Microorganisms isolated from Saharan dust intrusions in the Canary Islands and processes of mineral atmospherogenesis

Citation: Navarro, A.; del Moral, A.; de Pablos, I.; Delgado, R.; Párraga, J.; Martín-García, J.M.; Martínez-Checa, F. Microorganisms Isolated from Saharan Dust Intrusions in the Canary Islands and Processes of Mineral Atmospherogenesis. Appl. Sci. 2024, 14, 1862. https://doi.org/10.3390/ app14051862 Academic Editor: Paola Grenni Received: 31 January 2024 Revised: 16 February 2024 Accepted: 22 February 2024 Published: 24 February 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). applied sciences Article Microorganisms Isolated from Saharan Dust Intrusions in the Canary Islands and Processes of Mineral Atmospherogenesis Azahara Navarro 1, Ana del Moral 2,* , Irene de Pablos 1, Rafael Delgado 1, Jesús Párraga 1, Juan M. Martín-García1and Fernando Martínez-Checa 2,3 1Department of Soil Science, University of Granada, 18071 Granada, Spain; [email protected] (A.N.); [email protected] (I.d.P.); [email protected] (R.D.); [email protected] (J.P.); [email protected] (J.M.M.-G.) 2Department of Microbiology, University of Granada, 18071 Granada, Spain; [email protected] 3Center for Biomedical Research (CIBM), Institute of Biotechnology, University of Granada, 18071 Granada, Spain *Correspondence: [email protected] Abstract: Global warming due to climate change has increased the frequency of sand and dust storms that affect air quality and ecosystems in general, contributing to air pollution. The Sahara Desert is the most potent emitter of atmospheric dust. The atmosphere is an extreme environment and microorganisms living in the troposphere are exposed to greater ultraviolet radiation, desiccation, low temperatures and nutrient deprivation than in other habitats. The Iberian Peninsula, and specifically the Canary Islands—due to its strategic location—is one of the regions that receive more Saharan dust particles annually, increasing year after year, although culturable microorganisms had previously never been described. In the present work, dust samples were collected from three calima events in the Canary Islands between 2021 and 2022. The sizes, mineralogical compositions and chemical compositions of dust particles were determined by laser diffraction, X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), respectively. Particle morphology and biological features were also studied by scanning electron microscopy (SEM-EDX) and confocal laser scanning microscopy (CLSM). The mineral–bacteria interactions were described from microscopic observations, which revealed the presence of iberulites and small neoformed kaolinite crystals in association with bacteria. This article defines the term “mineral atmospherogenesis” and its variant, “mineral bioatmospherogenesis”, through microbial interaction. This is the first described case of kaolinite produced through mineral bioatmospherogenesis. The bacterial growth in atmospheric dust was illustrated in SEM images, constituting a novel finding. Twenty-three culturable microorganisms were isolated and identified by 16S rRNA sequencing. Members of the phyla Pseudomonadota,Bacillota and Actinomycetota have been found. Some of these microorganisms, such as Peribacillus frigoritolerans, have Plant Growth-Promoting Rhizobacteria (PGPR) properties. Potential human pathogenic bacteria such as Acinetobacter lwoffii were also found. The presence of desert dust and iberulites in the Canary Islands, together with transported biological components such as bacteria, could have a significant impact on the ecosystem and human health. Keywords: extremophiles; Saharan dust; iberulite; atmospherogenesis; Canary Islands; calima; biofilm 1. Introduction The amount of dust originating from desert areas and circulating around the planet has increased over the last few decades [ 1 ]. Numerous studies on Saharan dust and its consequences have sparked a great interest in dust storms and their influence on ecosystems. Desert areas and other arid regions constitute the main source of mineral dust particles in the atmosphere [ 2 ]. The Sahara Desert is the predominant source of mineral dust globally, which can be subsequently spread southwards (60%) and westwards to the Atlantic Ocean (25%), eastwards to the Middle East (5%) and northwards to Europe (10%) [3,4]. Appl. Sci. 2024,14, 1862. https://doi.org/10.3390/app14051862 https://www.mdpi.com/journal/applsci Appl. Sci. 2024,14, 1862 2 of 21 Biological material transported by dust storms deserves special attention. Extreme conditions such as high/low temperatures, high hydrostatic pressures, high salt concentration or high/low pH values define different types of extreme environments, suitable for extremophilic microorganisms [ 5 ]. The atmosphere, despite being the largest biome on Earth, remains one of the least understood environments in terms of microbial activity [ 6 ]. Due to radiation and temperature changes, it is one of the most extreme environments described so far. Some bacteria, fungi and viruses can survive in the atmosphere despite enduring different environmental stressors [7,8]. Microbes attached to dust particles can be transported through the atmosphere and dispersed in exogenous environments [ 9 – 12 ]. The long-range transport of viable bacteria along with mineral aerosols may represent a pathway for bacteria to colonize new environments and alter the existing diversity in remote terrestrial and aquatic habitats [7,13]. Dust intrusions can be accompanied by a characteristic precipitation known as red rain, dust rain, bloody rain, coloured rain or muddy rain [ 14 , 15 ]. Recently isolated culturable microorganisms and other microbial communities have been described in red rain episodes in the southeast of Spain [16]. A striking phenomenon is the occurrence of corpuscles with 50–200 µ m diameters and quasi-spherical morphology, known as iberulites [ 17 ]. Iberulites are typically observed during Saharan dust intrusions in the Iberian Peninsula and the Canary Islands. These particles account for atmospheric “giant” aerosols as they have a low density and a porosity about 50%, covering thousands of kilometres and facilitating the intercontinental transport of spore-forming and viable microorganisms either in their external rind or inside them [ 18 ]. The Canary Islands, situated between 100 and 500 km off the northwest coast of Africa, are often affected by Saharan dust intrusions also known as “calima”, which consist of a mass of hot air or heat haze that can reach much more height than a sandstorm [ 19 ]. Their occurrence is especially remarkable from January to March and the most intense events take place in winter [ 20 ]. Although this phenomenon is very recurrent in the islands, only a few severe episodes are registered per year [ 21 , 22 ]. In February 2020, the archipelago was affected by a severe Saharan dust intrusion that broke the record in regard to intensity since instrumental data came to exist. The objective of this research is to study the microbial communities found in dust particles and iberulites from the Canary Islands. To our knowledge, no studies on culturable microorganisms and mineral–bacteria interactions have been conducted in the Canary Islands. For that reason, dust samples have been collected in order to analyse their microbial diversity, mineralogical compositions and potential geomicrobial connections. This work lays the groundwork for subsequent studies that can shed light on microbial transport patterns and enhance our understanding of extremophilic life within the Earth’s atmosphere. 2. Materials and Methods 2.1. Sampling Site This study was conducted in the municipality of Teror (Gran Canaria, 28◦03′31.6′′ N , 15 ◦ 32 ′ 58.2 ′′ W), located in the Canary Islands (Figure 1). The weather is characterized by prevailing trade winds blowing north to northeast and the influence of the “Canary Current”, which flows in a northeast–southwest direction. The latitude and the weather conditions contribute to a milder-than-normal climate for the islands [21]. Appl. Sci. 2024,14, 1862 3 of 21 Appl. Sci. 2024, 14, x FOR PEER REVIEW 3 of 22 This study was conducted in the municipality of Teror (Gran Canaria, 28°03′31.6″ N, 15°32′58.2″ W), located in the Canary Islands (Figure 1). The weather is characterized by prevailing trade winds blowing north to northeast and the influence of the “Canary Current”, which flows in a northeast–southwest direction. The latitude and the weather conditions contribute to a milder-than-normal climate for the islands [21]. Figure 1. Description of the sampling area. Images retrieved from Google Earth. 2.2. Collection of Dust Dust samples were collected during three different events of Saharan dust intrusions bound to calima episodes (Table 1). For that purpose, we used a glass collector (17.5 cm diameter) previously sterilised in an autoclave (at 121 °C for 20 min). Table 1. Description of dust samples from African sources. Sample Sampling Date Period of the Event PM10 (μg/m 3 ) M1 2 October 21 1–3 October 2021 47.0 M2 6 February 22 1–14 February 2022 65.4 M3 17 April 22 16–19 April 2022 54.3 2.3. Recognition and Selection of Iberulites Sample M1 was initially screened under an Olympus B061 stereomicroscope to examine the content of iberulites. Then, iberulites were separated from the surrounding material and carefully hand-picked with a magnetized needle to avoid breakage. 2.4. Identification of Dust Sources and Characterization of the Events Records of African dust intrusions over the Canary Islands were obtained [23,24] to determine the events registered at the sampling site. Dust surface concentration maps were acquired using the MONARCH model (https://dust.aemet.es/products/daily-dustproducts (accessed on 7 May 2022)) [25,26] to ascertain the source and analyse the distribution of each event. The Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) (https://www.ready.noaa.gov/HYSPLIT.php (accessed on 7 May 2022)) [27] was used to obtain 72 h backward trajectories, with the aim of determining the source region of the air masses bound to each dust intrusion. To that end, we used the vertical velocity model, and the altitude was set to 750, 1500 and 2500 m.a.g.l., respectively. The length of each backward trajectory was measured in Google Earth. The mean PM10 concentration—registered during the sample collection period— bound to each dust event was estimated (Table 1) using data from the “Polideportivo Figure 1. Description of the sampling area. Images retrieved from Google Earth. 2.2. Collection of Dust Dust samples were collected during three different events of Saharan dust intrusions bound to calima episodes (Table 1). For that purpose, we used a glass collector (17.5 cm diameter) previously sterilised in an autoclave (at 121 ◦C for 20 min). Table 1. Description of dust samples from African sources. Sample Sampling Date Period of the Event PM10 (µg/m3) M1 2 October 21 1–3 October 2021 47.0 M2 6 February 22 1–14 February 2022 65.4 M3 17 April 22 16–19 April 2022 54.3 2.3. Recognition and Selection of Iberulites Sample M1 was initially screened under an Olympus B061 stereomicroscope to examine the content of iberulites. Then, iberulites were separated from the surrounding material and carefully hand-picked with a magnetized needle to avoid breakage. 2.4. Identification of Dust Sources and Characterization of the Events Records of African dust intrusions over the Canary Islands were obtained [ 23 , 24 ] to determine the events registered at the sampling site. Dust surface concentration maps were acquired using the MONARCH model (https://dust.aemet.es/products/daily-dust-products (accessed on 7 May 2022)) [ 25 , 26 ] to ascertain the source and analyse the distribution of each event. The Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) (https: //www.ready.noaa.gov/HYSPLIT.php (accessed on 7 May 2022)) [ 27 ] was used to obtain 72 h backward trajectories, with the aim of determining the source region of the air masses bound to each dust intrusion. To that end, we used the vertical velocity model, and the altitude was set to 750, 1500 and 2500 m.a.g.l., respectively. The length of each backward trajectory was measured in Google Earth. The mean PM10 concentration—registered during the sample collection period— bound to each dust event was estimated (Table 1) using data from the “Polideportivo Afonso-Arucas” station, located in the North of Gran Canaria (28 ◦ 06 ′ 41 ′′ N, 15 ◦ 31 ′ 15 ′′ W). The station cited previously belonged to the “Red de Vigilancia y Control de la Calidad del Aire de Canarias” [28]. Appl. Sci. 2024,14, 1862 4 of 21 2.5. Munsell Colour Dust colour was determined using Munsell soil charts. 2.6. Granulometry The particle size distribution of bulk dust dispersed in water was determined by laser diffraction on a Mastersizer 2000LF (CIC, Universidad de Granada). Granulometric results were interpreted using the Mastersizer 2000, v.5.61 software (www.malvernpanalytical.com (accessed on 7 May 2022), Malvern, UK). Analyses were only performed on samples M1 and M2; the quantity required was not obtainable in sample M3. 2.7. Mineralogical Composition Mineralogical composition was determined by XRD diffraction on a Brucker AXS D8 ADVANCE diffractometer equipped with a PILATUS3R 100K-A detector (Bruker, Germany). The measurement parameters were Cu K α radiation, 1.5406 wavelength ( λ ) and an exploration range from 3 ◦ to 75 ◦ 2 θ . XRD diagrams were interpreted using the Xpowder software (Ver. 12) [ 29 ]. Percentages of each mineral phase were estimated from the intensity factors [ 30 – 32 ]. Analyses were only performed on samples M1 and M2; the quantity required was not obtainable in sample M3. 2.8. Surface Chemical Composition Surface chemical composition was obtained by X-ray photoelectron spectroscopy (XPS) on a Kratos Axis Ultra-DLD spectrometer equipped with Al K α source (Kratos Analytical Ltd., Kyoto, Japan). For a wide scan, a pass energy of 160 eV was applied. The binding energies were calibrated with reference to C1s at 284.8 Ev. Spectra were interpreted using CasaXPS v2.3.16 Pre-rel 1.4 software (www.casaxps.com (accessed on 7 May 2022), Casa Software Ltd., Devon, UK). Analysis was only performed on sample M1. 2.9. Microscopy Analyses Iberulites were visualized by confocal laser scanning microscopy (CLSM) on a Leica TCS-SP5 microscope (CIC, Universidad de Granada). Dust material and iberulites were studied through scanning electron microscopy, employing a GEMINI (FESEM) CARL ZEISS apparatus equipped with EDX-OXFORD10 (CIC, Universidad de Granada). To enhance the visualization of bacteria, samples were initially subjected to treatment with a solution of 2.5% glutaraldehyde in a 0.1 M cacodylate buffer, followed by 1% osmium tetroxide. Subsequently, they were subjected to dehydration with alcohol, dried through the critical point method and eventually coated with carbon, as previously described [ 33 ]. Measurements of maximum diameter were made using the images, with IC Measure v.2.0.0.286 software (The Imaging Source, Bremen, Germany). 2.10. Isolation of Culturable Microorganisms For the study of culturable microorganisms, dust particles were deposited on plates with 10% Trypticase Soy Agar (TSA) medium and incubated at room temperature. The serial dilution method was used for the isolation of microorganisms, and a preliminary identification was carried out by Gram staining. 2.11. Identification of Isolated Culturable Microorganisms Isolated culturable microorganisms were identified by partial sequencing of the 16S rRNA gene. The “DNA Xtrem” kit was employed to extract DNA. Subsequently, universal bacterial primers, 16F27 and 16R1492, were utilized for PCR amplification. The resulting PCR products were then purified using the X-DNA purification kit (QIAquick PCR Purification Kit 250). Direct sequence determination of PCR-amplified DNA was carried out with the ABI PRISM dye-terminator, cycle-sequencing, ready-reaction kit (Perking-Elmer) and an ABI PRISM 377 sequencer (Perking-Elmer), according to the manufacturer’s instructions. The Appl. Sci. 2024,14, 1862 5 of 21 obtained sequences were visualized using Chromas 2.6.6 software (Chromas) and were compared to reference 16S rRNA gene sequences available in the GenBank, EMBL and DDBJ databases through the BLAST search [34] and the EzBioCloud server [35]. 3. Results 3.1. Identification of Dust Sources Linked to Calima Episodes The three dust events studied (samples M1–M3) were bound to African dust intrusions (Table 1and Figure 2). Sample M1 travelled the longest distance (around 1824 km), followed by samples M3 and M2 (Table 2). PM10 concentration during each event was variable, ranging from 47.0 to 65.4 µg/m3(Table 1). Appl. Sci. 2024, 14, x FOR PEER REVIEW 5 of 22 sal bacterial primers, 16F27 and 16R1492, were utilized for PCR amplification. The resulting PCR products were then purified using the X-DNA purification kit (QIAquick PCR Purification Kit 250). Direct sequence determination of PCR-amplified DNA was carried out with the ABI PRISM dye-terminator, cycle-sequencing, ready-reaction kit (Perking-Elmer) and an ABI PRISM 377 sequencer (Perking-Elmer), according to the manufacturer’s instructions. The obtained sequences were visualized using Chromas 2.6.6 software (Chromas) and were compared to reference 16S rRNA gene sequences available in the GenBank, EMBL and DDBJ databases through the BLAST search [34] and the EzBioCloud server [35]. 3. Results 3.1. Identification of Dust Sources Linked to Calima Episodes The three dust events studied (samples M1–M3) were bound to African dust intrusions (Table 1 and Figure 2). Sample M1 travelled the longest distance (around 1824 km), followed by samples M3 and M2 (Table 2). PM10 concentration during each event was variable, ranging from 47.0 to 65.4 μg/m 3 (Table 1). Table 2. Lengths of the backward trajectories (km). Data obtained from Google Earth. Sample Height 750 m 1500 m 2500 m Mean M1 1997.14 1670.67 1803.3 1823.70 M2 1813.57 1498.48 1417.04 1576.36 M3 1591.13 1301.58 2238.93 1710.55 (A) M1 M2 M3 (B) M1 M2 M3 Figure 2. Identification of the dust source of the events associated with each sample: M1, M2 and M3. (A) Dust concentration maps (MONARCH model, dust surface concentration μg/m 3 ). (B) Backward trajectories (at different altitudes): 750 m (red), 1500 m (blue) and 2500 m (green). Figure 2. Identification of the dust source of the events associated with each sample: M1, M2 and M3. (A) Dust concentration maps (MONARCH model, dust surface concentration µ g/m 3 ). (B) Backward trajectories (at different altitudes): 750 m (red), 1500 m (blue) and 2500 m (green). Table 2. Lengths of the backward trajectories (km). Data obtained from Google Earth. Sample Height 750 m 1500 m 2500 m Mean M1 1997.14 1670.67 1803.3 1823.70 M2 1813.57 1498.48 1417.04 1576.36 M3 1591.13 1301.58 2238.93 1710.55 3.2. Colour of Dust Samples Shades (hue) were variable according to Munsell notation (Table 3). Sample M1 belonged to 7.5YR; samples M2 and M3 corresponded to 10YR. The percentage of red pigment (5R–100%, 5YR–50% and 5Y–0%) ranged from 25% to 37.5%, with the major proportion detected in sample M1. Lightness (value) and saturation (chroma) showed a Appl. Sci. 2024,14, 1862 6 of 21 descending trend, since both attributes were higher in sample M1 (5/3.5) and decreased in samples M2 (4/2.5) and M3 (3/2). Table 3. Colour of dust samples (M1–M3). Sample Notation Name Hue Hue% red Value Chroma M1 7.5YR 5/3.5 Brown 7.5YR 37.5 5 3.5 M2 10YR 4/2.5 Dark greyish brown 10YR 25.0 4 2.5 M3 10YR 3/2 Very dark greyish brown 10YR 25.0 3 2 Mean 29.2 4.0 2.7 3.3. Particle Size Distribution of Dust Samples Mean granulometric results showed that dust samples were mainly composed of 59% silt (2–50 µ m), 34% sand (50–2000 µ m) and 7% clay (<2 µ m) (Table 4). The mean PM2.5 and PM10 contents were around 7% and 24%, respectively. Table 4. Granulometry (%). Samples M1 and M2. Sample Clay (<2 µm) Silt (2–50 µm) Sand (50–2000 µm) M1 10.3 70.3 19.4 M2 4.6 47.9 47.6 Mean (n= 2) 7.4 59.1 33.5 Sample M1 (Figure 3), proximate to a complex Gauss bell, has a bimodal distribution, with a main peak in the silt fraction (15–20 µ m) and a secondary peak in the sand fraction (350–500 µ m). Sample M2 (Figure 3) shows a unimodal distribution, with a main peak in the sand fraction (60–90 µ m); it also hints at a secondary peak in the sand fraction (300–600 µm). Appl. Sci. 2024, 14, x FOR PEER REVIEW 6 of 22 3.2. Colour of Dust Samples Shades (hue) were variable according to Munsell notation (Table 3). Sample M1 belonged to 7.5YR; samples M2 and M3 corresponded to 10YR. The percentage of red pigment (5R–100%, 5YR–50% and 5Y–0%) ranged from 25% to 37.5%, with the major proportion detected in sample M1. Lightness (value) and saturation (chroma) showed a descending trend, since both attributes were higher in sample M1 (5/3.5) and decreased in samples M2 (4/2.5) and M3 (3/2). Table 3. Colour of dust samples (M1–M3). Sample Notation Name Hue Hue% red Value Chroma M1 7.5YR 5/3.5 Brown 7.5YR 37.5 5 3.5 M2 10YR 4/2.5 Dark greyish brown 10YR 25.0 4 2.5 M3 10YR 3/2 Very dark greyish brown 10YR 25.0 3 2 Mean 29.2 4.0 2.7 3.3. Particle Size Distribution of Dust Samples Mean granulometric results showed that dust samples were mainly composed of 59% silt (2–50 μm), 34% sand (50–2000 μm) and 7% clay (<2 μm) (Table 4). The mean PM2.5 and PM10 contents were around 7% and 24%, respectively. Table 4. Granulometry (%). Samples M1 and M2. Sample Clay (<2 μm) Silt (2–50 μm) Sand (50–2000 μm) M1 10.3 70.3 19.4 M2 4.6 47.9 47.6 Mean (n = 2) 7.4 59.1 33.5 Sample M1 (Figure 3), proximate to a complex Gauss bell, has a bimodal distribution, with a main peak in the silt fraction (15–20 μm) and a secondary peak in the sand fraction (350–500 μm). Sample M2 (Figure 3) shows a unimodal distribution, with a main peak in the sand fraction (60–90 μm); it also hints at a secondary peak in the sand fraction (300– 600 μm). Figure 3. Particle size distribution. Samples: M1 (green) and M2 (red). Statistical parameters related to the particle size distribution (Table 5) revealed that the mean diameter of dust particles was around 65 μm. Both samples show a leptokurtic distribution (kurtosis > 3; mean = 11.083) and are positively skewed (skewness > 0; mean = 3.073). Figure 3. Particle size distribution. Samples: M1 (green) and M2 (red). Statistical parameters related to the particle size distribution (Table 5) revealed that the mean diameter of dust particles was around 65 µ m. Both samples show a leptokurtic distribution (kurtosis > 3; mean = 11.083) and are positively skewed (skewness > 0; mean = 3.073). Table 5. Statistical parameters related to particle size distribution. Statistics Mean (µm) Standard Deviation (µm) Kurtosis Skewness M1 45.593 87.938 15.500 3.723 M2 83.256 103.569 6.666 2.422 Mean (n= 2) 64.425 95.754 11.083 3.073 Appl. Sci. 2024,14, 1862 7 of 21 The maximum diameter of iberulites (n= 23) was measured (Figures 6 and 7). The mean size was approximately 110 µm, ranging from 50.9 to 193.5 µm. 3.4. Mineralogical Composition Dust samples (M1, M2) were composed of the following mineral phases (Table 6and Figure 4): phyllosilicates (clay minerals and chlorite), tectosilicates (quartz, k-feldspar and plagioclase), carbonates (calcite and dolomite), iron oxides (haematites) and gypsum. Phyllosilicates (39–59%) and tectosilicates (32–41%) were the main constituents. Carbonates (5–15%), iron oxides (4–5%) and gypsum (<1%) were present in minor proportions. Other mineral phases belonging to the group of clay minerals were qualitatively identified (Figure 4): smectite, palygorskite, illite, kaolinite and mixed-layer clay minerals. Table 6. Mineralogical composition (%). Sample Gy CM * Chl Qz Fd-K Pl Ca Do OxFe M1 <0.1 58 1 22 6 4 2 3 4 M2 <1 37 2 22 13 6 11 4 5 Mean (n= 2) <0.1 48 2 22 10 5 7 4 5 Legend: gypsum (Gy), clay minerals (CM), chlorite (Ch), quartz (Qz), K-feldspar (Fd-K), plagioclase (Pl), calcite (Ca), dolomite (Do), iron oxides (OxFe). * CM: smectite (Sm), palygorskite (Pal), illite (Ill), paragonite (Pa), kaolinite (Ka) and mixed-layer clay (MLC). Appl. Sci. 2024, 14, x FOR PEER REVIEW 7 of 22 Table 5. Statistical parameters related to particle size distribution. Statistics Mean (μm) Standard Deviation (μm) Kurtosis Skewness M1 45.593 87.938 15.500 3.723 M2 83.256 103.569 6.666 2.422 Mean (n = 2) 64.425 95.754 11.083 3.073 The maximum diameter of iberulites (n = 23) was measured (Figures 6 and 7). The mean size was approximately 110 μm, ranging from 50.9 to 193.5 μm. 3.4. Mineralogical Composition Dust samples (M1, M2) were composed of the following mineral phases (Table 6 and Figure 4): phyllosilicates (clay minerals and chlorite), tectosilicates (quartz, k-feldspar and plagioclase), carbonates (calcite and dolomite), iron oxides (haematites) and gypsum. Phyllosilicates (39–59%) and tectosilicates (32–41%) were the main constituents. Carbonates (5–15%), iron oxides (4–5%) and gypsum (<1%) were present in minor proportions. Other mineral phases belonging to the group of clay minerals were qualitatively identified (Figure 4): smectite, palygorskite, illite, kaolinite and mixed-layer clay minerals. Table 6. Mineralogical composition (%). Sample Gy CM * Chl Qz Fd-K Pl Ca Do OxFe M1 <0.1 58 1 22 6 4 2 3 4 M2 <1 37 2 22 13 6 11 4 5 Mean (n = 2) <0.1 48 2 22 10 5 7 4 5 Legend: gypsum (Gy), clay minerals (CM), chlorite (Ch), quartz (Qz), K-feldspar (Fd-K), plagioclase (Pl), calcite (Ca), dolomite (Do), iron oxides (OxFe). * CM: smectite (Sm), palygorskite (Pal), illite (Ill), paragonite (Pa), kaolinite (Ka) and mixed-layer clay (MLC). Figure 4. XRD diagrams. Samples M1 and M2. Figure 4. XRD diagrams. Samples M1 and M2. 3.5. Surface Chemical Composition The XPS spectrum of sample M1 (Figure 5and Table 7) revealed that the main constituents were O (47.97%), Si (16.03%) and C (15.64%); Al (7.45%) was detected in an intermediate proportion. Some elements such as Fe (4.40%), Ca (2.33%), Na (1.56%), Mg (1.37%) and K (1.01%) were found in minor proportions; N, Cl, S, Zn and P were present in trace amounts (<1%). Appl. Sci. 2024,14, 1862 8 of 21 Appl. Sci. 2024, 14, x FOR PEER REVIEW 8 of 22 3.5. Surface Chemical Composition The XPS spectrum of sample M1 (Figure 5 and Table 7) revealed that the main constituents were O (47.97%), Si (16.03%) and C (15.64%); Al (7.45%) was detected in an intermediate proportion. Some elements such as Fe (4.40%), Ca (2.33%), Na (1.56%), Mg (1.37%) and K (1.01%) were found in minor proportions; N, Cl, S, Zn and P were present in trace amounts (<1%). Table 7. Surface chemical composition (% mass concentration). Sample M1. C O N Ca Si Na Mg Al Cl S P K Fe Zn 15.64 47.97 0.96 2.33 16.03 1.56 1.37 7.45 0.57 0.27 0.16 1.01 4.4 0.27 Figure 5. XPS survey spectrum. Sample M1. 3.6. Microscopy Analyses Iberulites were visualised by CLSM for the first time, with this being a novel technique unemployed in the literature until now. Figure 6 shows a group of iberulites with an average diameter of approximately 115 μm, with their characteristic vortex being visible in some of them. Single red fluorescent particles distributed over iberulites’ surfaces indicate the existence of organic material. Figure 5. XPS survey spectrum. Sample M1. Table 7. Surface chemical composition (% mass concentration). Sample M1. C O N Ca Si Na Mg Al Cl S P K Fe Zn 15.64 47.97 0.96 2.33 16.03 1.56 1.37 7.45 0.57 0.27 0.16 1.01 4.4 0.27 3.6. Microscopy Analyses Iberulites were visualised by CLSM for the first time, with this being a novel technique unemployed in the literature until now. Figure 6shows a group of iberulites with an average diameter of approximately 115 µ m, with their characteristic vortex being visible in some of them. Single red fluorescent particles distributed over iberulites’ surfaces indicate the existence of organic material. Appl. Sci. 2024, 14, x FOR PEER REVIEW 9 of 22 Figure 6. Confocal laser micrographs of non-stained iberulites (87.1–193.5 μm). The organic material shows slightly high red autofluorescence. The vortex is visible in most of them, although it appears expanded and distorted because of the loss of coherence, due to the preparation for observation. A quasi-spherical iberulite of around 50 μm diameter was observed by SEM-EDX (Figure 7). We identified some typical features such as the vortex (Vr) and the external rind, the latter being partially covered by a biofilm (BF) and some filaments (Figure 8). Figure 7. Iberulite of 50.94 μm diameter and quasispherical morphology, observed in a sideways position. The orifice of vortex (Vr) is not visible. Figure 6. Confocal laser micrographs of non-stained iberulites (87.1–193.5 µ m). The organic material shows slightly high red autofluorescence. The vortex is visible in most of them, although it appears expanded and distorted because of the loss of coherence, due to the preparation for observation. Appl. Sci. 2024,14, 1862 9 of 21 A quasi-spherical iberulite of around 50 µ m diameter was observed by SEM-EDX (Figure 7). We identified some typical features such as the vortex (Vr) and the external rind, the latter being partially covered by a biofilm (BF) and some filaments (Figure 8). Appl. Sci. 2024, 14, x FOR PEER REVIEW 9 of 22 Figure 6. Confocal laser micrographs of non-stained iberulites (87.1–193.5 μm). The organic material shows slightly high red autofluorescence. The vortex is visible in most of them, although it appears expanded and distorted because of the loss of coherence, due to the preparation for observation. A quasi-spherical iberulite of around 50 μm diameter was observed by SEM-EDX (Figure 7). We identified some typical features such as the vortex (Vr) and the external rind, the latter being partially covered by a biofilm (BF) and some filaments (Figure 8). Figure 7. Iberulite of 50.94 μm diameter and quasispherical morphology, observed in a sideways position. The orifice of vortex (Vr) is not visible. Figure 7. Iberulite of 50.94 µ m diameter and quasispherical morphology, observed in a sideways position. The orifice of vortex (Vr) is not visible. Appl. Sci. 2024, 14, x FOR PEER REVIEW 10 of 22 Figure 8. Detail of the upper image, of the field marked with a rectangle (Figure 7). The iberulite surface is partially covered by a dark, mucilagenous biofilm (BF) in formation and some filaments (marked with ellipses). The mineralogical composition of dust (Table 6) was also corroborated by SEM-EDX. A quartz grain of around 20 μm with evidence of aeolian modelling is displayed in Figure 9. Figure 9. Mineral grain with a diameter of 21.71 μm. Chemical composition: 1. EDX, Si, O, Al (quartz). The roundness observed is due to wind erosion (aeolian modelling). The surface is covered by quite nano-sized particles, some of them with ellipsoidal morphologies which resemble possible bacteria. Figure 8. Detail of the upper image, of the field marked with a rectangle (Figure 7). The iberulite surface is partially covered by a dark, mucilagenous biofilm (BF) in formation and some filaments (marked with ellipses). Appl. Sci. 2024,14, 1862 16 of 21 exopolysaccharides, which may act as cement, co-adjuvant or, in other words, as an aggregating substance for agglomeration; a biofilm (Figure 8). (4) The last piece of evidence would account for bacterial participation in the processes of atmospherogenesis in mineral dust. We understand “mineral atmospherogenesis” as the genesis of minerals within the atmosphere. When the action or presence of living beings is needed for mineral genesis, it is known as “mineral bioatmospherogenesis”. The case shown in Figure 12 (also observed in Figure 11) is remarkable. It suggests atmospheric biotic participation in the neoformation process of kaolinite, a clay mineral commonly found in supergene environments. This fact has been observed for the first time here and will require further research, but if confirmed, it would be classified as “mineral bioatmospherogenesis”. The role of bacteria, as possible inductors of kaolinite neoformation, might imply the release of organic compounds (some of them acid). Then, bacteria would facilitate the hydrolysis of some primary aluminosilicate mineral particles and the subsequent neoformation of Al and Si gels (protokaolinite), which turn into authentic kaolinite sheets through growth. Likewise, these sheets would merge and encapsulate bacterial cells, as illustrated in the images. Until now, mineral synthesis and kaolinite neoformation processes had only been described in some modern natural environments and laboratory experiments [ 59 – 62 ]. These processes had never been described in the atmosphere and let alone, mediated by atmospheric microbiota via a process known as bacteria-induced mineral [ 63 – 65 ] precipitation [ 66 ]. Other organic compounds present in dust—not necessarily microbial—might collaborate in the atmospherogenesis of kaolinite, being that their presence was previously proved in the elemental surface composition (XPS) (Table 7). 4.7. Description of Culturable Microbial Communities Microorganisms are ubiquitous in the environment, and the atmosphere is no exception. However, airborne bacterial communities remain relatively unexplored. Enhancing our understanding of these communities and the mineral composition of dust particles is crucial for comprehending the impact on biodiversity and health. In total, 23 culturable microorganisms were isolated, being mostly present in samples M2 (ncm = 14) and M3 (ncm = 6) (Figure 13). In contrast, sample M1 showed the lowest number (ncm = 3). As previously stated, sample M1 not only had a finer granulometry, but also the longest backward trajectory compared to sample M2 (Tables 2and 4and Figure 2). The major distance travelled might imply a major dust elevation from the soil on the ground, causing a bacterial deprivation. Furthermore, the backward trajectory’s length, corroborated by the wind speed, would justify the residence time in the atmosphere, compatible with the time needed for bacterial growth (Table 2). Prior studies revealed that the bacterial abundance depended on dust granulometry [ 63 – 65 ]. The major abundance corresponded to sample M2, with its coarser granulometry and minor percentage of clay minerals (Tables 4and 6, Figures 3and 4). Stern et al. (2021) [ 65 ] observed a higher bacterial abundance in coarse particles (particles > 10 µ m), likely being derived from local sources. In our case, the highest bacterial abundance bound to the coarser granulometry might be attributed to the atmospheric dust genesis, considering the minor distance from soil. Thus, bacteria would travel attached to mineral particles or inside polymineral aggregates with strategic microsites suitable for bacterial growth. The visualisation of bacteria over the surface of mineral particles, as well as the geomicrobial interactions observed by SEM-EDX, would support these statements (Figures 7–12). Particle size had also an influence on the airborne bacterial communities. Some studies found that spore-forming microorganisms were more abundant in large particles, whereas viable microorganisms were mostly present in particles of reduced size [ 63 , 64 ]. Additionally, Stern et al. (2021) [ 65 ] reported a major abundance of pathogens in fine particles ( particles < 2.5 µm ), which can be suspended in air for a longer period of time. Appl. Sci. 2024,14, 1862 17 of 21 Therefore, fine particles pose a threat to human health due to their biological content and respirable size. In total, 19 out of 23 isolated culturable microorganisms were identified by 16S RNAr sequencing (Table 8). The identified microorganisms belonged to Pseudomonadota,Bacillota and Actinomycetota, being consistent with the dominant phyla in other dust studies [ 9 , 65 , 67 ]. Pseudomonadota (nmc = 6) was the predominant phylum in sample M2, followed by Bacillota (nmc = 4) and Actinomycetota (nmc = 2). On the other hand, sample M3 showed the same proportions in each phylum. Sample M1 was represented by only one microorganism belonging to Bacillota, corroborating its low bacterial abundance. Most of the identified microorganisms had previously been isolated from soil samples, with some of them being described as extremophiles. Bacteria with beneficial effects on plants, such as Plant Growth-Promotion Rhizobacteria (PGPR), were detected in our samples. Peribacillus frigoritolerans, isolated for the first time in arid soils from Morocco, is an extremophilic microorganism, involved in soil bioremediation, with a promising PGPR activity [ 68 – 70 ]. Bacillus safensis subsp. safensis and Paenarthrobacter nitroguajacolicus possess PGPR properties that may be potentially viable even in extreme environments due to their tolerance to harsh conditions [ 71 , 72 ]. On the other hand, Pseudomonas alloputida and Pseudomonas hunanensis have PGPR properties and are also efficient in soil bioremediation [ 73 , 74 ]. Pseudomonas hunanensis and Peribacillus frigoritolerans were previously isolated in samples of Sahara dust plumes deposited as red rain in the southeast of Spain [16]. Plant and animal pathogens were found among the identified species. Pantoea endophitica has recently been described as a plant pathogen, causing bacterial rot in tobacco plantations [ 75 ]. Sanguibacter inulinus and Sanguibacter keddieii are potential animal pathogens which were first isolated from blood in apparently healthy cows [76,77]. Bacteria with detrimental effects on human health were also isolated from our samples. Acinetobacter lwoffii and Niallia circulans are pathogen strains involved in human infections and especially in immunodeficient patients [ 78 , 79 ]. Similarly, Micrococcus luteus,Enterobacter cancerogenus and Pseudescherichia vulneris are opportunistic pathogens that cause infections in humans [ 80 , 81 ]. Interestingly, Acinetobacter lwoffii was also identified in Saharan dust collected in Greece (the eastern Mediterranean) [63]. There is a pressing need for more extensive, long-term studies to elucidate the observed variations in airborne microbial communities worldwide. Given the current scenario of global climate change and the potential impact of microorganisms on recipient ecosystems (such as public health and agronomy), it is essential to foster new scientific advancements and collaborative alliances. This will enable us to investigate the transport and viability of specific microbes through diverse atmospheric routes and evaluate their persistence over time. 5. Conclusions and Closing Remarks The Canary Islands are frequently affected by Saharan dust intrusions, owing to their proximity to North Africa, making them an ideal location for atmospheric dust sampling. Culturable microorganisms and their mineral–bacteria interactions were studied for the first time in Saharan dust collected during three calima events (2021–2022) in Gran Canary Island (close to Morocco). Iberulites—a singular type of giant quasi-spherical particle generated in the troposphere, with a diameter between 50 and 200 µ m—were identified during the events. Bacterial colonies and biofilm were observed in the mineral particle surfaces and in the iberulites. The atmospheric dust constitutes an authentic medium for bacterial growth, a novel finding evinced in the SEM images. For the first time, a process of neoformation of nanometric kaolinite crystals mediated by microorganisms has been described in the atmosphere, which has been limited to laboratory studies until now. Twenty-three culturable microorganisms were isolated and identified by 16S rRNA sequencing. Members of the phyla Pseudomonadota, Bacillota and Actinomycetota have been Appl. Sci. 2024,14, 1862 18 of 21 found. Some species have shown beneficial effects in plants (Peribacillus frigoritolerans), whereas others are potential pathogens for human health (Acinetobacter lwoffii). Calimas in the Canary Islands are natural phenomena, which are not controllable, nor is it possible to reduce them. The prevention and control of these phenomena should be approached from the novel and holistic perspective of “One Health”, which recognises that human health is closely linked to animal and environmental health. Our work can contribute to a better understanding of their effects on the population and ecosystems. Many new microbiomes undoubtedly await description, such as the aerobiome, and its emerging study may represent one of the major challenges of the future. Author Contributions: Methodology, A.d.M., R.D. and J.P.; software, A.N., J.M.M.-G. and F.M.-C.; formal analysis, A.N., I.d.P. and F.M.-C.; investigation, A.N., A.d.M., R.D., J.P., J.M.M.-G. and F.M.-C.; data curation, A.d.M., R.D., J.P., J.M.M.-G. and F.M.-C.; writing—original draft, A.N., A.d.M., R.D. and J.P.; visualization, J.M.M.-G. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data are contained within the article. Acknowledgments: The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and the READY website (https://www.ready.noaa.gov (accessed on 7 May 2022)) used in this publication. Dust surface concentration images were provided by the WMO Barcelona Dust Regional Center and the partners of the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) for Northern Africa, the Middle East and Europe. Conflicts of Interest: The authors declare no conflicts of interest. References 1. Rodríguez-Arias, R.M.; Rojo, J.; Fernández-González, F.; Pérez-Badia, R. Desert dust intrusions and their incidence on airborne biological content. review and case study in the iberian peninsula. Environ. Pollut. 2023,316, 120464. [CrossRef] 2. Zender, C.S.; Miller, R.L.; Tegen, I. 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