Sampling of aerial bioaerosols was conducted in four ecologically and anthropogenically distinct rural microresidences within a 10 km radius of Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India. The sites were also chosen strategically to represent agricultural, tribal, domestic, and commercial environments with diverse land-use characteristics that affect air quality and microbial communities. Angel Garden, Karuny Nagar (10.9386768 N, 76.7530944 E), was selected as the agricultural location. It is a crop-based area with minor structural enhancement and open-field exposure. In the tribal location, the Trishul Shelters, Boluvampatti, and Sadivayal (10.9391838 N, 76.7299982 E), a low-density tribal settlement on the fringe of the forest, with natural vegetation and minimal anthropogenic activities impacting the microbial air composition.

The domestic site was located near Nandangarai Dam, Boluvampatti (10.9322942°N, 76.7273448°E) and consisted of a small residential cluster with livestock feedstock, providing a microenvironment characterized by household emissions and organic matter. The commercial site was situated along Siruvani Main Road, Karunya Nagar (10.9383783°N, 76.7418690°E), a roadside business zone with continuous vehicular traffic and elevated pedestrian activity, serving as a hub of anthropogenic aerosol generation. Satellite world views were documented on January 17, 2025, and April 6, 2025, to capture seasonal conditions at the study locations visually. These contrasting temporal snapshots provided the environmental framework for assessing seasonal variability in airborne bacterial and fungal bioaerosols.

Airborne microbial sampling was conducted during two distinct seasons to capture temporal variability in bioaerosol concentrations. The number of observations (duplicate samples per site per season) was selected to match field feasibility, standard bioaerosol sampling protocols, and equipment availability. The design allowed controlled seasonal contrasts despite limited replication. All samples were collected outdoors, 1.5 m above ground. Indoor activities (e.g., cooking, livestock feeding) may contribute to outdoor microbial loads; however, the sampling was conducted strictly outdoors. Climatic variables (temperature and relative humidity) were recorded during sampling for comparison. Sampling followed a systematic, fixed-point approach, with duplicate runs conducted at predetermined coordinates within each microenvironment. The winter sampling was carried out on January 17, 2025, under ambient conditions of 29 °C temperature and 54% relative humidity. The summer sampling was conducted on April 6, 2025, when the temperature was 35 °C and the relative humidity was 49%. These two seasonal points were selected to represent typical cool–dry and hot–dry climatic conditions of Coimbatore’s rural belt.

In each of the four study locations, bioaerosol collection was conducted using standardized procedures to ensure the reproducibility and reliability of the data. The air was sampled with a calibrated MicroBio MB1 air sampler that uses impaction to collect airborne microorganisms onto agar media. All samplings were done around the same time of day to reduce variability and at a consistent sampling time, which corresponds to the human breathing zone. At both sites and across seasons, a sample was collected twice to account for site-specific variation. The open Petri dishes were covered with parafilm, placed in insulated containers, and transported to the microbiology laboratory within 2 h of sampling to avoid desiccation or contamination. The protocol ensured that a consistent determination of seasonal effects on airborne microbial load was possible and that the measure was consistent across locations. This process generated similar datasets for winter and summer by controlling volume, height, and sampling duration, followed by analysis of bacterial and fungal community structure and AMR profiles.

The MicroBio MB1 air sampler (Cantium Scientific, United Kingdom), a single-stage impactor specifically designed to quantify airborne microorganisms in the atmosphere and clinical practice, was used to sample airborne organisms. The working principle is that the instrument passes a specified amount of air through a perforated lid and directs the particles onto the surface of an agar plate, enabling enumeration of viable airborne bacteria and fungi. All runs were scaled to a volume of 0.2 m³ (200 L), which is appropriate for recovering culturable microorganisms without overloading the agar surface. The sampler was set at 1.5 m above ground level, which is within the approximate human breathing zone, making it relevant to respiratory exposure measurements. The instrument was placed on a tripod to reduce interference and vibration by the operator during sampling. There was consistency in sampling time across sites and seasons, following the manufacturer’s operating protocols, resulting in the best recovery rates. The standard 90 mm Petri dish size used by the MB1 gave a real area of exposure of the sample during a sampling run of ∼28.3 cm². Agar plates and sampler heads were sterilised before going to the field to avoid cross-contamination between sites. Precision and reproducibility were achieved by using the MicroBio MB1 at all sampling sites, and calibration of the instrument against known airflow rates provided a reliable method for converting colony counts to airborne microbial concentrations of colony-forming units per cubic meter (CFU m⁻³).

The air sampler was mounted on a tripod at 1.5 m above the ground, in the human breathing zone, at each of the four study sites during both sampling seasons. A total of 24 sampling events were conducted across the four study locations (three events per site). For each sampling event, microbial enumeration was performed using four bacterial plates and four fungal plates, and CFU/m³ values were calculated from the average colony counts obtained from the duplicate plates. Sterile 90 mm Petri dishes, filled with suitable culture media, were fitted onto the MicroBio MB1 air sampler before activation. Enumeration of total culturable bacteria was performed using Nutrient Agar (NA), and selective recovery of fungi was performed using Potato Dextrose Agar (PDA) supplemented with antibacterial agents. For each site, duplicate runs were performed to improve reproducibility and account for micro-scale spatial variability. Each run collected 0.2 m³ of air, yielding a total of 0.4 m³ per site per season. The effective surface area exposed to the impaction head during each run was approximately 28.3 cm², ensuring uniform particle deposition across the agar surface.

Immediately after air exposure, Petri plates were carefully sealed with parafilm to prevent post-sampling contamination and transported to the laboratory in insulated boxes maintained under cool conditions. The transport time from the field to the laboratory was kept to 2 h to preserve microbial viability for accurate quantification. This standardized procedure enabled direct comparison of bacterial and fungal loads across sites and seasons while ensuring consistency in sampling height, air volume, and plate handling. By maintaining rigorous aseptic conditions and duplicate sampling, the methodology provided reliable data for seasonal and spatial assessment of rural airborne bioaerosols.

Following sample collection, exposed agar plates were incubated under standardised conditions to facilitate the enumeration of viable airborne bacteria and fungi. For bacterial cultures, plates containing NA were incubated at 37 °C for 24–48 h. Colony growth was monitored, and counts were recorded either manually or using a digital colony counter. For fungal cultures, PDA plates were incubated at 25 °C for 3–7 days. To account for variation in fungal growth rates, colonies were recorded at both Day 3 and Day 7, ensuring accurate quantification of both fast- and slow-growing fungi.

The microbial concentrations were expressed as colony-forming units per cubic meter of air (CFU m⁻³). This was calculated by multiplying the number of colonies per plate by a standard conversion factor of 5, corresponding to a sampled air volume of 0.2 m³ per run. The use of duplicate plates per site and season ensured the reliability and reproducibility of results. CFU/m³ values were calculated using the average colony count from duplicate plates for each sampling event.

In addition to enumeration, morphologically distinct colonies were subcultured onto fresh media to obtain pure isolates for further characterisation. Bacterial colonies were streaked onto NA plates, while fungal colonies were transferred onto PDA plates. The streak-plate method was employed to ensure single colony isolation, enabling subsequent characterisation and identification of the predominant airborne microorganisms.

Pure isolates obtained from subculturing were subjected to standard staining techniques for preliminary characterization. For bacterial isolates, Gram staining was performed. Thin smears of bacterial culture were prepared on clean glass slides, heat-fixed, and sequentially stained with crystal violet, Gram’s iodine, 95% ethanol, and safranin. The slides were observed under oil immersion at 1,000× magnification using a compound microscope. This procedure allowed the determination of cell morphology (cocci or bacilli) and Gram reaction (positive or negative). For fungal isolates, Lactophenol Cotton Blue (LPCB) staining was employed. Small fragments of fungal mycelium were placed on a glass slide, treated with LPCB stain, and covered with a coverslip. The preparations were examined under light microscopy at 400× magnification to visualise structural features, including hyphae, conidiophores, spore arrangement, and septation patterns. These staining methods provided the morphological basis for further molecular identification of the isolates.

Superior isolates of bacteria and fungi were identified by MALDI-TOF Mass Spectrometry (MS). The study was conducted in Microbiological Laboratories, R.S. Puram, Coimbatore, Tamil Nadu, India, using a FLEX-PC Microflex mass spectrometer. New colonies were then selected and inoculated onto a MALDI target plate. All samples were spotted on a suitable matrix solution to ease ionisation. The ready target was then placed in the MALDI-TOF system. The spectral fingerprints of each isolate were compared with the instrument reference database to identify isolates at the species level, enabling fast, reliable analysis. The reason for choosing this method is that it offers high throughput, culture-based accuracy, and reproducibility, making it appropriate for differentiating airborne microbial isolates from environmental samples.

The susceptibility of bacteria and fungi to antimicrobial agents was assessed using the Kirby-Bauer disc diffusion test, according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI, 2025) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST). AST was performed only on dominant isolates identified by MALDI-TOF: Bacillus cereus, Bacillus flexus, Staphylococcus spp. (bacteria), and Aspergillus spp., Penicillium spp. (fungi). For bacterial isolates, overnight cultures were prepared and standardized to 0.5 McFarland turbidity. The bacterial suspension was spread evenly on Mueller-Hinton Agar (MHA) using a sterile cotton swab. The agar surface was inoculated antiseptically with antibiotic discs containing chloramphenicol (30 µg), tetracycline (30 µg), ciprofloxacin (5 µg), and erythromycin (15 µg). The plates were incubated at 37 °C for 24 h, after which the areas of inhibition (ZOI) were measured in millimeters using a digital Vernier scale.

For fungal isolates, spores were picked in sterile saline containing Tween-80 and diluted to a 0.5 McFarland standard. The suspension was uniformly swabbed on both PDA and RPMI agar plates. Antifungal discs that were tested consisted of itraconazole (10 µg), amphotericin B (20 µg), clotrimazole (10 µg), and fluconazole (25 µg). The plates were incubated at 25 °C–30 °C for 48–72 h, and the zones of inhibition were measured in millimeters. This standardized assay allowed the evaluation of susceptibility and resistance patterns of airborne bacterial and fungal isolates to the most commonly used antibiotics and antifungals, yielding reproducible, comparable results across locations and seasons. This study focused on phenotypic resistance patterns; genetic determinants of resistance (e.g., mecA, erm, β-lactamase genes) could not be assessed. We acknowledge that genetic assays would provide deeper insight into horizontal gene transfer and environmental mechanisms of AMR.

Table 1 gives the CFU concentrations of bacteria and fungi recorded across the four microenvironments during the winter season. Bacterial concentrations were consistently higher than fungal levels at all sites, with commercial areas showing the maximum load of 880 CFU m⁻³, followed by tribal with 635 CFU m⁻³, domestic with 410 CFU m⁻³, and agricultural zones with 370 CFU m⁻³. Fungal concentrations were comparatively lower, with the tribal area recording the highest value of 115 CFU m⁻³, followed by domestic (80 CFU m⁻³⁾, agricultural (70 CFU m⁻³⁾, and commercial sites (35 CFU m⁻³⁾. These values indicate that winter air quality in rural Coimbatore is dominated by bacterial aerosols, particularly in locations with greater human activity.

Table 1 also gives the CFU values recorded during the summer season. A general decline in bacterial concentrations was observed compared with winter, except in the domestic environment, where bacterial counts rose sharply to 720 CFU m⁻³, the second-highest among the studied zones. Commercial areas continued to exhibit the highest bacterial concentrations (785 CFU m⁻³), followed by tribal (515 CFU m⁻³) and agricultural sites (315 CFU m⁻³). In contrast, fungal concentrations exhibited more pronounced site-specific increases in summer. Domestic zones recorded the maximum fungal load (120 CFU m⁻³), while tribal areas remained relatively high (90 CFU m⁻³). Agricultural sites showed moderate fungal levels (45 CFU m⁻³), and commercial regions registered the lowest (10 CFU m⁻³).

From both tables, three consistent trends are evident. First, higher bacterial concentrations confirmed their dominance in rural airborne microbial communities. Second, commercial zones emerged as the bacterial hotspots, maintaining the highest loads in both winter and summer. Third, fungal concentrations exhibited seasonal variation, with tribal areas showing winter peaks and domestic areas reaching summer maxima (Bowers et al., 2013). These observations confirm the influence of seasonal and microenvironmental factors on airborne microbial distribution and highlight the significance of commercial and domestic sites in determining overall microbial exposure risks in rural Coimbatore.

Gram staining of bacterial isolates collected from the four rural microenvironments consistently demonstrated the predominance of Gram-positive organisms, which retained the crystal violet stain and appeared purple under oil immersion (Figure 1). These isolates were identified as either cocci or bacilli, with site-specific and seasonal variations in abundance and arrangement that reflected the environmental characteristics of each location. Bacterial isolates from the tribal site were small Gram-positive bacilli with scattered cocci, which are usually found in clumps and short chains. Their morphology and staining pattern are similar to those of the Bacillus cereus, a sporing bacterium that can withstand changing environmental conditions in forest-bordering rural areas. Their ecological plasticity is evidenced by their survival in winter and summer, highlighting their adaptability to both highly fertile soils and low-activity environments. Agricultural isolates showed a higher proportion of long Gram-positive bacilli, singly positioned, and fewer cocci in short chains. These characteristics are common to Bacillus pumilus and B. cereus, as confirmed by MALDI-TOF. Crop residues, soil organic matter, and agricultural activity largely determine their presence. Comparison of summer and winter revealed a slight increase in staining intensity and bacillary population density in summer, which higher microbial growth rates can explain during warmer, drier seasons (Bekhit et al., 2025).

The commercial location showed the most heterogeneous and densely populated areas when observed under a microscope. Gram-positive cocci, frequently in groups like those of Staphylococcus, with some scattered bacilli, dominated the winter. Both cocci and bacilli were found in equal numbers in summer, with an evident increase in concentration. This morphologic heterogeneity is consistent with the increased CFU counts observed at commercial sites. It could be explained by increased human activity, motorised emissions, and the resuspension of dust particles carrying human-related bacteria. A seasonal shift was present in domestic samples. Gram-positive cocci dominated the fields in winter, forming clusters, a pattern typical of Staphylococcus and Micrococcus species, which are common in the critical human environment and on the skin. Conversely, the summer samples showed a more mixed profile, with cocci persisting, but bacilli of varying lengths were also present. The greater diversity can also be associated with higher humidity and poor ventilation in rural houses, creating an environment where microbes can survive and thrive (Almatawah et al., 2022; Rakshith et al., 2025).

LPCB staining provided clear visualisation of the hyphal and conidial structures of airborne fungi isolated from the rural microenvironments, confirming the predominance of filamentous fungi belonging to the genera Aspergillus and Penicillium, along with site-specific differences in sporulation intensity and morphology as shown in Figure 2. In the agricultural samples, long, septate hyphae with dense branching and well-developed conidiophores were observed, indicative of Penicillium oxalicum and Aspergillus species. Their morphology reflects the strong soil–crop association of agricultural bioaerosols, where organic matter supports fungal growth (Lone, 2025). In commercial environments, LPCB staining revealed compact spore heads and rough conidiophores characteristic of Penicillium citrinum and Aspergillus parasiticus. The dense sporulation observed here is consistent with higher dust and vehicular activity, which favour the dispersal of spores into the atmosphere.

Domestic samples presented a mixed fungal profile. Winter isolates exhibited smaller spore clusters with limited branching, while summer isolates showed more abundant sporulation, with Aspergillus parasiticus being dominant (Andersson Aino et al., 2022). The increased hyphal density and sporulation in summer suggest that indoor humidity and ventilation constraints strongly enhance fungal persistence in residential environments. In tribal sites, LPCB staining highlighted conidial heads typical of Aspergillus terreus, with roughened conidiophores and spherical conidia (Henß et al., 2022). These structures were more pronounced in summer, reflecting the suitability of forest margins and humid surroundings for fungal proliferation. Seasonal comparison across all sites showed that winter isolates often had thinner hyphae and weaker sporulation, whereas summer isolates consistently exhibited abundant, mature conidiophores and denser spore arrangements.

Representative MALDI-TOF spectra of bacterial isolates from the four rural environments are shown in Figures 3a–d. Each spectrum produced reproducible peak clusters primarily within the 3,000–12,000 m/z window, which is characteristic of ribosomal proteins and suitable for species-level microbial identification. Distinct differences in spectral fingerprints were observed between sites, highlighting spatial variation in airborne microbial composition. The domestic environment spectrum, as given in Figure 3a, displayed its dominant peaks at 3,444.1, 4,293.9, 5,252.8, 6,665.2, 7,466.8, 9,950.3, and 11,129.7 m/z. The most intense signal was recorded at 5,252.8 m/z, with an amplitude of 1.08 × 10⁴ a. u. The presence of secondary high-mass peaks at 12,275.6 and 15,405.9 m/z further confirmed the protein complexity of the isolate. This fingerprint matched Rhodococcus rhodochrous, a species often associated with soil and dust particles that can infiltrate indoor environments (Singhal et al., 2015).

The commercial site spectrum, as shown in Figure 3b, exhibited a distinct profile dominated by peaks at 4,334.4, 5,170.6, 6,710.3, 7,766.6, and 9,639.3 m/z. Among these, the most intense peak occurred at 6,710.3 m/z, with an amplitude of 1.24 × 10⁴ a. u., which is a defining marker of Bacillus flexus. The strong dominance of the 6,700 m/z region distinguishes this isolate from others, reflecting its adaptation to outdoor environments with high human and vehicular activity. The relatively narrow cluster of peaks compared to domestic isolates indicates a lower protein diversity, which is typical of spore-forming Bacillus species well adapted to survive in fluctuating air conditions of commercial roadsides. The agricultural spectrum, as illustrated in Figure 3c, showed high-intensity peaks at 3,120.3, 4,337.8, 5,175.3, 5,941.4, 6,324.6, 7,371.3, and 7,774.5 m/z, with an additional peak at 9,218.0 m/z. The most prominent signals were observed at 4,337.8 and 5,175.3 m/z, each exceeding 1.0 × 10⁴ a. u. These markers are consistent with Bacillus cereus, which has been repeatedly associated with soil, crop residues, and agricultural aerosols. The broad distribution of peaks, particularly those between 5,900 and 7,700 m/z, reflects the ribosomal heterogeneity of this species. Its consistent presence in farming zones can be explained by the constant release of spores during soil-plant interactions, making B. cereus a dominant airborne bacterium in agricultural landscapes. The tribal environment spectrum, as depicted in Figure 3d, red showed a different pattern, with significant peaks recorded at 3,342.5, 4,336.2, 5,173.0, 6,681.7, 7,565.6, 7,770.1, and 9,212.7 m/z, along with higher-mass peaks at 10,432.2, 10,497.2, and 15,132.3 m/z. The most prominent peak was observed at 6,681.7 m/z, with an amplitude of ∼6.8 × 10³ a. u. The profile again corresponded to Bacillus cereus, confirming its ecological resilience across both agricultural and tribal sites. The presence of additional peaks above 10,000 m/z indicates the protein complexity of these isolates, consistent with the influence of the natural forest margins surrounding the tribal settlements.

The MALDI-TOF MS fingerprints obtained in this study are consistent with previously published environmental spectral profiles. Earlier work has shown that airborne and soil-associated Bacillus spp. typically display dominant ribosomal protein peaks within the 3,000–12,000 m/z range, matching the spectral window observed in our isolates (Ha et al., 2019). Similarly, characteristic spectral markers of the Rhodococcus spp. reported in environmental aerosols support our species-level assignments (De Alegría Puig et al., 2017). Among airborne fungi, Aspergillus species are known to produce reproducible peptide/protein signatures in this same mass range, consistent with our fungal spectral clusters (De Carolis et al., 2012). Incorporating these comparisons strengthens the reliability of our MALDI-TOF–based identification and confirms that the protein spectral patterns observed in rural air are consistent with established environmental microbial profiles.

The fungal isolates exhibited reproducible spectral clusters primarily within the 3,000–15,000 m/z region, in agreement with published fungal MALDI-TOF MS spectral windows (Chalupová et al., 2014).

This study has several limitations. First, sampling was conducted on a single winter and a single summer day, providing seasonal contrasts but not long-term temporal trends. Multi-year or repeated within-season sampling would improve generalizability. Second, culture-based enumeration does not capture VBNC organisms or the full spectrum of environmental microbial diversity. Third, MALDI-TOF identification relies on available database spectra and may miss rare or unculturable ecological taxa. Fourth, the AMR assessment was limited to phenotypic disc diffusion without genetic confirmation of resistance determinants. Fifth, we acknowledge that a larger sample size and more extensive spatial replication would enhance generalizability. However, logistical and resource constraints restricted sampling to two seasonal snapshots. Plate-wise raw colony count data from each sampling round were not available for retrospective inclusion due to the completed nature of the study, and this is acknowledged as a methodological limitation. Finally, contextual variables such as antibiotic usage patterns in livestock, agricultural practices, and wind-driven dispersal were not measured but could influence spatial AMR patterns. These limitations should be addressed in future One Health bioaerosol studies.