Characterization, Accumulation Profiles, and Antibiotic-Resistance of Bacteria on Worn Disposable Masks at Githurai Market in Nairobi County, Kenya

Abstract

The widespread use of masks in the community was occasioned by the COVID-19 global pandemic. This study examined bacterial contamination on surgical and face masks used in Githurai Market during daily activities, focusing on the sources, accumulation, and antibiotic resistance of bacteria. Sixteen respondents were selected to wear masks, from which bacteria were isolated from the inside and outside surfaces, as well as from swabs of their nose, mouth, and skin. The bacterial load was monitored at intervals of 0 h, 2 h, 4 h, and 6 h using culture-dependent methods. The identified bacteria included Staphylococcus, Klebsiella, Stenotrophomonas, Enterococcus, and Bacillus, amongst others sourced from the users’ mouth, skin, nose, and the environment. Bacterial accumulation increased with time, peaking at 6 h of mask use. Most of the bacteria isolates showed multidrug resistance to commonly used antibiotics including cefotaxime, streptomycin, and amoxicillin. This raises concerns about potential role of masks as reservoirs for pathogenic and antibiotic-resistant bacteria. The study emphasizes the need for better mask hygiene practices to reduce microbial contamination and the risk of spreading antibiotic-resistant bacteria. It also highlights the importance of developing strategies to address these risks and ensure the continued effectiveness of masks as a part of public health measures

1. Introduction

The rapid global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the resulting coronavirus disease 2019 (COVID-19) pandemic led to urgent efforts to prevent the viral transmission. The most traditional and reasonable method to prevent respiratory infections is to wear face masks, and several research groups have demonstrated its effectiveness against the respiratory viral transmission before the COVID-19 pandemic. During the COVID-19 pandemic, increasing lines of evidence supported the effectiveness of wearing face masks against SARS-CoV-2 and the droplets. However, the World Health Organization (WHO) claims that face masks are effective only when used with hand hygiene, the proper use, and disposal of masks.

Despite a wealth of research on the protective power of face masks against viral transmission, little is known about the hygienic concerns associated with mask use. The standard mask usage is disposable non-woven masks. In some cases, however, people may use non-woven masks repeatedly or use different types of masks in different situations depending on their socioeconomic status, such as lower total income and access challenges, leading to scarcity of masks.

The short supply of non-woven masks led to the repeated use of disposable non-woven masks and the use of other types of face masks, such as handmade masks and polyurethane masks. Even after the shortage of mask supply had been resolved, some people have used disposable non-woven masks repeatedly or other types of face masks [1].

Studies have reported the existence of bacterial contamination on masks in experimental and clinical settings; however, scanty findings have been documented on what and how many bacteria adhere to masks used daily in community setting bases, and this is a neglected hygiene issue under the COVID-19 pandemic [1].

Surgical and face masks were recommended PPE for use to reduce community transmission of the disease. Surgical masks are made of three layers that are spun-bound–melt-blown–spun-bound as compared to face masks that are made of two layers that are spun-bound [2]. Previously, the primary purpose of masks was to protect patients from contamination by bacterial or viral infections from healthcare workers [3]. Surgical masks are made with different thicknesses and layers, and this determines their different abilities to prevent contact with liquids and particulate matter. They may be effective as a fluid barrier and filtration of droplets from coughs or sneezes [4]. On the other side, face masks may not meet the efficiency in filtration levels, as they do not filter very small particles in the air transmitted through coughing and sneezing. Surgical masks and face masks do not provide complete protection from microbes, such as viruses, bacteria, and other contaminants, due to the loose fit between the surface of the mask and the wearer’s face [5].

Generally, it is assumed that the use of disposable face and surgical masks is safe. However, there is limited information to confirm the safety of these masks against microbial contaminations. Improper touching and handling of the masks, as well as loose fitting between the face and masks, exposes the mask to pathogenic bacteria from the environment [6]. Nevertheless, populations have had limited knowledge of proper mask use, handling, and disposal. Putting on masks for an extended period exposes the person to secondary infections. In addition, human saliva and exhaled breath are a source of pathogenic bacteria. These pose a biosafety and health concern to wearers of the masks.

The widespread use of masks during the COVID-19 pandemic may have contributed to the emergency and re-emergence of multidrug-resistant microorganisms [7]. Improper disposal of surgical masks to the environment is a public health biosafety concern, as some of the bacteria present in the masks are pathogenic with antibiotic-resistant genes. This improper disposal of used masks to the environment creates a cycle where antibiotic-resistant genes get into soils and plants consumed by animals. This, in turn, is passed to humans through the consumption of the plant food and animal products [8]. Therefore, this study hypothesized that worn face masks have diverse antibiotic-resistant microbes, which increase on prolonged use of the masks.

Since masks can be a direct source of infection to the respiratory tract, digestive tract, and skin, it is crucial to maintain their hygiene to prevent bacterial and fungal infections that can exacerbate COVID-19. Therefore, in this study, following a survey of 16 volunteers on their mask usage, we aimed to quantify and identify the bacteria attached to face masks by culturing microbes isolated from masks.

The study aimed to determine the bacteria accumulation profile, identify and characterize antibiotic-resistant bacteria on disposable surgical and face masks, and determine their sources.

2. Materials and Methods

2.1. Site Description

The study was carried out at Githurai market in Nairobi, Kenya. It is one of the largest open-air and busy markets known mostly for selling food products, amongst other trades; is located in the Roysambu constituency in Nairobi county along the Thika superhighway; and houses over 1500 traders and vendors. The area is 15 km from the city center and lies on the latitude 1°12′11″ S and longitude 36°55′02″ E.

2.2. Sampling of Respondents

Sixteen respondents were recruited by simple random sampling and were assigned masks purposively. The respondents were then educated on the research study. The inclusion criteria consisted of those who were 18 years of age and above, those who gave consent to participate in the study, respondents with no history of pre-existing conditions, and respondents that worked for more than six hours.

2.3. Sample Collection

Before the respondents wore the mask, at 0 h, samples from the masks and swabs from the respondents’ mouth, nose, and skin were collected and put in sterile zip lock bags, sealed, and put in a cool box. The respondents then each wore a mask for 2 h, and after, the masks were collected from the respondents, carefully put in a zip lock bag, and put in a cool box then transported to Kenyatta University microbiology lab for isolation of bacteria. The respondents wore the masks on differential periods of 4 h and 6 h on different days, the masks were collected from them, and bacteria was subsequently isolated from them.

2.4. Enumeration of Bacteria on Worn Masks

The inner and outside parts of the masks were carefully cut and separated and put into a 50 mL flask containing sterile isotonic solution made of 0.9% NaCl, shaken well, and left to soak for a while. A volume of 0.1 mL of the sample solution was cultured by spread plating on nutrient agar and incubated for 24 h at 37 °C. The colonies on nutrient agar following incubation were counted to determine the CFUs using a colony counter on the inside and outside part of the mask to quantify the bacteria and its accumulation over time after 0 h, 2 h, 4 h, and 6 h [5].

2.5. Isolation of Bacteria from Masks

One ml of sample solution was inoculated in nutrient broth and incubated for 24 h at 37 °C. The mask inoculum was then cultured by streak plating on blood agar and incubated at 37 °C for 24 h. The colony morphology of bacteria from blood agar was described, and bacteria colonies obtained from the blood agar were then plated on nutrient agar for 24 h at 37 °C. Sequentially, the bacterial colony morphological features on nutrient agar were described and recorded after 24 h. The swabs collected from the nose, skin, and mouth were carefully cut aseptically, put into nutrient broth, and incubated for 24 h at 37 °C. The swab inoculum was streaked on blood agar and incubated for 24 h at 37 °C, and the colony morphology was recorded. The colonies were then transferred to nutrient agar, and further identification was described after incubation at 37 °C for 24 h. The isolated cultures were then purified and stored properly.

2.6. Identification and Characterization of Bacteria from Worn Masks

The microbes from blood agar were sub-cultured on nutrient agar to obtain pure cultures, and the plates were incubated for 24 h at 37 °C in aerobic conditions. The morphological characteristics of pure cultures on blood agar were described based on hemolysis, and those on nutrient agar were described based on shape, color, margin, and size. Gram stain was done on them to identify the morphology of the bacteria under a microscope [9]. Routine biochemical tests were done on the isolated pure cultures of the bacteria to further determine their identities like nitrate test, oxidase test, catalase test, coagulase test, SIM (Sulfur Indole Motility) test, MIU (Motility Indole Urease) test, TSI (Triple Sugar Iron) test, MR-VP (Methyl Red–Voges–Proskauer) test, citrate test, bile esculin test, and urease test. The isolated cultures were also tested for carbohydrate fermentation to different sugars to test for acid and gas production, including glucose, galactose, lactose, mannitol, dulcitol, sucrose, and maltose, amongst others.

2.7. Molecular Characterization

The genomic DNA from the pure isolates culture was extracted using a robust universal method for extraction of genomic DNA of bacterial species using the CTAB method [10]. The extracted DNA was then mixed with loading dye and run through 0.8% gel electrophoresis for 45 min at 100 V to check for the quality of the bands visualized under UV trans illuminator, and a photograph of them was taken and recorded. The DNA was stored at −20 °C for further analysis.

The isolated DNA was subjected to Polymerase Chain Reaction (PCR) for amplification using the Thermofisher 2X protocol. The targeted segment was amplified using universal primers 27F (5′ AGAGTTTGATCTTGGCTCAG 3′) and 1492R (5′ TACGGTTACCTTGTTACGAC 3′) for 16S rRNA [11]. To confirm the success of the amplification process, 3 µL of the PCR product was mixed with loading dye and loaded onto 1% agarose gel containing SYBR Green (Thermofisher Scientific, Waltham, MA, USA) and subjected to gel electrophoresis for 30 min at 100 V. The bands were then visualized under a UV trans illuminator and documented by taking a photograph.

The obtained PCR product was purified and subjected to 16S rRNA sequencing by Sanger sequencing using an automated machine for genome sequence analysis in Inqaba Biotech in Pretoria, South Africa. For sequencing, 27F and 1492R primers were used. The sequences were trimmed by Chromas for low-quality deletion, cleaned, and consensus sequences created using BioEdit 7.0.9 software, and the sequences obtained were compared with sequences in the National Centre for Biotechnological Information (NCBI) GenBank database using Basic Local Arrangement Search Tool (BLAST) program. The evolutionary history of the isolates was presented in a neighbor-joining phylogenetic tree drawn using MEGA software (version 11).

2.8. Antibiotic Susceptibility Testing

The isolated pure bacterial cultures were subjected to antibiotic susceptibility testing (AST) using standard antibiotic discs containing different antibiotics like ampicillin, streptomycin, spectinomycin, cefotaxime, amoxicillin, and sulfran. The Kirby–Bauer disk diffusion method was used to test whether they are sensitive, intermediate, or susceptible [12]. This was determined by measuring zones of inhibition using a metric ruler and comparing it against the CLSI standards.

2.9. Data Analysis

The differences and similarities in morphological and biochemical characteristics of isolated bacteria were coded in Excel and imported to Python software version 3.11 and used to cluster the isolates based on their morphology and different biochemical uses. In addition, the significant difference in bacterial accumulation between mask type and time was analyzed using two-way ANOVA at p < 0.05, and Tukey’s Honest Significance Difference (HSD) test was used to separate the means in SAS software version 9.0. The sequence obtained from Sanger sequencing in the molecular analysis was cleaned using BioEdit 7.0.9 software and blasted on the NCBI database, similar sequences were obtained and aligned through multiple sequence alignment, and the data were used to draw a phylogenetic tree using MEGA software version 11. The isolated bacteria colonies were analyzed for antibiotic sensitivity with reference to the disk diffusion method using antibiotic disks to test whether they are resistant (R), intermediate (I), or susceptible (S) and compared against CLSI standards. The significant difference in antibiotic sensitivity of the bacteria to different antibiotics was analyzed using one-way ANOVA at p < 0.05, and Tukey’s HSD test was used to separate the means in SAS software version 9.0.

3. Results

3.1. Isolation of Bacteria

A total of 30 bacterial isolates were recovered from worn surgical masks, worn face masks, nose, mouth, and skin and grouped based on different morphological characteristics to create the morph groups.

3.2. Morphological Identification

In Figure 1, the morphological descriptors that largely helped to cluster the isolates were Gram stain, shape, opacity, hemolysis, and size. Based on morphometric identification, isolate SD8 resembled Bacillus subtilis, isolate SD1 was identical to Staphylococcus aureus, and isolate SD35 had the same features as Enterobacter cloacae. The bacteria isolates had different colors ranging from yellow, white, cream, cream white, beige, pale white, and orange. For instance, isolate SD28 was yellow, SD12 cream white, SD46 orange, and SD20 pale white. The shape margin was either irregular or regular with isolates SD24, SD23, and SD19 having irregular margins while SD56, SD20, and SD49 having regular margins. The isolates showed different hemolysis, including alpha, gamma, or beta hemolysis. Isolate SD28 and SD46 showed beta hemolysis, SD48 gamma hemolysis, and SD19 alpha hemolysis. In opacity, the isolates were either opaque or translucent, with most being opaque and SD2O being translucent. The size of the isolates was either small, medium, or large. Finally, the gram stain and cell shape of the isolates were gram +ve rods, gram +ve cocci, gram –ve rods, or gram –ve cocci. Most of the isolates were Gram-positive rods with irregular shape margins and opaque (Figure 1) (Supplementary Table S1). The isolates clustered in two major clades and various subclades, whereas the isolates with significant diversity in color clustered into different clades, including isolates SD20 and SD49 that were closely related to Streptococcus pneumoniae clustered in Clade I. Isolates SD23 and SD8 that were closely related to B. subtilis clustered in Clade II.

3.3. Biochemical Identification

The biochemical tests that helped to cluster the isolates in Figure 2 were the TSI test, SIM test, MIU test, oxidase, catalase, urease, nitrate reductase, MR-VP test, and bile esculin test. Based on the TSI test, bacteria that had acid/acid (yellow slant/yellow butt) reaction indicated that they are lactose or sucrose fermenters, while those that had alkali/acid (red slant/yellow butt) reaction indicated that they were glucose fermenters. The lactose fermenters included isolates in groups SD31, SD60, SD8, SD4, SD21, SD38, and SD53, amongst others. The glucose fermenters included isolates in groups SD52, SD6, SD45, SD18, SD58, and SD30. Isolate SD53 among the lactose fermenters produced gas, while isolate SD60 produced hydrogen sulfide. Isolate SD3 among the glucose fermenters produced gas, while isolates SD52, SD6, SD39, SD3, and SD19 produced hydrogen sulfide.

Moreover, the SIM test was used to test for the ability of an organism to reduce sulfur, produce indole, and be motile. Isolates in groups SD31, SD8, SD60, SD1, and SD52 reduced sulfur to hydrogen sulfide, while isolates in groups SD60, SD8, SD21, SD38, SD53, and SD19 produced indole, and isolates in groups SD1, SD60, SD12, SD28, and SD56, amongst others, were motile.

An MIU test was done for the detection of urease activity, motility, and indole production. Isolates in groups SD31, SD8, SD60, SD38, SD53, SD19, and SD3 were urease-indole-positive. The majority of the isolates were urease-positive except for isolates in groups SD6, SD45, SD18, SD58, SD49, and SD56.

In addition, a nitrate reductase test was done to determine the reduction of nitrate to nitrite or to nitric oxide, as well as nitrous oxide or nitrogen gas by nitrate reductase enzyme produced by some bacteria. Isolates in all morphological groups did not produce gas except SD60, SD53, SD39, SD3, SD19, SD28, and SD30, amongst others, that reduced nitrate to nitrite.

Additionally, a methyl red (MR) test was done to determine the ability of bacteria to utilize glucose and convert it to stable organic acids such as lactic acid through the mixed-acid pathway. Most of the isolates were MR-positive except isolates in groups SD53, SD5, SD6, SD18, SD1, and SD35, which were MR-negative. A Voges–Proskauer (VP) test was done to determine the ability of bacteria to produce acetyl methyl carbinol from glucose fermentation. Isolates in groups SD38, SD53, SD18, SD49, SD1, SD52, SD39, and SD3 were VP-positive, while the rest were negative.

A urease test was done to determine the ability of bacteria to hydrolyze urea to ammonia and carbon dioxide. Most isolates were urease-positive except SD19, SD24, SD36, SD12, SD49, and SD46. Furthermore, a citrate test that tested for the ability of organisms to utilize citrate as the only source of carbon was also done. The majority of the isolates tested citrate-positive, except isolates in groups SD31, SD4, SD21, SD38, SD19, SD3, SD20, SD56, SD46, and SD35.

In addition, for the catalase test, all isolates were catalase-positive except isolates in groups SD49 and SD20. A coagulase test was done to identify pathogenic Staphylococcus species. Isolates from morphological groups SD49 and SD20 were coagulase-positive. Furthermore, an oxidase test that was used to differentiate between the families of Pseudomonadaceae (Ox+) and the Enterobacteriaceae families (Ox−) was also done, and a majority of the isolates were oxidase-negative apart from isolates SD53, SD12, and SD25 that were oxidase-positive.

Finally, the bile esculin test was based on the ability of certain organisms to hydrolyze esculin in the presence of bile, and based on this test, majority of the isolates were positive except for isolates in groups SD31, SD8, SD60, SD48, SD36, SD20, SD56, SD28, SD23, SD12, and SD1 (Supplementary Table S2).

These are shown in Figure 2.

Carbohydrate Fermentation Biochemical Test

The different bacterial isolates were tested for their ability to utilize different sugars, including arabinose, rhamnose, fructose, glucose, sucrose, mannose, mannitol, dulcitol, sorbitol, lactose, galactose, raffinose, and maltose. The results were presented as positive or negative for acid and gas production, as shown in Figure 3. The majority of the isolates utilized different sugars, with fructose (93.6%) being utilized the most by bacterial isolates and dulcitol (61.3%) being utilized the least by bacterial isolates. In addition, other sugars were utilized by the different bacteria isolates as follows: glucose (87.1%), galactose (77.4%), mannose (87.1%), mannitol (83.9%), sorbitol (71.0%), arabinose (87.1%), lactose (64.5%), raffinose (64.5%), sucrose (90.3%), and maltose (90.3%).

Based on the sugar fermentation, the bacteria isolates clustered into two main clades. In Clade 1, the majority of the isolates were positive for maltose, sucrose, mannose, fructose, lactose, and dulcitol. The isolates included SD48, SD23, SD2, and SD12, among others. Moreover, the isolates had similar characteristics to the Bacillus subtilis, Staphylococcus aureus, and Proteus mirabilis used as the reference bacteria isolates. In Clade 2, the majority of the isolates were negative for gas production during fermentation by lactose, galactose, fructose, and glucose, among others. Based on the various types of sugars used, the isolates clustered into two main clades with subclades. Clade I had isolates that were positive for both acid and gas production by most of the sugars. These isolates included SD12, SD35, and SD30 that were closely related to Enterobacter cloacae, which is a reference bacterium in this study. Clade II had a significant difference in acid production by the isolates to fermentation by various sugars (Figure 3) (Supplementary Table S3).

3.4. Molecular Identification

Gel electrophoresis was done to confirm if the genomic DNA extraction was successful and to confirm the quality of the genomic DNA. The gel electrophoresis showed that the bands were of the right quality and were subjected to PCR using 27F and 1492R primers. The amplified PCR product was between 1200 bp and 1500 bp in size.

Phylogenetic Analysis

Based on phylogenetic analysis, there were fourteen bacterial genera. However, 57% of the bacteria were from the genus Bacilli, followed by Klebsiella, which was represented by 10% of the isolates, and Staphylococcus and Enterococcus were represented by 6% of the isolates each (Figure 4). In addition, some genera had only one isolate. These included Mammaliicoccus, Pseudomonas, Acinetobacter, Stenotrophomonas, and Myroides (Figure 4).

3.5. Sources of Isolated Bacteria

In this study based on the isolation of bacteria from the worn surgical and face masks and swabs from the nose, mouth, and skin, 30% of isolated bacteria were from worn surgical masks, 23% from the nose, 20% from the mouth, 16% from worn face masks, and 10% from the skin (

Table 1. Identities and sources of isolated bacteria.

Isolate	Molecular Identity	Accession Numbers	Genera	Isolation Source	% Similarity Index
SD4	Bacillus acidiproducens	PP412020	Bacillus	Worn face mask	96.75
SD38	Klebsiella pneumoniae	PP406796	Klebsiella	Nose	98.79
SD39	Bacillus subtilis	PP406797	Bacillus	Worn surgical mask	94.48
SD45	Bacillus cereus	PP406798	Bacillus	Worn surgical mask	99.51
SD46	Mammaliicoccus sciuri	PP406799	Mammaliicoccus	Won surgical mask	95.63
SD56	Staphylococcus aureus	PP406800	Staphylococcus	Mouth	96.14
SD53	Klebsiella pneumoniae	PP406801	Klebsiella	Worn face mask	90.31
SD18	Bacillus licheniformis	PP406802	Bacillus	Skin	94.64
SD49	Enterococcus faecalis	PP406803	Enterococcus	Mouth	99.69
SD48	Lysinibacillus xylanilyticus	PP406804	Lysinibacillus	Worn face mask	95.34
SD2	Bacillus toyonensis	PP412026	Bacillus	Worn surgical mask	94.39
SD3	Bacillus cereus	PP406805	Bacillus	Nose	96.54
SD6	Bacillus pumilus	PP406806	Bacillus	Worn face mask	95.90
SD8	Lysinibacillus sphaericus	PP406807	Lysinibacillus	Worn surgical mask	100
SD20	Enterococcus faecalis	PP406808	Enterococcus	Mouth	99.11
SD21	Bacillus cereus	PP406809	Bacillus	Nose	99.78
SD30	Stenotrophomonas maltophilia	PP406810	Stenotrophomonas	Nose	98.73
SD28	Staphylococcus aureus	PP406811	Staphylococcus	Skin	99.21
SD24	Bacillus cereus	PP406812	Bacillus	Nose	100
SD23	Bacillus proteolyticus	PP406813	Bacillus	Worn surgical mask	100
SD19	Bacillus thuringiensis	PP412025	Bacillus	Worn surgical mask	91.15
SD58	Bacillus altitudinis	PP412024	Bacillus	Worn surgical mask	100
SD60	Pseudomonas stutzeri	PP412023	Pseudomonas	Mouth	98.16
SD12	Bacillus cereus	PP412022	Bacillus	Nose	99.51
SD31	Proteus vulgaris	PP412021	Proteus	Mouth	100
SD35	Enterobacter asburiae	PP406814	Enterobacter	Skin	100
SD52	Acinetobacter haemolyticus	PP406815	Acinetobacter	Mouth	98.09
SD5	Klebsiella aerogenes	PP406816	Klebsiella	Nose	94.89
SD1	Myroides odoratus	PP406817	Myroides	Worn surgical mask	99.92
SD36	Neisseria perflava	PP406818	Neisseria	Worn face mask	92.33

The accession numbers of these isolates are found at https://submit.ncbi.nlm.nih.gov/subs/?search=SUB14275542 (accessed on: 3 April 2024) https://submit.ncbi.nlm.nih.gov/subs/?search=SUB14274965 (accessed on: 3 April 2024).

).

3.6. Enumeration Profile of Bacteria

In this study, there was a significant difference between the mask types at p < 0.0001, with surgical masks showing the highest CFU of bacteria compared to face masks. However, there was no significant difference in the CFU of bacteria in the face mask control and surgical control—new unworn masks. In addition, there was a significant difference in the bacterial accumulation between different time intervals at p < 0.0001, with six hours recording the highest CFU, followed by four hours and two hours. There was also a significant difference in the CFU of bacteria based on the location of the mask at p < 0.0001, whereby the inside part had a higher CFU than the outside part (Figure 5B). Moreover, there was significant interaction between mask type×ime and mask type×location at p < 0.0001, location × time at p < 0.0070, and mask type × location × time at p < 0.0002. (

Table 2. Enumeration of bacteria on face and surgical masks.

Mask Type	CFUs/1 µL
Face mask	196.29 ± 16.77 b
Surgical	246.48 ± 15.60 a
Face mask control	42.00 ± 0.99 c
Surgical control	31.11 ± 0.08 c
Time
Two	51.39 ± 3.16 c
Four	101.39 ± 7.29 b
Six	234.13 ± 16.87 a
Location
Inside	141.40 ± 11.32 a
Outside	116.54 ± 8.50 b
p values of the main effect and their interactions
Mask type	<0.0001
Time	<0.0001
Location	<0.0001
Mask type × Time	<0.0001
Mask type × Location	<0.0001
Location × Time	0.0070
Mask type × Location × Time	0.0002

Key: The letters ^a, ^b, ^c are separation of means by Tukey’s post hoc test. Means within the same column with the same superscript letters are not statistically significant at p < 0.05.

). The effect of time on the bacterial load depends on time. The growth over time was high on worn masks but negligible on the controls (Figure 5A). Similarly, the effect of time on the bacterial load depends on the mask location. Inside parts of the masks accumulated bacteria faster than outside parts, especially at 4 h. At 6 h, both locations had closely similar levels of bacterial load (Figure 5B).

3.7. Bacterial Sensitivity to Different Antibiotics

All the bacterial isolates were subjected to antibiotic susceptibility testing to different antibiotics, including cefotaxime, ampicillin, sulfran, amoxicillin, streptomycin, and spectinomycin. The results were recorded as susceptible, intermediate, or resistant (Figure 6). The majority of the isolates were resistant to ampicillin, sulfran, and cefotaxime, whereby 57% of the bacteria isolates were resistant to ampicillin, 57% to cefotaxime, 50% to sulfran, 47% to streptomycin, 47% to spectinomycin, and 47% resistant to amoxicillin. Based on the sensitivity to various antibiotics, the isolates clustered into two main clades, with Clade I having isolates that were mostly susceptible to the antibiotics and with the least resistance including isolates SD45, SD3, and SD58. Clade II had isolates that were mostly resistant to various antibiotics used, including SD52, SD8, and SD12. The antibiotics used in this study clustered into two main clades, with ampicillin, amoxicillin, and spectinomycin having most isolates resistant to them clustering in Clade 1. Clade 2 had the most isolates that were susceptible to sulfran, streptomycin, and cefotaxime (Figure 6).

Antibiotic Sensitivity of Isolated Bacteria to Different Antibiotics

There was a significant difference in the sensitivity between the bacteria isolates to streptomycin at p = 0.0001. A comparison of the bacteria isolates based on sensitivity to streptomycin showed that isolates SD5, SD12, SD23, SD3, and SD49 were resistant, while SD56, SD18, and SD28 were susceptible. There was a significant difference in the sensitivity of the bacterial isolates to spectinomycin (p = 0.0001), with isolates SD56, SD52, SD6, SD28, and SD49—among others—showing resistance, while SD45, SD58, and SD8 were susceptible. Additionally, there was a significant difference in sensitivity between the bacterial isolates on cefotaxime. Bacterial isolates SD45, SD56, SD5, SD12, and SD28 were resistant to cefotaxime, while SD18, SD6, and SD46 were susceptible. Furthermore, the sensitivity between the bacterial isolates and amoxicillin differed significantly. A comparison of the bacteria isolates based on their sensitivity to amoxicillin showed that isolates SD5, SD52, SD56, SD28, SD46, and SD20 were resistant, while SD18, SD6 SD3, SD49, and SD1 were susceptible. Bacterial isolates SD45, SD56, SD18, SD20, SD1, and SD58 were susceptible, while SD5, SD52, SD12, SD49, SD35, SD36, SD38, and SD21 were resistant to sulfran. In addition, there was a significant difference in the sensitivity between the bacteria isolates and ampicillin (p = 0.0001). Isolates SD45, SD56, SD5, SD52, SD12, SD28, and SD46 showed resistance to ampicillin, while isolates SD8, SD49, SD20, SD1, SD58, and SD60 were susceptible (Figure 6).

4. Discussion

In this study, 30 isolates were isolated from disposable surgical and face masks. Most of the isolates were Gram-positive rods and were closely similar to the Bacillus species. According to [13], most of the bacteria isolated on masks were Gram-positive. The diversity in color of the isolates can be attributed to different genera of the isolates, whereby most Bacillus species appeared cream white, while Staphylococcus species had yellow or orange pigmentation, as described by [14]. Different isolates showed different hemolysis in blood agar, including beta, alpha, or gamma hemolysis. This is in agreement with those described by [15].

TSI is a test commonly used in the identification of bacteria in the Enterobacteriaceae family and contains three sugars: lactose, sucrose, and glucose. Bacteria isolates that recorded acid/acid (yellow slant/yellow butt) reactions indicated that they are lactose or sucrose fermenters, while those that had alkali/acid (red slant/yellow butt) reactions indicated that they were glucose fermenters. Similarly, the bile esculin test is used to identify bacteria with the ability to hydrolyze esculin in the presence of bile. In this study, bacteria identified as Enterococcus faecalis hydrolyzed esculin and changed color to black, for example. This is in agreement with MacFaddin (2000) [16], who established that Enterococcus faecalis and other bacteria in the Enterococcus genera hydrolyzed esculin in the bile esculin test. In addition, an oxidase test that is used to differentiate between the families of Pseudomonadaceae (Ox+) and the Enterobacteriaceae families (Ox−) was also done, and the majority of the isolates were oxidase-negative.

Additionally, some of the bacteria isolates such as Proteus vulgaris were positive in the SIM test, demonstrating their ability to the produce cysteine desulfurase enzyme known to change the color of the medium from cream to black. This is in agreement with [17], who demonstrated that some bacteria are SIM-positive because they produce cysteine desulfurase enzyme, which alters the media color to black. Similarly, the coagulase test is used to determine the ability of the bacteria to produce coagulase enzymes. In this study, bacteria isolates identified as Staphylococcus aureus were coagulase-positive. These groups of bacteria are known to produce different virulent factors such as leucocidins, proteases, enterotoxins, hemolysins, and immune-modulating factors, thus causing human infections [18]. Most bacteria isolates were catalase-positive except Staphylococcus aureus, hence collaborating with a previous study by [19].

The majority of the isolated bacteria from masks utilized fructose. According to [20], fructose is easily utilized by bacteria through different metabolic pathways such as the fructose-1-phosphate pathway. Similarly, fructose is a common carbohydrate carbon source in most human diets, and considering that the bacteria were isolated from worn masks, fructose might have been available for the bacteria to use. This is in agreement with a previous study by [21], which confirmed the utilization of fructose in the human gut microbiota by different bacteria. In this study, dulcitol was the least utilized sugar, and this can be attributed to the fact that dulcitol is not abundant in the human diet and has a complex metabolism not used by many bacteria. Some bacteria utilize glucose, sucrose, lactose, and galactose, amongst other sugars, as carbon sources for energy and growth. However, their ability to be utilized as carbon sources differs among the bacterial species, as reported by [22].

The most dominant genus that was isolated from worn disposable masks was Bacillus. Among the Bacillus species were Bacillus toyonensis, Bacillus subtilis, Bacillus pumilus, Bacillus proteolyticus, Bacillus thuringiensis, Bacillus cereus, Bacillus altitudinis, and Bacillus licheniformis. Bacillus and Lysinibacillus species have been reported to have endospores that are resistant to harsh conditions such as heat and disinfectants and thus enhanced survival in places such as masks [23]. These spores are easily disseminated and thus can be easily transmitted through different environments and surfaces and isolated in different materials, including worn surgical and face masks. Moreover, bacteria in this genus are mostly found in terrestrial environments. The study was done in a food market where there is constant contact with soil and plant materials, allowing the transfer of the Bacilli spores to the masks through contact by hand.

Additionally, bacteria species isolated in this study included Staphylococcus aureus, Acinetobacter haemolyticus, and Enterococcus faecalis, which are in agreement with a previous study by [24], who reported these bacteria from used cotton and face masks worn for 2 h and 4 h. Other bacteria were identified as Bacillus acidiproducens, Lysinibacillus sphaericus, Lysinibacillus xylanilyticus, Mammaliicoccus sciuri, Myroides odoratus, Neisseria perflava, Klebsiella aerogenes, Klebsiella pneumoniae, Stenotrophomonas maltophilia, Pseudomonas stutzeri, Proteus vulgaris, and Enterobacter asburiae. Most of these bacteria are pathogenic to humans and are capable of causing secondary infections in humans.

Klebsiella spp. and Proteus spp. isolated in this study are high-risk pathogens associated with diverse human infections, including urinary tract infections, pneumonia, bloodstream infections, and meningitis [25,26]. Staphylococcus aureus is commonly associated with skin infections, including acne, cellulitis, and abscesses [26]. Stenotrophomonas maltophilia isolated in this study is associated with wide clinical syndromes, including pneumonia, bloodstream infections, meningitis, endocarditis, and cystic fibrosis [27]. Also, Myroides odoratus isolated in this study, which is an uncommon pathogen mainly affecting immunocompromised patients, can cause bacteremia and cellulitis [28]. In addition, the majority of the isolates were Bacillus spp., with the pathogenic ones including Bacillus cereus, which are commonly known to cause food poisoning [29].

4.1. Sources of Bacteria on Disposable Surgical and Face Masks

In this study, some of the bacteria isolated from the mouth swabs were found on the inside part of the masks, including Klebsiella pneumoniae, Staphylococcus aureus, Proteus vulgaris, and Enterococcus faecalis. This is in agreement with a study by [30], which reported that human saliva harbors a wide range of these bacteria, including Klebsiella pneumoniae, Staphylococcus aureus, and Proteus vulgaris. Isolation of these bacteria on the masks could be due to the transfer of the bacteria to the masks during coughing, sneezing, or talking. Based on different user activities like speaking or eating, bacterial transfer from the saliva to the inner surface of the masks might differ, whereby speaking increases the release of salivary droplets to the inner surface, while eating—on the other side—effects bacterial transfer by contamination during handling and re-wearing of the masks. This may cause secondary infections in the mask user. Additionally, saliva has nutrients, sugars like glucose and lactose, and moisture that are necessary for the growth of microbes [31]. In addition, bacteria on the human skin and upper respiratory tract could be transferred while wearing masks. The human skin contact with the surface of the masks allows for the growth of bacteria, because the sweat provides nutrients and moisture due to the exhaled air and water vapor [24]. The constant touching of the face and mostly mucoid membranes like the nose, mouth, or eyes provides a route for microbial infections [32]. In addition, contact between the skin and the masks creates a conducive temperature for the microbes to thrive and multiply. Therefore, some bacteria isolated from the face and surgical masks are normal flora of the mouth, skin, and nose. Exhaled breath is also a source of pathogenic bacteria that may cause secondary infections. Accumulation of these microbial pathogens on masks could result in health complications such as respiratory infections or skin diseases such as abscesses and cellulitis [33]. Prolonged wearing of masks has also been associated with headaches, distress, and discomfort [34]. These diseases may weaken the immune system, thus compromising the body’s immune response to COVID-19 infection.

The environment could also be a source of bacteria on masks, as this study was carried out in Githurai market, which is an open-air market for traders and vendors dealing with food products amongst other items. Bacillus being one of the majority isolates isolated from the masks could be attributed to the fact that they are mostly found in terrestrial habitats and are transferred by vendors when in contact with soil and plant materials [23].

4.2. Enumeration of Bacteria on Masks

In this study, the bacterial CFUs differed significantly between face masks and surgical masks, with surgical masks having a higher number of bacteria compared to face masks. This can be attributed to the fact that surgical masks are made of three layers that are spun-bound, melt-blown, and spun-bound as compared to face masks that are made of two layers that are spun-bound, which may affect bacteria retention [1]. Consequently, surgical masks retain more moisture than face masks and create a more favorable and conducive environment for the growth, colonization, and accumulation of bacteria [24]. This agrees with a previous study by [24], where surgical masks showed an increase in bacterial load.

There was a significant difference in the bacterial CFUs between the layers of the masks, with the inner layer of the masks recording a higher number of bacteria than outside. This may be attributed to the difference in the mask’s pore sizes and the difference in the inner and outer materials [1]. In the inside layers of the masks, there is moisture from exhaled breath and sweat from the skin, thus providing a conducive environment for the multiplication of bacteria. Also, human saliva has nutrients such as sugars (glucose), which can be utilized by bacteria as a carbon source, hence favoring their growth and multiplication [31]. The contact between the skin and the masks also contributes to the introduction of bacteria to the inner parts of the masks [35]. In addition, the contact between the skin and the inner parts of the mask allows these parts to naturally acquire body temperature, which promotes the growth and multiplication of these bacteria [36].

Additionally, the bacteria CFUs differed significantly between the worn durations. The CFUs systematically increased with prolonged time (0 h, 2 h, 4 h, and 6 h). This agrees with a previous study by [24,37] who reported that prolonged wearing of surgical masks significantly increased the bacterial CFUs. This may be attributed to the masks providing nutrients and a conducive environment to allow their colonization on the masks.

4.3. Antibiotic Resistance Profiles of Isolated Bacteria from Disposable Masks

There was a difference in the antibiotic resistance profiles of the bacteria. Generally, Gram-negative bacteria showed a higher antibiotic resistance than Gram-positive bacteria. The majority of the isolates were resistant to ampicillin, sulfran, and spectinomycin. This can be attributed to the widespread use of these antibiotics in agriculture, medicine, animal husbandry, and the development of antibiotic-resistant genes in the environment. This agrees with [24] that reported 43% of bacteria isolated from masks were resistant to ampicillin and erythromycin. Ampicillin is a beta-lactam antibiotic with a similar mode of action to amoxicillin. According to [38], Enterococcus species, including Enterococcus faecalis and Staphylococcus aureus, have been reported to have significant resistance to beta-lactam antibiotics. This is in agreement with a previous study by [39], who also reported that Klebsiella pneumoniae, Enterococcus spp., and Pseudomonas aeruginosa are resistant to beta-lactam antibiotics. These bacteria evade beta-lactam antibiotics action through efflux pumps that actively pump the antibiotics out of the cell and effectively reduce the concentration of the antibiotics inside the cell [39]. These bacteria are part of ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Enterobacter species) pathogens that are responsible for a substantial percentage of nosocomial infections, and the majority of these isolates present resistance to antimicrobial agents, bringing a serious therapeutic dilemma to physicians.

The majority of the isolates showed multidrug resistance, whereby the isolates were resistant to at least three different antibiotics. According to [40], bacteria in the Enterobacteriaceae genus, including Klebsiella pneumoniae, Enterobacter spp., and Proteus mirabilis isolated from face masks, were resistant to tetracycline, gentamycin, ceftadizime, and ciprofloxacin.

The study findings demonstrate that bacterial loads on both surgical and face masks peak sharply at six hours of continuous use. This has direct public health implication, particularly in high density environments such as community markets, where prolonged mask use is common. Based on this, we recommend change of mask every four hours to limit bacterial exposure. The recommendation is supported by previous study by [41,42] involving surgical masks and cotton masks worn for four hours that reported a substantial bacterial accumulation on both types, with significantly higher counts on cotton masks. This supports timely mask replacements, especially in environments conducive to bacterial growth [41].

Isolation of multidrug-resistant (MDR) Klebsiella pneumoniae and Enterococcus feacalis in this study underscores heightened risk, particularly for immunocompromised vendors and shoppers. According to [24], high filtration and medical-grade surgical masks may be used by immunocompromised persons because they are less likely to retain moisture and bacterial flora than cloth masks. In addition, the masks should be proactively changed even in the absence of noticeable soiling. Moreover, the masks can be disinfected using safe and appropriate methods. An in vitro research showed that spraying used masks with 70% ethanol, followed by sealing for at least five minutes, achieves significant bacterial reductions [42]. Also, direct exposure to sunlight with strong UV light inactivates bacteria on the mask surface and may be an accessible disinfection method in many community settings [42].

The small sample size may limit the statistical power of the study, reducing the ability to detect significant effects and increasing the risk of Type I and Type II errors. It may also limit the generalizability of the findings to the wider population and make the results more vulnerable to the influence of outliers. Future studies with larger samples are recommended to validate these preliminary observations.

5. Conclusions

The study revealed different identities of bacteria isolated from worn disposable surgical and face masks. These bacteria were from diverse genera, including Bacillus, Staphylococcus, Klebsiella, Proteus, Myroides, Neisseria, Enterococcus, Acinetobacter, Stenotrophomonas, Pseudomonas, Acinetobacter, Lysinibacillus, and Mammaliicoccus. The majority of these have been reported to be pathogenic and capable of causing secondary infections. The sources of the bacteria in the masks were from the nose, skin, mouth, or the environment. Disposable surgical and face masks can be worn for up to 4 h before they being discarded safely. Most of the isolated bacteria from masks showed multidrug resistance to at least three antibiotics.