dataesr/scientific-paragraphs-categorization huggingface dataset:
S3  and Dataset S1A, Methods). Phylogenetic comparisons of metabolomes might be confounded by dietary and environmental differences between species (6). To address this issue, we additionally analyzed a metabolome dataset of fibroblasts isolated from 16 mammals and cultured under identical in vitro conditions  (21). Despite large differences between cell types and study conditions, the MCS values calculated from the in vitro fibroblast data show highly significant correlations with those based on the in vivo assessment of the four organs (SI Appendix, Fig. S4  and Dataset S1A). Furthermore, MCS extensively varies among different metabolites (up to 290-fold) in the fibroblast dataset as well. Thus, large differences in the conservation of individual metabolite concentrations hold in an independent dataset that is not confounded by environmental differences.
This, together with previous observations in primates  (6) , suggests that environmental differences do not substantially confound phylogenetic comparisons of tissue metabolomes. Conservation of a metabolite might vary across the phylogeny due to lineage-specific shifts in selective pressure (i. e. , adaptive evolution). However, such heterogeneities are unlikely to confound our inferences. First, in each organ, only a small fraction (7 to 29%) of metabolite levels show lineage-specific shifts  (7) , and MCS is robust to such effects (SI Appendix, Fig. S5 , see Methods). Second, we show that the rate of evolutionary change of metabolite levels is largely homogenous across the phylogenetic tree. To assess the variability of the rate of evolutionary change between clades, we calculated separate MCS values on two independent clades of the tree: rodents, rabbit and primates versus all other placental mammals (Dataset S1A).
Abundance and Essentiality Are Important Determinants of Evolutionary Conservation. By analogy to the neutral theory of sequence evolution  (22) , we hypothesize that conserved metabolites are subject to stronger functional constraints against concentration changes. If so, MCS should largely be determined by the functional role and biochemical properties of metabolites. To test this, we compiled 17 features capturing the biological and chemical properties of metabolites, including pathway membership (Dataset S1B), the number of network connections (network degree), absolute metabolite concentration (abundance) in mice  (17) , chemical class, toxicity, and various physicochemical properties (Fig. 2A  and SI Appendix, Table  S1  and Dataset S1A, see Methods). We also included "essentiality," a feature describing whether a metabolite participates in a reaction catalyzed by an essential enzyme, as determined by gene deletions in mice  (23).
S7 , Methods). Furthermore, the conclusion also holds when inferring MCS from the in vitro fibroblast dataset and correlating it with absolute metabolite concentrations measured in mouse cell culture  (10) , suggesting that it is not an artifact of comparing species with different diets (SI Appendix, Fig. S8 ). Conservation is largely independent of the chemical class, physicochemical properties, toxicity, pathway membership, network position, and interaction degree of metabolites in the multivariate model (SI Appendix, Table  S4 ). For instance, while metabolites participating in many reactions or serving as allosteric activators of enzymes tend to be conserved, these relationships disappear when accounting for other metabolite properties (SI Appendix, Table  S4 ). Thus, contrary to intuitive expectations, metabolites interacting with multiple enzymes are not more strongly constrained.
To test whether this finding applies to other diseases beyond IEM, we used MarkerDB, a comprehensive database of clinical biomarkers  (32)  and focused on 11 broad disease conditions with sufficient numbers of metabolites (SI Appendix, Table  S10  and Dataset S1C). As expected, metabolites associated with metabolic disorders, including many IEMs, tend to be highly conserved (Fig. 5B ). More remarkably, we identified two additional broad disease conditions-cancers and cardiovascular diseases-that are independently associated with highly conserved metabolites (Fig. 5  C and D and SI Appendix, Table  S10 , Methods). For instance, choline, a precursor in lipid metabolism, is highly conserved in all four organs, but is not associated with any IEMs (SI Appendix, Fig. S13 ). Notably, abnormal choline metabolism is a general hallmark of cancers, and both phosphocholine and total choline-containing metabolite levels are used to detect malignant tumors  (33).
Indeed, the conservation score shows a positive correlation with the number of specific diseases involving a particular metabolite (SI Appendix, Fig. S14 ; effect is independent of abundance and essentiality, SI Appendix, Table  S11 ). Metabolome Conservation in the Drosophila Genus. To test the generality of our main findings, we also analyzed metabolome evolution in the distantly related genus Drosophila, across a 50-My phylogeny (SI Appendix, Fig. S15A ). We calculated metabolitespecific conservation scores using data on 92 nonlipid metabolites measured in whole adults of 11 Drosophila species under the same controlled environment (35) (Dataset S1D, Methods). Just as in mammals, MCS varies extensively across different metabolites, spanning over three orders of magnitude (SI Appendix, Fig.
S15B ). Remarkably, using an independent dataset of absolute metabolite concentrations in Drosophila melanogaster (36) (Dataset S1D), we found a significant positive correlation between abundance and the conservation score, with an effect size similar to that in mammals (SI Appendix, Fig. S15C ). Furthermore, metabolites involved in human IEMs tend be highly conserved in Drosophila as well (SI Appendix, Fig. S15D ). We conclude that metabolome evolution is governed by similar principles in two distant animal phyla.
Metabolite abundance emerged as the main determinant of conservation, with highly abundant metabolites displaying the highest level of conservation, as evidenced by three independent datasets of absolute metabolite concentrations in mice (Fig. 2 ), D. melanogaster (SI Appendix, Fig. S15 ) and in vitro cell culture pnas. org (SI Appendix, Fig. S8 ). Importantly, any particular metabolite displays stronger conservation in organs where it is more abundant, demonstrating that abundance per se affects conservation. Systems modeling further showed that abundant metabolites are subject to stronger functional constraints (Fig. 4 ). Why should it be so? First, the levels of highly abundant metabolites might be more rate-limiting for key fluxes than those of low-abundance metabolites, implying a causal effect of metabolite level on fitness.
Methods Calculating MCSs. To study metabolome conservation in mammals, we obtained metabolomic measurements of 139 nonlipid metabolites from a multispecies study  (7). The dataset contains relative metabolite levels across 26 mammalian species in four organs (brain, heart, kidney, and liver) and is based on targeted metabolomics measurements involving three distinct liquid chromatographymass spectrometry (LC-MS) methods. Note that the measured samples were homogenates of freshly frozen tissues of killed animals, matched by age (i. e. , young adults) and sex  (7). We calculated the mean of the normalized (log 10transformed) relative metabolite level across all biological replicates so that each metabolite in each species and organ is represented by a single relative concentration value. We then used these values as continuous molecular traits for which conservation scores are computed.
To calculate the MCS of individual metabolites, we first fit a simple BM model of trait evolution on the relative levels of each metabolite in each organ across the phylogeny, using the fitContinuous function in the Geiger R package  (43). The BM model represents evolution of a continuous trait through time as a random walk process in which, during any elapsed time Δt, the value of the trait ( x ) changes by a random number drawn from a normal distribution with a mean of 0 and a variance of σ 2 Δt. As such, at any timepoint t 1 , the level of the trait can be estimated as:  [1]  x(t 1 ) ∼  x t 0 , σ 2 Δt. This BM process can then be applied to a phylogenetic tree, as described by Felsentein  (44). In short, given a known phylogeny and known trait values at the tips of the tree, we can use Felsenstein's method to estimate the value of σ 2 that gives rise to the observed trait values in the timeframe supplied by the branch lengths of the phylogenetic tree, while also accounting for the phylogenetic relationships between the species.
Metabolite Features Associated with MCS. Seventeen distinct classes of metabolic features were collected in order to probe their relationship with MCS. Information on the regulatory roles of metabolites (enzyme activator, inhibitor, and cofactor function) was obtained from ref. 46  which was compiled from the BRENDA database  (47). Information on the chemical properties of metabolites (chemical class, molecular weight, dissociation constants, water solubility, and hydrophobicity) were collected from the HMDB and KEGG databases  (48, 49). Metabolite toxicity information, in the form of mouse LD50 values (the concentration of the metabolite that is lethal to 50% of specimens, in mg/kg) was collected from the ChemIDPlus database (https://chem. nlm. nih. gov/chemidplus/). Pathway membership and broad position in the metabolic network (biosynthetic, degradation, and energy metabolism) were collected from the KEGG and HumanCyc databases, respectively  (48, 50).
We note that pathway membership was used only for those metabolic pathways that pnas. org contained at least five metabolites for which we had conservation score calculated, yielding 27 pathways in total. Organ-specific absolute metabolic abundance measurements were obtained for mouse from the Mouse Multiple tissue Metabolome DataBase (MMMDB)  (17). Network degree (the number of reactions a metabolite participates in) was determined using a genome-scale reconstruction of the human metabolic network  (51). Metabolites involved in metabolic reactions that are encoded by essential genes were identified using phenotypic data from mouse knockout lines. In short, we identified genes whose deletion caused either a lethal phenotype or infertility in the Mouse Genome Database  (23). Next, we defined essential reactions as reactions where the majority (>50%) of the genes associated with the reaction in the human metabolic network are essential.
Metabolome Conservation in the Drosophila Genus. Metabolomics data of 92 nonlipid metabolites measured in 11 Drosophila species (D. ananassae, D. yakuba, D. erecta, D. melanogaster, D. simulans, D. sechellia, D. pseudoobscura, D. persimilis, D. willistoni, D. virilis, and D. mojavensis) and the phylogenetic tree describing the evolutionary relationship between the species were obtained from ref. 35. Conservation scores were computed as described above (see "Calculating MCSs")  (35). Absolute metabolite concentrations of 35 nonlipid metabolites, as quantified by NMR metabolomics, were obtained from ref. 36. We used the metabolite concentrations measured in whole D. melanogaster larvae samples, in order to best match the samples used in ref. 35. Of these 35 metabolites, 24 overlapped between the datasets.
ACKNOWLEDGMENTS. We thank  Csaba Pál ,  Martin J. Lercher , and  László G. Nagy  for discussions and critical comments on the manuscript. This work was supported by the  National Research, Development and Innovation Office Élvonal Program   KKP 129814  (B. P. ), the  "Lendület" program  of the  Hungarian Academy of Sciences   LP2009-013/2012  (B. P. ), the  European Union 's  Horizon 2020 research and innovation program  Grant No. 739593  (B. P. ), the  National Laboratory for Health Security  Grant  RRF-2. 3. 1-21-2022-00006  (B. P. ), the  National Laboratory of Biotechnology  Grant  NKFIH-871-3/2020  (B. P. ), The  Hungarian Academy of Sciences Premium Postdoctoral   Research Program  ( PREMIUM-2018-294  to B. S. ),  János Bolyai Research Fellowship  from the  Hungarian Academy of Sciences  ( BO/00728/21/8  to B.
3 ± 2. 6‰; n = 3). Grazers and browsers differed significantly from carnivores (p < 0. 001), but, in contrast to the enamel dataset, the mixed feeders did not differ from carnivores (p = 0. 95). We found a significant, positive correlation between δ 15 N enamel and δ 15 N bone-collagen values (Pearson's correlation r (31) = 0. 865, p < 0. 001; Fig. 2 ). An ordinary least squares regression yielded the following relationship: δ 15 N enamel ~0. 88 [95% confidence interval (CI): 0. 66 to 1. 1] × δ 15 N bone-collagen + 0. 43‰ [95% confidence interval (CI): -0. 8 to 2. 0] with no consistent, directional offset in δ 15 N values. Trophic enrichment between herbivores and carnivores (Δ 15 N = δ 15 N carnivore -δ 15 N herbivore ) is apparent in both datasets but is larger in enamel (3. 7‰) compared to bone collagen (3.
Fossil mammals Nitrogen content. The nitrogen content of modern African mammalian enamel was typically 2 to 10 nmol/mg ( x = 4. 8 ± 2. 0 nmol/mg; n = 54) after reductive-oxidative cleaning (see Methods). Fossil tooth enamel N content was between 4 and 10 nmol/mg ( x = 6. 4 ± 1. 6 nmol/mg; n = 10) after cleaning, thus falling within the range of the modern enamel samples (Fig. 4  and Tables  1, 2 ). No differences were observed between dietary or taxonomic groups in either modern or fossil datasets (Fig. S3 ), and, importantly, no significant correlation was observed between δ 15 N enamel and N content (Pearson's correlation r (62) = 0. 0033, p = 0. 979). Nitrogen isotopes. The Late Pleistocene mammals from SE Asia exhibited a range of δ 15 N enamel values (2. 6 to 11. 1‰, n = 10) similar to those of the modern African mammals.
When added to the regression of the modern African mammal δ 15 N bone-collagen and δ 15 N enamel values, the four fossil specimens show a moderate, positive correlation, and-although this relationship is not significant (Kendall's Tau r τ = 0. 667, p = 0. 333)-the regression residuals are mostly within the range of modern mammals (Fig. 2  and S7). As observed in the modern dataset, δ 15 N enamel values were lowest in the herbivores (6. 1 ± 2. 7‰; n = 5), highest in the carnivore (a leopard, Panthera pardus; 11. 1‰), and intermediate in the omnivores (7. 3 ± 2. 4‰; n = 4; Fig. 5 ). The grazers, including an Asian water buffalo (Bubalus bubalis) and an unspecified bovine (Bos sp. ), had the lowest values (4. 0 and 2. 6‰, respectively), while the mixed-feeding cervid (Muntiacus muntjak; 7. 6‰), the browsing rhinoceros (Rhinoceros sondaicus; 7.
7‰) and serow (-15. 2‰). The mixedfeeding muntjac had an intermediate value of -12. 9‰. The bovine (indet. ) and Asian water buffalo, both grazers, had the two highest values (-1. 5 and -0. 8‰, respectively). The suids, macaque, bear, and leopard all had similar δ 13 C enamel values, ranging between -14. 3 and -13. 3‰ (see Table  2 ). As with modern mammals, carbonate content in the fossil enamel samples was typically between 4 and 7% wt. Only four THM specimens were sufficiently preserved for δ  13  C dentin-collagen analysis (data from Bourgon et al. 40  ), but they show a positive relationship with δ 13 C enamel data from the same specimens, consistent with the regression obtained for modern specimens (Fig. S4 ).
While the organic fraction of bone consists mainly of collagen (90%), the organic matter in enamel is comprised of enamelspecific proteins (predominantly amelogenin) and proteases  27, [52] [53] [54]. There should thus not necessarily be a perfect 1:1 correlation between δ 15 N enamel and δ 15 N bone-collagen. Nevertheless, the positive correlation between enamel and bone collagen from the same individuals and the clear enrichment in δ 15 N enamel across trophic levels confirm that δ 15 N enamel records diet and trophic level in a manner similar to δ 15 N bone-collagen. Importantly, our dataset also includes measurements of nitrogen and carbon isotope values using the same aliquot of tooth enamel. δ 15 N enamel and δ 13 C enamel values are plotted together in Fig. 3  and reveal clear, interpretable patterns that are in good agreement with expected dietary habits for the modern taxa included in this study.
1c ). Despite this overlap, mixed feeders still differ significantly from carnivores in δ 15 N enamel. This is not the case for δ 15 N bone-collagen , although this difference may have been driven, at least in part, by the smaller size of the collagen dataset. These herbivore δ 15 N values are consistent with previously published herbivore data from modern ecosystems  6, 8, 25, 36, [41] [42] [43] 61, 66. Ambro e  41  observed relatively high δ 15 N bone-collagen values (also overlapping with those of co-occurring carnivores) in mixed-feeding herbivores from eastern Africa, Sealy et al. 8  observed higher δ 15 N bone-collagen values in mixed-feeding springbok compared to other herbivorous taxa in southern Africa, and Codron et al. 42  measured the highest herbivore δ 15 N values in the feces of mixed feeders (impala and nyala) in their study of herbivores in Kruger National Park.
African elephant tissue δ 15 N values vary widely, depending on which region of Africa the animals inhabit, but our observed δ 15 N enamel values (5. 4 to 10. 0‰) fit well within the large range of published bone collagen values (2. 0 to 16. 0‰) for this taxon 8,67-69. Th re is much debate regarding the possible mechanisms driving elevated values in mixed feeders and it remains unclear why mixed feeders tend to have higher δ 15 N values than other herbivores overall (see Fig. S6  and Supplementary Discussion for a more detailed discussion of this topic). Our δ 15 N enamel dataset for one given locality in Africa is too small to test if this holds true for tooth enamel amongst mixed feeders more broadly. Regardless the overall pattern observed in our dataset is consistent with data published for herbivores from African and South American ecosystems  36, 61, 66.
One individual was measured for all taxa, with the exception of the wild boar. Green shaded bars at the top of the figure indicate tooth enamel δ 13 C isotopic ranges for herbivores corresponding to pure C 3 (browsing) and C 4 (grazing) resource utilization (enamel δ 13 C after Cerling et al. 104  and corrected for a fossil-fuel-induced shift in the δ 13 C atmospheric CO 2 of ~-2. 0‰  98  ). Grazing taxa are clearly distinguished from the rest of the fauna by their higher δ 13 C enamel values. Most of the THM fauna lived and foraged in predominantly C 3 habitats. Herbivores and omnivores have lower δ 15 N enamel values compared to the single carnivore, which has the highest value (Panthera pardus). The δ 15 N enamel values we obtained for baboons are consistent with existing stable isotope data for these primates  62.
Baboon δ 15 N enamel values were significantly lower than those of carnivores and were instead comparable to those of herbivores, specifically the mixed feeders (Fig. 1 ). Although some studies have found that baboons have low δ 15 N values compared to sympatric herbivores  6, 62  , perhaps related to the consumption of N 2 -fixing plants and/or underground storage organs, no clear tendency towards lower values was observed in baboon δ 15 N enamel values compared to herbivores in our dataset. The teeth sampled for this study would have formed just at the end of the juvenile period, and young, low-ranking baboons rarely consume meat, a behavior that has primarily been observed in dominant adult males  36, 75, 76. Thus the relatively low δ 15 N enamel values for the baboons are expected. δ  15  N enamel values were the highest for the carnivores, evidencing clear trophic enrichment compared to herbivores and falling into the range of δ 15 N bone-collagen values typical for carnivores.
Within the carnivore guild, we also observed differences in δ 15 N enamel between taxa. Leopards (Panthera pardus) and wild dogs (Lycaon pictus), for instance, had lower δ 15 N enamel values than spotted hyenas (Crocuta crocuta) and lions (Panthera leo). Overall, the δ 15 N enamel values of spotted hyenas are higher than those of other carnivore species, and, in two individuals, substantially higher than all other δ 15 N values measured for this species in this study. It is probable that these higher values incorporate a nursing signal, as the permanent dentition of spotted hyenas mineralizes early and erupts at approximately the same time that weaning occurs  77. If these two outliers are excluded from the carnivore δ 15 N enamel dataset, Δ 15 N carnivore- herbivore decreases to 3. 1 ‰, but trophic enrichment between herbivores and carnivores nevertheless remains significant and equal to that of δ 15 N bone-collagen.
Although the observed differences between carnivore δ 15 N enamel values are potentially related to niche separation and differential habitat use/prey preference, no strong conclusions can be drawn from the differences in δ 15 N enamel values alone, especially when considering that these samples are drawn from disparate localities. However, carbon isotope data help shed further light on niche separation between carnivore taxa. For instance, while all carnivores included in this study are typical savanna dwellers, δ 13 C enamel values for leopards and wild dogs in this dataset indicate that these two taxa relied more heavily on browsing prey (i. e. , C 3 -consuming prey) compared to spotted hyenas and lions (Fig. 3 ). Most carnivores selectively hunt specific taxa and their diets can be strongly influenced by competition with other carnivores.
Leopards, for example, prefer relatively small prey (e. g. , body mass 10 to 40 kg), which occur in dense habitats; for example, impala, bushbuck, and common duiker, while larger prey and species restricted to open vegetation are generally avoided  78. Similarly, wild dogs tend to hunt in areas of denser vegetation and target browsing and mixed-feeding herbivores in regions where they co-occur with hyenas and lions  79. Lions and hyenas, in contrast, have higher δ 13 C enamel values, consistent with the consumption of a greater proportion of grazing taxa (i. e. , C 4 -consuming prey) which occupy more open environments. These carnivore data illustrate the potential to refine reconstructions of trophic niches using combined δ 15 N enamel and δ 13 C enamel analyses. Importantly, this study was not designed to explicitly test the effect of the potential confounding abiotic or biotic factors that may be driving variation in herbivore/carnivore δ 15 N values, and our δ 15 N enamel dataset for any one given locality in Africa is too small to do so properly.
Rather, we set out to demonstrate that δ  15  N enamel values record diet in a robust manner comparable to other commonly measured tissue types, especially collagen, the material most frequently measured in the archeological and fossil record. Our data conclusively demonstrate that tooth enamel organic matter records dietary information, confirming the utility of δ 15 N enamel as a trophic level proxy. Tooth enamel isotopes measured in Late Pleistocene fossil teeth indicate good preservation of enamel-bound organic matter and record diet and trophic level information. In their study of zinc isotopes in fossil tooth enamel from THM, Bourgon et al. 40  attempted to extract collagen from dentin for δ 13 C and δ 15 N analysis. Of 72 samples, 23 had enough dentin to attempt collagen extraction, but only four specimens had sufficiently preserved collagen (i.