fragmentation of the overheated tektite melt by separating vapor phase18. These ideas were further developed for tektites of the Central European tektite field (moldavites)4. This latter conceptual model of formation of tektites considers two main pathways of the behavior of the ejected supercritical fluid during adiabatic decompression: (i) the supercritical matter approaches the sub-critical vapor/melt boundary from the vapor phase stability field and most matter is vaporized, or (ii) the less energetic part of the ejected matter reaches the vapor/melt boundary from the melt stability field and a directly formed overheated melt is fragmented due to separation of the vapor phase . The melt fragmentation can strongly be amplified by the escape of water-, carbonate- and/or organic matter-based volatiles derived from the target, which were effectively lost from the tektite melts11. Immediate coalescence (accretion) of small melt droplets into larger tektite bodies, probably underscored by formation of late condensation spherules, appears to be the most viable process which may explain the general chemical homogeneity of tektites, in parallel to their large micro-scale chemical heterogeneity, and the general absence of condensation and/or inner diffusion profiles in tektite bodies4.Tektites  and other impact-related glasses  are natural glassy materials which are genetically related to hypervelocity impacts of large extraterrestrial bodies on the Earth’s surface. They are produced by intense melting and partial evaporation of the target materials during the impact event, and may bear traces of the impactor16O, 17O, 18O) ratios have been used to classify asteroidal and planetary materials in the Solar System19 and O isotopes could thus be used to help identify the impactor. Large mass-independent fractionation (MIF) of oxygen isotopes has been recognized for different Solar System bodies most likely inherited from MIF processes during early Solar System formation, whereas common terrestrial and other planetary materials  have 18O/16O and 17O/16O ratios which are solely fractionated by mass-dependent processes21. The only isotopically anomalous components of Earth are found in the atmosphere. Molecular oxygen has a distinctly negative Δ17O anomaly22 (see Methods for definition of Δ17O) that is mainly caused by biological proceses , and by minor effects of photochemical reactions in the upper atmosphere23. Due to high temperatures of impact ejecta at the time of formation and during atmospheric re-entry, O isotope anomalies in tektites and related glasses could also be caused by partial post-impact exchange with the Earth’s atmosphere24 although this process has not yet been reported for truly terrestrial samples. In fact, small negative Δ17O offsets (as low as −0.18‰) were reported for some tektites20 but it remains unclear whether these low values could provide evidence for such a process or, alternatively, for the presence of impactor material with low Δ17O values.Oxygen isotope  systematics to characterize the impactor type was proven in several cases, including the Chicxulub impact at the Cretaceous–Paleogene boundary2. Distinct planetary bodies and meteorite groups show resolved differences in the 53Cr/52Cr and 54Cr/52Cr ratios26, underscored by particularly high Cr abundance in chondrites, compared to the terrestrial continental crust. Because individual chondrite groups have distinctive 17O–54Cr isotope fingerprints3, combined O–Cr isotope measurements may allow identification of impactor material and distinction between impactor- or atmospheric exchange-related variations in Δ17O.The utility of chromium isotope , and 14 Central European tektites (moldavites), related to the Ries impact event in Germany. Chromium isotope compositions were obtained for two impact-related glasses from Zhamanshin, one moldavite, and terrestrial BHVO-2 reference basalt. The detailed analytical procedures for O and Cr isotope measurements and notations for O and Cr isotope compositions are detailed in the Methods section. All samples were previously characterized for major and trace element systematics29, paleogeography (dry vs. wet area) and indications of the presence vs. absence of extraterrestrial addition in some types of impactites. The Zhamanshin impactor is interpreted to have been about one order of magnitude lower in mass than that of the Ries impact event and it probably was below the size limit necessary for production of distal ejecta, i.e., true tektites. In addition, taking into account the distribution of proximal ejecta, trajectories of both projectiles differed; in case of Zhamanshin the impact must have been much steeper27 than in case of a relatively shallow trajectory of the Ries projectile30. The target surface conditions of Zhamanshin and Ries were also different. While the target of the Ries impact event in the Miocene was a wet area near the limit of the Miocene Upper Freshwater Molasse (‘Obere Süsswassermolasse’—OSM) sedimentary basin31, probably densely overgrown by forests, dry and possibly cold desert conditions are to be expected during the Quaternary in central Asia27. Therefore, the quantity of volatiles  produced during the Zhamanshin impact can be estimated to be more than one order of magnitude lower than in the case of Ries. The compressed and ejected material of shallow layers of Zhamanshin target thus did not travel to a great distance. Instead, the glass droplets which formed from disintegrated near-surface melts were falling back through the explosion plume and collected small particles both of the mechanically disintegrated impactor matter and condensed particles from the portion of the matter which was evaporated. These glass droplets then coalesced together to form irghizites28. In a number of cases, the surface layers of primary droplets within irghizites are strongly enriched in Fe, Mg, Cr, Co, Ni and P32.Zhamanshin and Ries differ in the size of impactor (estimated diameter of ~0.6 km vs. ~1.2–1.5 km)2-rich  irghizites34 which have commonly been formed by coalescence of < 1 mm glass droplets and have elevated concentrations of Ni, Co and Cr28, (ii) morphologically rather uniform drops and their fragments composed of more basic glass, termed ‘basic splash forms’ (53–56 wt.% SiO2)38, and (iii) composite splash forms, defined as inhomogeneous acidic splash forms with abundant mineral inclusions28. Impact glasses occurring in larger irregularly shaped fragments and large blocks called ‘zhamanshinites’33 were not the subject of this study because earlier studies excluded any presence of the impactor matter in these objects28. We refer to the Supplementary Note We explore several types of glasses from the Zhamanshin impact structure (48°24’N/60°58’E), all belonging to the fallback and proximal ejecta. The major focus of the study is on tektite-like splash-form glassy objects sized usually up to several centimetres. Three major chemical types are distinguished: (i) SiO39. Unconsolidated sandy, silty and clayey sediments of the OSM, probably covering most of the target area at the time of the impact, are generally considered to be the dominant source material of moldavites46. The origin of moldavites in relation to the Ries Impact Structure has also been confirmed by generally consistent ages of moldavites and impact-related glasses from the Ries Impact Structure itself at 14.75 ± 0.20 Ma47. The nature of the impactor remains elusive49 due to difficulties in finding unequivocal extraterrestrial chemical signatures both in moldavites and impact-related glasses50.Tektites of the Central European strewn field (moldavites) are genetically related to the Ries Impact Structure, Germany (48°53’N/10°33’E), a complex type astrobleme with a diameter of ~26 km17O values of moldavites 53. The larger variability in δ18O likely is a consequence of analyzing a chemically more variable suite of moldavites29. The new data set confirms the ~3–5‰ offset in δ18O between moldavites and unconsolidated OSM quartz-rich sands . The OSM sands, which are are assumed to be the dominant source for moldavites41, showed δ18O values from 14.1 to 16.5‰ with an average of 15.3‰ (ref. 41) and the predominance of sands in moldavites is also reflected in low MgO and CaO contents and moderate δ18O  that also overlap with crustal rocks. The Δ17O values measured for irghizites (−0.22 ⩽ Δ17O ⩽ −0.14‰) are significantly lower than those measured for basic splash forms, for the moldavites, and also those reported for common crustal rocks . The Δ17O = −0.09‰ for composite splash-form IR-7 is at the low end of values for a given δ18O = 7.0‰  which is clearly outside the terrestrial range  that are consistent with common sedimentary precursors and weathered residues41 , which is identical to the values reported for a range of pristine terrestrial materials56 , and requires mass-dependent 18O depletion  partly filling ~40–45 vol.% of pore spaces of the OSM sands, followed by conversion of the matter to plasma and its condensation back to a silicate glass was advocated41. However, to shift the δ18OSMOW of the moldavite parent mixture from the OSM sand average value of 15.3‰ to the moldavite average value of 11.5‰ would require addition (and full isotope homogenization) of a much higher proportion of meteoric water. The mid-Miocene climate of this part of Europe was significantly warmer than modern climate61 and the average δ18O values of Miocene meteoric water were also higher, most probably in the range −5.6 ± 0.7‰ (ref. 62). This higher δ18O value would further increase the necessary proportion of fully homogenized meteoric water to unrealistic levels at ~30–40 vol.% of the mixture.The consistent negative δ18O are generally poor  mixing of quartz, clay, carbonate and some other minor components in varying proportions; (ii) addition of ~10–30 vol.% of water into the parent mixture; and (iii) isotope fractionation between the molten glass and separated volatiles at temperatures above 1200 °C. These findings are also supported by moderate to significant losses of highly and moderately volatile elements68, while less volatile elements appear to have been quantitatively transported into moldavite melts without accompanying isotope fractionation69. Unfortunately, the O isotope fractionations for the gas phase-melt systems are not calibrated in the temperature range of interest . By projection of the available fractionations70 into this high-temperature region it can be assumed that escaping volatiles  should have their δ18O values several tenths or a few per mil units higher than the silicate melt, shifting the residual melt δ18O to a lower values.Therefore, it can be assumed that the observed δ18O between moldavites and their inferred parent materials (this study and refs. 51), overlapping O isotope compositions were found for the Ivory Coast tektites, and their likely parental metasedimentary rocks and granitic dykes in the Bosumtwi impact structure, Ghana71. Therefore, the magnitude of the δ18O shift observed during tektite formation can perhaps be related to the quantity of volatile-bearing species  present in the target area. Such an observation implies that solely the transformation of target materials into tektites does not generate mass-independent effects and other pertinent processes are required to modify Δ17O.In contrast to a resolved difference in δ17O values reported for moldavites, oxygen isotope systematics of irghizites and splash forms from Zhamanshin show several peculiar traits. The most appealing feature of the data set are the uniformly low Δ17O values in the irghizites ( ⩽ −0.14‰) relative to basic splash forms ( ⩾ −0.10‰) while, at the same time, irghizites display higher δ18O values  oxygen from the projectile. While both chondritic and iron meteorites were proposed as possible impactors for Zhamanshin36, in the context of an impactor origin of the O isotope anomaly in irghizites, oridinary chondrites and iron meteorites would be excluded as impactor. Addition of ~2–10% oxygen from a carbonaceous chondrite impactor would explain the O isotope systematics of irghizites but most classes of carbonaceous chondrites were excluded on the basis of siderophile element systematics28. The abundances of highly siderophile  and moderately siderophile  elements as an indicator for impactor contribution differ greatly between irghizites and basic splash-forms28. In particular, Ni, Co and Cr are enriched in irghizites relative to basic splash forms (up to ~2000 p.p.m. Ni in the former)36, suggesting a resolved addition from a Ni-rich chondrite. To qualify the impactor more precisely, the unique 54Cr excess of 1.54ε units found for irghizite IR-8 . It also requires two different target lithologies with low (IR-8) and intermediate (IR-7) Cr abundance, fully consistent with recent investigations28 and oxygen isotope constraints (this study). At present, combined 54Cr–17O isotope data are only collected for a limited number of individual carbonaceous chondrites and the possibility of the existence of chondrites with yet unaccounted 54Cr–17O isotope systematics is not eliminated. For example, ~5% admixture of a hypothetical Ni-rich carbonaceous chondrite with ε54Cr = 1.6 and Δ17O of ~−2‰, which would fall close to the field of CR carbonaceous chondrites, would explain the observed composition of irghizites without a need for isotope exchange with Earth’s atmosphere, discussed below. However, a meteorite with such an isotope signature has not yet been reported and 54Cr isotope signature in particular represents a serious constraint for tracing a suitable impactor type.The low Δ17O value of −0.47‰ (ref. 22); with a correction of δ17O (see ref. 76 for discussion). At high temperatures, a limited extent of mass-dependent isotope fractionation is expected between molecular O2 and silicate melt so that the composition of the irghizites may represent a mixture of the target rocks and air O2  due to their instantaneous dislocation from the area of origin.The Earth’s atmospheric molecular oxygen carries a Δ17O in irghizites. The Δ17O of both CI carbonaceous chondrites and Tagish Lake chondrite is close to the terrestrial fractionation line. The Cr concentration in irghizite IR-8 is 213 p.p.m., whereas it is presumably low (~20 p.p.m.) in possible target lithologies28. The 54Cr systematics indicates that >90% of Cr is derived from the impactor  with a CI-like impactor having δ18O = 16.3‰ and Δ17O = 0.2 ± 0.2‰ (ref. 78) (Tagish Lake chondrite has a similar composition) would not result in the observed low Δ17O of the irghizites. Therefore, we conclude that exchange with atmospheric O2 in a vapor plume could lead to the observed low Δ17O in irghizites. Apart from rare sulphates79 and fossil biominerals81, this makes irghizites of the Zhamanshin astrobleme one of the few terrestrial materials in the geological record that carries traces of the isotope anomaly of air O2.Combining O and Cr isotope data allow both classifying the impactor type and pinpoiting the process, which gives rise to the unsually low Δ54. In brief, ~2 mg of a powdered sample were reacted with fluorine gas at a low pressure (~20 mbar) and heated with a CO2-based laser. Excess fluorine was removed by hot NaCl and chlorine was subsequently trapped with liquid nitrogen cold trap. Oxygen liberated from analyzed samples was collected on 5 Å molecular sieves and cleaned by gas chromatography for mass spectrometry analysis. For some samples, oxygen was extracted using an improved protocol that applies BrF5 as the fluorinating agent (details of this protocol are given elsewhere76). All three oxygen isotopes were measured using a Finnigan MAT 253 gas source mass spectrometer, housed at the Göttingen University. The results are reported in δ17O–δ18O (‰) notation and Δ17O (‰) values relative to VSMOW2 reference material. The Δ17O is defined relative to a reference line with the slope of 0.5305 and zero intercept54 as Δ17O = 1000ln(δ17O/1000 + 1) − 0.5305 × 1000ln(δ18O/1000 + 1), with San Carlos olivine having a Δ17O = −0.05‰ (ref. 76). The 1 s.d. reproducibility of the measurements was always better than 0.3‰ for δ18O and 0.01‰ for Δ17O values, respectively, based on repeated analyses of reference quartz NBS-28  and San Carlos olivine.The procedures for the oxygen extraction and high-precision triple-oxygen isotope measurements followed the methodology outlined elsewhere3 in Teflon bombs at 140 °C for several days until complete dissolution of all phases. Chromium was purified by cation exchange chromatography following the method described elsewhere55. The 53Cr/52Cr and 54Cr/52Cr isotope ratios were measured using a Triton thermal ionization mass spectrometer  following the method described elsewhere26. Briefly, samples were loaded in chloride form on the outgased W filaments together with an Al-silicagel–H3BO3 emitter. Each run comprised 20 blocks of 20 cycles and each single run was a combination of three successive multi-collection measurements in static mode. The measured 53Cr/52Cr and 54Cr/52Cr ratios are reported in ε53Cr and ε54Cr notation  and were normalized using an exponential law to 52Cr/50Cr = 19.28323 (ref. 82). Each sample was measured two to four times , one moldavite sample (SBM-88) as well as the basalt BHVO-2  were dissolved in a mixture of concentrated HF and HNOAll relevant data are available from the authors on request and/or are included with the manuscript in the form of data tables and data within figures.Supplementary InformationPeer Review File


Lipids produced by the dominant member of the archaeal community, the Lost City Methanosarcinales, largely lack 14C, but metagenomic evidence suggests they cannot use formate for methanogenesis. Instead, sulfate-reducing bacteria may be the primary consumers of formate in Lost City chimneys. Paradoxically, the archaeal phylotype that numerically dominates the chimney microbial communities appears ill suited to live in pure hydrothermal fluids without the co-occurrence of organisms that can liberate CO2. Considering the lack of dissolved inorganic carbon in such systems, the ability to utilize formate may be a key trait for survival in pristine serpentinite-hosted environments.Hydrogen produced during water-rock serpentinization reactions can drive the synthesis of organic compounds both biotically and abiotically. We investigated abiotic carbon production and microbial metabolic pathways at the high energy but low diversity serpentinite-hosted Lost City hydrothermal field. Compound-specific  Alkaline serpentinization environments have been proposed as promising locations for the emergence of early life, in part because the high concentrations of H2 that are a natural outcome of water-rock reactions can promote the non-biological synthesis of some organic molecules3. These environments are widespread in oceanic and continental settings4, may have been even more extensive prior to ~3 billion years ago5, and may be active on other planetary bodies such as Saturn’s moon Enceledus6. While the chemical energy for the synthesis of organic compounds is abundant in serpentinization systems, the relative importance of abiotic vs. biotic processes is unknown. We carried out studies at an alkaline serpentinization system to investigate the abiotic production of organic molecules and to identify how present-day microbial communities interact with these geologically-driven reactions.Deep sea hydrothermal systems have long been recognized as important zones of biological activity in the anoxic subsurface, and as potential locations for the evolution of early life on Earth15. Pure hydrothermal fluids can support anaerobic metabolisms such as methanogenesis and sulfate reduction in the absence of mixing with seawater18.The reaction of ultramafic rocks with water results in high concentrations of hydrogen that can provide the geochemical fuel for both biotic and abiotic organic synthesis. Resulting fluids contain high concentrations of reduced carbon compounds such as methane, short chain n-alkanes, and formate that have been proposed to form abiotically based on thermodynamic calculations, laboratory experiments, and geochemical and isotopic measurements2 or its other forms  are typically presumed to be the starting material for the abiogenic formation of organic molecules and for primary production. However, oceanic low-temperature alkaline serpentinization environments such as the Lost City Hydrothermal Field, or analogous land-based environments in Oman, California, and Italy, are characterized by extremely low concentrations of dissolved inorganic carbon due to its reduction to hydrocarbons and the rapid precipitation of calcium carbonate at pH above ~923. Thus, the availability of oxidized carbon may be a limiting factor for both abiogenic organic carbon synthesis and for the habitability of serpentinization environments. The organic acid formate has been proposed as an alternative starting material. Benchtop experiments have demonstrated that formate can rapidly form under high H2, reducing conditions11, and that certain abiotic synthesis reactions proceed more readily when formate is used as a starting material25.The oxidized carbon species CO14:The Lost City Hydrothermal Field is an iconic example of a low-temperature serpentinization system, and fluids there have elevated formate concentrations (36–158 µM) that have been proposed to form abiotically, through equilibration26. If mixing is also required for formate production at Lost City, neither it nor ∑CO2  would be available as a starting material for abiotic synthesis or primary production during much of the hydrothermal fluid pathway, potentially limiting the importance of alkaline serpentinization in the development of early life.Formate has also been proposed to form abiotically in the lower pH system of Mid-Cayman Rise, but only after mixing of the hydrothermal fluids with local seawater13C and 14C analyses to identify the origin of formate at Lost City and to determine if this compound represents an important carbon source to the dense microbial communities that inhabit the Lost City chimneys. The anoxic interior of chimneys are dominated by a single archaeal phylotype, the Lost City Methanosarcinales (LCMS)28. Endmember fluids retain 1–4 mM sulfate that co-exists with hydrogen, and geochemical trends across the field indicate microbial sulfate reduction is an important subsurface process30, possibly carried out by organisms related to Desulfotomaculum31. Chimney exteriors host organisms involved in the oxidation of sulfur and CH4 28.We carried out a series of 13C, 14C) of formate was determined for 6 fluid samples collected from Lost City chimneys at 4 locations , demonstrating that it is ultimately derived from 14C-free carbon  overlap with those of 14C-free methane (−13.6 to −9.3%) and short-chain hydrocarbons (−16.9 to −13.1%)13. Mantle CO2 is inferred to be the starting material for C1 + alkanes; although this CO2 is subsequently removed from the fluids due to abiotic reduction to organic compounds and/or precipitation as carbonate. Input of mantle volatiles is also evident from elevated 3He/4He ratios13. The lack of 14C in the formate indicates it is also formed from mantle CO2. Temperatures in the subsurface of Lost City (~180 °C32) where this starting material would be available are sufficiently high to promote its abiotic conversion to formate (>175 °C)10 and above the current temperature limit to life (122 °C33). In contrast, formate from Markers B and 3 was present in higher concentrations, was somewhat modern (F14C = 0.14–0.56), and had more positive δ13C values (−9.1 to −4.3%)  Fig. . The mor2 in Lost City fluids suggest they are not controlled by purely equilibrium processes. In almost all locations at Lost City, formate is present in far higher concentrations than expected for the amount of ΣCO2 present . The one exception is at Marker 3 where the two species are close to equilibrium due to ΣCO2 concentrations that are more than an order of magnitude higher than those at other vents (10–26 versus 0.1–0.6 µmol/L)13. Fluids from Marker 3 have been influenced by near-surface mixing with seawater that is the likely source of the additional inorganic carbon34.The relative concentrations of formate and ΣCO14C free source with a more negative δ13C signature and an additional source derived from modern inorganic carbon in seawater (F14C = 0.993–1.05213) and a more positive δ13C signature. By using the average endmember concentration and F14C and δ13C of formate at each vent, it is possible to calculate the concentrations of formate that are derived from each of these two endmembers. The data from Markers C, 2 and B could be accounted for with a constant contribution of a 14C-free endmember with a concentration of ~112 ± 20 µmol/L and a δ13C value of −12.7 ± 3.8%, plus contributions of a modern endmember with an isotopic signature of F14C = 1.02 ± 0.04 and δ13C =  + 8.4 ± 1.6% and a concentration that varies between locations, from 3–40 µmol/L. The derivation of these values is described in full in the Supplemental Materials.In the simplest scenario, formate has two sources: an abiotically synthesized, mantle-derived, F14C-free formate at Marker 3 is remarkable given that its total concentration is higher than the other locations. When combined with the observation that the concentrations of formate and ΣCO2 are close to equilibrium in this location, the F14C data point to a rapid equilibration of both concentrations and isotopes between these two species at Marker 3. This equilibration is, presumably, due to biological processes as the abiotic equilibration between the two is expected to be exceedingly slow at temperatures <175 °C10 and fluid temperatures are 88 °C21. In contrast, the biological conversion between CO2 and formate is rapid and reversible36. Therefore, microbial communities living along the fluid pathway of Marker 3 may be rapidly converting between the mantle-derived, 14C-free-formate carried with pure endmember fluids and the inorganic carbon that is present in the seawater that has been entrained. If true, the 14C of the ΣCO2 from Marker 3 should be a similar mixture of modern and dead carbon. Unfortunately, it has not been possible to make this measurement due to low fluid concentrations13. This same process likely occurs at other locations but is less evident due to a lower amount of seawater entrainment.The calculated concentration of formate that is radiocarbon-free at Marker 3 is significantly less (72 ± 8 µmol/L), while the calculated concentration of modern-derived formate is significantly more (~90 µmol/L) than in the other chimneys. This apparently lower contribution of 14C content of lipid biomarkers from a Lost City chimney (Marker 7) that could be attributed to specific microbial communities. Previous work has demonstrated that bacterial fatty acids have a bimodal 13C distribution in many chimneys, with fully saturated C16:0 and C18:0 having more positive isotopic signatures than unsaturated molecules (e.g. −25.4 to −16.8 versus −9.1 to −1.1 respectively at Marker 7)37. This pattern has been attributed to a distinction between bacteria inhabiting the interior of the chimney where seawater DIC availability is limited and those living on the exterior of the chimney where it is abundant37. In agreement with this interpretation, the saturated C16:0 fatty acid lacks 14C while, in contrast, the mono-unsaturated fatty acids C16:1 and C18:1 have a mixed F14C signature of 0.68 ± 0.03  similar to other alkaline serpentinization systems15, Lost City endmember fluids lack significant concentrations of any ∑CO2  calcium carbonate from actively venting chimneys has modern 14C signatures, indicating that it is precipitated from seawater bicarbonate, and that mantle CO2 is not available  were detected in the chimney metagenomes; the closest bacterial database matches were with sequences related to methylotrophic and sulfate-reducing bacteria  that can use formate as an electron donor39. However, the Lost City sequences were still quite divergent from any previously reported fdhA genes , and they could not be placed on a phylogeny of fdhA with high confidence.Metagenomic data from two Lost City chimneys  are also consistent with the ability of some chimney microorganisms to metabolize formate. The enzyme formate dehydrogenase catalyzes the reversible oxidation of formate to CODesulfotomaculum alkaliphilum in Lost City chimneys and fluids40. Desulfotomaculum alkaliphilum, like Desulfitibacter alkalitolerans, is also a member of the family Peptococcaceae and is thermophilic, alkaliphilic and a sulfate-reducer capable of growth on formate41. Desulfotomaculum fdhA genes also show similarity to the Lost City bacterial fdhA sequences described above, and dsrA  sequences similar to Desulfotomaculum genes are also abundant in the Lost City chimney metagenomes. Therefore, these results suggest that sulfate reduction at Lost City is most likely to be mediated by Desulfotomaculum-like bacteria and that these organisms may be fueled by formate instead of or in addition to hydrogen.Previous studies have detected 16 S rRNA gene sequences similar to 40. Unusually positive δ13C values of lipid biomarkers that are exclusively produced by methane-metabolizing archaea, pentamethylicosane and its unsaturated related compounds (PMIs), have been attributed to carbon limitation by methanogens consuming dissolved inorganic carbon42. Attempts to fully isolate the PMIs for 14C analysis were unsuccessful as they co-elute with a minor unresolved complex mixture (UCM) hump. The total F14C value of the combined isolate was F14C = 0.39 ± 0.02 , to the point that they are the only detectable archaea in some locationsfdhA enzyme were also identified in the metagenomic data  These four fdhA sequences form a clade that is clearly distinct from any fdhA sequences from known formate-utilizing or hydrogenotrophic methanogens 28.Ideally, all three lines of evidence presented here would have been carried out on samples from the same suite of Marker locations. The vast majority of samples from Lost City have been previously consumed during earlier analyses. Here we have applied techniques that have been developed in the >12 years since these samples were collected to the few that remained in our laboratories. In many cases, however, extrapolating between locations is justified by results from previous studies. For example, while the lipid 2  while methane cycling archaea are only identified in older, more established chimneys44.The picture that emerges is a system in which abiotic formate is consistently supplied with pure hydrothermal fluids and utilized by sulfate reducing bacteria who, in part, convert it to ∑CO2 Fig. . This CO2, CO2, and N2 in an environment such as Lost City45. The core metabolic reactions of LUCA may have evolved as mimicry of geochemical reactions that result in the abiotic synthesis of organic compounds, which still occur in the subsurface of Lost City today. Our results complicate this scenario somewhat by indicating that the methane-cycling archaea presently inhabiting this environment do not have ready access to dissolved CO2 and, instead, rely on the biological conversion of formate.Serpentinization systems have been increasingly proposed as locations where early metabolic pathways could have emerged on Earth and other planets, and they are also critical to understanding the extent and activity of life below the oxygenated surface of Earth. Abundant geochemical energy is available to drive abiotic synthesis and/or microbial metabolisms but the lack of dissolved inorganic carbon may limit the reactions that can proceed. The last universal common ancestor (LUCA) has been proposed to be an anaerobic autotroph similar to methanogens and clostridia, living off of H46 and the Hydrothermal Fluid and Particulate Sampler (HFPS)47. These samplers are well-suited for the analysis described here because they have low organic carbon blanks when properly cleaned48. Both filtered (in situ) and unfiltered HFPS samples were collected; filters used in situ were either glass fiber filters  or 0.2 µm nitrocellulose filters (Millipore). Upon arrival on deck, subsamples for organic analyses were stored in 100 mL glass vials  with acid-washed Teflon lined caps ; samples were then stored frozen (20 °C) until analysis on shore.Fluids from eight actively venting carbonate-brucite chimneys across the Lost City hydrothermal field were collected in 2003 by DSV Alvin using previously described ‘major’ samplers49. Lipids were extracted from the Marker 7 sample as described below. Geochemical analysis of sample 3862-1325 was previously published51. No previous microbiological analyses of this sample have been published, but a similar sample collected from Marker 3 during the same expedition (3881-1408) was the subject of previously published DNA sequencing studies40. The concentrations and 13C signatures of lipids, DNA fingerprinting with TRFLP , and quantification with qPCR (quantitative polymerase chain reaction), were previously described for samples H02_072605_Bio1slurpA2_0354 and LC_H08_080105_Bio5slurpB1 in ref.42, where they were referred to as LC-7a and LC-5, respectively.The chimney samples used for isotopic and metagenomic analyses were collected during two cruises. Sample 3862–1325 was collected from Marker 3 in 2003 by DSV Alvin aboard the R/V Atlantis. Samples H08_080105_Bio5slurpB1, from Marker 5, and H02_072605_Bio1slurpA2_0354, from Marker 7, were collected in 2005 during a National Oceanic and Atmospheric Administration (NOAA) Ocean Explorer cruise with the ROV Hercules aboard the R/V Ronald H. Brown. In all cases, samples were immediately placed in a sterile Whilr-Pak® sample bag upon arrival on deck and stored at −80 °C until analysis. DNA was extracted from the Marker 3 and Marker 5 samples according to a previously published protocol53. Briefly, the method consisted of the following steps: (1) Apolar material is removed from 5–15 mL samples by passing them over a C18 SPE cartridge; (2) Sample pH is adjusted to > 9 with NaOH and concentrated by freeze-drying; (3) Organic acids are separated by HPLC; (4) Fractions are collected in sealed 12 mL Exetainer® screw capped vials that had been previously spiked with a chemical oxidant and purged with helium; (5) oxidation of the organic acids to CO2 is achieved by heating the samples to 90 °C for 15 minutes; (6) the δ13C value of the CO2 is determined by injection into a gas chromatograph coupled to an isotope ratio mass spectrometer  maintained at 100 °C, interfaced with a ConFlo IV to a Delta V Plus Mass Spectrometer, both ThermoFisher Scientific); and (7) the Δ14C value of the remaining CO2 is determined by Accelerator Mass Spectrometry (AMS) at the Institute of Particle Physics of the ETH Zürich using the gas ion source of the 200 kV using a Mini Carbon Dating System (MICADAS)54.The isotopic signatures of formate and acetate were determined with the method ofSample H02_072605_Bio1slurpA2_0354 was sequentially extracted three times each with methanol, a 1:1 methanol:dichloromethane mixture, and dichloromethane (DCM). The extracts were combined and the solvent removed under vacuum. The total lipid extract was saponified with 0.5 M KOH in methanol for 2 hours at 70 °C. After cooling, the mixture was back extracted with hexane three times to isolate the neutral fraction, then acidified to pH 2 with 12 M HCl and back extracted three times with hexane:DCM (8:2) to isolate the acid fraction. Identification, quantification, and final checks on compound purity of isolated fractions were performed on a Hewlett Packard 6890 Series gas chromatography system equipped with a mass selective detector (Hewlett Packard 5973).3 groups could be accounted for in reporting final isotope values. The fatty acid methyl esters (FAMES) were separated over silver impregnated silica gel (AgSiO2) with 100% hexane, 100% DCM, and Hexane:ethyl acetate (98:2). Unsaturated fatty acids eluted in the hexane:ethyl acetate fraction and contained primarily (>95%) 16:1 and 18:1, with smaller contributions of other unsaturated fatty acids. This fraction was prepped for radiocarbon analysis without further purification. The DCM fraction contained saturated fatty acids, which were further separated with urea adduction into branched (non-adducted) and unbranched (adducted) compounds55. Both fractions were further purified over silica gel to eliminate any traces of urea. The non-adducted fraction contained solely phytanic acid while the adducted fraction contained straight-chain fatty acids, dominated by C16:0. Both fractions were prepped for radiocarbon.The acid fraction was methylated overnight at 45 °C with 1.2% HCl in methanol. Phthalic acid of known isotopic composition was simultaneously methylated so that the addition of the –CH2 gel and the hexane fraction was collected. After these steps, the PMI peak contributed 80% of the total peak area.The neutral fraction was passed over columns of activated copper and sodium sulfate to remove sulfur and water, respectively. The neutral fraction was then separated over 5% deactivated silica gel . Polar neutral compounds were eluted with DCM:MeOH (1:1) and n-alkanes were eluted with hexane:DCM (9:1). The n-alkane fraction contained saturated and unsaturated pentamethylicosanes (PMIs), squalane, squalene, and variably unsaturated squalenoids. A preparative gas chromatograph was used to further separate these compounds. It consisted of an HP 6890 gas chromatograph with a cooled injection system , a megabore fused silica column , a flame ionization detector, and a preparative fraction collector . Compounds were collected in glass u-traps attached to the PFC. Collection windows were timed to isolate all of the PMIs, the squalenoids, and squalene. The squalenoid fraction was lost; the squalene fraction was pure and was prepped for radiocarbon. The PMIs contained not only the compounds but also a significant UCM hump. To further purify this fraction the PMIs were first hydrogenated to the fully saturated PMI. The fraction was then passed over Ag-SiO14C-free C26 alkane  and a modern C30 alkane  were subjected to similar isolation steps to characterize the contribution of extraneous carbon. For the compounds isolated by AgSiO2 chromatography and urea adduction , different concentrations of both process standards were subjected to AgSiO2 chromatography, urea adduction, and a final purification over 5% deactivated silica gel. Because the alkane standards will not elute in the same fraction as more polar the compounds of interest, all eluted fractions were combined as one to obtain a maximum representative blank. A separate series of both standards was also injected into the preparative gas chromatograph, trapped, and processed in the same way as the samples. In both cases, the process standards incorporates any extraneous carbon contributed from the vacuum oxidation and introduction into the AMS.Two procedural standards, a 2 overnight at 950 °C. The CO2 was quantified on a vacuum line and transferred to 4 × 70 mm Pyrex tubes for subsequent AMS measurement.Isolates to be prepped for radiocarbon were dissolved in DCM:MeOH (9:1) and passed over a very short silica gel column directly into pre-combusted  quartz tubes. After addition of pre-combusted  CuO, the tubes were flame sealed under vacuum and the compounds oxidized to CO56 at the laboratory of Ion Physics of the ETH. Results are reported as F14C57. Different amounts of radiocarbon-dead phthalic acid and modern oxalic acid (OX-2) were also placed in quartz tubes and prepared in a similar way as the samples and process standards.The radiocarbon content was analyzed with a miniaturized radiocarbon dating system (MICADAS)14C values for the saturated fatty acids, the phytanic acid, and the unsaturated fatty acids were corrected using the extraneous carbon determined by column chromatography and for the addition of the –CH3 group. The F14C of squalene was corrected for the extraneous carbon determined by prep-GC. In all cases, the extraneous carbon contributed ≤3% of the total C in the sample. Propagated errors from the blank correction and the AMS analysis are reported.The final F58 with a kmer of 41. Paired-end reads were subsequently mapped to contigs with fdhA or fdhB sequences, and these reads were re-assembled with a kmer of 61. Several assembly strategies and parameters were tested and compared with MetaQuast59 and ALE60. The Prokka pipeline61 was used for gene prediction and functional annotation. The arguments–metagenome and–proteins were used with Prokka v.1.12 to indicate that genes should be predicted with the implementation of Prodigal v.2.6.262, optimized for metagenomes, and then searched preferentially against a custom protein database as well as the default databases included with Prokka, including Pfam. The database provided was the last free version (2011) of the Kyoto Encyclopedia of Genes and Genomes63, obtained from MG-RAST64. Contig coverages were calculated by mapping merged reads onto the assembled contigs with Bowtie2 v.2.2.665 and then multiplying the number of mapped reads to each contig by the average read length of 108 base pairs and dividing by the length of the contig. Detailed documentation of all metagenomic data processing is provided on the Brazelton lab’s website (https://baas-becking.biology.utah.edu/data/category/18-protocols), and all custom software and scripts are available at https://github.com/Brazelton-Lab.Purified DNA extracted from the two chimney samples was sent to the Josephine Bay Paul Center, Marine Biological Laboratory (MBL) for Illumina shotgun sequencing. Metagenomic libraries were constructed with the Nugen Ultralow Ovation kit according to the manufacturer’s instructions. Paired-end sequencing was conducted with a 100 cycle Illumina HiSeq run. All unassembled sequence data related to this study are available via the SRA identifier SRP049438 and BioProject PRJNA265986. Raw sequence data was processed by the Brazelton lab to trim adapter sequences, remove artificial replicates, and trim reads based on quality so that all reads have a minimum quality score of 25 over a sliding window of 6 bases. Paired-end reads from each chimney sample were assembled separately with Ray MetafdhA sequences, i.e. those that encode the alpha subunit of formate dehydrogenase (K00123), were identified in each chimney metagenome. The best matches to the predicted fdhA genes were identified by conducting a blastx search with each predicted fdhA nucleotide sequence against the NCBI non-redundant protein sequences (nr) database. The best match reported in Table fdhA were obtained from all finished archaeal genomes in JGI’s IMG database in July 2016. Predicted fdhA protein sequences from the Lost City contigs were included in the tree, and the final tree in Supplemental Figure 66, and the phylogeny was built using RaxML and the “-f a” option with 100 bootstrap replicates.Assembled metagenomic contigs with predicted nase K0013, were inase K0013, were iAccession codes can be found in the materials and methods and all computer codes are published and referenced in the text.Supplementary Information


This fact associated with the wide variety of sources for N2O emissions requires appropriate sensor technologies facilitating in-situ monitoring, compact dimensions, ease of operation, and sufficient sensitivity for addressing such emission scenarios. In this contribution, we therefore describe an innovative portable mid-infrared chemical sensor system for quantifying gaseous N2O via coupling a substrate-integrated hollow waveguide (iHWG) simultaneously serving as highly miniaturized mid-infrared photon conduit and gas cell to a custom-made preconcentrator. N2O was collected onto a solid sorbent material packed into the preconcentrator unit, and then released via thermal desorption into the iHWG-MIR sensor utilizing a compact Fourier transform infrared (FTIR) spectrometer for molecularly selective spectroscopic detection with a limit of detection (LOD) at 5 ppbv. Highlighting the device flexibility in terms of sampling time, flow-rate, and iHWG design facilitates tailoring the developed preconcentrator-iHWG device towards a wide variety of application scenarios ranging from soil and aquatic emission monitoring and drone- or unmanned aerial vehicle (UAV)-mounted monitoring systems to clinical/medical analysis scenarios.Following the Kyoto protocol, all signatory countries must provide an annual inventory of greenhouse-gas emission including N Since the remarkable invention of the Haber-Bosch process in the beginning of the last century, an unlimited supply of Nr has been deposited worldwide, thus enabling an abrupt growth of the human population due the increase in food availability3.Nitrogen was first identified as an essential nutrient for all plants and humans in the middle of the 194 proposed a safe operating space for mankind, is associates the earth as an eco-system with anthropogenic procedures and their thresholds. If certain boundaries are crossed, unacceptable environmental changes may be initiated putting the rather delicate environmental balance at risk. Among the procedures that have already extensively exceeded the safety threshold is the nitrogen cycle. As mentioned, large amounts of reactive nitrogen are annually applied into the soil during food production as a major component of fertilizers. Recent studies have shown that less then 40% of Nr is used by plants, thus resulting in an excess of reactive nitrogen spreading into various environmental compartments3. Most nitrogen-based fertilizers use soluble nitrates, urea or ammonium. Consequently, lixiviation of soluble Nr to aquatic systems such as rivers, lakes, estuaries, and aquifers has been described of major environmental concern5. This fact results in thousands of tons of Nr annually moved to atmosphere as volatile forms , which contributes to extend the range of this pollution to regional and even global scale7.Approximately 100 years after the introduction of the Haber-Bosch process, a study led by Rockstrom and colleagues8. Since the introduction of the Haber-Bosch process, the background levels of N2O in atmosphere have increased by almost 20% from 270 to 330 ppb8. Nitrous oxide is considered a major greenhouse gas next to carbon dioxide and methane with an estimated contribution of approx. 6% to global warming, despite the fact that N2O is present at much lower concentration than CO2. The global warming potential (GWP) of N2O is approximately three hundred times larger than CO2. Besides, in the stratosphere N2O is oxidized to NO and NO2, which are both among the constituents responsible for the destruction of the ozone layer. Hence, next to its role as environmental contaminant, nitrous oxide is considered among the most relevant ozone-depleting gas during in the 20th century9.According to the nitrogen cycle, both bacterial nitrification and denitrification pathways are responsible for the emission of nitrous oxide into the atmosphere2O10. However, establishing the N2O budget is non-trivial due to (i) the low concentration of N2O in the atmosphere  when compared to CO2, and (ii) the spatial and temporal variations in the episodes of N2O emission from soil and aquatic systems9. In addition, a wide range of factors affects the rate of emission including but not limited to pH, temperature, moisture, soil composition, and microflora5. Currently, extensive research has been focused on fundamentally understanding the processes involved in N2O emissions from soil and aquatic systems, and have triggered substantial interest in the to the development of analytical strategies and methods providing reliable and accurate data15.According to the Kyoto protocol, all signatory nations must provide an annual greenhouse gas inventory, which should include N2O release into the atmosphere. For characterizing such scenarios, the development of sensor systems capable of in-situ in-field determination with suitable sensitivity and reliability are an essential demand. Conventionally, gas chromatography with electron capture detector (ECD) is applied during laboratory studies on collected environmental samples providing high sensitivity and accuracy9. However, extended sampling and measurement times, and the dimensions and operational requirements of the instruments render them less feasible for in-field scenarios, and certainly do not allow for potential usage as drone- or unmanned aerial vehicle (UAV)-mounted sensing systems.Latent emissions provided by aquatic systems and soil reactions are believed to be the dominating mechanisms for N2O detection17 utilizing IR-absorption phenomena18. To achieve the desired sensitivity, usually multi-pass gas cell providing extended absorption path lengths are applied. Again, despite many studies demonstrating suitable sensitivity the involved cost of instrumentation and optically sophisticated gas cells along with bulky system dimensions to date limit extended field applications of such MIR analyzer systems.Among the optical sensors, the mid-infrared spectral region  has been widely utilized for N19. If gaseous samples are injected into the hollow core, the HWG may simultaneously act as a miniaturized gas cell providing several meters of optical path length yet demanding only minute gas sample volumes . Simultaneously, HWGs serve as an optical waveguide propagating radiation at rather low attenuation losses. Consequently, HWGs facilitate the development of miniaturized MIR gas sensing systems providing extended and well-defined optical path lengths with high optical throughput, while maintaining fast response times (<1 min) due to the small transient gas sample volume. The utility and adaptability of HWGs coupled to FTIR spectrometers operating in the MIR spectral range for various gas sensing applications has extensively been described in literature22.As a viable alternative to complex gas cells, hollow waveguides (HWG) serving as a light pipes made of dielectric materials or metals with a coaxial channel enabling radiation propagation by reflection at the inside wall have emerged23 with exceptionally compact substrate dimensions , an adaptable  optical path lengths via the integration of meandered hollow waveguide channels at virtually any desired geometry into an otherwise planar substrate. Furthermore, a minute volume of gas sample is required for analysis , and the short transient residence time of these sample volumes within the active transducer region facilitate real-time monitoring rendering iHWGs tailorable to a wide range of application scenarios27.Substrate-integrated hollow waveguide (iHWGs) constitute a new generation of hollow waveguides pioneered by the research team of Mizaikoff and collaborators2O gas sensor operating at the demanded concentration levels. Nitrous oxide was collected from gaseous samples using molecular sieve 5 A during 10 min at a gas sample flow rate of 200 mL min−1 corresponding to a total sampled volume of 2 L, and was then thermally desorbed at 270 °C for 1 min into a gas volume of 5 milliliters, thus facilitating an enrichment effect by a factor of 400. For quantitative analysis, the pronounced fundamental v3 MIR band of the N2O molecule occurring at 2222–2177 cm−1 range was evaluated enabling a limit of detection of 5 ppbv.Combining the iHWG technology with a compact preconcentrator device, we demonstrate in the present study the first field-deployable, compact MIR N28. N2O molecules were trapped using molecular sieve 5 A as sorbent, and were then thermally desorbed into nitrogen with the desorption flow carrying the molecules into the iHWG. Sampling of 5 ppmv of N2O at 200 mL min−1 for 10 min was used during the optimization. The desorption flow was evaluated in the range from 3 to 20 mL min−1  was considered at three-times the standard deviation of the blank signal, and was determined at 5 ppbv. The obtained analytical figures-of-merit are summarized in Table For quantification, a calibration function was established based on the evaluation of the peak area with integration boundaries from 2222 to 2177 cm® gas sampling bags were (i) filled with untreated atmospheric air collected outdoors and quantitatively spiked with N2O obtaining a final concentration of 0.5 and 2.5 ppmv for calibration purposes, and (ii) filled only with untreated atmospheric air for analyzing the real-world background concentration based on the established calibration. Thereafter, these samples were inserted into the preconcentration system by suction using a pocket pump set at 200 mL min−1 for 10 min, and were then analyzed as previously described for the calibration samples. The obtained concentrations of the spiked samples derived from the calibration function were 0.42 ± 0.09 and 2.39 ± 0.11 ppmv resulting in recovery rates of 84% and 96%. The N2O concentration was then determined in untreated atmospheric samples was 306 ± 1 ppbv. This value is in excellent agreement with the anticipated atmospheric background concentration of N2O .In order to evaluate the utility of the proposed methodology for analyzing real-world atmospheric samples, Tedlar3 vibration of the N2O molecule located at 2270–2160 cm−1 . The preconcentrator-iHWG system was then purged with nitrogen for 200 s to ensure complete removal of N2O from the sorbent, thereby avoiding any memory effects.The relation between the absorption signal and desorption time is demonstrated using nitrogen as desorption gas at a flow rate of 5 mL min−1. A gas sample flow of 200 mL min−1 for 10 min was determined providing an optimum signal; however, the flow rate may readily be adapted to other measurement scenarios and sampling requirements.A gas phase preconcentration-based analytical method may be also evaluated by its efficiency in trapping molecules passing through the solid sorbent. Fundamentally, the trapping efficiency increases with the sample flow rate up to a maximum value, and then decreases. For the current configuration, the sample flow rate was evaluated in the range of 50–200 mL min2O molecules were trapped at room temperature using molecular sieve 5 A, and were then thermally desorbed at 270 °C into the iHWG-FTIR detection system using nitrogen at a flow rate of 5 mL min−1. For quantitative purposes, integration boundaries from 2222–2177 cm−1 were utilized to avoid spectral interference by CO2. Using a sampling flow rate of 200 mL min−1 for 10 min enabled a limit of detection of 5 ppbv. The sensitivity of the method may readily be improved by increasing the sampling flow rate and the analysis time, and by increasing the absorption path length provided by the iHWG. Furthermore, alternative  sorbent materials may further improve the achieved preconcentration effect. Smartly optimizing these parameters, it is immediately evident that the developed iHWG MIR sensor system provides a generic transducer platform that may be flexibly and modularly adapted to a wide range of monitoring scenarios. Besides, replacing the FTIR spectrometer with a suitable tunable quantum cascade laser (tQCL) light source should result in a significant reduction of the physical dimensions of the developed IR sensing device.In summary, in the present study N30 – was 40 mm. Thermal desorption was performed using a heating wire wrapped around the tube and connected to a voltage/current controller . All measurements were performed using a compact portable FTIR spectrometer  equipped with a liquid nitrogen cooled mercury-cadmium-telluride (MCT) detector . A straight-line iHWG made from polished aluminum providing an integrated hollow waveguide channel  of 15 cm at device dimensions of 150 × 46 × 17 mm (length x width x depth) was coupled to the spectrometer using gold-coated off-axis parabolic mirrors with a focal length of 1′′ . IR spectra were recorded in the range of 4000–650 cm−1 at a spectral resolution of 4 cm−1; 10 spectra were averaged per measurement. The OPUS 7.2 software package  was used for data acquisition and evaluation.Nitrous oxide and nitrogen were acquired from MTI Industriegase AG . The sample preconcentration tube was custom-made from a quartz tube in U-shape with an inner diameter of 3.5 mm. The effective packaging length containing molecular sieve 5 A  – a crystalline metal aluminosilicate frequently applied as solid sorbent for gaseous compounds® adapters were used to connect the system components. Three-way gas valves were adjusted for switching different sample pathways during a measurement routine. The calibration protocol was executed in four steps (a–d) as follows:Standard gas mixtures: Nitrous oxide and nitrogen cylinders were used to prepare standard gas mixtures. Suitable gas flow rates of N2O and N2 were mixed and delivered to the sensing system at a flow rate of 200 mL min−1. The sample preparation was carried out for a period of 3 min to obtain homogenous solutions. Then, valves V1 and V4 were set to enable the passage of the sample through the preconcentration tube.Sampling: Samples were introduced into the preconcentration tube containing the sorbent at a gas flow rate of 200 mL min−1 for 10 min . For the standard gas mixtures, the flow was regulated using the gas mixing system. For real-world samples, Tedlar® gas sampling bags containing air samples were attached to the preconcentration tube, and the gas sample was transported through the system by suction using a pocket pump  with a calibrated gas flow rate of 200 mL min−1.Cleaning: After sampling, the valves V1 and V4 were set to close the preconcentration pathway. Nitrogen at a flow rate of 200 mL min−1 was used to regenerate the system for 3 min. Thereafter, a background IR spectrum was collected averaging 100 scans.Thermal desorption/Data acquisition: After cleaning, the preconcentration tube was heated  for 1 min. For the elution procedure, nitrogen was inserted into the preconcentration tube via V1 and V4 at a flow rate of 5 mL min−1, thereby carrying the desorbed N2O molecules to the iHWG-FTIR sensing device through valve V5.The experimental setup is schematically shown in Fig. Supplementary Information


K satisfies a certain Hörmander type condition. Let b be a function satisfying Suppose that the kernel  K be a singular kernel in C is a fixed constant. Consider the family of operators ρ-variation operator is defined byLet Variation and oscillation can be used to measure the speed of convergence of certain convergent families of operators. The operators of variation and oscillation have attracted many researchers’ attention in probability, ergodic theory, and harmonic analysis. Bourgain  obtainedirection –7.K satisfies the Let We notice that depth in .K satisfy ..\documenK satisfies  (see ).By definition, it is obvious thatThe following lemma gives an estimate on Taylor series remainder.Letbbe a function onwithmth order derivatives infor someThenwhereis the cube centered atxand having diameterFollowing , let \doE the mixed norm Banach space of two-variable function h defined on E-valued operator On the other hand, we consider the operatorB be a Banach space and φ be a B-valued function, we define the sharp maximal operator as follows:Let Finally, let us recall some results about the boundedness of LetKsatisfy ,mentclass2pt{minimmentclass2pt{minimB, we get For As for Let us estimate (i)(ii)(iii)(iv)Finally, let us estimate t satisfying In case (i) we observe that mentclass2pt{minimSimilarly,mentclass2pt{minimIn this paper, we have established the weighted  work in .