Ecology

Escherichia coli is amongst the dominant pan-aminoglycoside-resistant bacteria from wastewater and river waterA total of 168 bacteria highly resistant to aminoglycosides were obtained by growing collected samples in MacConkey media supplemented with high aminoglycoside concentrations, from both WWTPs (66 isolates) and rivers (102 isolates) sampled at the same period of time and located in the Barcelona region. Most of the isolates were identified as Escherichia coli, being the predominant Enterobacteriaceae species in WWTPs (50 isolates, 75.76%) and the second most prevalent in rivers (20 isolates, 19.61%). Klebsiella pneumoniae was the predominant bacterium identified in river environments (50 isolates, 49.02%), although its presence in WWTP samples was scarce (7 isolates, 10.61%). The remaining aminoglycoside-resistant species, members of genus Enterobacter, Citrobacter and Aeromonas among others, represented a low fraction in WWTPs (9 isolates, 13.64%) comparing to river environments (32 isolates, 31.37%), showing a higher bacterial diversity of natural over WWTP niches (Fig. 1, Supplementary Data 1).Fig. 1: Geographical distribution of sampled points in the region of Barcelona (Spain).The location of Barcelona city is indicated by black circled city icon. The Llobregat river is presented in light blue and the Cardener river in dark blue. The three river sampled locations are indicated by black circled river icon. The two sampled WWTPs are indicated by black circled droplet icon. The collection area of the El Prat WWTP is highlighted in dark green, whereas the area of the Gavà WWTP is highlighted in pale green, collecting the wastewater of 2,000,000 and 370,000 inhabitants, respectively. Total number of pan-aminoglycoside-resistant bacteria collected from each sampling location is indicated in the center of the sunburn diagrams. Inner rings represent the proportion of different pan-aminoglycoside-resistant bacterial species identified in each sampling location, indicating the total number of E. coli, K. pneumoniae and other species, and the number of E. coli isolates selected for later Illumina (I) and Nanopore sequencing (N). Outer rings show the 16S-RMTase gene harbored by these bacteria.Full size imageAntimicrobial resistance in E. coli varies between wastewater and river water environmentsResistance to diverse antibiotic compounds was related to the sampling origin and the species of the isolates. All isolates were highly resistant to 4,6-DOS aminoglycosides, since they were selected according to their resistance to this family of antibiotics. The 16S-RMTase gene identified in most wastewater isolates was rmtB (55 isolates, 83.33%), whereas armA was the responsible in the remainder (11 isolates, 16.67%). On the contrary, 100% of isolates from river environments harbored the armA gene (Fig. 1, Supplementary Data 1). No other 16S-RMTase gene was detected neither in wastewater nor river isolates. Bacteria from wastewater samples showed higher MIC values to all tested antibiotics (e.g., 77.3% isolates resistant to cefotaxime) than bacteria from freshwater environments (e.g., 0% isolates resistant to cefotaxime), even when comparing isolates belonging to the same species. This was also the case for E. coli, where isolates from WWTPs were among the most resistant (e.g., 90% isolates resistant to cefotaxime) while those from rivers were among the most susceptible ones (e.g., 0% isolates resistant to cefotaxime), highlighting key differences between bacteria from these different ecological niches (Supplementary Data 1).Distinct E. coli populations exist in wastewater and river water environmentsPulsed-field gel electrophoresis (PFGE) of E. coli isolates revealed the existence of two highly prevalent pulsotypes present in the two WWTPs (31 isolates, 62%), and a total of 5 characterized pulsotypes (≥90% similarity in the PFGE pattern) from wastewater samples. Interestingly, 15 isolates (30%) from both WWTPs could not be typed by PFGE. In contrast, river environments showed higher clonal diversity, with up to 10 different pulsotypes characterized, despite the lower number of E. coli isolates recovered from these samples (Supplementary Fig. 1). Of the 70 E. coli isolates, 43 were selected for further analyses and sequencing by Illumina technology (25 from WWTPs and 18 from river environments), ensuring wide representation in relation to the origins, clonal relatedness, and antibiogram resistance profiles.Multi-locus sequence typing (MLST) results were highly correlated with PFGE profiles. Almost all E. coli isolates from wastewater samples (23 isolates, 92%) belonged to two predominant sequence types (STs) (Fig. 2). The most prevalent one, ST1196/ST632 (Warwick/Pasteur MLST scheme), encompassed the two main pulsotypes identified by PFGE. ST1196 is an increasingly prevalent ST related to OXA-48-carbapenemase production and associated with the mcr-1 colistin-resistance gene expansion in clinical settings9, hospital wastewater10 and companion animals11. Minimal inhibitory concentration (MIC) values of the isolates belonging to this ST showed resistance to numerous antibiotic classes, including clinically critical antibiotics such as 3rd generation cephalosporins and colistin6. The other predominant ST in WWTPs, ST224/ST479, comprised all the isolates which were non-typeable by PFGE. ST224 is a pandemic multi-drug resistant ST previously associated with NDM-, CTX-M- and KPC-carbapenemase production, found in both clinical human12 and animal13 samples, but also in natural environments14. ST224 E. coli isolates identified exhibited a common resistance profile, including resistance to 3rd generation cephalosporins. However, two isolates from river samples belonging to this same ST showed a different resistance pattern, revealing the influence of the niche in the bacterial resistance phenotype, even within the same ST. One of the E. coli isolates from El Prat WWTP was also identified as ST131, a clonal group present in multiple environments with a plethora of resistance mechanisms and virulence factors, representing a major public health concern15. River-related E. coli showed a higher number of E. coli STs compared to wastewater isolates, comprising up to 6 different E. coli STs (Fig. 2). All river E. coli STs presented similar MIC values for most of the tested antibiotics, which were lower than those exhibited by wastewater E. coli. ST607 (Warwick MLST scheme) was the most prevalent ST found in rivers. This ST has been scarcely reported, although it has been already detected in river sediments16. MICs of plazomicin for all isolates, both from wastewater and river environments, were ≥512 mg/L, demonstrating the high-level resistance to aminoglycosides conferred by 16S-RMTases, even to an aminoglycoside that has not yet been approved for clinical use in the EU (Fig. 2).Fig. 2: Sequenced E. coli data.The source of the isolates is specified by different colors in the genomic SNP-tree branches, as well as the related sequence type. Level of resistance to all tested antibiotics is shown in a gradient of colors: PLZ (plazomicin), GEN (gentamicin), AMP (ampicillin), FOT (cefotaxime), TAZ (ceftazidime), MERO (meropenem), CHL (chloramphenicol), TMP (trimethoprim), AZI (azithromycin), COL (colistin), CIP (ciprofloxacin), NAL (nalidixic acid), TET (tetracycline), TGC (tigecycline), and SMX (sulfamethoxazole). The presence and absence of antibiotic resistance genes and plasmid incompatibility groups are indicated by circle and triangle symbols, respectively. The presence and absence of specific 16S-RMTase genes are indicated by star symbols.Full size imageResistome analysis results were highly correlated with resistance phenotypic profiles. Thus, isolates from WWTPs harbored an heterogenous antibiotic resistance gene content depending on the E. coli ST, such as the strong association between the mcr-1 gene and isolates belonging to ST119617. This heterogenicity was even present between isolates belonging to ST1196, which exhibited different resistance levels to chloramphenicol and tetracycline depending on the presence of cmlA1/floR and tet(A), respectively. However, all wastewater isolates showed a common high-level resistance to β-lactam compounds, including third generation cephalosporins, which could be attributed to the presence of blaCTX-M-55 (ST1196) and blaCMY-2 (ST224) (Fig. 2). On the contrary, all isolates from river environments possessed a uniform antibiotic resistance gene content, despite comprising different STs (Fig. 2). Almost all of them (17 isolates, 94.4%) were susceptible to β-lactams, including the isolates belonging to ST224, contrasting with wastewater isolates, which have been under anthropogenic pressure, such as clinical treatments with a combination of aminoglycosides and β-lactams18, that led to this resistance associations. Likewise, plasmidome analysis revealed that the total plasmid content, based on the plasmid incompatibility groups, was heterogeneously distributed among isolates from WWTPs according to E. coli STs and closely correlated with the resistance gene content (an average of 6.36 different plasmid replicons per isolate). ST1196 isolates carried a higher plasmid content, exhibiting different plasmid profiles among them. The only plasmid incompatibility group carried by all wastewater isolates was IncFII type, specifically a pC15-1a-like plasmid (Fig. 2). Considering river E. coli STs, the total plasmid content was generally lower (an average of 3.72 different plasmid replicons per isolate) and more uniform compared to wastewater STs, similar to the pattern of the resistome (these differences are addressed in the E. coli pan-genome structure and genome, plasmid and antibiotic resistance gene diversities section). The most prevalent plasmid incompatibility group found among them was IncHI2A, present in all river isolates except ST224, which harbored a completely different plasmid content (Fig. 2).
E. coli STs have a similar genomic complexity in wastewater and river water, but the diversity of plasmids and resistance genes is higher in wastewater STsThe pan-genome of all 43 E. coli isolates, with the independence of the origin, was constituted by a total of 13,819 different genes. The pan-genome was distributed in a common core-genome of 3109 genes (22.5%) and a variable accessory-genome of 10,710 genes (77.5%), covering a considerable E. coli diversity, considering that the estimation of the global E. coli core-genome comprises around 1500 genes19 (Supplementary Fig. 2). Attending to the pan-genome configuration depending on the water source, 3340 out of a total of 9099 genes (36.71%) were included in the core-genome of wastewater isolates, and the core-genome of river isolates was formed by 3410 out of 9927 genes (34.35%), showing that river isolates presented a larger total gene pool and a smaller relative core-genome comparing to WWTP isolates. The genes conforming the pan-genomes of wastewater and river water E. coli were statistically different, considering the genes that were present and absent in each niche from the total pan-genome (Jaccard, P-value = 0.001) (Fig. 3a), indicating that the different environments, and/or upstream environments from which they have seeded, led to the selection of specific genomic populations, even between members of E. coli ST224 originating from the two different environments (Jaccard, P-value = 0.049). The genomic diversity of the whole E. coli population from river water was significantly higher than the one found in wastewater (Jaccard, P-value = 3.599 × 10−8) (Supplementary Fig. 3a). However, considering the number of different STs constituting the genomic pool of each environment, the genetic diversity of an E. coli ST from wastewater was statistically similar to the diversity of an E. coli ST from freshwater (Jaccard, P-value = 0.3123) (Fig. 3b). This model, which took into account the number of STs from each source in the diversity analysis, was previously checked by random sampling analysis, obtaining similar results. Essentially, the diversity of the total E. coli population was dependent on the number of different STs that defined the population, but the diversity of a specific ST was independent of this factor and more suitable to estimate the variability of specific bacterial clones according to the origin. Likewise, the diversity of plasmid content, taking into account the different plasmid incompatibility groups identified, was distinctive for each water type (Jaccard, P-value = 0.001) (Fig. 3c). Thus, the ecological niche also influenced the presence of specific plasmid types. The level of complexity of the E. coli plasmid pool circulating in each aquatic environment was statistically similar (Jaccard, P-value = 0.2447) (Supplementary Figure 3b). However, the number of different plasmid types carried by each E. coli ST was significantly higher in WWTPs than in rivers (Jaccard, P-value = 1.037 × 10−14) (Fig. 3d). Both wastewater and river E. coli populations also showed a great divergence in the antibiotic resistance gene content (Jaccard, P-value = 0.001) (Fig. 3e), showing different resistance mechanisms to particular antimicrobial classes. Furthermore, this diversity was significantly higher in the total E. coli population from wastewater comparing to the E. coli population from river water (Jaccard, P-value = 5.093 × 10−14) (Supplementary Fig. 3c), even when the latter possessed a higher total genomic diversity. Thus, the sum of genetic resistance determinants carried by each E. coli ST from wastewater environments was much higher than for each E. coli ST from natural effluents (Jaccard, P-value  More

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Establishing the variables involved in rock weathering and fire behaviour is a key aspect of developing an accurate fire-induced rock spalling hypothesis. We expand on these variables by drawing on field observations and existing findings outlined below.Mechanical weatheringThe physical breakup and removal of rocks of varying hardness and degrees of weathering via mechanical weathering is the primary process that denudes and sculpts uplifted regions of Earth’s surface. Sub-critical cracking describes the slow propagation of microfractures through a rock in low-stress, near-surface conditions as a result of thermal stress, ice wedging, mineral alteration (volumetric expansion) and biomechanical processes such as root growth25. Sheeting is characterised by thick (0.1–1 m) layers of rock peeling off exposed surfaces roughly parallel to the surface topography. There is debate as to whether sheeting is related to gradual unloading and release of stresses near the surface or a combination of other stresses26,27. The physical process of thermal expansion and contraction of rocks over thousands of years is responsible for the thinner, gradual flaking (exfoliation) of rock surfaces, which can be observed all over the surface of inselbergs in central Australia5 and presumably the main process responsible for the slow rates of erosion at the tops of inselbergs14.Fracture propagation is facilitated by the presence of water28, which helps to break chemical bonds leading to more fractured rock at shallow, superficial levels of the crust. Thus, rocks are generally more fractured in the superficial, near-surface environments than at deeper levels. Spontaneous rock-burst events were captured on video during a hot summer of 2014 in California when a granite dome at Twain Harte began explosively exfoliating29. Extreme thermal stresses associated with fire and lightning strikes are acknowledged as mechanisms of critical stress fracturing in rocks but generally considered to be a rare form of rapid and catastrophic mechanical weathering25. Our observations of rock surfaces following wildfires are that fire-related rock spalling is a commonly observed phenomenon wherever high-intensity fire has swept across rocky outcrops (for example, Figs. 5 and 6). We suggest that fire-spalling is a significant driving mechanism of physical weathering in arid, fire-prone environments and has been overlooked as an important agent of geomorphic change and landscape evolution.Fig. 6: Existing and new models of flared slope development using Uluru as an example and a graphical representation of the formula for erosion due to fire-spalling in different fire regimes.a The model of Twidale and Bourne 199822 involving subsurface weathering via shallow groundwaters to form soft regolith or unconsolidated soil that is subsequently removed by erosion and landscape lowering; b a new model of flared slope development via fire-induced rock spalling associated with episodic wildfire events. Note the charcoal on the recently burnt trees is the same height as the flared slope; c inverse correlation relationship between rates of erosion E(t) plotted against fire recurrence interval (t) using the formula E = W.A/t (see https://www.geogebra.org/calculator/uwa68amr). Rock-type and fire temperatures tend to control the thickness of spalled sheets (W) whilst fire intensity and duration are the main controls on the surface area spalled (0–100%). The inverse correlation of rates of fire-spalling erosion with average recurrence intervals (t) results in an increasing rate of weathering with smaller average fire recurrence intervals. Fire recurrence intervals are largely controlled by climatic and vegetation regimes and examples from Figs. 2 and 4 are shown and plotted on the graph according to the fire recurrence interval for that region.Full size imageWildfire temperaturesA detailed study of high-intensity wildfires in eucalypt forests of SW Australia30 revealed that these fires burn at temperatures between 300 °C at the tips of visible flames and up to a maximum of 1100 °C near the flame base, while temperatures of up to 1330 °C were recorded in Canadian crown fires31. Experimental fires conducted in jarrah forests of south-west Western Australia (Project VESTA) reveal that temperature correlates directly with the rate of spread, fire intensity, flame height and surface fuel bulk density30. This single case study measured the average flame-front residence time in eucalypt forest fuels of about 37 s. However, radiant heat and hot winds fanning out in front of the fire have the ability to pre-heat the rock surface and vegetation before and after the arrival of the fire front31 particularly along cliff lines.We report the first documented case of spalling in basalt from Mount Kaputar in northern N.S.W. (Fig. 4d). Basalt is a high-temperature volcanic rock with no quartz content. Fire-spalling was minimal across most of the outcrops and generally consisted of dislodged pyroxene phenocrysts. However, a few basalt outcrops adjacent to nearby fallen burnt logs were intensely scorched and displayed thin (1–4 mm) spalled flakes of basalt indicating that fire-spalling is not restricted entirely to quartz-rich lithologies. In mature eucalypt forests with large, woody fuels, termed ‘down wood’32, fires can burn or smoulder for days, providing prolonged heat required for extensive spalling. Some cliff faces record distinct ghosted impressions of nearby tree trunks with the resultant spalling hollowing out the line and shape of a tree trunk in an otherwise flat, vertical rockface (Fig. 5a—right-hand side). A discarded brown glass bottle adjacent to the basalt spalling had softened and undergone ductile collapse and partially melted. The glass had cooled slowly enough to avoid shattering indicating prolonged heating from the smouldering downward. This glass was collected and placed in a high-temperature oven where it was observed to become soft and malleable at 750 °C and completely collapsed and started melting at 830 °C indicating that this fire sustained ground surface temperatures of between 750 and 830 °C next to the smouldering tree and fallen logs.Fire-induced rock spallingFire is known to accelerate the rock flaking process25,33,34,35,36,37,38 resulting in rock spalling36,39 and shattering38. Conflagration leads to the rapid disintegration of the rock surface due to the differential expansion of the hot rock surface compared with the cooler interior. Fire-spalling can remove between 10 and 100% of the burnt rock surface in sheets between 5 and 50 mm thick37 depending upon rock type and fire intensity. Detailed measurements of post-fire rock spalling after the Esperanza chaparral fire in California revealed that 7–55% of the granodiorite boulder surfaces were spalled to a depth of 11–24 mm33. They found that the thickest spalled sheets occurred around the flanks of the boulders and cautioned that, if sampled for cosmogenic dating, these freshly exposed, spalled surfaces would produce a significant underestimate of exposure age. These figures match our own observations of spalled granite following the fires in Cobargo, Moonbi and Thredbo N.S.W. (Fig. 4) in which granite boulders spalled sheets between 5 and 50 mm thick, while sandstones from the Blue Mountains spalled sheets between 5 and 22 mm thick (Fig. 5).Quartz expands four times more than feldspar and twice as much as hornblende and shows a 3.76% volume expansion when heated from room temperature to 570 °C40. Thus, quartz-rich rocks have a greater expansion potential and are more likely to spall. Experimental studies41 show that rock elasticity reduces significantly at temperatures as low as 200 °C, over a relatively short period of time. Goudie et al.41 postulated that rock outcrops subject to intense fires would have an increased susceptibility to erosion via spalling and weathering. However, these findings have not been applied to broader landscape models or the formation of flared slopes around inselbergs.Fire regimesThe potential rate of erosion due to fire-spalling at the base of inselbergs will be strongly influenced by fire severity and recurrence intervals, which vary greatly across Australia from 1- to 5-year recurrence intervals and 100-year intervals and >10,000 kW m−1 for tall, open forests of the cool, temperate south42. Accurately calculating the fire return period is difficult due to limited historical records but estimates for arid, spinifex-dominated regions such as the Tanami are in the order of every 7–9 years43. Analyses of satellite data between 1998 and 2004 revealed that 27% of arid Australia burnt at least once over that 6-year period44. Figure 1a shows the areas burnt in Australia since 2001. The surface area of the rock affected by spalling depends on the rock-type and severity of the fire. Fire severity is strongly determined by the bulk density45, height and proximity of the adjacent vegetation to rock surfaces and the surrounding slope gradient. All the examples of flared slopes shown in Figs. 1 and 2 reveal a close relationship between the height of the encroaching vegetation and the height of the concavity. Katter Kich, Pildappa Rock and Walga Rock form distinct embayments where the flared slopes are most pronounced, which appear to promote denser, taller vegetation growth and hence greater fuel loading and thus higher fire severity (Fig. 3).The impermeable nature of inselbergs results in rapid and efficient water runoff from the bare-rock surface before draining into adjacent, thin soil profiles. This creates a “roof and gutter” effect around the periphery of many inselbergs which creates permanent water holes and shallow groundwater within easy reach of deep-rooted plants. Inselbergs create important geodiversity within otherwise flat landscapes and thus host important niche ecosystems that add to the overall biodiversity of desert regions46. Accessible groundwater around the fringes of the inselbergs encourages denser, taller vegetation at the interface between bare rock and unconsolidated surficial sediments which in turn increases the fuel load. Inselbergs are prominent topographic features in flat deserts that provide sources of permanent water, abundant flora and fauna and shelter.Grassy plains and savannahs of central Australia are characterised by regular, low-intensity fires with fire recurrence intervals between 1 and 5 years42. However, where these fires encounter inselbergs they move into thicker, taller vegetation regimes with greater fuel loads (Figs. 2 and 3). Inselbergs are topographic highs within relatively flat landscapes and the slight increase in slope gradient around the inselberg will accelerate and intensify an approaching fire front. Steep slopes around the margins of inselbergs possibly act as chimneys, drawing in hot air from the surrounding plains and channelling them upwards. These factors possibly help to draw in fires from the surrounding plains into and around topographically high inselbergs where the intensity is enhanced at the base of inselbergs due to the denser vegetation and greater fuel load.A fire-induced spalling weathering formulaFire-spalling leads to physical weathering (erosion) and disintegration of exposed rock faces36,37 as shown in Figs. 3–5. The degree and extent of spalling on different rock types and at varying temperatures and durations is less well understood and requires further experimental work41 but essentially fire-spalling is a function of fire intensity (temperature), duration and rock type with quartz-rich rocks having a greater propensity to expand and spall40.We developed a simple fire-spalling erosion formula to estimate a long-term rate of fire-induced spalling that broadly considers the net result of fire-spalling in terms of the thickness (width) of the spalled flakes produced by a single fire event, the total surface area as a percentage of the exposed rock face affected by a single fire-spalling event, and the average fire recurrence interval for a given region. Together these variables can give some indication as to the long-term rates of erosion due to fire-spalling at the base of an inselberg or cliff face where there is significant vegetation to fuel a wildfire.The formula for erosion due to fire-spalling.$$E = frac{{W times A}}{t}$$
(1)
where, E = rate of erosion due to fire-spalling (mm yr−1), W = average width (thickness) of spalled sheets (mm) for a single fire event. Dependent on rock type (quartz content and texture), rock strength, fire temperature and duration, A = area of rock surface affected by fire-spalling as a percentage (%) of total surface area. Dependent on temperature and duration of the fire, t = average fire recurrence interval (years). Determined from regional, historic fire records or palaeofire records for longer time periods. Dependent on vegetation, climatic regimes and land management practices.Limitations: this equation applies to a near-vertical rock face at ground level which receives uniform heat radiation from a fire that burns right up to the rock face at ground level. The intensity of radiation will vary according to the dynamics of the fire front, fuel loading, vegetation type and slope gradient. Flame height is not critical to the overall rate of retreat of the cliff face because fire-spalling at the base of the cliff will gradually remove material supporting the cliff resulting in over-steepening at the base of the cliff and periodic sheeting and rockfalls as the overhanging cliff face becomes gravitationally unstable. The formula assumes that fire recurrence intervals have remained constant but we know from palaeofire records47,48 that fire intensity and recurrence intervals are largely controlled by long-term climatic variations which affect vegetation types and thus fuel loads. Below, we give two end-member examples of long-term rates of spalling-related erosion for low and high-frequency fire regimes that may apply to temperate and arid environments, respectively.Example 1. Low intensity, irregular fire regime. In this scenario, the average fire against a cliff results in spalling and flaking of ~10 mm sheets off ~20% of the surface area at ground level during a single fire event. Fire recurrence interval is one event every 50 years.$$E = frac{{W times A}}{t} = frac{{10;{mathrm{mm}} times 0.2}}{{50}} = 0.04;{rm{mm}};{rm{yr}}^{ – 1} = 40;{rm{m}};{rm{Ma}}^{ – 1}$$Example 2. High intensity, high-frequency fire regime. In this scenario, the average fire against a cliff results in spalling and flaking of ~20 mm sheets (Fig. 5) off ~80% of the surface area at ground level. Fire recurrence interval is one event every 5 years.$$E = frac{{W times A}}{t} = frac{{20;{mathrm{mm}} times 0.8}}{5} = 3.2;{rm{mm}};{rm{yr}}^{ – 1} = 3200;{rm{m}};{rm{Ma}}^{ – 1}$$In an intensely fire-prone environment such as example 2 above, it may only take about 625 years of fire-induced spalling to weather out a 2 m deep flared slope at the base of a vertical rock face. The point at which undercutting due to fire-spalling would trigger massive sheeting of the unsupported, overhanging rock ledge and subsequent rockfall event is not well constrained but some of the flared slopes around Uluru and Walga Rock are at least 2–3 m deep (Fig. 2h).Sediment production ratesIf rates of erosion due to fire-spalling around the periphery of an inselberg are orders of magnitude greater than those across the top of the inselberg, then this has implications for mechanisms of sediment production in flat, arid environments like Central Australia.Spalling of a 20 mm sheet from a 1 m2 area of granite with a density of 2691 kg m−3 will yield 0.02 m3 (53.82 kg) of rock. A flared slope around an inselberg such as Uluru with a circumference of ~10,000 m and a height of 2 m, would produce 400 m3 (1,076,400 kg) in a single event in which 100% of the 2 m high flared slope was spalled. Obviously, 100% spalling of the entire flared slope would never occur in a single event, so we use the long-term erosion rate based on fire recurrence intervals and average area spalled calculated in Eq. 1. This long-term estimate of sediment production from a single inselberg is compared with quantitative measurements of spalled granite surfaces sampled after the 2019–2020 fires in Cobargo on the south coast of N.S.W., Australia.The formula for sediment production.$$S_{rm{FS}} = P.H.E$$where, SFS = sediment production from fire-spalled rock surface (cubic metres per year), P = perimeter of the inselberg (metres), H = height of the flared slope around the inselberg as determined by vegetation and fire height, E =  rate of erosion due to fire-spalling (Eq. 1).Fire-spalling sediment production around the periphery of an inselberg such as Uluru with a perimeter of roughly 10,000 m and flared slope height of 2 m, would be$$S_{mathrm{FS}}=10,000, {mathrm{m}}times 2, {mathrm{m}} times 0.0032, {mathrm{m}}, {mathrm{yr}}^{-1}=64, {mathrm{m}}^{3}, {mathrm{yr}}^{-1}=172,224, {mathrm{kg}}, {mathrm{yr}}^{-1}$$This can be standardised to give a volume of rock spalled per year per square metre, which is the same as the erosion rate but in cubic metres per year. Given the density of the rock (granite = 2691 kg m−3 and compacted, meta-arkose sandstone (Uluru) are about the same) we can calculate the average mass of rock spalled each year. In the above scenario, it equals 8.61 kg per square metre per year.The rate of background (non-fire related) sediment production (SBA) from erosion of the surface area of an inselberg such as Uluru is equivalent to the surface area (~3,440,000 m2) multiplied by the average denudation rate of ~0.3–0.6 m/Ma (0.0003 mm yr−1) as established from cosmogenic studies.$$S_{mathrm{BA}}=3,440,000, {mathrm{m}}^{2}times 0.0000003, {mathrm{m}}, {mathrm{yr}}^{-1} =, sim! 1, {mathrm{m}}^{3}, {mathrm{yr}}^{-1}=2691, {mathrm{kg}}, {mathrm{yr}}^{-1}$$This equates to only 0.00081 kg per square metre per year. We estimate that fire-spalling on a 2 m high perimeter produces in the order of 64 times more sediment than the erosion of the entire surface of the inselberg due to background (non-fire related) processes.Spalled granite material was collected from two locations following the 2019–2020 fires in the Cobargo region along the south coast of N.S.W. (Fig. 4) to assist in quantifying the amount of rock spalled from a single rock face. Spalled surface area can be estimated simply by measuring the maximum height and width of the spalled surface in the field. We also created a digital surface using photogrammetry MetaShapePro software to calculate a precise surface area of the spalled surface. All of the spalled material was weighed and a standard granite density of 2691 kg m−3 was used to determine total volume. Generally spalling occurs as thin (1–3 cm) sheets but occasionally includes large 20–30 cm thick slabs that substantially add to the overall weight of spalled material. Whilst complete spalling of a 2 cm sheet from one square metre of granite surface will produce 53.82 kg m−2 of rock, our two sites (Cobargo2 and 3A) produced 23.65 kg total (16.89 kg m−2) and 41.60 kg m−2 total (33.55 kg m−2), respectively, indicating an average spalling thickness of 0.63–1.25 cm although the spalled thickness was highly variable with spalling distinctly more prominent along sharp or protruding edges than on flat surfaces. Large logs or tree trunks have the potential to continue burning long after the fire front moves through and their presence near rock surfaces significantly increases the degree of spalling. The most intense spalling was observed at Moonbi Granite near Tamworth in northern N.S.W. where some granite boulders had 100% surface spalling up to 2 m above ground level and not one but several spalled sheets (5–20 cm total thickness) exfoliating off during a single, intense fire creating several hundred kilograms of spalled rock debris on the granite surface facing the fire front (Fig. 4). Likewise, lichen coated granites from Australia’s most elevated alpine regions in the Snowy Mountains (Thredbo) displayed intense spalling but were covered in snow six months later. The fire recurrence interval for these alpine regions is probably in the order of one every 20–100 years thus the effects of fire-spalling are less pronounced than in arid regions and less evident than other forms of fluvial or chemical weathering that dominate in wetter climates. However, the abundant spalled surfaces shown in Fig. 4 reveal that large, intense fires such as the Black Summer fires of 2019–2020 will result in significant erosion and sediment production even in alpine environments. More

SizesAs from the measurements, all collected coprolites vary in sizes (Table 1). The smallest and complete specimen is IVPP V 27,545 (Fig. 2D–G), and while IVPP V 27,550 (2 V-Z) is multiple time larger. The maximum length for specimen IVPP V 27,544, IVPP V 27,546, IVPP V 27,547 and IVPP V 27,549 have not been determined due to their incompleteness.Table 1 Biometrical and morphological features of spiral coprolites from Tsagan-Tsab Formation (Lower Cretaceous), Tatal, western Mongolia. Paul Rummy, Kazim Halaclar & He Chen.Full size tableSurface adhesion and marksAll specimens contained some degree of bone fragments and rhomboidal-shaped ganoid scales adhered to the coprolite surfaces (Fig. 3). Additionally, all specimens have smooth surfaces with little abrasion. The inner coil lines of specimen IVPP V 27,549 adhered with a matrix of red clay with silt (Fig. 2S–U). Only specimen IVPP V 27,550 has been seen with concentric cracks (Fig. 2V–Z). Bite marks have also been found on specimen IVPP V 27,545, in which these traces were short, parallel, shallow and isolated. They have been formed from 3 furrows of roughly 3.8 mm long and 0.3 mm deep (Fig. 4).InclusionsThrough CT scans and surface observation, we noticed that all specimens contained bone fragments and scales of varying degrees (Fig. 5). We were unable to identify the bones in detail for specimen IVPP V 27,544, IVPP V 27,546, IVPP V 27,547, IVPP V 27,548, IVPP V 27,549 and IVPP V 27,550, as they were excessive in amount and extremely fragmentary. On the contrary, for specimen IVPP V 27,545, we noticed a rather complete bone structure, such as the ribs and a segment of an infraorbital (Fig. 5H–N). SEM photograph from one random point of specimen IVPP V 27,545 yielded results of the existents of pollen grain (Fig. 6C).BoringsSurface borings of invertebrate burrowing can be seen in 2 spiral coprolites, namely IVPP V 27,547 (Fig. 2D–G) and IVPP V 27,550 (Fig. 2V–Z). CT scans revealed that the borings of specimen IVPP V 27,550 did not intrude internally, and it was the same for some of IVPP V 27,547 as well (Fig. 7). Specimens IVPP V 27,546, IVPP V 27,547, IVPP V 27,548 and IVPP V 27,549 are shown to have traces of internal borings (Fig. 5C–F).EDS analysesIn this work, in regards to Tatal’s coprolites, the mineral elements were examined by using EDS and the photos were taken with SEM. Analyses was conducted on 2 specimens (IVPP V 27,546 and IVPP V 27,545) with two sample points for each. All 4 samples showed high peaks of calcium and phosphorus. EDS results of specimen IVPP V 27,546 (Fig. 6A–B) and specimen IVPP V 27,545 (Fig. 6C–D) gave similar atomic compositions. They were mainly composed of Ca, P and O and small peaks that belong to Nb, Si, C, K, Fe and Al. We have also described a potential pollen structure under SEM image (Fig. 6C). This possible pollen structure in specimen IVPP V 27,545 (Fig. 6C) showed different atomic elements from the other EDS results, where it contained high peaks of Na and Cl.Taphonomy inferencesNo signs of abrasion were found on all of the coprolites. Coloration of the coprolites varied, thus, indicating they were buried in different sedimentary conditions. Through the shape of the coprolites, we can deduce that they have indeed spent different amounts of time or phases in water bodies before burial (see above description/discussion). Meanwhile, specimen IVPP V 27,550 showed shallow coil deepness, therefore, this indicates that it was buried rapidly after excretion.Discussion and interpretationThere are several pivotal evidences that corroborate to fecal origins of the Tsagan-Tsab Formation material: (1) basic morphology; (2) general shape and size (3) inclusions of the fecal matter; (4) high calcium and phosphorus content; (5) bioerosional scars; (6) borings and cavities; (7) concentric cracks.The fundamental puzzle in the studies of coprolite is the difficulty in identifying the potential producer, which can be due to their nature and preservation. Also, that includes the methods used to deduce them with their producer, which were done by inferring with various forms of relationship based on stratigraphy and geographical relationships, as well as on neoichnology studies7,23,54,55. Such problems similarly arose in our context as well, and the materials were collected from a stratum that were interpreted as lake deposit margins, thus, suggesting an amphibious or aquatic producer. The paleoenvironment correlates with the findings of pterosaur fossils such as the Noripterus44 or argued as ‘Phobetor’56, and the diets of these pterosaurs were dependable on the lake environment57,58,59,60. Above all, and more importantly, that the shape of the coprolite has to be intact in order to represent the shape of the internal intestine of the producer, whereby, anatomically it can lead to a certain biological aspect and digestive system of the organism. Despite these, there are on-going controversies on the origin of the spiral shaped bromalites in regards to whether or not they signify fossilized feces, or they are the cololite that was formed within the colon6,21,23,61,62.Spiral coprolites are producer of an animal with spiral intestine valves to increase the surface area of absorption, to slow down food movement in the bowel to maximise nutrient absorption, which has a significant strategy in surviving uncertain and harsh environment conditions28,63,64. Referring to past literature, it is generally agreed upon that the spiral shape is the only distinctively coprolite morphology, whereby it has been regarded as a true coprolite and can be correctly associated to the source animal, such as a range of fishes in particular6,22,52. Many primitive bony fishes (except those of teleosts), fresh water sharks (elasmobranches), coelacanths, Saurichthys, sturgeons and lungfishes are known to have the spiral valve intestine51,64,65,66. Also, Price67 suggested that the amphipolar form could have been derived from palaeoniscoids. Additionally, Romer & Parsons68 noted that the spiral valves are secondarily lost in teleost and tetrapods, while Chin69 noted a few teleosteans still possessing them.The spiral coprolites collected for this study are mainly amphipolar in shape and one in scroll. As we know, generally heteropolar spiral coprolite are produced by sharks, which have complex spiral valves62. Therefore, we can exclude those in the family of elasmobranches as the potential producers and this can also be supported by the non-marine geological settings of Tsagan-Tsab Formation. But it is also noteworthy to mention that in previous studies, some workers have conducted observations on sharks that were kept in tanks, and were not been able to find any spiral fecal pellets. The reasons given were that the sharks’ eating habits could have changed due to the tank environment, which would have differed from the natural marine environment. Also, modern day sharks are totally unrelated to the ancient Permian pleuracanth sharks6. Despite these, evidence of spiral fecal pellet can still be observed in some of the present-day fishes, such as the African lungfish Protopterus annectans, the Australian lungfish Neoceratodus forsteri, the long-nosed gar Lepisosteus osseus and the spotted gar Lepisosteus oculatus6,70,71,72. As for scroll coprolites, it is generally known to be produced by animal with longitudinal valves (valvular voluta), whereby the valves naturally rolls in upon itself , in a way that it maximises nutrient absorption8,9,17,18. Gilmore17 in his work mentioned that this type of valve must be primitive than the transverse valve (valvular spiralis), which could be a modification of the previous ones. This form is especially known to sharks of carcharhiniforms73, and it is evident that it could have been associated with sarcopterygian53, as well as anaspid and thelodont agnathans17.In this study, we recognised four new ichnotaxa for all the seven coprolite specimens. Assigning four new ichnotaxa does not conclude that the coprofauna are of four different types of animals. Considering there are two distinct morphologies, which are the amphipolar spiral and scroll, we can deduce that at least two animals can produce these coprolites. But we have to carefully consider that diverse diets at different times for the same animal can often be variable, and soft fecal materials can range disparately after defecation, as well as taphonomy influence74,75. Specimen IVPP V 27,550 is remarkably huge and its producer should be a massive animal since large animals could produce small excrement, but small animals would not be able to produce big excrement52,54. Moreover, since there are no relevant fossils fauna found in the locality, we were unable to exactly identify the specific producer, rather, we deduced with relevant sources. However, we do know that both amphipolar spiral and scroll coprolites can be attributed to certain types of fishes. As of these, we can conclude that the coprolites were produced by fishes in different sizes. Specimen IVPP V 27,545 differs from the rest by its shape and size, which makes prediction even harder, because it could be produced by either large or smaller animals.CT scans revealed that bony inclusions are evident in all of the coprolites (Fig. 5). However, except in specimen IVPP V 27,545, the bones in the rest of the coprolites are fragmentary. Specifically, bones in specimen IVPP V 27,545 are rather unaffected by the acidity of the digestive enzyme and these were evident by the presence of clusters of entire bones in the coprolite (Fig. 3A–C), as contrast to the fragmentary bones in the rests of the coprolites. Furthermore, we identified an infraorbital bone of a fish. CT scans revealed that the infraorbital bone has a sensory canal where it branches off at both ends (Fig. 5M–N). With these, we can indicate that the producer of specimen IVPP V 27,545 poorly masticated the prey and also had a rather low gut digestion for food28,55,76,77,78. Through these results, we can infer the digestive strategies of the producers were in correlation with food intake and digestion process, as discussed in Barrios-de Pedro & Buscalioni77. Specimen IVPP V 27,545 might belong to the first type of digestive strategy, whereby the producer has limited food processing in the mouth and the food stays in the digestive system for a short period of time. This strategy is regarded to be efficient in conditions where food sources are abundant and the nourishment levels are sufficient79. The rest of the coprolites possibly belong to the second digestive strategy, as the bone content is fragmentary. This suggest the producer might have limited mastication with improved digestive assimilation and longer gut time to favour better absorptions of nutrients55,80,81,82,83. The third type of digestive strategy does not imply in our study. It is also noteworthy to mention that the quantity of the inclusions is not correlated to the size of the coprolite, rather, it is dependable on the above-mentioned biological variables28,84.Carnivorous coprolites are normally composed of calcium phosphate and other organic matter, but it is important to be aware that the initial compositions are usually altered during fossilization processes33. Meanwhile, the excretion of herbivores is generally lacking in phosphates and their fossilization are mostly dependable of the mineral enrichment85. Through the morphological shape, the density of bone and scale inclusions on the surface from the CT scans, we can directly assume that these coprolites are inevitably produced by carnivorous organisms. Despite that, we still conducted SEM–EDS tests on two specimens, IVPP V 27,546 and specimen IVPP V 27,545 (Fig. 6), in order to determine its mineral content, and to prove them as a valid coprolite material because we were not able to compare these materials to any attached locality matrix at the time the study. The reason for that was because the specimens were collected almost two decades ago and they were very well-kept in the archives throughout these years. As predicted, all 4 samples gave higher content of Ca and P, thus, there is no doubt that they are indeed fossilized fecal materials. Also, in regards to the SEM–EDS on specimen IVPP V 27,545 (Fig. 6C–D), when randomly pointed to a particular structure, it yielded unusual results from the rest, in which the EDS peaks are composed of Na and Cl. At the same time, the SEM image potentially showed a pollen grain like structure. Hollocher and Hollocher86 documented a pollen image by using SEM, which brings our potential pollen image (Fig. 6C) dimensionally compatible with their sample. Although specimen IVPP V 27,545 is produced by an unidentified carnivorous vertebrate, it is common for carnivore coprolites to have plant remains within them. Also, it is known that spores and pollens are exceptionally well preserved within the encasement of calcium phosphate, which inhibits sporopollenin degradation87. Various reasons can be inferred for the presence of the pollen in specimen IVPP V 27,545, to which it could either be by accident or by preying on an herbivorous animal. Furthermore, it could also be through the adhesion on the excrement when the fecal is still fresh88. Pollens are in fact valuable information provider for paleoenvironment reconstruction, as well as for understanding the vegetation state of a particular era87,89,90,91,92. Hence, further palynology analyses are needed for future work.EDS mineral composition and coprolite coloration can be correlated to a certain degree, in which it could also explain depositional origin27. Most of the Tatal’s coprolites are pink-whitish in color, which is highly associated with the presence of calcium through its carnivorous diets93,94,95,96. The dark colors can also be due to the presence of iron or it could also be due to complete phosphatisation23,27. However, a large part of the colorations was influenced by diagenesis27,28.Traces of burrows are evident on the surface of specimen IVPP V 27,547 and IVPP V 27,550, but CT scans revealed internal traces burrowing did occur in specimen IVPP V 27,546, IVPP V 27,547, IVPP V 27,548 and IVPP V 27,549 (Fig. 5). Since not all possible burrows were dug-in, we gave the term ‘pseudo-burrow’ on those burrows that were abandoned in the early stages. For example, on all of the burrow traces in specimen IVPP V 27,547, only one traces showed burrowing holes, while the rest did not form a hole. While those specimens with internals, but without any traces on the outer surface, this can be explained by taphonomy processes, whereby the outer surface is covered with sedimentary and non-differentiable. It was reported in Tapanila et al.97, that marine bivalves are potential makers of the burrows in coprolites by expanding the diameter of the hole as they dig in, although Milàn, Rasmussen & Bonde98, reported a contradictory example, where the holes were indeed constant in diameter. In our study, we couldn’t determine if the holes were constantly in diameter or not. Numerous tiny holes were visible on all of the coprolites surface, as well as within it, and these were most probably caused by gases within the fecal matters. These holes can be called as microvoids or ‘degassing holes’, which contain gases trapped during digestion74,99,100. Microvoids are quickly filled with water when fecal matter is excreted from the animal body, thus making the fecal becoming heavy and sinking to the lake floor74.A series of three parallel furrows or bioerosional scars were evident on the surface of specimen IVPP V 27,545 (Fig. 3). Those lines only occurred once without any repetition on the rest of the surface. The information from these furrows were insufficient to deduce any potential biters, as widely discussed in the work of Godfrey & Palmer101, Godfrey & Smith102, Dentzien-Dias et al.103, and Collareta et al.104. On the other hand, deducing from the dented surface on the bitten marks, we predicted that the marks were most probably made by the biting pressures from the fish mandibles, which may indicate coprophagous behavior. The biting could have happened on the lake floor just before sedimentary deposition. Since the bitten marks are on the surface, this probably suggests unintentional scavenging and was eventually aborted during food search.In general, coprolites can be transported from the original place through various modes25 and this can be evident by the traces of abrasion51,65. However, in Tatal’s coprolites, there were little or almost no marks of abrasion. Yet again, this supports our hypothesis that these coprolites were excrements in shallow waters, such as in the lake banks with little turbulence and current, where the fecal matter was dropped in-situ after excrement. As stated in previous literature105,106, radial and concentric cracks are also evident on the surface of specimen IVPP V 27,550, therefore, these indicate that the coprolite was excreted on a very shallow environment where the water body was vastly evaporated and left for subaerial exposure before embedment. This phenomenon caused the coprolite to dehydrate through the cracking, and shrinking occurred in a low magnitude process while retaining its overall shape27,54,107. Previous authors have also discussed that the cracks could possibly be due to synaeresis under certain conditions27,54,108.It has been frequently reported in records that almost all spiral coprolite fossilization from various Phenerozoic ages have occurred in low-energy shallow marine environments54. Feces that are being excreted in this humid environment have a higher chance of preservation due to the rapid burial, as well as on the acidity level of the water bodies5,7,109,110,111. There are also several crucial factors that are involved in fecal fossilization. Among them, one of the most important criteria includes the content and composition of the fecal matter, and those of carnivorous diets tend to form coprolites than those who consumed an herbivorous diet75. As mentioned in Dentzien-Dias et al.111, there are three main stages involved in a coprolite taphonomy history, which include stages before final burial, after the final burial and after exposure. In accordance to this, we introduced the usage of phases to discuss the spiral coprolites morphologies in this study (see material and methods). The phase concept of spiral coprolites disentanglement has been widely discussed in early days by various workers6,22,70. Coprolite specimen IVPP V 27,544 and IVPP V 27,547 are considered as Phase 1, as the coils are not deep, and this can be explained as during excrement, there’s a mucosal membrane covering the surface of the fecal matter and embedment occurring rapidly, thus retaining most of its surface structure. Although there are signs of disentanglement, we predict that the uncoiling on the surface was not by natural processes, but has been caused by a breakage after on. Both of these two coprolites could have been large in actual size. Similar explanations can be given to specimens IVPP V 27,548 and IVPP V 27,550, whereby the coils are shallow, thus, classifying them as to had occurred in Phase 1. We classify specimen IVPP V 27,546 and IVPP V 27,549 as Phase 2, in which the spaces between the coils of IVPP V 27,546 were slightly separated and in IVPP V 27,549, they were strongly separated. Both of these specimens could have spent more time in water bodies before burial. Specimen IVPP V 27,545 does not provide any external information in regards of phases approach because of its non-spiral morphology. While it is also worthwhile to mention that none of them have spent sufficient time in the water bodies in order to possess the Phase 3 structure. Through these, we can also conclude that smaller coprolites are much complete while bigger coprolites tend to easily break-off. However, having mentioned that, the preservation of specimen IVPP V 27,550 is indeed valuable.Through the above morphological points, we predict that the amphipolar spiral coprolites could have belonged to groups of either prehistoric lungfishes or Acipenseriformes (sturgeon and paddlefish). Another aim of this work is to portray the existence of possible prey-predation relationships from the collected coprolites. In order to narrow down the identity of the potential producer and possibly the prey, we looked into some related fauna list from past literature. Geological settings have indicated that the Lower Cretaceous Tsagan-Tsab formation is not only recorded in the area of Tatal, but also in other regions of Mongolia as well36. There are two possibilities on the deduced prey and predator, they are either of Asipenceriformes—Lycopteriformes relationship or Asipenceriformes—Pholidophoriformes relationship. We suggest Pholidophoriformes as a much potential prey than the Lycopteriformes in the Tsagan-Tsab Formation, and the reasons will be explained thoroughly. As for the producer, we knew that Asipenceriformes are largely known from the Lycoptera-Peipiaosteus (Asipenceriformes) Fauna or the “Jehol Fauna”, as these assemblages of fishes were not only abundant in the Lower Cretaceous Yixian Formation of northeastern China, but also widely distributed over the region of eastern Siberia, Mongolia, northern China and northern Korea112. It is also noteworthy to mention that the Tsagan-Tsab formations and the Yixian formation were similar in geological age. In the same context, Jakolev35 described Stichopterus popovi (Asipenceriformes) and recorded amphipolar spiral coprolites from the Aptian lacustrine of Gurvan-Eren Formation of Mongolia , a locality that is close to Tatal. Although there are differences in the geological period of Tsagan-Tsab and Gurvan-Eren Formation, it is highly possible that Asipenceriformes existed in these areas. Furthermore, Asipenceriformes are shown to have spiral valves113, and this can be further proven with the work of Capasso64 on Peipiaosteus pani, thus, contributing to the morphology of the spiral coprolites. With these, we strongly suggest that the amphipolar spiral coprolites of Tsagan-Tsab Formation and for Gurvan-Eren Formation to belong to Asipenceriformes. As for prey, we know from existing literature that there is a close relationship between Asipenceriformes and Lycoptera, as evident in the name Lycoptera-Peipiaosteus Fauna. Yondon et al.36 reported Lycoptera middendorfii, a form of small freshwater Teleost fish from the Eastern Gobi—Tsagan-Tsab formation. But, it was clearly mentioned that Bon-Tsagan/Bon-Chagan (Fig. 1) is the westernmost locality of Lycoptera in Mongolia114. Another fact that was taken into account for the possible prey is the shape of the scales found in the inclusions, whereby Lycoptera are known for their cycloid shaped scales, while the ones in our specimens are more towards rhomboidal-shaped ganoid scales. These facts crucially eliminate the possibilities of Lycoptera for the Tsagan-Tsab fauna. With this, we further examined Jakolev35′s works and discovered the species that he described, Gurvanichthys mongoliensis (Pholidophoriformes) from the Gurvan-Eren Formation has rhomboidal-shaped ganoid scales. The size, shape of the scale and the nature of this fish fits well as a prey for the Stichopterus popovi (Asipenceriformes). Through these interpretations, we can possibly infer that the spiral coprolites in our study might have belonged to Asipenceriformes and Pholidophoriformes as the prey, which could further affirm the occurrence of prey-predator inter-relationship in the Lower Cretaceous of Tsagan-Tsab Formation.As for the sole scroll coprolite in this study, we do not intend to further deduce any detailed possibilities. Based on other works, chondricthyans origins or a sarcopterygian for scroll coprolites were suggested18,53,but such deduction is difficult to be purported in our studies as there is a lack of such fossil materials in the locality and surrounding localities. The chances of the underived producer to be a sarcopterygian is much higher than to be a chondricthyan, mainly due to its geological settings. The discovery of the single scroll coprolite can be a window opening to many paleontological questions for Tsagan-Tsab Formation. More

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Combined culture-dependent and culture-independent approach identifies the prevalent and viable bacterial community members of the human lung post-transplantTo characterize the bacterial community composition of the lung microbiota post-transplant, we performed 16S rRNA gene amplicon sequencing of 234 longitudinal BALF samples from 64 lung transplant recipients collected over a 49-month period (Fig. 1a, Supplementary Table 1). A total of 7164 operational taxonomic units (OTUs) were identified, excluding OTUs contributing to reads in 11 negative control samples32 (see “Methods”, Supplementary Fig. 1a, Supplementary Data 1 and 2). In accordance with previous studies on BALF samples from healthy non-transplant individuals4,5,6,26, we found that Bacteroidetes and Firmicutes followed by Proteobacteria and Actinobacteria are the most abundant phyla in the post-transplant lung (Fig. 1b). Prevalence analysis across all BALF samples showed that the community composition is highly variable with only 22 OTUs shared by ≥50% of the samples (Supplementary Fig. 1b, Supplementary Data 3). However, these 22 OTUs constituted 42% of the total number of rarefied reads, indicating that they are predominant members of the post-transplant lung microbiota (Fig. 1c, Supplementary Fig. 1c, Supplementary Table 2, Supplementary Data 3). They belonged to the genera Prevotella 7, Streptococcus, Veillonella, Neisseria, Alloprevotella, Pseudomonas, Gemella, Granulicatella, Campylobacter, Porphyromonas and Rothia, the majority of which are also prevailing community members in the healthy human lung3,5,7,26, suggesting a considerable overlap in the overall composition of the lung microbiota between the healthy and the transplanted lung.Fig. 1: Combining BALF amplicon sequencing and bacterial culturing to deduce the microbial ecology of deep lung microbiota.a Schematic of the sampling of Bronchoalveolar lavage fluid (BALF) from lung transplant recipients over time (months post-transplant). b Relative abundances (%) of most abundant phyla across BALF samples. Box plots show median (middle line), 25th, 75th percentile (box) and 5th and 95th percentile (whiskers) as well as outliers (single points). c Prevalence (% samples) vs contribution to total reads across samples for most abundant phyla. Dot color shows different genera and size show total rarefied reads. Gray dashed horizontal line shows prevalence ≥50%. d Scatter plot shows correlation between number of observed OTUs and bacterial counts per BALF sample obtained by quantifying 16S rRNA gene copies with qPCR. Linear regression is shown by the blue line with gray shaded area showing 95% confidence interval (n = 234, two-sided, F(1, 232) = 91.04, P = 2.2 × 10−16), Coefficient of correlation; R2 = 0.28. e Bar chart shows lung taxa (genera; OTU IDs) that contributed ≥75% of total bacterial biomass across samples (n = 234). Venn diagram inset shows overlap (yellow) between the most prevalent (≥50% incidence, light blue) and the most abundant (≥75% total count, red) taxa in the transplanted lung. Bar colors also show the same.Full size imageDifferences in bacterial loads between samples can skew community analyses when based on relative abundance profiling alone. Therefore, we used qPCR to determine the total copies of the 16S rRNA gene as an estimate for bacterial counts, and normalized the abundances of each OTU across the 234 samples (absolute abundance). We found that the bacterial counts vastly differed between samples, ranging between 101 and 106 gene copies per ml of BALF (Supplementary Fig. 1d). The number of observed OTUs increased with decreasing counts (Fig. 1d) suggesting that a large fraction of the OTUs were detected in samples of low bacterial biomass and hence represent either transient or extremely low-abundant community members, or sequencing artefacts and contaminations. In turn, 19 of the 7164 OTUs constituted >75% of the total bacterial biomass detected across the 234 BALF samples (Fig. 1e). This included 11 of the 22 most prevalent OTUs (see above) plus eight OTUs that were detected in only a few samples but at very high abundance (Staphylococcus; OTU_2, Corynebacterium 1; OTU_16 and OTU_24, Anaerococcus; OTU_49 and OTU_234, Haemophilus; OTU_78, Streptococcus; OTU_6768, Peptoniphilus; OTU_63, Supplementary Table 2). It is important to differentiate these opportunistic colonizers from other community members with low incidence, as they reached very high bacterial counts in some samples with potential implications for lung health.To demonstrate the viability of prevalent lung microbiota members and to establish a reference catalogue of bacterial isolates from the human lung for experimental studies, we complemented the amplicon sequencing with a bacterial culturing approach (Supplementary Fig. 2). We cultivated 21 random BALF samples from 18 individuals, on 15 different semi-solid media (both general and selective) in combination with 3 oxygen concentrations; aerobic, 5% CO2, and anaerobic (See “Methods” and Supplementary Table 3), representing 26 different conditions. We cultured fresh BALF immediately upon extraction (within 2 h), as we observed loss in bacterial diversity upon cultivating frozen samples. This resulted in a total of 300 bacterial isolates, representing 5 phyla, 7 classes, 13 orders, and 17 families from which we built an open-access biobank called the Lung Microbiota culture Collection (LuMiCol, Supplementary Data 4, https://github.com/sudu87/Microbial-ecology-of-the-transplanted-human-lung).To examine the extent of overlap between bacteria in LuMiCol and the diversity obtained by amplicon sequencing, we included 16S rRNA gene sequences from 215 isolates that passed our quality filter into the community analysis, which allowed for the retrieval of OTU-isolate matching pairs32 (Methods). We found that 213 isolates matched to 47 OTUs (Fig. 2a, c, Supplementary Data 5), including 17 of the most prevalent and abundant bacteria (Fig. 1e, Supplementary Table 2). As expected, bacteria with high abundance in the amplicon sequencing-based community analysis were isolated more frequently, with Firmicutes revealing the highest isolate diversity (Fig. 2a–c, Supplementary Data 4, 5) and being recovered under the most diverse culturing conditions.Fig. 2: A lung microbiota culture collection (LuMiCol) reveals extended diversity and phenotypic characteristics of the lower airway bacterial community.a Phylogenetic tree of the 47 OTU-isolate matching pairs inferred with FastTree. Branch bootstrap support values (size of dark gray circles) ≥80% are displayed. b Growth characteristics of each OTU-isolate matching pair in three different oxygen conditions (Anaerobic – light brown, 5% CO2-yellow, aerobic-light blue, n = 3). Column with pie charts shows growth on semi-solid agar. Heatmap shows median change in Optical Density (OD) at 600 nm growth in three different liquid media (THY, RPMI, RPMI without glucose) over 3 days. c Cumulative counts of each OTU-isolate matching pair across all BALF samples (gray). d Number of isolates in Lumicol (black) per OTU-isolate matching pair. Taxa are labeled as genus; OTU ID, with an indication of whether they are prevalent (gray rectangle) or opportunistic (magenta rectangle) in the lower airway community. The names of the closest hit in databases: eHOMD and SILVA are used as species descriptor.Full size imageIn summary, our results from the combined culture-dependent and culture-independent approach show that the lung microbiota post-transplant is highly variable in terms of both bacterial load and community composition with many transient and low-abundant bacterial taxa. However, a few community members display relatively high prevalence and/or abundance suggesting that they represent important colonizers of the human lung.LuMiCol informs on the diversity and metabolic preferences of culturable human lung bacteriaWe characterized the culturable community members of the lower respiratory tract contained in LuMiCol by testing a wide range of growth conditions and phenotypic properties (see “Methods”). The majority of the cultured isolates could taxonomically be assigned at the species level based on genotyping of the 16S rRNA gene V1-V5 region. However, the limited taxonomic resolution offered by this method does not allow to discriminate between closely related strains, which can include both pathogenic and non-pathogenic bacteria. Hence for Streptococcus, we additionally tested for type of hemolysis (alpha, beta, or gamma) and resistance to optochin, which differentiates the pathogenic pneumococcus and the non-pathogenic viridans groups (Fig. 2a, Supplementary Fig. 2b, c). This demonstrated that the 16 Streptococcus OTU-isolate pairs belong to the viridans group of streptococci (VS)33. Interestingly, these isolates exhibited the highest genotypic and phenotypic diversity throughout our collection and belonged to five OTUs among the 22 most prevalent community members, with Streptococcus mitis (OTU_11) present in 93.6% of all samples.BALF from healthy individuals contains amino acids, citrate, urate, fatty acids, and antioxidants such as glutathione but no detectable glucose34, which is associated with increased bacterial load and infection35,36,37. To get insights into basic bacterial metabolism, we assessed the growth of all 47 isolates matching an OTU under different oxygen concentrations. We used undefined rich media (Todd-Hewitt Yeast extract) and defined low-complexity liquid media (RPMI 1640), including a glucose-free version to mimic the deep lung environment (see “Methods”). Despite the presence of oxygen in the human lung, the majority of the isolates were either obligate or facultative anaerobes (Fig. 2a), including some of the most prevalent members (Prevotella melaninogenica (OTU_3), Streptococcus mitis (OTU_11), Veillonella atypica (OTU_6) and Granulicatella adiacens (OTU_17). A similar trend was also observed in liquid media under anaerobic conditions, with the exception of the genera Prevotella, Veillonella and Granulicatella. Most streptococci from the human lung grew best in complex liquid media containing glucose under anaerobic conditions, including the most prevalent species in our cohort, S. mitis (OTU_11) (Fig. 2b). However, noticeable exceptions were S. vestibularis (OTU_34), S. oralis (OTU_3427 and OTU_1567), and S. gordonii (OTU_10031), which grew equally well in the presence of oxygen and in low-complexity liquid medium (Fig. 2b). Most Actinobacteria grew best on rich medium in the presence of 5% CO2, with an exception of Actinomyces odontolyticus (OTU_39), which required anaerobic conditions. Some Actinobacteria grew equally well in anaerobic conditions as in the presence of 5% CO2, i.e., Corynebacterium durum (OTU_501), Actinobacteria sp. oral taxon (OTU_328 and OTU_228).The two most predominant opportunistic pathogens in our lung cohort, P. aeruginosa (OTU_1) and S. aureus (OTU_2), grew best in rich liquid medium in the presence of oxygen (Fig. 2c), although these also grew to lower degree under anaerobic conditions. These results indicate that changes in the physicochemical conditions in the lung may favor the growth of these two opportunistic pathogens. In summary, our observations from the bacterial culture collection provide first insights into the phenotypic properties of human lung bacteria and will serve as a basis for future experimental work.Identification of four compositionally distinct pneumotypes post-transplant using machine learning based on ecological metricsTo detect and characterize differences in bacterial community composition between BALF samples from transplant patients, we clustered the samples using an unsupervised machine learning algorithm based on pairwise Bray–Curtis dissimilarity32 (beta diversity, See “Methods”, Supplementary Data 6). This segregated the samples into four partitions around medoids (PAMs) at both phylum and OTU level (Fig. 3a, b, Supplementary Fig. 3a, b). We refer to these clusters as “pneumotypes” PAM1, PAM2, PAM3, and PAM4 (Supplementary Table 4). PAM1 formed the largest cluster consisting of the majority of samples (n = 115) followed by PAM3 (n = 76), PAM2 (n = 19), and PAM4 (n = 24) (Supplementary Data 7). Examination of various diversity measures (Species occurrence, OTU diversity, OTU richness, Fig. 3c–e), distribution of the dominant community members (Fig. 3f), and bacterial counts (16S rRNA gene copies, Fig. 3g) revealed distinctive characteristics between the four pneumotypes.Fig. 3: Bacterial communities of the lung post-transplant fall into four ‘pneumotypes’ with distinct community characteristics.a, b Principal component analysis shows Partition around medoids (PAMs) at phylum and OTU level respectively generated by k-medoid-based unsupervised machine learning using Bray–Curtis dissimilarity (occurrence and abundance). Pneumotypes are color coded: Balanced (red, n = 115), Staphylococcus (green, n = 19), Microbiota-depleted (MD, blue, n = 76), and Pseudomonas (orange, n = 24). c–g Violin plots show distributions of pairwise species occurrence (Sorenson’s index, PERMANOVA, two-sided, F(3, 229) = 8.49, P = 9.9 × 10−5), OTU diversity (Kruskal–Wallis test, χ2 = 89.2, df = 3, two-sided, P = 2.2 × 10−16), OTU richness (ANOVA, F(3, 229) = 43.9, two-sided, P = 2.2 × 10−16), proportion of most dominant OTUs (Kruskal–Wallis test, χ2 = 94.45, df = 3, two-sided, P = 2.2 × 10−16), and total bacterial counts (ANOVA, F(3, 229) = 43.9, two-sided, P = 2.2 × 10−16), respectively, across the four pneumotypes. h, i Enrichment analysis of prevalence (green dotted line ≥50%) and absolute abundance across all samples of the 30 most dominant taxa (i.e., OTUs) in PneumotypeBalanced and PneumotypeMD respectively, when each was compared to the other three combined pneumotypes (gray boxes). Differential abundances after enrichment analysis was calculated between each PAM and the other three PAMs combined, using ART-ANOVA. j Heatmap shows relative percentage of taxa (right colored panel) cultured from paired samples of Bronchial aspiration (BA) and Bronchoalveolar lavage fluid (BALF) from each pneumotype (left colored panel). Oropharyngeal flora mainly corresponds to PneumotypeBalanced (i.e., Streptococcus, Prevotella, Veillonella). All box plots including insets show median (middle line), 25th, 75th percentile (box) and 5th and 95th percentile (whiskers) as well as outliers (single points). Multiple comparison of beta diversity indices was done by pairwise PERMANOVA (adonis) with False Discovery rate (FDR). Post hoc analyses (95% Confidence Interval) were done by using Tukey’s test (ANOVA) or Dunn’s test (Kruskal test) with False Discovery Rate (FDR) or least-squares means (ART-ANOVA) with False Discovery Rate (FDR). * P  More