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G.M., L.O.A., L.V.G. and L.E.O.C.A. thank the São Paulo Research Foundation (FAPESP) for funding (grants 2019/25701-8, 2020/08916-8, 2016/02018-2 and 2020/15230-5, respectively). L.O.A. and L.E.O.C.A. thank the National Council for Scientific and Technological Development (CNPq) for funding (grants 314473/2020-3 and 314416/2020-0, respectively). G.d.O. thanks the University of South Alabama Faculty Development Council Grant for funding (grant 279600-2022). More

Study population and study designThis is a prospective interventional cohort study of healthy S. aureus carriers and noncarriers in the Netherlands. All experiments were performed in accordance with the Dutch Medical Research Involving Human Subjects Act (WMO). The study protocol was approved by the local Medical Ethical Committee of the Erasmus University Medical Centre Rotterdam, The Netherlands (MEC-2018-091). Written informed consent was obtained for all participants. Participants were recruited through advertisements at Dutch universities and the research teams social networks. Exclusion criteria were age  8 CFU/mL for each culture. Noncarriers were defined as 2 S. aureus-negative cultures. Intermittent S. aureus carriers were excluded from further participation in the study. Eligible volunteers were enrolled on a first-come, first-served basis.Eligible participants were asked to fill out a questionnaire regarding risk factors for S. aureus acquisition. All participants received decolonization treatment. Decolonization consisted of mupirocin nasal ointment (2%, GlaxoSmithKline BV, Zeist, the Netherlands) twice daily and chlorhexidine gluconate cutaneous solution (4%w/v, Regent Medical Overseas Limited, Oldham, UK) once daily, both for 5 days.Nasal samples were taken 1 day before decolonization (D0) and 2 days (D7), 1 month (M1), 3 months (M3) and 6 months (M6) after decolonization. All participants received a personal demonstration for nasal sampling by the executive researcher. Thereafter, all specimens were taken by the participants by inserting a swab (ESwab, 490CE.A, Copan Italia, Brescia, Italy) into one nostril and rotating 5 times, repeating this in the second nostril using the same swab. Swabs were collected in a container filled with 1 ml modified Liquid Amies, a collection and transport solution, and sent through regular mail service (non-temperature controlled) or deposited at the laboratory personally.
Staphylococcus aureus quantitative cultureQuantitative S. aureus cultures were conducted to examine the dynamics of S. aureus carriage over the 6-month follow-up period after decolonization. Swab containers were vortexed for 20 s before plating. Serial dilutions of Amies medium were plated onto phenol mannitol salt agar (PHMA) and incubated for 2 days at 37 °C. Swabs were placed in phenol mannitol salt broth (PHMB) and incubated for 7 days at 37 °C for enrichment. S. aureus growth was confirmed by a latex agglutination test (Staph Plus Latex Kit, Diamondial, Vienna, Austria). Morphologically different S. aureus colonies were selected for spa typing and methicillin resistance screening using BBL CHROMagar MRSA II agar (BD, Breda, The Netherlands).
Spa typingMolecular typing of S. aureus isolates was performed to infer whether recolonization with S. aureus in decolonized carriers involved the same spa-type. Typing was limited to the last S. aureus positive culture moment and the last S. aureus positive culture moment after decolonization in recolonised carriers. S. aureus DNA lysates were prepared by boiling in 10 mM Tris–HCl, 1 mM disodium EDTA, pH 8.0 or extraction with the QIAamp DNA Mini Kit (QIAGEN, Venlo, The Netherlands) according to the manufacturer’s instructions. Amplification of the S. aureus protein A (spa) repeat region was performed by PCR with 2 sets of primers. One set consisted of forward primer spa-1113, 5′-TAAAGACGATCCTTCGGTGAGC-3′ and reverse primer spa-1514, 5′-CAGCAGTAGTGCCGTTTGCTT-3′24. The other set consisted of forward primers spa-F1, 5′-AACAACGTAACGGCTTCATCC-3′ and spa-F2 5′-AGACGATCCTTCAGTGAGC-3′ and reverse primer spa-R1 5′-GCTTTTGCAATGTCATTTACTG-3′. Amplicons were purified with ExoSAP-IT (Applied Biosystems) according to the manufacturer’s instructions and sent for sequence analysis (Baseclear, Leiden, The Netherlands). Resulting sequences were analysed using BioNumerics v7.6 (Applied Maths NV, Sint-Martens-Latem, Belgium) and the spa types were assigned by use of the RidomStaphType database (Ridom GmbH, Würzburg, Germany).16S ribosomal RNA sequencing of nasal microbiotaThe impact of decolonization on the nasal microbiome and the recovery of the microbiome structure after decolonization were examined by means of 16S rRNA metabarcoding. Amies medium from each nasal swab container was stored at − 80 °C on the day of receipt at the study laboratory in Rotterdam, NL, then sent at − 80 °C to the microbiome analysis laboratory in Lyon, FR. To properly capture the impact of decolonization on the living microbiota, metabarcoding used RNA-based 16S ribosomal RNA (rRNA, which is preserved in living cells but quickly cleared after cell death or lysis) rather than the DNA coding sequence, as DNA can persist for prolonged time periods after cell death25,26,27,28. RNA was extracted using the Mag Bind® Total RNA 96 Kit (Omega Bio-tek) tissue protocol from 150 µL of samples’ material. Cell lysis was performed using beads (Disruptor plate C plus—Omega Bio-tek) and proteinase K for 15 min at 2600 rpm, followed by 10 min at room temperature without agitation, and finished with a DNase I digestion of 20 min at room temperature. RNA was quantified using QuantiFluor RNA kit on Tecan Safire (TECAN). 10 ng total RNA was used for reverse transcription using FIREScript RT cDNA synthesis kit (Solis Biodyne) with random primers, then cDNA was purified with SPRIselect reagent (Beckman coulter) and quantified.The rRNA V1–V3 region was PCR amplified using the 5× HOT BIOAmp® BlendMaster Mix 12,5 mM MgCl 2 (Biofidal), 10× GC rich Enhancer (Biofidal) and BSA 20 mg/mL. The PCR reaction consisted of 30 cycles at 56 °C using the forward primer 27F, 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG AGAGTTTGATCCTGGCTCAG-3′ and reverse primer 534R, 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGATTACCGCGGCTGCTGG-3′ in 25 µL of solution. PCR products were purified using SPRIselect beads (Beckman Coulter) in 20 µL nuclease-free water and quantified using QuantiFluor dsDNA (Promega). Samples were indexed with lllumina’s barcodes with the same PCR reagents during a 12 cycles PCR, then purified and quantified as previously mentioned. Samples were normalized and pooled, then sequenced using Illumina MiSeq V3 Flow Cell following the constructor’s recommendations for a 2 × 300 bp paired-end application. A mean of 130 k proofread reads per sample was obtained.Experiment buffers were used as negative controls to detect contamination by out-of-sample bacterial RNA. RNA extraction was controlled using an in-house mix of live Staphylococcus aureus ATCC29213 and Escherichia coli ATCC25922 in equal proportions, allowing for assessing extraction bias in Gram-positive and -negative bacteria. PCR amplification bias was controlled using a commercial DNA mix of 8 bacterial species (ZymoBIOMICS™ Microbial Community DNA Standard).Bioinformatics and statistical analysesSequencing reads were quality checked and trimmed. Paired-ended read pairs were merged using BBMap version 38.49 (available at https://sourceforge.net/projects/bbmap/), with default options besides a minimum single size of 150 bp with an average Phred quality score higher than 10, and a total pair size of minimum 400 bp. PCR adapters were removed with cutadapt v.2.1 (Martin 2011) then dereplicated using vsearch v.2.12.029 with the sizeout option. For species assignment, reads were aligned to sequences of NCBI blast 16S_ribosomal_RNA database (version date 03.12.2020) using Blastn v.2.11.0+30,31, keeping a maximum of 20 reference targets. Read counts per bacterial species were normalized to account for taxon-specific variations of the copy number of 16S rRNA genes using NCBI rrnDB-5.5 database based on the mean gene copy number in the taxon.To optimize the resolution of sequencing read taxonomic assignment, we used in-house bioinformatic software publicly available at https://github.com/rasigadelab/taxonresolve. Briefly, when a read matches sequences from several species with identical alignment scores, taxonomic assignment pipelines typically output the higher taxonomic level such as the genus (e.g., Staphylococcus spp. when a read matches S. aureus and S. epidermidis). This loss of information can be problematic when species-level discrimination is important. To prevent losing species-level information, the taxonresolve software assigns reads with uncertain species to groups of species rather than to genera.Bacterial species deemed present from contaminating sources such as kits reagents and found in negative controls, mostly from the Bacillus genera, were removed. A total of 1376 species or group of species were retained. The rarefaction curves corresponding to the sequencing effort to assess the species richness within samples are shown in Supplementary Fig. 3. Most samples reached a plateau after 40,000 sequences.Given the small sample size compared to the number of variables and species considered in this study, no hypothesis testing was performed, and we provide a descriptive assessment of the results. In figures, 95% confidence intervals of the means were computed based on normal approximation, after log transformation for CFU/mL and log odds transformation for quantities restricted to the [0, 1] interval, such as proportions.In microbial diversity analyses, we retained the 9 most prevalent bacterial species and pooled the other species into an ‘Others’ category. To assess the disruption and possible recovery of the microbiota, the divergence of sampled microbiota relative to the initial, pre-treatment microbiota (D0) was assessed using the Bray–Curtis dissimilarity at each sampling time point relative to the first sample of the same patient.Software code of the analyses are available at https://github.com/rasigadelab/macotra-metabarcoding. Data are available at https://zenodo.org/record/6382657. Analyses and figures used R software v3.6.032 with packages dplyr33, ggplot234, vegan35, and MicrobiomAnalyst available at https://www.microbiomeanalyst.ca36,37. More

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According to the target of the present study, the mortality incidence on P. nobilis in local populations along the Apulia peninsula (the Southeast coast of Italy) following the MME was assessed. In addition, an investigation on the species distribution and densities in the Adriatic and the Ionian Sea was carried out, which allowed us to build a picture of species populations before the MME.Concerning the P. nobilis distribution in the Apulia region before the MME, unfortunately, there is a lack of information at the wide scale, and literature reports only concern semi-enclosed systems such as the Taranto basins17,18,19 and the Aquatina lagoon20. No large-scale monitoring program on P. nobilis, in fact, has been carried out previously along the Apulian coast, although this kind of surveys is indispensable for the management of a protected species and must become mandatory for a critically endangered species such has become P. nobilis. The present data-gathering, that is aimed to partially address this information gap, based on the monitoring of recently dead specimens, allowed to realize a plausible map of P. nobilis distribution and densities before the MME in 30 areas distributed along the entire Apulian region coast.Along the Ionian coast, recently dead P. nobilis were detected in all the areas studied, highlighting a continuous distribution of the species prior to the MME, differently from the not continuous distribution along the Adriatic coast. The occurrence of P. nobilis was recorded in the areas surveyed in the south, from A7 to A17, but no traces were found along the northernmost areas except for the Tremiti archipelago, suggesting that the northernmost Adriatic coast of the region does not meet the environmental conditions suitable for hosting this species. Nevertheless, in the Gulf of Manfredonia multiple reports from fisherman indicating the presence of the species in a local Cymodocea nodosa meadow before the 1980s, suggest that this area may have been an exception in the past. Therefore, we can assume that excessive fishing and anthropogenic activities in this area are likely to have caused the species to disappear many decades ago.Data regarding the mortality incidence after the MME in Apulian populations is scarce. Panarese et al.11 reported the advent of the disease in Mar Piccolo di Taranto but without describing the disease incidence. In this study, a mortality incidence of 100% in all basins, bathymetric (down to 15 m) and habitat types, was recorded, demonstrating the severity of the situation along the entire Apulian coast, both inshore and offshore, and in lagoon and marine-protected areas.Although the availability of nutrients and the trophic conditions are assumed to be very different between offshore, inshore, and transitional systems, the archipelago of Tremiti islands, located 13 miles away from the coast, showed no differences in mortality incidence from sites along the coast, evidencing the same critical conditions in all environments.Many Mediterranean lagoon systems, including the Ebro Delta, Mar Menor Lagoon in Spain21, the Rhone delta, Leucate and Thau in France22,23,24, Venice, Grado-Marano and Faro in Italy25,26,27, Bizerte in Tunisia24 are considered the last healthy shelters for P. nobilis populations in the Mediterranean Sea22. These systems seem to offer a degree of resistance against the disease and are all characterized by high seasonal fluctuations of environmental parameters, such as temperature and salinity. It has been supposed that the effect of these fluctuations could make these environments less suitable for the spread of the disease and reduce the rate of transmission21,22. In the present study, two lagoon systems were also investigated, but no live specimens were found. These systems are strongly affected by the saltwater intrusion and the freshwater inputs became very low during the dry season. Hence, we can assume that during the summer season, when P. nobilis become susceptible to the disease, no salinity barrier against the pathogen spread persists in these lagoons systems.Considering that the lagoon refuges currently represent the main source of larval production for P. nobilis recruitment22,28, the collapse of these populations confirms the severity of the situation for species conservation. For the Italian coast, the last live populations are those in the lagoons located in the northen Adriatic Sea (Venice and Grado-Marano lagoon). These environments can act as larval exporters for the Adriatic Sea taking advantage of the mobility of the larvae that can spread over hundreds of kms28.Regarding the timeframe of the spread of the MME along the Apulian coast, the first report of the infection dates back to 201818, in the Mar Piccolo di Taranto. Compared to the first MME event observed in the Spanish coast in 20165,7, the disease has spread from the western to the eastern basin of the Mediterranean Sea over a period of 2 years. Our surveys, carried out in 2020, showed that 91% of the shells were still undamaged and with joined valves. Based on the state of conservation of the shells29 it is possible to hypothesize that the death of the specimens was a recent phenomenon that had occurred in Apulia in the two years preceding our surveys, and most probably it should be dated back to 2019.Kersting and Ballesteros30 have suggested that other species, such as P. rudis, could benefit from the collapse of the P. nobilis population. During our surveys, only 5 specimens of P. rudis were found, located in 2 sites, but it must be considered that the survey was carried out only a short time after the MME of P. nobilis. Further studies aimed at assessing an increase in P. rudis in the investigated areas would be of great interest to corroborate this hypothesis.In these surveys, P. nobilis showed transverse distribution among habitat types occurring both in marine and lagoon systems, inside and outside seagrass meadows, on sandy, rocky, and maerl beds substrate. Nevertheless, on a spatial macro (from a few kilometers to tens of kilometers) and mesoscale (from hundreds to thousands of meters), an overlap with the distributional range of seagrass meadows emerges. A clear cross-boundary subsidy trend was evidenced by the data collected on P. nobilis distribution in association with seagrasses. The specimens inside seagrass meadows were almost double than those detected nearby and a gradual decrease was observed with the increase of the distance from the seagrass patches (Fig. 2). This is particularly evident along the northern Adriatic coast of the region, where extended seagrass meadows are absent and, no trace of P. nobilis was encountered, except in the Tremiti archipelago where both P. oceanica meadows and pen shells were found. By contrast, present data reporting P. nobilis as associated with various seagrass species, such as P. oceanica, C. nodosa, and Zostera sp., are consistent with the macroscale and mesoscale association between P. nobilis and seagrass meadows sensu lato and most literature reporting ubiquitous distribution of P. nobilis both in lagoon-estuarine21,22,24,25,26,31 and in marine ecosystems4,7,9,14,16,24.However, regarding their microscale distribution, the pen shells in our surveys were recorded also outside the seagrass meadows boundaries, at times up to 1 km away. Hence, seagrass sheltering can potentially be ruled out as the sole explanatory factor for the distribution pattern of the species. The pattern emerging from this study led us to hypothesize that a trophic link with the seagrass detritus food-chain may explain both the macroscale–mesoscale association with seagrass species and the microscale cross-boundary distribution. In fact, seagrass detritus is highly refractory, since it is largely exported to the nearby areas where it can represent the major food source for other invertebrates32,33,34. This hypothesis is consistent with the stomach contents observations reported by Davenport et al.3 indicating detritus as the bulk component, accounting for 95% of the total ingested material.One of the main factors underlying the distribution pattern in benthic invertebrates is indeed food availability35,36. According to the Ideal Free Distribution (IFD) theory, the individuals in a population disperse to different resource patches within their environment, minimizing competition and maximizing fitness37. When the IFD assumptions are met, the number of individuals who aggregate in patches is proportional to the amount of food resource available in each one. Accordingly, the distribution of large, long life, and sessile organisms such as P. nobilis would be expected to depict the species trophic supply, by analyzing the resources available in those patches.Studies on the seagrass system energy flow have shown that seagrass debris must be fractionated before entering the food chain33. In this way, plant material becomes fine particulates moving in the boundary layer over the sediment–water interface38,39. These processes take time, and while the matter is transported, heterotrophic bacteria grow exponentially, turning it into a high quality and protein-enriched food for consumers. Hence, bacteria adhering to seagrass detritus may play a key role in this benthic food chain and sediment–water interface consumers may incorporate more energy from associated microbes than from the detritus itself32,38. On the basis of these considerations, it is reasonable to hypothesize that the quantity, composition and origin of the suspended particles are regulated by a drift mechanism and that this mechanism may explain local densities of P. nobilis as a response to sinking rates and resuspension effects. This hypothesis explain also the species distribution in systems, characterized by strong dominant current and shallow seabeds where the seagrass detritus can be spread/drift several kilometers away from the meadows. An example of this condition is encountered in the north Adriatic Sea (e.g., Gulf of Trieste) where extensive population of P. nobilis develops on several sink areas even kilometers downstream from the meadows. The assumption of the species’ ability to feed on seagrass detritus, together with the high biomasses reached (large size specimens and high density), lead us to suppose that P. nobilis may play a key role in the processing of matter and in the energy pathway deriving from seagrass detritus in Mediterranean coastal areas. This makes the repercussions of the MME not only a problem of conservation, but also and above all, an ecological-functional issue.We can, therefore, conclude that Mediterranean seagrass meadows not only constitute a habitat for P. nobilis, but probably also a food source through refractory detritus generation which is transferred and transformed outside the meadows. Unfortunately, literature is lacking on this topic and further investigations are needed to define the trophic role and function of these filter feeders in the different seagrass meadows.The density values that emerged were significantly different among basins. In the Adriatic Sea, where all the coastal values were recorded, the densities were consistently lower than those reported in the Ionian Sea, except for the two southernmost areas. In the Adriatic basin, it was also possible to recognize a north-south trend when considering the densities of pen shells in the coastal areas. Although the values recorded along the southern coast of the region were much greater than those recorded in the central coast, they were far lower than those reported by Čižmek et al.40 in the Croatian coast (North Adriatic Sea). Similar values to ours within the same basin were reported by Celebicic et al.41 in Bosnian waters (0.12 individuals/100 m2).On the other hand, in the Ionian areas, the values recorded were consistently >0.1 individuals/100 m2. The values recorded in the Mar Grande di Taranto were higher than those reported by Centoducati et al.17 (0.1–0.7 ind/ha2). From interviews with fishermen, it emerged that illegal trawling in this area has strongly impacted the natural populations of the Mar Grande di Taranto, and a partial reduction of this activity, in recent years could explain the slight increase in density compared to the 2004 survey data17.In interpreting our data, it should be considered that the surveys were carried out employing an extensive sampling protocol conceived to assess wide surface densities on coastal areas investigating across several habitat types. Therefore, literature density values focused only on local areas or habitat patchiness that were not randomly selected must be contextualized when compared with these data. In addition, given the scale of the presented surveys, emphasis must be given to P. nobilis absence data of which the literature appears poor. Indeed, contrary to the data on presence, reliable absence data are difficult to obtain requiring much greater effort to rule out a rare occurrence42. The absence data obtained in this study derive from the merger of two different data types. The first come from the local ecological knowledge obtained from interviews with the local fishermen, which allowed us to confirm our data, excluding spot occurrences in the same areas. Furthermore the interviews allowed us to collect information on a historical series of species presence/absence in the areas, which was helpful to confirm local absence when no P. nobilis specimens were recorded in our surveys. The second derives from the complete vision of divers during the field surveys. Indeed the scuba diver’s view was at least 10 times wider than 50 cm from the side around the rope and hence, the perception of absence can be extended over a much larger surface area investigated. By merging these two sources of information, we can assume that the absence data collected in exhaustive and complete.In conclusion, this study investigated different basins, habitat types, and bathymetries along the Apulian coast. The shells spatial distribution that arise from this study allowed to obtain important information on the species trophic ecology. Indeed, the species distributional pattern showed a strong overlap with seagrass meadows on meso and macro geographical scale, however this was not the case on a micro scale. This result indicates that although there is a strong relationship between P. nobilis and seagrass meadows, it is not limited to the habitat patch but crosses the boundaries of seagrass. This result led us to hypothesize that the distribution of P. nobilis displays a trophic link through the cross-boundary subsidy occurring from seagrass meadows to the nearby habitat, by means of the refractory detrital pathway. However, further investigations taking into account other factors such as hydrodynamics, are needed to investigate this topic.No live specimens of P. nobilis were found in >800 km of coastal line, leading us to the conclusion that the coastal and lagoon population had totally collapsed in the region after the MME. The seriousness of the situation on the Apulian coasts, just as in the other Mediterranean ecoregions, indicates that the MME that began in 2016 is still in progress, and no local population can be considered safe. Given the gravity of the current situation, it is vital for species preservation to extend the survey across the entire Italian coast to gain a overall picture of the status of the P. nobilis population on a national scale. Indeed, other regions may reveal the existence of natural shelters, where live populations of P. nobilis may still persist. If this is the case, it is essential to identify and protect them in time. As already suggested by Kersting et al.9, this initiative should be conducted in parallel by all the nations of the Mediterranean basin to implement standard guidelines for the monitoring, protection, and recovery of this critically endangered species. More

Bacterial density and growth potential in the rearing water were related to the microbial carrying capacityQuantifying the bacterial density in each tank verified that we obtained a higher bacterial load in the systems with added organic material. The bacterial density was, on average, 7.8× higher in the systems with high compared to low bacterial carrying capacity. This difference was particularly evident at 2 (34.8×, Kruskal–Wallis p = 0.0008) and 9 DPH (9.1×, Kruskal–Wallis p = 0.0007) (Fig. 1). The bacterial density increased throughout the experiment for the tanks with low microbial carrying capacity (treatment group MMS−, FTS−), reflecting increased larval feeding and defecation. Contrastingly, the bacterial density was relatively stable over time in the MMS+ treatment and even decreased over time in the FTS+ treatment. When averaging the densities at 11 and 15 DPH within each rearing treatment, we observed that the ‘MMS+ to FTS+’ had a considerable difference in the bacterial density between incoming and rearing water (24.2×). In contrast, this difference was below 8.2× in all other treatment tanks. Such differences in density indicated that some communities were below the microbial carrying capacity of the systems. We thus investigated the growth potential to determine if carrying capacity was reached in the rearing water.Figure 1Bacterial density (million bacterial cells mL−1) at various days post-hatching (DPH) in incoming and rearing tank water. Note that the y-axis is log scaled. Colours indicate the rearing treatment, and shape signifies rearing (filled circle) and incoming water (filled triangle).Full size imageThe bacterial net growth potential in the intake and rearing water was quantified as the number of cell doublings after incubation for 3 days11. Generally, the FTS− and MMS− rearing water had net growth potential with an average of 0.2 and 0.1, respectively (Supplementary Fig. 2). In contrast, the rearing water of the FTS+ and MMS+ had a negative net growth potential with averages of −0.2 and −0.06, respectively. In the case of negative net growth potential, the bacterial density decreased during the incubation. A negative net growth potential suggested that the rearing water bacterial communities were at the tank’s microbial carrying capacity at the time of sampling. Thus, the bacterial communities were at the carrying capacity of the high (+) carrying capacity systems and below in the low (−) systems. To gain a deeper understanding of the bacterial community characteristics the 16S rRNA gene of the bacterial community was sequenced at 1 and 9 DPH.Initial rearing condition did not leave a legacy effect on bacterial α-diversityThe bacterial α-diversity of the rearing water was investigated at 1 and 12 DPH (Fig. 2). At 1 DPH, the richness was comparable between the FTS−, FTS+ and MMS+ treatments, but on average, 1.5× higher for the MMS− treatment (307 vs 205 ASVs, Tukey’s test p  More

PTM concentrationsIn Table 1, the descriptive statistics of PTMs in 50 dust samples from Qom city are described. The background values were used based on the concentrations of metals in the Upper Continental Crust. The mean concentration of As, Cd, Cu, Mo, Pb, Sb, and, Zn exceeded the background value. Also, Cd, Cu, Mo, Pb, Sb, and, Zn had a coefficient of variation (C.V.) greater than 50%, indicating a severe variability in PTMs concentrations in the atmospheric dust of the studied area2. Metals with C.V.  Pb  > Zn  > As  > Cd  > Cu  > Mo  > Cr  > Mn  > Ni = Co. Antimony (38.55) and Pb (35.13) had the highest average EF values, which means they were enriched very high in the windowsill dust. Also, they had a wide range of EF values in the 50 stations: from 4.0 to 227.0 for Sb, and from 8.3 to 140.8 for Pb which might reflect the existence of discrete multiple sources in the studied area. The degree of enrichment for Pb and Sb in the industrial sector was extreme and in the commercial sector was very high; also, the other sectors were significantly enriched. Zinc and As had a more homogenous enrichment in the area. In all the functional sectors, 95% and 84% of stations were significantly enriched by As and Zn, respectively. Copper, Cd, and Mo were moderately enriched in all functional sectors, but the greenspace sector had minimal enrichment by these elements. Some areas in the industrial sector had significant to very high enrichment of Cd. The EF value indicated Co, Cr, Mn, and Ni were minimally enriched in all the stations.Figure 2Box plot of the (a) enrichment factor (EF), and (b) geo accumulation index (Igeo) for the dust samples in the studied area.Full size imageThe highest average values of Igeo were obtained in the order of Pb  > Sb  > As  > Zn. PTMs included Co, Cr, Ni, Fe, and Mn were categorized as unpolluted and Cd, Cu, and Mo were in the category of unpolluted to moderately polluted. In the industrial zone, the windowsill dust was extremely polluted with Sb and Pb. The sequence of contamination intensity with Pb, Zn and Sb according to land use was: industrial  > commercial  > residential  > greenspace. The highest concentration of arsenic in the study area belongs to the industrial area.To evaluate the pollution level based on land use, PLI and mCd indices were utilized (Fig. 3). These cumulative indices showed that the dust in Qom city is considerably contaminated with PTMs. According to the PLI index, all the stations were categorized as polluted sites. The PLIzone values were in the order of industrial (3.77)  > commercial (2.05)  > residential (1.67)  > green space (1.38). This pattern was also repeated with the mCd index. The mCd for the industrial sector ranged from 6.98 (high contamination level) to 39.60 (ultra-high contamination level). In the commercial sector, fifty percent of dust samples were classified as having a high degree of contamination. All the greenspace stations were in the moderate pollution category. This shows the possible effect of tree density in diminishing the risk of dust pollution to the receptors.Figure 3Pollution level indexes (a) mCd and (b) PLI, based on four functional areas.Full size imageSpatial distribution of PTMsThe As, Cd, Cu, Sb, Pb, and Zn content in 100% of the dust samples exceeded the background value. Spatial distribution maps were generated for the hotspot PTMs (As, Sb, Pb, Cd, Cu, Mo and Zn) by applying the inverse distance weighted (IDW) interpolation method (ArcGIS 10.3). Figure 4 demonstrates that PTMs dispersions were slightly influenced by the prevailing wind direction (from the west), suggesting they came from the point- or area- sources. On the other hand, the K–S test showed that the overall distribution of PTMs was not normal in the studied region. This might signify the influence of industrial activities and the presence of multiple sources of dust.Figure 4Spatial distribution maps of seven PTMs in windowsill dusts of Qom, Iran. This map was constructed using ArcGIS version 10.3. (https://www.esri.com/en-us/arcgis/products/arcgisdesktop/overview).Full size imageThe highest pollution load of PTMs belonged to the industrial section. The level of pollution gradually decreased from Shokouhieh to Mahmoudabad industrial zones. The reason is related to more active industries, a closed environment, and more construction existing in Shokouhieh industrial town than in Mahmoudabad industrial town.There is a clear decreasing trend from the central part to southern (downtown area) and southwestern (suburb area) parts of the city. In fact, these parts are diffusely populated and the southwestern part is almost new with lots of barren lands. Copper, Mo, and Cd show high concentrations toward the central part of the city. Educational, cultural and commercial activities are mainly located in the central part of the city. Also, historical and religious districts in the city center are accompanied by a huge influx of tourists throughout the year. For this reason, the central part of the city has various public transportations such as bus stands and taxi stations, and is dominated by a high load of motorcycles.In the eastern part of the city, some hotspots can be observed (Fig. 4). This part includes an important transportation system (like highways and a complex interchange) where exhaust traffic emissions might be a probable source of As, Sb, Pb, and Zn. Unlike Pb and Zn, several peaks of As are scattered in the western part, suggesting an area source might exist in the region. It is noteworthy that the western area is densely populated with lots of residential buildings. Bisht et al. (2022)35 also observed hotspots of As in the residential area of Dehradun, India.PTM potential sourcesTo evaluate the relationship between PTMs in dust samples, the Spearman correlation and PCA were developed (Fig. 5) and more details are given in Table S7. Statistical analysis can help to identify the potential source of contamination in urban dust. The Spearman correlation was significant at p  residential ≈ greenspace. The five PTMs with the highest overall HI are ranked as follows: Pb  > As  > Cr  > Mn  > Sb (Fig. 7). The HI values in all the sections were lower than the permissible level (1.00), except for Pb. In the industrial section, Pb recorded the highest HI value for children (HI = 1.73) which exceeded the acceptable value. The HI values were 10 times higher for children than adults indicating they are more susceptible to PTMs in the dust.The dominant pathway for noncancerous risk was ingestion followed by dermal contact and inhalation. The trend is in line with previous research25,51,52. However, for Co and Mn, the descending order was different as follows ingestion  > inhalation  > dermal contact. The highest contribution of HQinh and HQderm to HI was measured for Co (34.0%) and Cd (29.0%), respectively.In this study, the carcinogenic risk from windowsill dust was estimated for the carcinogens including Cd, Co, Cr and Ni, Pb, and As through the possible routes (Fig. 8, Table S9). The contribution of PTMs to CR decreased in the order of Cr (3.24E−05)  > As (2.05E−05)  > Pb (2.52E−06)  > Co (6.91E−09)  > Ni (1.72E−09)  > Cd (2.58E−10). The average CR values for target PTMs through inhalation ranged from 7.9E−10 to 1.7E−07, which remained in the safety zone (CR  inhalation  > dermal (Fig. 8). While the contribution of Cr to carcinogenic risk was higher through inhalation than ingestion. The reports concluded that the primary exposure route of Cr is inhalation54. Considering the predominant forms of Cr in the environment, CrVI is more toxic than CrIII. Exposure to CrVI can cause immunological diseases, dental effects and carcinogenic effects (lung cancer, nose and nasal sinus cancer, suspected laryngeal and stomach cancers)54,55.The result of health risk from target PTMs in windowsills of Qom indicates significant chronic exposure to Pb can take place for children in the industrial zone. The ingestion route is the most probable pathway for children due to their hand–to–mouth behavior56. Lead can bio-accumulate in the body without any obvious symptoms of toxicity56. The total CR values for Pb, Cr and As in different land-use types were in the range of tolerable carcinogenic risk (1 × 10−4  More