Ecology

Metabolic profiling of EP and LE root exudates and root periderm samplesHigh performance liquid chromatography (HPLC) analysis of root exudates and root periderm reported the presence of five bioactive NQs. The identified NQs included shikonin (SK), acetylshikonin (AS); isobutyrylshikonin (IBS); β, β-dimethylacrylshikonin (DMAS); and isovalerylshikonin (IVS) (Fig. 1a–d). This suggests that SK and its derivatives accumulate in the rhizosphere of both EP and LE via root exudation. Though all the five NQs were found to be exuded in the rhizosphere however they varied quantitatively among EP and LE species. LE samples had higher SK and its derivatives production compared to EP (Figs. S5–S6). Our results also displayed quantitative variations in SK and its derivatives production among two soil types (Table 1a,b). However, regardless of variation, SK, AS, DMAS, and IVS were consistently present among all the samples.Figure 1Images and chromatograms representing qualitative and quantitative variation of SK and its derivatives production in root periderm extracts. Chromatograms of root extracts of E. plantagenium (EP) and L.erythrorhizon (LE) specimens grown in Peat potting artificial soil (a) EP.PP, (c) LE.PP; and Natural campus soil (b) EP.NC, (d) LE.NC. Resulting peaks correspond to shikonin (SK), acetylshikonin (AS); isobutylshikonin (IBS); β, β-dimethylacrylshikonin (DMAS); and isovalerylshikonin (IVS). Chromatogram for each sample represents a composite sample of 3–4 individual plants. Figure represents only one replicate for each sample while the rest of the two replicates for each sample with standard chromatogram are provided in Fig. S5.Full size imageTable 1 Quantitative analysis of shikonin and its derivatives via HPLC in (a) root periderm; (b) root exudates samples of E. plantagineum (EP) and L.erythrorhizon (LE).Full size tablePacBio sequence reads statistics and taxonomic profilingAfter quality filtering, removal of chimera, chloroplast and mitochondrial sequences, approximately 165,570 high quality sequences (Tags) were obtained. Tags were clustered into 14,429 microbial operational taxonomic units (OTUs) at a 97% sequence similarity cutoff level (Table S2). All OTUs with species annotation are summarized in Table S3. Taxonomic profiling for taxonomic affiliations revealed Proteobacteria, Bacteroidetes, Planctomycetes, Cyanobacteria, Acidobacteria, and Actinobacteria to be the dominant phyla among all the samples (Fig. S7). These 6 phyla accounted for 70.97–96.61% of the total microbial OTUs. The Proteobacterial microbes mainly belonged to Classes Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria that accounted for 13.94–40.54% of the total microbes (Table S4).Host plant genetics are the drivers for distinct microbiomeTo identify the effects of host plant genetics on microbial acquisition, microbial community composition of bulk soil was compared with root and rhizospher soils of EP and LE. α-diversity estimates revealed a significantly higher observed species richness (Sobs), and shannon diversity for bulk soil (Fig. 3a,b; Table S5). This indicates that bulk soil serves as a reservoir for microbial acquisition in other rhizo-compartments. At different taxonomic levels, microbes associated with Proteobacteria, Planctomycetes, Bacteroidetes and Cyanobacteria were all present in relatively higher abundance in EP and LE rhizo-compartments compared to bulk soil in two different soil types (Fig. 2a; Table S6). Wilcox test also displayed quantitative variation in microbial acquisition at order level. For example, compared to bulk soil, Flavobacteriales, Sphingomonadales, and Verrucomicrobiales had a relatively higher abundance in EP rhizosphere, while Caulobacterales, and Sphingomonadales were significantly higher in LE rhizosphere (Fig. S8, P  More

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P. aeruginosa produces novel glycolipids in response to Pi stressTo determine changes in the membrane lipidome in response to P-stress, the model P. aeruginosa strain PAO1 was grown in minimal medium under high (1 mM) or low Pi (50 µM) conditions (Fig. 1a). The latter condition elicited strong alkaline phosphatase activity, measured through the liberation of para-nitrophenol (pNP) from pNPP (Fig. 1b), this being a strong indication that cells were P-stressed. Analysis of membrane lipid profiles using high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS) revealed the presence of several new lipids under Pi stress conditions (Fig. 1c). Thus, during Pi-replete growth (1 mM phosphate), the lipidome is dominated by two glycerophospholipids: PG (eluted at 6.8 min) and PE (eluted at 12.2 min). During Pi-stress a lipid species with mass to charge ratio (m/z) of 623 and 649 were also found, with MS fragmentation resulting in a 131 m/z peak, a diagnostic ion for the amino-acid containing ornithine lipid. This is consistent with previous reports of ornithine lipids in the P. aeruginosa membrane in response to Pi stress [29, 30].Fig. 1: Lipidomics analysis uncovers novel glycolipid formation in Pseudomonas aeruginosa strain PAO1 in response to phosphorus limitation.a Growth of strain PAO1 WT in minimal medium A containing 1 mM phosphate (+Pi, blue) or 50 µM phosphate (−Pi, black) over 12 h. Data are the average of three independent replicates. b Liberation of para-nitrophenol (pNP) from para-nitrophenol phosphate (pNPP) through alkaline phosphatase activity, under Pi-replete (1 mM, black) and Pi-deplete (50 µM, yellow) conditions. Error bars represent the standard deviation of three independent replicates. c Representative chromatograms in negative ionisation mode of the P. aeruginosa lipidome when grown under phosphorus stress (−Pi, black) compared to growth under phosphorus sufficient conditions (+Pi, orange). PG phosphatidylglycerol, PE phosphatidylethanolamine, OL ornithine lipids. Lower panel: extracted ion chromatograms of three new glycolipid species in P. aeruginosa which are only produced during Pi-limitation (black, 1 mM; orange, 50 µM). MGDG monoglucosyldiacylglycerol, GADG glucuronic acid-diacylglycerol and UGL unconfirmed glycolipid. d Mass spectrometry fragmentation spectra of three glycolipid species present under Pi stress in P. aeruginosa, at retention times of 7.7 (m/z 774.7), 8.7 (m/z 786.7) and 9.8 (m/z 788.6) minutes, respectively. Each spectrum depicts an intact lipid mass with an ammonium (NH4+) adduct exhibiting neutral loss of a head group, yielding diacylglycerol (DAG) (595 m/z). Further fragmentation yields monoacylglycerols (MAG) with C16:0 or C18:1 fatty acyl chains.Full size imageFurther to ornithine lipids, three unknown lipids eluting at 7.7, 8.7 and 9.8 min, were only present under Pi stress conditions (Fig. 1c). Using several rounds of MS fragmentation (MSn), with a quadrupole ion trap MS, fragmentation patterns characteristic of glycolipids were found for all three peaks. For each peak of interest, the most predominant lipid masses of 774.7, 786.8 and 788.6 m/z were analysed by MSn in positive ionisation mode (Fig. 1d). In each case, an initial head group was lost leaving a significant signal of 595.6 m/z, the mass of the glycolipid building block diacylglycerol (DAG). Further fragmentation leads to the loss of either fatty acyl chain from DAG, leaving monoacylglycerols of 313.2 and 339.3 m/z. Two monoacylglycerols with different masses are produced as a result of the original lipid containing 16:0 and 18:1 fatty acids (313.2 and 339.3 m/z monoacylglycerols, respectively). To further elucidate the identity of the peaks, a search for a neutral loss of a polar head group was carried out. Thus, the intact masses of 774.7 and 788.6 m/z in positive ionisation mode leads to the loss of a head group of −179 and −193 m/z, which corresponds to a hexose- and a glucuronate- group, respectively (Fig. 1d), suggesting the occurrence of novel monoglucosyldiacylglycerol (MGDG) and glucuronic acid diacylglycerol (GADG) glycolipids in P. aeruginosa. The third glycolipid peak at 8.7 min remains an unknown lipid with intact mass of 786.8 m/z (hereafter designated as a putative unknown glycolipid, UGL). Together, these data confirm the production of new glycolipids in P. aeruginosa in response to Pi stress.Comparative proteomics uncover the lipid renovation pathway in P. aeruginosa
To determine the proteomic response of P. aeruginosa to phosphorus limitation, and identify the genes involved in glycolipid formation, strain PAO1 was cultivated under high and low Pi conditions for 8 h and the cellular proteome then analysed. A total of 2844 proteins were detected, 175 of which were found to be differentially regulated by Pi availability (Fig. 2a, Table S1). In line with previous transcriptomic studies of strain PAO1 [18], major phosphorus acquisition mechanisms were highly expressed under Pi stress conditions, e.g. the Pi-specific transporter PstSCAB, the two-component regulator PhoBR (Table S1) [31].Fig. 2: Comparative multi-omic analyses for the identification of the PlcP-Agt pathway responsible for glycolipid formation in Pseudomonas aeruginosa strain PAO1.a Volcano plot depicting differentially expressed proteins when comparing Pi-replete and Pi-deplete conditions. Significantly upregulated proteins when under Pi stress are shown in red (left), and those that are significantly upregulated when Pi is sufficient are in green (right). Significance was accepted when the false discovery rate (FDR) was More

IACUC approval: all work described below was approved by the Boise State Institutional Animal Care and Use Committee: AC15-021.Site layoutWe selected 20 sites, across five drainages, within the Pioneer Mountains of Idaho—matched for elevation and riparian habitat. We split these 20 sites into 10 noise playback sites, and 10 control sites (Fig. 1A; S1). The control sites ranged from quiet, slow-moving streams to relatively loud whitewater torrents. Noise playback sites, on the other hand, were relatively quiet (not whitewater) sites, where we broadcast loud whitewater river recordings with speaker arrays hung from towers (Fig. S1; S2; S3; S4; see supplementary information for more details on noise file creation, playback equipment, and experimental setup). At five of the noise playback sites we broadcast normal river noise (hereafter referred to as ‘river noise’ sites), and at the other five noise sites we broadcast spectrally-altered river recordings (hereafter referred to as “shifted noise” sites).Our field sites were oriented along the riparian zone, with data collection occurring at three primary locations within each site (Fig. S1): (1) roughly in the middle of the speaker tower systems, (2) at a shorter distance from the middle location (mean: 198.2 ± 54.5 m SD; range: 117.6–384.5 m), and (3) and a longer distance from the middle location (in the opposite direction from the nearer location; mean: 312.7 ± 64.7 m SD; range: 249.1–479.6 m). Thus, sites were approximately 510.9 ± 98.3 m long (range: 374.7–850.6 m), along the riparian corridor. All control sites were, at minimum, 1 km apart along the riparian corridor from any noise site, to maintain acoustic independence (see Fig. 1A; S1).Data collectionBirds
We conducted three-minute avian point counts between one half hour before sunrise and 6 h after sunrise (roughly 0530–1130 h). During the project, we conducted 1330 point-counts from 28 May to 20 July 2017 and 1639 point-count events occurred from 7 May to 24 July in 2018.
Caterpillar deploymentWe deployed a total of 720 clay caterpillars throughout the 2018 breeding season. Forty caterpillars were glued to stems and branches of trees between 1 and 2.5 m high at each site (Fig. S8). Twenty caterpillars surrounded the middle point count location at each site (a set of 10 were placed upstream, and another set of 10 were placed downstream starting from the middle ARU location), while the other twenty were at upstream and downstream sampling locations (10 each at upstream and downstream locations). We placed each caterpillar along the riparian corridor, at least 1 m apart from each other30. See Supplementary information for details on caterpillar predation scoring.Bird trait analysisWe performed a trait-based analysis to understand the mechanistic patterns of bird distributions in our study paradigm. Avian vocal frequencies and body mass were collected from Hu and Cardoso 2009, Cardoso 2014, and Francis 201516,31,32. When multiple sources contained data, the values were averaged. There were a few cases where none of those sources contained a vocal frequency or mass measurement for species of interest. Thus, representative songs were downloaded from the Macaulay Library of the Cornell Lab of Ornithology based on recording quality and geographical relevance (MacGillivray’s warbler: ML42249; dusky flycatcher: ML534684; red-naped sapsuckers: ML6956), and analyzed with Avisoft SASLab Pro to obtain a peak frequency measure. Mass measurements for these ‘missing’ birds were taken from the ‘All about birds’ webpage of the Cornell Lab of Ornithology.BatsMeasuring and identifying bat callsWe measured bat activity using Song Meter 3 (hereafter “SM3”) recording units (Wildlife Acoustics Inc., Massachusetts, USA) equipped with a single SMU (Wildlife Acoustics Inc.) ultrasonic microphone. One recording unit was used at each site and we pseudo-randomly rotated the unit between the three point-count locations so that each location was monitored for at least 21 days. We mounted microphones on metal conduit at a height of ~3 m, oriented perpendicular to the ground and facing away from the stream to optimize recording conditions (Fig. S9; S10; see Supplementary information for more information).Robotic insectsWe used a modified version of Lazure and Fenton’s26 apparatus to present bats with a fluttering target (Fig. S12). This consisted of a 3 cm2 piece of masking tape affixed to a metal rod [30.48 cm length × 3.25 mm diameter], which itself was connected to a 12-volt brushed DC motor (AndyMark 9015 12 V, AndyMark Inc., Kokomo, IN, USA). The no-load revolution speed of these motors (267 Hz) falls within the range of wingbeat frequency measured in Chironomidae27,33, a group that is an important food source for many North American bat species34.We attached each motor to a tripod made of PVC piping and positioned the tripod such that the target was approximately 1.2 m above the ground. Each motor was powered by a 12 V battery (35Ah AGM; DURA12-35C, Duracell) which was controlled by a programmable 12 V timer (CN101, FAVOLCANO) to automatically start and stop the motor each night. The rotors were powered for 2 h following sunset.Prey-sound speaker playbackWe created a playlist composed of several insect acoustic cues to present gleaning bats: a beetle (Tenebrio molitor) walking on dried grass, a cricket (Acheta domesticus) walking on leaves, mealworm larvae (Tenebrio molitor) on leaves, fall field cricket (Gryllus pennsylvanicus) calls, and fork-tailed bush katydid (Scudderia furcata) calls. The cricket and katydid calls were sourced from the Macaulay Library (ML527360 and ML107505, respectively).Experimental setup for bat foraging testsMost sites received two rotors (Fig. S12) and two speakers (Fig. S13): one of each at the center of the site, and one of each at approximately 125 m from the center of the site (in opposite directions in order to have tests in a range of acoustic environments), placed roughly 10 m from the edge of the riparian zone. Rotors and speakers at the center locations were separated by at least 50 m. The exception to this setup were the four positive control (loud whitewater river) sites, which only received a single rotor and speaker separated by 50 m because of logistical difficulties of accessing those sites. We paired each rotor and speaker with an SM2BAT + bat detector equipped with an SMX-US microphone (Wildlife Acoustics Inc.)35, using tripods to elevate the microphones approximately 1 m off the ground and ~1 m from the speaker/rotor. We programmed the bat detectors with a gain of 36 dB and a trigger level of 18 dB to limit recordings to bats that were passing within the immediate vicinity. To allow for a comparison of activity between speakers and rotors, bat activity was only considered for the first two hours following sunset.Bat trait analysisWe collected bat foraging behavior and peak echolocation frequency information to use as predictors in a phylogenetically controlled trait analysis (Tables S8; S13). We based our behavioral foraging classifications on the categories of Ratcliffe et al.36 and followed the classifications of Gordon et al.37 where possible, and others38,39,40,41,42,43 where necessary. We extracted peak echolocation frequency from the 2017 and 2018 SM3 field recordings and employed two controls to decrease variability in call parameters potentially introduced via this method. First, we selected only recordings made on control sites in 2017 and 2018 (n = 740,848 calls), as echolocation call characteristics may be affected by local acoustic environments (e.g., Bunkley et al.)22. Secondly, we averaged all call parameters per species per hour at each site to decrease the possible effects of few individuals driving measurements. This resulted in 9538 species-hours of recordings, which themselves were averaged per species (Table S13).Quantifying environmental variablesWe used long-term monitoring of the acoustic environment (via Roland R05 recorders) to calculate daily sound pressure level (L50 dBA) and median frequency (kHz) values for each location (see supplementary information for details on quantification of all predictor variables).Sound pressure level (SPL)We converted 106,769 h of long-term ARU recordings into daily-averaged median sound pressure levels (L50; measured as dBA rel. 20 µPa) see refs. 13,44 using custom software ‘AUDIO2NVSPL’ and ‘Acoustic Monitoring Toolbox’ (Damon Joyce, Natural Sounds and Night Skies Division, National Park Service).Acoustic environment spectrumWe used custom software45 in the programming language R and the package ‘FFmpeg’ in command prompt to convert 106,769 h of long-term recordings into 71,282 individual 3-minute files starting each hour of the day (Fig. S5). Thus 24, 3-min files were created per acoustic recording location per day (one for every hour). We then used the packages “tuneR” and “seewave” to read in and measure the median frequency of sound files, respectively45,46,47. These hourly metrics were then averaged by date to create a daily metric.StatisticsAll models of abundance, activity, and foraging transects were generalized linear mixed effects models (glmm) in R48 using the package ‘lme4’49,50 or ‘glmmTMB’51. All distribution families were selected based on theoretical sampling processes of the data, models were checked for collinearity (VIF scores)52, and model fits were visually checked with residual plots (see supplemental R code)53.Bird abundance and bat activity
Model predictors and covariates
Both bird and bat models had the following variables in a glmm: site and bird/bat species were random effects terms and sound pressure level (dBA L50), sound spectrum (median frequency), the interaction between sound pressure level and spectrum, elevation, percent riparian vegetation, ordinal date (and a quadratic version of this), and year as fixed effects. While year is sometimes used as a random-effect term, it is suggested to be used as a fixed effect if fewer than five levels exist for that factor, as variance estimates become imprecise54,55. Additionally, moon phase was a fixed effect in the bat models56, while spectral overlap (the absolute difference between sound spectrum and bird species vocalization frequencies) and the interaction between sound pressure level and spectral overlap were fixed effects in bird models.
We attempted to fit both sound pressure level and spectrum as having random slopes for each species, yet both bat and bird models would not converge with such complex model structure. Thus, we followed group models with individual species models (see Supplementary information).

Model family distribution and link function
For both bird and bat counts, we used a negative binomial distribution with a log link, rather than a Poisson distribution, because data were over-dispersed. We plotted variance-mean relationships and residuals of multiple models to select the appropriate variance structure, and compared these with AIC to select the best-fitting distribution (see R script for further justification of these methods)54.

Individual species models
Individual species models were parameterized the same as above (except without the species term). All 12 bat species (see Tables S6; S10) and 26 of the most common birds (see Tables S2; S9) were modeled individually to be able to interpret model parameter estimates, with complex interactions, for each species.
Clay caterpillar predationWe modeled caterpillar predation with a glmm (binomial family; logit link function), using the number of individual scorers as weights in the model. Like the bird abundance model, we used site as a random effect and sound pressure level (dBA L50), spectral frequency (median), elevation, percent riparian vegetation, ordinal date, and year as fixed effects (Table S4). Additionally, the predicted number of birds at a site were modeled as fixed effects to control for varying amounts of foraging birds on the landscape.Robotic moths and prey-sound speakersRobotic moth and prey-sound speaker models were parameterized exactly the same as the overall bat activity model. That is, the model was fit with a negative binomial family (log link) with site and species as random effects and sound pressure level (dBA L50), sound spectrum (median frequency), the interaction between sound pressure level and spectrum, moon phase, elevation, percent riparian vegetation, ordinal date (and a quadratic version of this), and year as fixed effects. Additionally, the predicted number of bats at a site were modeled as fixed effects to control for varying amounts of foraging bats on the landscape.Trait analysesWe performed trait analyses with phylogenetic generalized least squares (PGLS) to control for relatedness while predicting species responses to noise12. We performed PGLS analyses with the gls function in the R package nlme57, and accounted for error in the response variable with a fixed-variance weighting function of one divided by the square root of the standard error of the response estimate58,59. We accounted for phylogenetic structure by estimating Pagel’s λ60. When λ estimates fell outside of the zero to 1 range, we fixed λ at the nearest boundary. For bird models, we used a pruned consensus tree from a recent class-wide phylogeny61. For bats, we used a pruned mammalian tree62. We used initial global models with all traits as variables that explained the responses to sound pressure level (SPL; birds and bats), spectral overlap with birdsong (birds), background frequency (bats), and the interaction between SPL and each measure of frequency (birds and bats). We then used AIC model selection63 to choose top models in explaining these patterns. Models with dAIC ≤4 are included in Table S3 (birds) and Table S8 (bats), and the top model is interpreted in the main text.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

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Morphological analysisFood preparation or processing of plant material involve multiple activities and all of them can potentially leave micro-traces in the tartar, together with the environmental components.Eleven dental calculi showed plant record: starches, pollen grains, one trichome, one sporangium, and tissue fragments (Table 1).Table 1 Plant microdebris recovered from dental calculus samples of Casale del Dolce.Full size tablePlant hairTrichomes are epidermal outgrowths characterized by different structure and function. Although plant hairs are some of the most common findings in the overall particulate matter carried by air (as pollen grains), in literature, only very few examples of trichomes in ancient contexts have been reported28,29,30. Trichome identification is not a common area in dental calculus research since they do not have a diagnostic morphology. For this reason, the identification of such type of microdebris must be based on realistic criteria, also in accordance with the geographical and historical context, providing all possible interpretative scenarios. The detection of trichomes in ancient tartar may disclose other lines of evidence than nutrition, representing a reliable archaeological environmental proof31.One plant hair was identified in CDD1 sample (Table 1). This remain (Fig. 2L) falls into the general class of dendritic trichomes and its peculiar morphology has been more specifically termed a candelabrum or abietiform32. The overall structure corresponded to non-glandular and pluricellular trichomes with a central uniseriate axis and whorls of unicellular rays emerging at the joints of the axis. Usually, 4 radii from each node occurred perpendicular to the central axis. As exhaustively reported in literature, dendritic trichomes are known in ferns, different groups of modern monocots and basal eudicots, such as Scrophulariaceae and Platanaceae. Although dendritic, trichomes of ferns and monocots were excluded. Indeed, the first ones possess single secondary branches that alternatingly arise at an angle of 70°–120° with respect to the main axis along a single plane33, while the second ones show morphological features and appearance different from the ancient debris34,35. Candelabrum-like trichomes have been usually detected in Verbascum L. and Platanus L. species36. For this work, an experimental reference collection of trichomes from these plants was created (Supplementary Information 1). The general aspect of mullein trichomes appears to be capitate, bigger, more elongated, and slenderer than the microremain found in tartar sample. In addition, these trichomes seem to possess a pair of secondary elements per side or single secondary branches, which depart from the nodes, only rarely perpendicular to the central axis37,38,39. Thanks to the well-preserved morphology, the ancient candelabrum hair was interpreted as a Platanus sp. foliar trichome based on literature40 and our experimental reference, although mullein cannot be totally excluded. Dimensions, distance between nodes and the number of tapering secondary branches attached to the central axis of the microremain were like those of all plane species documented in literature40,41,42.Figure 2Plant microremains identified by light microscopy in dental calculus samples. Some of the images captured by optic microscopy were shown. Aggregate of Triticeae starch granules and relative polarized image (A); Fabaceae starch granule and relative polarized image (B); Pinaceae pollen grain (C); aggregate of Triticeae starch granules and relative polarized image (D); Cupressaceae pollen grain (E); Poaceae spontaneous group pollen (F); polyhedral starches of morphotype II (G,H); fragments of plant tissues (I–K); dendritic hair (L). The scale bar indicates 15 µm [45 µm for panel (L)]. Small flecks of calculus still attached to microremains can be observed in some panels.Full size imageThis finding leads to consider some paleoenvironmental implications. Fossil pollen analysis has demonstrated that, during the Plio-Pleistocene, Platanaceae were present in the Upper Valdarno (Italy)43. For the Holocene, likely as a consequence of Pleistocene glaciations, fragmentary and scarce evidence of plane tree have been found in Spain and French Mediterranean coast; no record of Platanus sp. has hitherto been found in Italy44,45. This thermophylous taxon has reappeared later as an ornamental tree, providing shade, during Roman times46. As we applied rigorous decontamination protocols, the evidence of this ancient trichome, probably accidentally inhaled by CDD1, may testify the presence of Platanus sp. and humid environments in central Italy during the Neo-Chalcolithic period.Starch granulesMore than 70 starches were retrieved from calculus samples (Table 1). Some of them were found in an extraordinary state of preservation, likely due to intentional ingestion and/or accidental inhalation during the processing of starchy foods. These grains were clustered in three different morphological types, based on the morphometric parameters (i.e., shape, size, presence of lamellae and hilum, aggregation level, and other secondary features) evidenced by literature. They were described using the International Code for Starch Nomenclature47,48.Morphotype I These starches were consistent with those of Triticeae Dumort. tribe and occurred in almost all samples, as the most copious group (Table 1; Fig. 2A,D). Some grains were still lodged together. The morphotype was characterised by a bimodal distribution, or rather co-presence of large and small granules. Occasionally, the morphology was not completely intact, probably due to chewing as well as grinding and/or cooking procedures. These starch grains were similar to those occurring in caryopses of cereals, such as Hordeum sp. L. and Triticum sp. L. In particular, the diagnostic starches were oval to sub-round in 2D shape (15–43 µm in length; 10–35 µm in width). They had a central and distinct hilum and, sometimes, no visible lamellae. The small granules (≤ 10 μm in diameter) were spherical in shape with a central hilum. Knowledge about the Neo-Eneolithic period in central Italy is characterized by discontinuous data. The archaeobotanical dataset available for Latium is still limited49 but information about cultivated and wild-collected plants from Casale del Dolce site exists. In fact, the carpological analysis previously conducted50 has identified several caryopses of barley and wheat, supporting our results. The recovery of these starch grains, in almost all samples, suggested that the use of cereals was common and probably frequent for Casale del Dolce people, even if it is quite difficult to correlate presence of plant remains in calculus and quantity of consumed food26. The hypothesis of cereal consumption for this community has been also proposed by stable isotope data. Isotopic values would suggest a subsistence economy based on a great intake of carbohydrates and a lifestyle characterized by a progressive agricultural exploitation, even more evident than other Eneolithic sites of central Italy6,51. Lastly, Triticeae starches have been also found in dental calculus from Grotta dello Scoglietto (southern Tuscany), for the same pre-historical period52.Morphotype II A low number of starch granules with faceted shape, perpendicular extinction cross and, sometimes, evident central fissures was recovered from dental calculus (Table 1; Fig. 2G,H). The morphology appeared oval to polygon (2D) with centric hilum and fissures radiating from it. The most frequent size distribution length was 14–25 μm in length and 13–17 μm in width. This type of grains exists in seeds of grasses belonging to the Andropogoneae Dumort. and Paniceae R. Br. tribes, as shown in the modern reference material19. Since an overlap in size and shape occurs among starches of species related to these tribes, the identification of these plant remains is arduous at a lower taxonomic level. Sorghum sp. Moench (sorghum), Setaria sp. P. Beauv. (foxtail millet) and Panicum sp. L. (millet) can be considered as potential candidates. Unfortunately, no phytolith, which would have helped us in distinguishing between the species of Paniceae53, was detected. In addition, the lack of an isotopic signal specific for this type of consumption and the absence of relative carpological remains for the archaeological site of Casale del Dolce might be due to a limited usage of these plants. In fact, although several species of these genera were diffused in Italy, little is known about their employment. The archaeobotanical evidence of millets (i.e., Panicum sp. and Setaria sp.) from the Late Neolithic period has been discussed; however, their cultivation is certain during the Bronze and Iron Ages52,54,55. Recently, Accelerator Mass Spectrometry-datings of prehistoric charred broomcorn millet grains has pinpointed the earliest occurrence of Panicum miliaceum L. in Europe at the middle of the 2nd millennium BCE (Middle/Late Bronze Age)56.Morphotype III Only one grain contributed to the third type of starch (Table 1; Fig. 2B). It appeared to be consistent with the Fabaceae family, probably Vicieae (Bronn) DC. tribe (e.g., vetches) for its oval to elongated (irregular) shape and kidney-like. The hilum was obscured and sunken, while the lamellae were not fully visible. The size was 42 μm in length and 30 μm in width. Data about pulses are scarce for this period. In northern Italy, a high variety of pulses was already present in the Neolithic57,58 but this starch grain would seem to be one of the few and unique evidence of consumption in central and southern Italy. As this finding refers to a single individual, certainly, it is not expected to provide an exhaustive image of the use of pulses for the period and region but its presence, together with the carpological remains of Fabaceae49,50, could attest plant protein consumption.A single starch granule was not classified because missing diagnostic and distinguishable characteristics. Probably modification events, such as grinding process, cooking procedure in water and/or chewing, and exposure to alfa-amylase, altered its shape.Pollen grainsFour calculus samples showed the presence of different pollen types (Table 1). In total, 49 grains were found. Three of them were detected in CDD2, 4, and 9 (Fig. 2C,EF), while the remaining ones (46), both in single and in aggregate form, were retrieved from only one individual (CDD7) (e.g., in Fig. 3). All palynomorphs were identified according to morphometric parameters described in literature and evidenced in the Palynological Database59 and the names of the pollen types refer to literature60,61,62.Figure 3Plant micro-remains detected by morphological analysis in the dental calculus of CDD7 sample. Representative images obtained by light microscopy analysis were shown. Aggregates of pollen and spores (A,B); Pinaceae and Cupressaceae pollen grains (C); Brassicaceae pollen grain (D); Pinaceae pollen grains (E,F); Cupressaceae pollen (G); Quercus deciduous pollen (H); Alchemilla type pollen (I); sporangium of Monylophyta (J). The scale bar indicates 15 µm. Small flecks of calculus still attached to microparticles can be observed in some panels.Full size imageIn this paragraph we describe the pollen grains found in CDD2, 4, and 9 samples.The ancient microremain embedded in sample CDD2 was apolar and medium in size (63 µm in diameter), showing a morphology which typically occurs in Poaceae63,64. The stenopalynous nature of such type of pollen (that is, uniform monoporate) makes its systematic identification difficult. Although a low taxonomic determination limits paleoecological inferences, the evidence of Poaceae pollen is usually interpreted as indicative of open grasslands65.One ancient palynomorph displayed morphological traits consistent with Pinaceae (sample CDD4). It appeared as a bisaccate monad with an elliptic corpus and medium reticulation on bladders59,66,67. Including sacci, the dimension was 56 µm in equatorial view.A non-saccate Cupressaceae-type pollen, instead, was found in sample CDD9. It appeared spherical (with polar and equatorial axes of 30 µm) and inaperturate at light microscope; the protoplast exhibited itself star-like. Pollen grains produced by several species of Cupressaceae are considered morphologically uniform68. Since prehistoric times, Gymnosperm wood has been widely used as raw material and firewood, while needles, nuts and inner bark represented the edible parts of these trees69. Noteworthy is that the resins of these plants, possessing adhesive qualities and antibacterial properties, might have been also appreciated by Neanderthal14. Cupressaceae pollen grain is generally scarce in ancient sediments and one of the most underrepresented palynomorph in archaeological context. Several archaeobotanical studies have demonstrated the use of Juniperus L. species in the Mediterranean basin since the Holocene. In particular, the use of them as a source of aromatic foliage and resins employed for medicinal purposes, wood as fuel and for construction of dwellings, and fresh or dried berries as food has been proposed70,71,72. Sporadic fossil discoveries of Cupressus sp. L, instead, are rather sparse in the Mediterranean area, although some ancient record has been registered in Italy during the Quaternary73. Thus, the investigated plant microdebris testify the presence of Cupressaceae and provide additional evidence about the possible existence of evergreen Mediterranean forests, during the Neo-Chalcolithic period, in the Sacco River Valley.Pollen grains in CDD7CDD7 specimen (Fig. 1B), an adult male affected by severe malocclusion, preserved an interesting set of microparticles at microscopic analysis; therefore, we decided to report and discuss separately the data obtained from his calculus.Eleven pollen grains out of 46 were not distinguishable due to the lack of diagnostic characteristics. The remaining 35 were found (singly, in pairs, or aggregates; Table 1, Fig. 3) in good or excellent state of conservation. The latter appeared as clusters of Pinaceae pollen (Gymnosperm) and other palynomorphs, including spores. Examples are shown in panels A and B of Fig. 3.Two Cupressaceae, ten Pinaceae and one Poaceae pollen, presenting the same morphological features described in the previous paragraph, were also found in this sample (e.g., see Fig. 3C,E,F,G).In addition, pollen grains from four herbaceous plants, namely Cyperaceae, Urticaceae, Trifolium, and Alchemilla species, and from the arboreal genus Corylus L. were detected and aredescribed below. Although pollen morphological variation within Cyperoideae subfamily is notable, one ancient microremain, possessing a pear-shape and a scabrate sculpture on its surface, appeared belonging to the genus Carex74,75. In equatorial view it was triangular and the polar axis length was 41 µm. A second pollen grain was recognised as Urticaceae-type; it exhibited spheroidal shape (equatorial diameter 23 μm) and scabrate ornamentation. This morphology occurs both in Parietaria sp. and Urtica sp. pollen grains59,62 and it is very difficult to distinguish them by optical microscope, especially if degraded. The shape of a third ancient monad, attributed to Trifolium-type (Fabaceae), was subprolate in equatorial view (46 μm) with scabrate ornamentation76. The Alchemilla-type (Rosaceae) microremain (26 μm equatorial view, Fig. 3I) was radially symmetrical, elliptic and prolate in shape77. Finally, another pollen type was found and attributable to Corylus sp. L. (Betulaceae). It was oval in equatorial view (19 μm), smooth, and tripolar with deep oncusis in each pore78.Seven pollen grains were single, prolate, isopolar, and elliptic in equatorial view (polar axis 19–25 µm long). They were tricolpate, with long and narrow colpi. Pores were at times indistinct. Pollen of the different species of Fagaceae shows a high variability in form, size, sculpturing; for this reason, most of them overlap in morphology. The ancient palynomorphs in exam were closely similar to a Quercus-type (examples in Fig. 3A,H)79,80.The last 10 grains showed a morphology (3-colpate, reticulate and subprolate) ascribable to Brassicaceae pollen grains (example in Fig. 3D). This is a stenopalynous family in which pollen varies among the genera but rarely in the species under the same genus81,82.Intriguingly, pollen findings in sample CDD7 were numerous and deriving also from insect-pollinated plants (e.g., Brassicaceae). This evidence appeared like a honey palynospectrum. This type of assemblage has been never registered in dental calculus deposits and, especially for the aggregates, the hypothesis of accidental inhalation seems implausible. Precisely, the presence of aggregates induced us to reflect upon a common origin of the whole pollen record. However, for single granules, to date, the supposition of aspiration cannot be completely excluded, due to the multiple pathways of inclusion of such type of microparticles27. The high pollen variety could be explained by the presence of residues of natural matrices, as well as honey or beehive products (e.g., wax, propolis), in the calculus sample. To support our hypothesis, we prepared a reference collection based on modern multifloral honey samples (Supplementary Information 1, panel E–J).Archaeological finds of bee products are quite rare83,84,85,86,87,88. Since the end of the upper Palaeolithic, honey has been employed as sweetener, while beeswax for technological, ritual, cosmetic and medicinal applications89,90. Regarding the latter, Bernardini et al.91 have found fascinating traces of a filling with beeswax, highlighting Neolithic dentistry procedures. It is important to recall that bees may also visit non-nectariferous plants (e.g., Poaceae, Betulaceae like Corylus sp.) for collecting pollen as protein source. Moreover, Pinaceae (Pinus sp. L. and Abies sp. Mill.) and Fagaceae (Fagus sp. L. and Quercus sp. L.), among others, emit sweet secretions and may be classified as honeydew producers88. Therefore, it is not unlikely to discover pollen grains of pine, hazel, oak, and cereals mixed with melliferous taxa. In fact, similarly, Carboni et al.92 have observed a lump of pollen inside an Eneolithic vessel, suggesting the use of a fermented honey-based drink, the mead, for ritual purposes.According to all this evidence, the pollen record detected in the present ancient calculus could be likely interpreted as direct honey consumption and/or remain of food or beverage including honey as natural sweetener. However, the use of conifer resins as antimicrobial or flavouring agents, mixed to honey or alone, cannot be excluded, together with the hypothesis of inhalation of bisaccate pollen from the immediate environment.Unfortunately, for the investigated site, no evidence supporting the previous hypotheses exists. Nevertheless, it is possible that the individuals from Casale del Dolce practised bee-keeping culture near woodland pastures, although this interpretation cannot be definitive.Currently, pollen spectra from beehive products are used to deduce plant biodiversity of the areas visited by insects for nectar collection93,94. Bearing in mind this indication and the typical habitats of the identified plant taxa, some ecological implications were inferred. A thermophilic broad-leaved forest mainly made up of conifers (such as Pinus) and several deciduous trees (such as Quercus and Corylus), together with wet grasslands (Cyperaceae, Urticaceae, Alchemilla sp.), was outlined by pollen analysis. This hypothesis would seem consistent with Coubray’s work50, who has identified the wood charcoals found in the archaeological site of Casale del Dolce as Carpinus L., Quercus, Maloideae, Cornus L., Corylus, Ulmus L., Fraxinus L., and Acer L. remains. In addition, palynological analyses performed in the same region95,96,97 have detected similar vegetational elements.Other plant microremainsWe detected an unusual range of microparticles, that is, fragments of plant tissues and a sporangium, rarely documented in human dental calculus investigations (Table 1)69,98,99,100.Among the first, one microparticle was made up of plant cells associated to a scalariform xylem vessel (Fig. 2I), while another debris showed wood cells with simple pits (Fig. 2J). A brown-yellowish fragment was also photographed (Fig. 2K). As reported in literature99, no evidence of charring or burning may be attributed to this type of darkening colouring but, if so, it would suggest an involuntary inhalation of ash particles from trees or shrubs used for fire. Thus, this type of microremain could derive from both non-edible and edible plants. In general, all these fragments retrieved from calculus might be the result of some activities, such as chewing of fresh plant organs, food and/or other uses of bark, oral hygiene procedures with woody dental picks, and/or use of teeth as a third hand99,101,102.The second type of uncommon microparticle, found in sample CDD7 (Table 1), appeared morphologically like a sporangium, probably from Monylophyta (Fig. 3J). It was brownish in colour and ovoid in shape. This type of microremain has never been observed in so ancient human dental calculus. A more specific taxonomical identification is very complex and would be risky, since at palaeobotanical and/or archaeological level there is no evidence to support this finding. However, considering that sporangia are typically attached to the abaxial surface of the leaf and that airborne dispersal capability of fern spores into stronger wind currents is rare and improbable100,103, the recovery of the whole sporangium allowed us to hypothesize a voluntary use of fern leaves.Biochemical analysisGC–MS approach revealed the presence of organic compounds derived from the matter ingested and/or inhaled by the individuals. However, the potential of the biomolecular approach on dental calculus is still highly challenging and the capacity to trace the origin of some molecules is still difficult, due to the multifactorial dental calculus’s aetiology31,104.In Supplementary Information 2 (SI2), the molecules detected in each sample were listed and clustered in chemical classes. The chromatographic profiles were dominated by a series of C6 to C30 n-alkenes and n-alkanes, not reported in SI2 because ubiquitous and not taxonomically specific. They could probably come from degradation of oral bacteria or consumed food, representing, for instance, fragments of unsaturated or saturated lipids14,105,106,107.The typology of residues accumulated in dental calculus and their adsorption capacity determine the lipid profile of this matrix, considering that different foods naturally possess variable lipid composition. For this reason, it is difficult to associate fatty acids to specific dietary sources. The presence of fatty acids (e.g., odd, short, and long chains), ubiquitous components of organic matter, could be considered indicator for consumption of animal fats or plant oils (e.g., oil-rich seeds and fruits)104,108,109,110,111,112,113. Long-chained polyunsaturated fatty acid derivatives (PUFAs; e.g., eicosapentaenoic acid, EPA), abundant in dried fruits114, were detected in some samples. Polyunsaturated omega-3 fatty acids have been rarely identified in archaeological contexts115, due to their highly inclination to oxidative alteration116. However, dental calculus has shown itself conservative for this type of molecules31. The consumption of aquatic organisms cannot be excluded, being rich of PUFAs114 and considering the proximity of the ancient settlement to the Sacco River.Monoterpene derivatives, non-specific compounds with volatile nature, retrieved from some samples, such as citronellol, menthol and pinanol (commonly found in leaves, fruit, and bark of a wide range of plant species), could generically indicate the ingestion of plant materials or waxes109.In CDD5 calculus, azulene and coumarin derivatives were also recovered. These secondary metabolites usually occur in species belonging to Apiaceae, Asteraceae, and Rutaceae families, well known medicinal plants possessing a wide range of biological activities117,118. As suggested by Hardy et al.14, the plant species rich in such type of bitter-tasting compounds might have been ingested for self-medication.Two alkaloids were found: trigonelline and hordenine, respectively, in CDD4 and CDD7 specimens. The first one, whose accumulation takes place in various plant species (i.e., Achillea sp. L.) and especially in Fabaceae seeds (e.g., Trigonella sp. L., Trifolium sp. L., and Medicago sp. L.)119,120, might represents a further proof for consumption of pulses.Hordenine, which naturally occurs in certain grasses, like cereals (e.g., barley, millet, and sorghum)121, could demonstrate the ingestion of starchy material, as already testified by the detection of a Triticeae starch granule in the same calculus flakes and the recovery of caryopses at the site50. More

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