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Quantitative and Qualitative Research of Surface Bacteria on the Floor of Station Restrooms with Two Types of Cleaning Method

There are two types of method for cleaning station restrooms. One method uses water for cleaning floors, whereas the second does not. This study describes quantitative and qualitative research into the surface bacteria found on station restroom floors where these two cleaning methods were used. Samples for analysis were collected from five positions on the floor of each restroom in each railway station investigated. Samples were treated using a conventional culture method to measure the concentrations of surface bacteria on each restroom floor. Samples were then analyzed with bacterial 16S rRNA genes to analysis the microbiomes on these restroom floors. Results showed that the restrooms cleaned without water had lower concentrations of bacteria, than the microbiomes from restroom floors cleaned with water.


Introduction
Railways are a public mode of mass transportation, and stations are a core facility in the railway system. As such, station restrooms are a key passenger facility. Station restrooms receive a high volume of users, therefore, railway companies and cleaning companies invest considerable time and effort every day to maintain and manage them. Nevertheless, surveys conducted by the authors in the past revealed that users are highly sensitive to station restroom odors [1,2]. Ammonia, which is one of the main components of the unpleasant odor in restrooms, is thought to be generated by the decomposition of urea contained in urine stains by the ammonia-producing bacteria existing on the floor surface [3]. Therefore, the removal of ammonia-producing bacteria, can be considered to be one of countermeasures for reducing amount of ammonia in station restrooms.
Station restrooms are generally cleaned using one of two possible methods: "wet cleaning" or "dry cleaning", depending on the floor structure. Wet cleaning, which is the most common method, is used in the case of porcelain tile and joint floors. Wet cleaning involves first spreading water on the floor before scrubbing off the dirt with a brush or other similar cleaning tool.
Dry cleaning is used in the case of floor structures consisting of sheets and tiles, such as vinyl chloride. This type of flooring has become increasingly popular in recent years, to allow dry cleaning. In the dry cleaning method, dust and dirt are removed with a machine which scrapes or wipes dirt off the floor with a dry mop or equivalent piece of equipment.
While the number of floor structures suited to dry cleaning is increasing, floor structures requiring wet cleaning are more common in station restrooms in Japan. Wet cleaning is more time and labor intensive than dry cleaning because water on the floor must be wiped and dried after cleaning. In addition, user feedback on both types of cleaning method in station restrooms show that odor tolerance rates are lower in the case of station restrooms where wet cleaning is performed [2].
This suggests that the cleaning method may affect customer experience when using restrooms. However, few studies have examined the difference in the characteristics of bacteria on station restroom floors. Therefore, we carried this study in which we collected bacteria from facilities and the air inside/outside of station restrooms and performed microbiome analysis using 16S rRNA gene [4][5][6][7][8]. This study reports on the quantity and characteristics of bacteria found on railway restroom floors where these two types of cleaning method are used.

Materials and methods
This study describes the quantitative and qualitative investigations of bacteria taken from the floors of station restrooms [8] to confirm the difference in quantity and characteristics of bacteria in restrooms where dry and wet cleaning methods are used.

Subjects of this study
For the purpose of this study one male restroom was selected in four separate stations. In order to ensure comparability, restrooms were selected in stations which had a similar footfalls and been built or renovated all at around the same time. The footfall in each restroom and the main specifications of each are shown in Table 1. In Stations A and B, the selected restrooms had rubber tiled floors and were dry cleaned. In stations C and D, the restrooms had porcelain tiled floors with mortar joints and were wet cleaned.

Investigation period
Quantitative investigations were conducted in Stations A and C in October 2018, January and July 2019, and in Stations B and D in July 2019. At Stations A and C, a qualitative investigation was conducted during the daytime (during business hours) on January 8, 2019 ( Table 2). The temperature and humidity recorded at the time of the investigation are listed in the same table.

Sampling positions
Each of the 5 sampling positions were investigated qualitatively and quantitatively: under washbasins, under urinals, between urinals, and the central and back corners of the floor, in each station.

Bacterial quantity investigation method
Bacteria was collected from floors using one of two possible methods. The first method used a 10-cm square frame, which was

Development and Application of Aseismic Reinforcement Method for Railway Earth Retaining Structures
Foundation and Geotechnical Engineering Laboratory, Structure Technology Division

Masayuki KODA Structure Technology Division
Earth retaining structures, such as bridge abutments and retaining walls, are constructed at the boundary of bridges or embankments. There are a variety of earth retaining structure failure modes, therefore in order to be able to ensure rational aseismic reinforcement, it is necessary to develop a range of different aseismic reinforcement methods adapted to the relevant earth retaining structure's failure mode. Moreover, there are many cases where construction work is severely restricted due to various limitations, such as land boundaries, available space, and time available for construction work. Therefore, the authors propose an aseismic reinforcement method, which can both improve seismic performance of earth retaining structures and be carried out efficiently. This paper outlines this research and describes some examples of the practical application of the newly developed reinforcement method.

Introduction
This paper presents the development and applications of aseismic countermeasures for earth retaining structures such as bridge abutments and retaining walls. In the 1995 Hyogo-ken Nanbu Earthquake, not only bridges and viaducts but also many earth retaining structures were severely damaged. In response to this, what is known as level 2 seismic motion is now considered in the Japanese railway design, and aseismic reinforcement of existing structures is being implemented to ensure the seismic performance of the railway structures. Aseismic reinforcement of bridges and viaducts, to prevent shear failure is now almost complete in Japan. Now, implementation of aseismic countermeasures for existing earth structures, earth retaining structures, and bridge foundations has begun. Figure 1 shows conventional aseismic reinforcement methods applied to a bridge abutment: strut work, injection method with sheet pile shut-off work, and installation of ground anchors or soil reinforcement. Figure 2 illustrates a typical type of aseismic reinforcement method applied to a masonry wall by soil reinforcement with additional RC facing construction. However, carrying out these reinforcement methods requires occupying a large space in front of the structure during construction. In locations where space is limited, such as in urban areas, construction itself often becomes difficult due to site restrictions and the construction environment. Nevertheless, the vast number of existing earth retaining structures and structures requiring aseismic reinforcement in urban areas, means that there is strong demand for the development of an economical aseismic reinforcement method that can be applied even on sites subject to severe constraints. This paper reports on the research, development and application of aseismic countermeasures for earth retaining structures that can not only secure performance against level 2 seismic motion but are also suitable for these restrictive construction conditions in urban areas.

Aseismic reinforcement of bridge abutments
Following massive earthquakes in Japan, many cases in of residual sliding and tilting displacement of the abutment and associated backfill settlement were observed. Residual displacement of the abutment and settlement of the backfill soil results in relative displacement between the abutment and the backfill. In the case of railway structures, this relative displacement causes a significant track irregularity, which has a direct impact on train running laid on the floor and the surface within the square was then wiped with a cotton swab (Eiken Chemical) (Fig. 1). Cotton swabs were then suspended in 10 ml of phosphate buffered saline, and a certain amount of suspension was applied on soybean casein digest medium containing lecithin and polysorbate 80 (SCDLP), which inactivates the effects of detergents, inter alia. The colonies appearing on the SCDLP plates after culturing at 32C° for 48 hours were then counted.
The second method collected bacteria adhering to the surface of the target floor using a circular stamp-type agar medium with an area of 25 cm 2 using the same soybean casein digest medium as described above (SCDLP, Eiken Chemical, Fig. 2. left). Two samples were collected from each sampling site, and after culturing at 32°C for 48 hours, the number of bacterial colonies (Fig. 2, right) that appeared on the agar medium was measured. Since the survey in July 2019 was conducted with the monitor survey [2] on the same day, the easier sampling method with stamp-type agar media was performed.

Qualitative method used for investigating bacteria
Microbiome analysis using the 16S rRNA gene, inherent to bacteria, was used to investigate the bacteria qualitatively.

Microbiome analysis
The microbiome analysis flow chart is shown in Fig. 3. Details are described below.  (1) Sampling method A 10-cm square frame was placed near the position where the quantitative survey was conducted (Fig. 1, left), and the inside of the frame was wiped off with a dry cotton swab (4N6FLOQSwabs, Copan Flock Technologies). One sample was collected at each location, and the cotton swab after wiping was sealed in a 1.5 ml container by cutting off only the cotton part of the cotton swab, and used for the subsequent DNA extraction procedure.
(2) DNA extraction The PowerLyzer PowerSoil DNA Isolation Kit (QIAGEN) was used for DNA extraction. Qubit 3.0 (Thermo Fisher Scientific) was used to measure the concentration of the extracted DNA.

(3) Library preparation
Using the extracted DNA as a template, PCR (polymerase chain reaction) was performed using primers targeting the 16S rRNA gene V3-V4 region of bacteria. The number of PCR amplifications was set to 35 cycles, the same as in the previous study [8,9]. The obtained PCR products were indexed and purified after confirming the peak size by LabChip GX Touch HT (PerkinElmer), ready for the library preparation.

(4) Bacterial flora analysis
The gene sequence was determined by reading 300 bases using the next-generation sequencer MiSeq (Illumina). The obtained gene sequence information was analyzed by QIIME (ver1.9.0). A group having 97% or more target sequence similarity was defined as an OTU (operational taxonomic unit). OTUs were identified by matching the sequences with data in the SILVA 132 database. In the process of calculating the Shannon index, each OTU defined in this study was treated as individual type of bacteria.

Result of the quantitative investigation
The results of quantification of adherent bacteria collected by wiping men's restroom floors in October 2018 and January 2019 in Stations A and C, are shown in Fig. 4. Figure 4 does not show the amount of adherent bacteria under the wash basin at Stations A and C in October 2018, because the number of colonies appearing on the agar mediums was very large and it was difficult to measure them. Comparing the amounts of bacteria in October and January at all collection points, the amount of bacteria found in October was larger than in January. In addition, the largest amounts of bacteria tended to be detected under the wash basins in both stations. Comparing the average number of bacteria in October and January from four sampling points, excluding the point beneath the washbasins, in Station A (dry cleaning) and Station C (wet cleaning), showed that the number of colonies/25 cm 2 ranged between 663 and 3,831 for Station A where dry cleaning was used, and between 14,550 to 27,169 in Station C where wet cleaning was used. The number of bacteria was statistically significantly higher in Station C than in Station A (p <0.05, t-test). Comparing the amounts of adherent bacteria in October and January, no significant difference was found in Station A, but a significant difference was found in Station C (p<0.05, t-test).
The results of collecting floor bacteria using a stamp-type agar medium in stations A, B, C, and D in July 2019, are shown in Fig. 5. In all sampling positions, the attached bacteria detected in order of quantity in each station was: Station C> Station D> Station B> Station A. In addition, looking at each sampling position, a large amount of average adherent bacteria was detected under the urinal and in the back corners of the floor.

Bacterial genus
Bacteria are classified by the hierarchy of kingdom, phylum, net, order, family, genus, and species [9]. In this study, the number of bacterial genera identified by microbiome analysis are shown in Table 3. As a result, more genera were detected from the restroom in Station A than from the restroom in Station C, in all of the five sampling points except the central part of the floor.
The characteristics of the genus of bacteria detected from each collection point at Stations A and C, are shown in Table 4. The genus Kocuria and the genus Deinococcus were commonly detected in all the samples in the men's restrooms of both Stations A and C. It has been reported that the genus Kocuria includes ammonia-producing bacteria in the environment such as water and soil and is also indigenous to human skin [10,11]. The genus Kocuria has also been detected in the air inside the men's restrooms and inside stations at both Stations A and C [6]. The genus Deinococcus has been reported to be detected in activated sludge [12].
On the other hand, the genus Streptococcus, containing ammonia-producing bacteria, was detected only from samples of the floor in the men's restroom at Station A. The genus Streptococcus has been detected in household toilets [13] and has been reported to exist as a human intestinal bacterium [14]. The genus Pseudomonas and Acinetobacter, containing ammonia-producing bacteria, were detected only in samples from the floor in the men's restroom in Station C. These genera are also reported to have been detected in households [15,16] and in soil [17,18].

Microbiome analysis
The Shannon index is an index that indicates the number of types of bacteria detected in a sample and the uniformity of the composition ratio of the types [19]. The results of the Shannon index value obtained by microbiome analysis in this study are shown in Fig. 6. The higher the Shannon index, the higher the number of bacteria types and uniformity of the composition of bacterial types. From Fig. 6, the Shannon index was higher on average for Station A, suggesting that the number of bacterial types and the type composition ratio on the floor of men's restroom were highly uniform, compared to Station C. The Shannon index was the highest for the floor (between urinals) in the restroom in Station A and was the lowest for the floor (under urinals) of the restroom in Station C. In other words, the number of bacterial types present on the floor (between urinals) in Station A was higher and the types composition ratio was more uniform. There are fewer bacterial types and the type composition ratio was lower, and uniformity was also low on the floor (under the urinals) of the restroom in Station C, suggesting that specific bacterial types may be distributed on the floor.
The results of the principal coordinate analysis for each sample are shown in Fig. 7. At Station A, the data plots at five sampling positions are close (solid circle), suggesting that the microbiomes at five positions on the floor are similar. On the other hand, for Station C, each data plot (dotted line circle) is wider than for Station A, which suggests that the similarity of the microbiomes from the five sampling positions was lower than those found in Station A. The results for the point under the urinals in Station C is located slightly off, and the Shannon index value is also low as described above (Fig. 6), suggesting that the microbiome under the urinals in this station was different from other four sampling positions. From these points, it is suggested that the point under the urinals has a particu-larly small number of bacterial types, and specific bacterial types may be distributed under the urinals in the restroom in Station C.

Discussion
This section considers the characteristics of dry and wet cleaning, based on the results of the above quantitative and qualitative investigation of collected bacteria.

From the results of the quantitative investigation
The time and place where many bacteria are detected in this study are considered as follows from the bacterial growth conditions, such as amount of water, temperature, and nutrients (urine Table 3 Number of identified bacterial genera Table 4 Examples of bacterial genus and origins detected at Station A and Station C

Fig. 6 Shannon index value of each sample
stains in the case of restrooms). As mentioned in 3.1, the difference in amount of bacteria collected in October and in January, where there was a temperature difference between both months (Table 2), was not significantly different for Station A, but was significantly different in Station C (Fig. 4).
With wet cleaning, floors take time to dry completely, soil therefore attaches to the soles of the shoes of users, which might then adhere to the floors. Floors which are wet-cleaned are environments where microorganisms have been brought in from outside, and therefore, these microorganisms can thrive because of the moisture introduced during wet cleaning. It is considered that the temperature affects the growth of bacteria, and thus, in this environment, the higher the temperature, the more easily the bacteria can grow. On the other hand, since dry cleaning does not involve spreading water on the floor, it is considered that the amount of bacteria on the floor in Station A was less affected by temperature as Station C.
In addition to the water spread on the floor during wet cleaning, water droplets can fall on the floor under the washbasin during hand washing. Therefore this could mean that the amount of water found under washbasins will be higher than in other sampling positions. In addition, there are many drops of urine around urinals. As such, urine is likely to be carried under the users' shoes from the area around the urinal to the area under the washbasin, as they go to wash their hands. At the time of the investigation at each station, the sampling position where many bacteria were detected, were not always the same. However, a large amount of bacteria was considered to be detected in places where amount of water and nutrients, which are the conditions for bacterial growth, are high.

From the results of the microbiome analysis
The microbiome analysis showed that the genera Kocuria, Streptococcus, Pseudomonas, and Acinetobacter, including ammonia-producing bacteria, were detected on men's restroom floors in Stations A and C. These results suggest that if these bacterial genera could be removed by cleaning, the number of ammonia-producing bacteria could be reduced, and as a result, the generation of ammonia in station restrooms could be reduced.
At Station C, the amount of bacteria under the urinals was lower in January than in the other sampling positions. However, this amount was found to be higher in July (Figs. 4 and 5). This demonstrates that the position on the floor with the largest amounts of bacteria, is not fixed throughout the year. From this, it would be interesting to see whether the ratio of bacterial type composition remains stable while the amount of bacteria fluctuates, or whether the quantity of bacteria fluctuates, as the bacterial type composition ratio varies. Therefore, further investigations carried out in different seasons to confirm the presence or absence of microbiome fluctuations at the time of the survey will be needed to clarify this point.

Conclusions
This study investigated the bacteria found on the surface of men's restroom floors in railway stations which employed either wet or dry cleaning methods, quantitatively by culture method and qualitatively by genetic analysis. The results showed that the floors in men's restrooms where wet cleaning was used in Station C, produced a larger amount of bacteria than in Station A, and that the microbiome tended to differ from point to point on the floor. Future work will seek to confirm the reduction of ammonia-producing bacteria after cleaning, in order to more effectively keep unpleasant odors in railway restrooms to a minimum, by characterizing the distribution of ammonia-producing bacteria on floors with wet and dry cleaning.