A Comprehensive View of Microbial Communities in the Laundering Cycle Suggests a Preventive Effect of Soil Bacteria on Malodour Formation

Assessing Antibiotic-Resistant Genes in University Dormitory Washing Machines

University dormitories represent densely populated environments, and washing machines are potential sites for the spread of bacteria and microbes. However, the extent of antibiotic resistance gene (ARG) variation in washing machines within university dormitories and their potential health risks are largely unknown. To disclose the occurrence of ARGs and antibiotic-resistant bacteria from university dormitories, we collected samples from washing machines in 10 dormitories and used metagenomic sequencing technology to determine microbial and ARG abundance. Our results showed abundant microbial diversity, with Proteobacteria being the dominant microorganism that harbors many ARGs. The majority of the existing ARGs were associated with antibiotic target alteration and efflux, conferring multidrug resistance. We identified tnpA and IS91 as the most abundant mobile genetic elements (MGEs) in washing machines and found that Micavibrio aeruginosavorus, Aquincola tertiaricarbonis, and Mycolicibacterium iranicum had high levels of ARGs. Our study highlights the potential transmission of pathogens from washing machines to humans and the surrounding environment. Pollution in washing machines poses a severe threat to public health and demands attention. Therefore, it is crucial to explore effective methods for reducing the reproduction of multidrug resistance.

Bacterial Contamination in the Different Parts of Household Washing Machine: New Insights from Chengdu, Western China

The moist and warm environment in the household washing machine provides ideal living conditions for the growth and survival of various microorganisms. However, the biodiversity of bacterial community in the different parts of washing machine from Chinese households has not been clarified. In this study, we assessed the bacterial communities in sealing strip, detergent drawer, inner drum, water filter and greywater of ten domestic washing machines quantitatively and qualitatively in Chengdu, southwestern China. The microbial cultivation results indicated that the washing machines from Chengdu had a severe microbial contamination reflected by large counts on bacteria, fungi and coliform. Furthermore, the sequencing data showed that the different parts displayed distinctive bacterial compositions. At the level of genus, the anaerobic bacteria of Caproiciproducens and Acidipropionibacterium were predominant in sealing strip. Barnesiella, Shinella and Sellimonas were detected as the characteristic bacteria in detergent drawer. The pathogens of Luteibacter and Corynebacterium at the genus level were the dominant bacteria in inner drum and water filter, respectively. The genera of Azospira, Roseococcus, Elstera and Aquicella, which belonged to the pathogenic phylum of Proteobacteria, were identified as bioindicators for the greywater. Gene function analysis on the sequencing data illustrated that the bacteria from washing machines were potentially associated with bacterial infectious diseases and antimicrobial resistance. This study shows the bacterial diversity in the different parts of washing machines, providing new clues for bacterial contamination in washing machines from Chinese households.

Toward sustainable household laundry. Washing quality vs. environmental impacts

We tested the efficacy of standard soil removal and bacterial reduction from textile. A life cycle analysis for different washing cycles was also performed. The results show that washing at 40 °C and 10 g/L was the most effective and resulted in good removal of standard soiling. However, bacteria reduction was highest at 60 °C, 5 g/L and 40 °C, 20 g/L (> 5 log CFU/carrier). With the 40 °C, 10 g/L scenario, we approached the standard requirements for household laundry of ~ 4 log CFU/carrier reduction and good soil removal. Howsoever, life cycle analysis shows that washing at 40 °C and 10 g/L has a higher environmental impact than 60 °C and 5 g/L due to the significant contribution of the detergent. Reducing energy consumption and reformulation of detergents needs to be implemented in the household laundry to achieve sustainable washing without compromising the quality.

Metabarcoding Analysis of Microorganisms Inside Household Washing Machines in Shanghai, China

Washing machines are one of the tools that bring great convenience to people's daily lives. However, washing machines that have been used for a long time often develop issues such as odor and mold, which can pose health hazards to consumers. There exists a conspicuous gap in our understanding of the microorganisms that inhabit the inner workings of washing machines. In this study, samples were collected from 22 washing machines in Shanghai, China, including both water eluted from different parts of washing machines and biofilms. Quantitative qualitative analysis was performed using fluorescence PCR quantification, and microbial communities were characterized by high-throughput sequencing (HTS). This showed that the microbial communities in all samples were predominantly composed of bacteria. HTS results showed that in the eluted water samples, the bacteria mainly included Pseudomonas, Enhydrobacter, Brevibacterium, and Acinetobacter. Conversely, in the biofilm samples, Enhydrobacter and Brevibacterium were the predominant bacterial microorganisms. Correlation analysis results revealed that microbial colonies in washing machines were significantly correlated with years of use and the type of detergent used to clean the washing machine. As numerous pathogenic microorganisms can be observed in the results, effective preventive measures and future research are essential to mitigate these health problems and ensure the continued safe use of these household appliances.

High resolution ITS amplicon melting analysis as a tool to analyse microbial communities of household biofilms in ex-situ models

Biofilms are the most common growth types of microorganisms. These complex communities usually consist of different species and are embedded in an extracellular matrix containing polymers, proteins and DNA. This matrix offers protection against different (a)biotic environmental factors and generally increases resistances. Higher resistances against antibiotics are one of the main reasons why biofilms are often associated with healthcare settings. Nevertheless, they are also found in domestic settings, mostly in humid places with abundant nutrients like dishwashers or washing machines. Biofilms in these areas show individual compositions and are influenced for example by temperature, frequency of use or the age of the device. In this study, we introduce a model for the ex-situ cultivation of domestic biofilms from household appliances. Furthermore, we tested the ability of high resolution melting analysis (HRMA) as a tool for analysing these biofilms. Our goal was to maintain a high amount of complexity in the ex-situ biofilms that is characterized by the melting behavior of the contained DNA. Dishwasher and washing machine biofilms were sampled in private households and cultivated for 10 d. After DNA extraction, 16S rDNA was sequenced and melting behavior of the bacterial Internal Transcribed Spacer (ITS) region was analysed. Additionally, testing for independence of continuous new sampling, storage of cultivated biofilms in glycerol stocks and following recultivation of them was done up to three times. Our results show that a high level of complexity could be maintained in the ex-situ biofilms after 10 d of cultivation, although in general the bacterial diversity slightly decreased compared to the original biofilm in most cases. Recultivation of a similar biofilm from glycerol stocks was possible as well with some impact by various factors. Differences in the bacterial composition of biofilms could clearly made visible by HRMA although it was not possible to match peaks to a specific phylogenetic group. Still, HRMA proved to be a less costly and time consuming alternative to sequencing for the characterization of biofilms.