Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics

Runoff microbiome quality assessment of a city center rainwater harvesting zone shows a differentiation of pathogen loads according to human mobility patterns

The hygienic quality of urban surfaces can be impaired by multiple sources of microbiological contaminants. These surfaces can trigger the development of multiple bacterial taxa and favor their spread during rain events through the circulation of runoff waters. These runoff waters are commonly directed toward sewer networks, stormwater infiltration systems or detention tanks prior a release into natural water ways. With water scarcity becoming a major worldwide issue, these runoffs are representing an alternative supply for some usage like street cleaning and plant watering. Microbiological hazards associated with these urban runoffs, and surveillance guidelines must be defined to favor these uses. Runoff microbiological quality from a recently implemented city center rainwater harvesting zone was evaluated through classical fecal indicator bacteria (FIB) assays, quantitative PCR and DNA meta-barcoding analyses. The incidence of socio-urbanistic patterns on the organization of these urban microbiomes were investigated. FIB and DNA from Human-specific Bacteroidales and pathogens such as Staphylococcus aureus were detected from most runoffs and showed broad distribution patterns. 16S rRNA DNA meta-barcoding profilings further identified core recurrent taxa of health concerns like Acinetobacter, Mycobacterium, Aeromonas and Pseudomonas, and divided these communities according to two main groups of socio-urbanistic patterns. One of these was highly impacted by heavy traffic, and showed recurrent correlation networks involving bacterial hydrocarbon degraders harboring significant virulence properties. The tpm-based meta-barcoding approach identified some of these taxa at the species level for more than 30 genera. Among these, recurrent pathogens were recorded such as P. aeruginosa, P. paraeruginosa, and Aeromonas caviae. P. aeruginosa and A. caviae tpm reads were found evenly distributed over the study site but those of P. paraeruginosa were higher among sub-catchments impacted by heavy traffic. Health risks associated with these runoff P. paraeruginosa emerging pathogens were high and associated with strong cytotoxicity on A549 lung cells. Recurrent detections of pathogens in runoff waters highlight the need of a microbiological surveillance prior allowing their use. Good microbiological quality can be obtained for certain typologies of sub-catchments with good hygienic practices but not all. A reorganization of Human mobility and behaviors would likely trigger changes in these bacterial diversity patterns and reduce the occurrences of the most hazardous groups.

The composition of the bacterial communities collected from the PM10 samples inside the Seoul subway and railway station

Health implications of indoor air quality (IAQ) have drawn more attention since the COVID epidemic. There are many different kinds of studies done on how IAQ affects people's well-being. There hasn't been much research that looks at the microbiological composition of the aerosol in subway transit systems. In this work, for the first time, we examined the aerosol bacterial abundance, diversity, and composition in the microbiome of the Seoul subway and train stations using DNA isolated from the PM10 samples from each station (three subway and two KTX stations). The average PM10 mass concentration collected on the respective platform was 41.862 µg/m3, with the highest average value of 45.95 µg/m3 and the lowest of 39.25 µg/m3. The bacterial microbiomes mainly constituted bacterial species of soil and environmental origin (e.g., Acinetobacter, Brevundimonas, Lysinibacillus, Clostridiodes) with fewer from human sources (Flaviflexus, Staphylococcus). This study highlights the relationship between microbiome diversity and PM10 mass concentration contributed by outdoor air and commuters in South Korea's subway and train stations. This study gives insights into the microbiome diversity, the source, and the susceptibility of public transports in disease spreading.

An overview of the bacterial microbiome of public transportation systems-risks, detection, and countermeasures

When we humans travel, our microorganisms come along. These can be harmless but also pathogenic, and are spread by touching surfaces or breathing aerosols in the passenger cabins. As the pandemic with SARS-CoV-2 has shown, those environments display a risk for infection transmission. For a risk reduction, countermeasures such as wearing face masks and distancing were applied in many places, yet had a significant social impact. Nevertheless, the next pandemic will come and additional countermeasures that contribute to the risk reduction are needed to keep commuters safe and reduce the spread of microorganisms and pathogens, but also have as little impact as possible on the daily lives of commuters. This review describes the bacterial microbiome of subways around the world, which is mainly characterized by human-associated genera. We emphasize on healthcare-associated ESKAPE pathogens within public transport, introduce state-of-the art methods to detect common microbes and potential pathogens such as LAMP and next-generation sequencing. Further, we describe and discuss possible countermeasures that could be deployed in public transportation systems, as antimicrobial surfaces or air sterilization using plasma. Commuting in public transport can harbor risks of infection. Improving the safety of travelers can be achieved by effective detection methods, microbial reduction systems, but importantly by hand hygiene and common-sense hygiene guidelines.

YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample

MOTIVATION

In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome. Existing tools generally return point estimates, with no associated confidence or uncertainty associated with it. This has led to practitioners experiencing difficulty when interpreting the results from these tools, particularly for low-abundance organisms as these often reside in the "noisy tail" of incorrect predictions. Furthermore, few tools account for the fact that reference databases are often incomplete and rarely, if ever, contain exact replicas of genomes present in an environmentally derived metagenome.

RESULTS

We present solutions for these issues by introducing the algorithm YACHT: Yes/No Answers to Community membership via Hypothesis Testing. This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of ANI, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. After introducing our approach, we quantify its statistical power and how this changes with varying parameters. Subsequently, we perform extensive experiments using both simulated and real data to confirm the accuracy and scalability of this approach.

AVAILABILITY AND IMPLEMENTATION

The source code implementing this approach is available via Conda and at https://github.com/KoslickiLab/YACHT. We also provide the code for reproducing experiments at https://github.com/KoslickiLab/YACHT-reproducibles.

Get to Know Your Neighbors: Characterization of Close Bacillus anthracis Isolates and Toxin Profile Diversity in the Bacillus cereus Group

Unexpected atypical isolates of Bacillus cereus s.l. occasionally challenge conventional microbiology and even the most advanced techniques for anthrax detection. For anticipating and gaining trust, 65 isolates of Bacillus cereus s.l. of diverse origin were sequenced and characterized. The BTyper3 tool was used for assignation to genomospecies B. mosaicus (34), B. cereus s.s (29) and B. toyonensis (2), as well as virulence factors and toxin profiling. None of them carried any capsule or anthrax-toxin genes. All harbored the non-hemolytic toxin nheABC and sphygomyelinase spH genes, whereas 41 (63%), 30 (46%), 11 (17%) and 6 (9%) isolates harbored cytK-2, hblABCD, cesABCD and at least one insecticidal toxin gene, respectively. Matrix-assisted laser desorption ionization-time of flight mass spectrometry confirmed the production of cereulide (ces genes). Phylogeny inferred from single-nucleotide polymorphisms positioned isolates relative to the B. anthracis lineage. One isolate (BC38B) was of particular interest as it appeared to be the closest B. anthracis neighbor described so far. It harbored a large plasmid similar to other previously described B. cereus s.l. megaplasmids and at a lower extent to pXO1. Whereas bacterial collection is enriched, these high-quality public genetic data offer additional knowledge for better risk assessment using future NGS-based technologies of detection.

The microbial biodiversity at the archeological site of Tel Megiddo (Israel)

Introduction

The ancient city of Tel Megiddo in the Jezreel Valley (Israel), which lasted from the Neolithic to the Iron Age, has been continuously excavated since 1903 and is now recognized as a World Heritage Site. The site features multiple ruins in various areas, including temples and stables, alongside modern constructions, and public access is allowed in designated areas. The site has been studied extensively since the last century; however, its microbiome has never been studied. We carried out the first survey of the microbiomes in Tel Megiddo. Our objectives were to study (i) the unique microbial community structure of the site, (ii) the variation in the microbial communities across areas, (iii) the similarity of the microbiomes to urban and archeological microbes, (iv) the presence and abundance of potential bio-corroding microbes, and (v) the presence and abundance of potentially pathogenic microbes.

Methods

We collected 40 swab samples from ten major areas and identified microbial taxa using next-generation sequencing of microbial genomes. These genomes were annotated and classified taxonomically and pathogenetically.

Results

We found that eight phyla, six of which exist in all ten areas, dominated the site (>99%). The relative sequence abundance of taxa varied between the ruins and the sampled materials and was assessed using all metagenomic reads mapping to a respective taxon. The site hosted unique taxa characteristic of the built environment and exhibited high similarity to the microbiome of other monuments. We identified acid-producing bacteria that may pose a risk to the site through biocorrosion and staining and thus pose a danger to the site's preservation. Differences in the microbiomes of the publicly accessible or inaccessible areas were insignificant; however, pathogens were more abundant in the former.

Discussion

We found that Tel Megiddo combines microbiomes of arid regions and monuments with human pathogens. The findings shed light on the microbial community structures and have relevance for bio-conservation efforts and visitor health.

Built environment microbiomes transition from outdoor to human-associated communities after construction and commissioning

The microbiota of the built environment is linked to usage, materials and, perhaps most importantly, human health. Many studies have attempted to identify ways of modulating microbial communities within built environments to promote health. None have explored how these complex communities assemble initially, following construction of new built environments. This study used high-throughput targeted sequencing approaches to explore bacterial community acquisition and development throughout the construction of a new build. Microbial sampling spanned from site identification, through the construction process to commissioning and use. Following commissioning of the building, bacterial richness and diversity were significantly reduced (P < 0.001) and community structure was altered (R2 = 0.14; P = 0.001). Greater longitudinal community stability was observed in outdoor environments than indoor environments. Community flux in indoor environments was associated with human interventions driving environmental selection, which increased 10.4% in indoor environments following commissioning. Increased environmental selection coincided with a 12% reduction in outdoor community influence on indoor microbiomes (P = 2.00 × 10-15). Indoor communities became significantly enriched with human associated genera including Escherichia, Pseudomonas, and Klebsiella spp. These data represent the first to characterize the initial assembly of bacterial communities in built environments and will inform future studies aiming to modulate built environment microbiota.

NS, Víšová I, Vrabcová M, Houska M, Anthi J, Spasovová M, Mustacová J, Štěrba J, Dostálek J, Tung CP, Yang AS, Jack R, Dejneka A, Hajdu J, Vaisocherová-Lísalová H. Negligible risk of surface transmission of SARS-CoV-2 in public transportation

BACKGROUND

Exposure to pathogens in public transport systems is a common means of spreading infection, mainly by inhaling aerosol or droplets from infected individuals. Such particles also contaminate surfaces, creating a potential surface-transmission pathway.

METHODS

A fast acoustic biosensor with an antifouling nano-coating was introduced to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on exposed surfaces in the Prague Public Transport System. Samples were measured directly without pre-treatment. Results with the sensor gave excellent agreement with parallel quantitative reverse-transcription polymerase chain reaction (qRT-PCR) measurements on 482 surface samples taken from actively used trams, buses, metro trains and platforms between 7 and 9 April 2021, in the middle of the lineage Alpha SARS-CoV-2 epidemic wave when 1 in 240 people were COVID-19 positive in Prague.

RESULTS

Only ten of the 482 surface swabs produced positive results and none of them contained virus particles capable of replication, indicating that positive samples contained inactive virus particles and/or fragments. Measurements of the rate of decay of SARS-CoV-2 on frequently touched surface materials showed that the virus did not remain viable longer than 1-4 h. The rate of inactivation was the fastest on rubber handrails in metro escalators and the slowest on hard-plastic seats, window glasses and stainless-steel grab rails. As a result of this study, Prague Public Transport Systems revised their cleaning protocols and the lengths of parking times during the pandemic.

CONCLUSIONS

Our findings suggest that surface transmission played no or negligible role in spreading SARS-CoV-2 in Prague. The results also demonstrate the potential of the new biosensor to serve as a complementary screening tool in epidemic monitoring and prognosis.

Evaluation of rRNA depletion methods for capturing the RNA virome from environmental surfaces

OBJECTIVE

Metatranscriptomic analysis of RNA viromes on built-environment surfaces is hampered by low RNA yields and high abundance of rRNA. Therefore, we evaluated the quality of libraries, efficiency of rRNA depletion, and viral detection sensitivity using a mock community and a melamine-coated table surface RNA with levels below those required (< 5 ng) with a library preparation kit (NEBNext Ultra II Directional RNA Library Prep Kit).

RESULTS

Good-quality RNA libraries were obtained from 0.1 ng of mock community and table surface RNA by changing the adapter concentration and number of PCR cycles. Differences in the target species of the rRNA depletion method affected the community composition and sensitivity of virus detection. The percentage of viral occupancy in two replicates was 0.259 and 0.290% in both human and bacterial rRNA-depleted samples, a 3.4 and 3.8-fold increase compared with that for only bacterial rRNA-depleted samples. Comparison of SARS-CoV-2 spiked-in human rRNA and bacterial rRNA-depleted samples suggested that more SARS-CoV-2 reads were detected in bacterial rRNA-depleted samples. We demonstrated that metatranscriptome analysis of RNA viromes is possible from RNA isolated from an indoor surface (representing a built-environment surface) using a standard library preparation kit.

Toward Oral Thanatomicrobiology-An Overview of the Forensic Implications of Oral Microflora

Introduction

The oral cavity is home to numerous microorganisms including bacteria, fungi, and viruses which together form the oral microflora. It is the second most diverse microbial site in the human body after the gastrointestinal tract. Microbial degradation is a common phenomenon that occurs after death, with the early and advanced stages of decomposition being closely associated with oral microbial activity.

Methods

This article reviews the current state of knowledge on the role of the oral microflora in postmortem events, and highlights the growing importance of terms such as forensic microbiology and thanatomicrobiome. This article also discusses next-generation sequencing, metagenomic sequencing studies, and RNA sequencing to study the oral thanatomicrobiome and epinecrotic communities in forensic oral genetics.

Results

The indigenous microorganisms in the oral cavity are among the first to respond to the process of decomposition. DNA/RNA sequencing is a relatively simple, precise, and cost-effective method to estimate biological diversity during various stages of postmortem decomposition. The field of thanatomicrobiology is rapidly evolving into a key area in forensic research.

Conclusion

This article briefly narrates oral microflora and its implications in forensic odontology. The role of microbial activity in postmortem events is gaining importance in forensic research, and further studies are needed to fully understand the potential applications of advanced technology in the study of the oral thanatomicrobiome.

Pest Alert Tool-a web-based application for flagging species of concern in metabarcoding datasets

Advances in high-throughput sequencing (HTS) technologies and their increasing affordability have fueled environmental DNA (eDNA) metabarcoding data generation from freshwater, marine and terrestrial ecosystems. Research institutions worldwide progressively employ HTS for biodiversity assessments, new species discovery and ecological trend monitoring. Moreover, even non-scientists can now collect an eDNA sample, send it to a specialized laboratory for analysis and receive in-depth biodiversity record from a sampling site. This offers unprecedented opportunities for biodiversity assessments across wide temporal and spatial scales. The large volume of data produced by metabarcoding also enables incidental detection of species of concern, including non-indigenous and pathogenic organisms. We introduce an online app-Pest Alert Tool-for screening nuclear small subunit 18S ribosomal RNA and mitochondrial cytochrome oxidase subunit I datasets for marine non-indigenous species as well as unwanted and notifiable marine organisms in New Zealand. The output can be filtered by minimum length of the query sequence and identity match. For putative matches, a phylogenetic tree can be generated through the National Center for Biotechnology Information's BLAST Tree View tool, allowing for additional verification of the species of concern detection. The Pest Alert Tool is publicly available at https://pest-alert-tool-prod.azurewebsites.net/.

YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample

In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome. While tools exist to answer this question, all existing approaches to date return point estimates, with no associated confidence or uncertainty associated with it. This has led to practitioners experiencing difficulty when interpreting the results from these tools, particularly for low abundance organisms as these often reside in the "noisy tail" of incorrect predictions. Furthermore, no tools to date account for the fact that reference databases are often incomplete and rarely, if ever, contain exact replicas of genomes present in an environmentally derived metagenome. In this work, we present solutions for these issues by introducing the algorithm YACHT: Yes/No Answers to Community membership via Hypothesis Testing. This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of average nucleotide identity, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. After introducing our approach, we quantify its statistical power as well as quantify theoretically how this changes with varying parameters. Subsequently, we perform extensive experiments using both simulated and real data to confirm the accuracy and scalability of this approach. Code implementing this approach, as well as all experiments performed, is available at https://github.com/KoslickiLab/YACHT.

Shaping the subway microbiome through probiotic-based sanitation during the COVID-19 emergency: a pre-post case-control study

BACKGROUND

The COVID-19 pandemic has highlighted the extent to which the public transportation environment, such as in subways, may be important for the transmission of potential pathogenic microbes among humans, with the possibility of rapidly impacting large numbers of people. For these reasons, sanitation procedures, including massive use of chemical disinfection, were mandatorily introduced during the emergency and remain in place. However, most chemical disinfectants have temporary action and a high environmental impact, potentially enhancing antimicrobial resistance (AMR) of the treated microbes. By contrast, a biological and eco-sustainable probiotic-based sanitation (PBS) procedure was recently shown to stably shape the microbiome of treated environments, providing effective and long-term control of pathogens and AMR spread in addition to activity against SARS-CoV-2, the causative agent of COVID-19. Our study aims to assess the applicability and impact of PBS compared with chemical disinfectants based on their effects on the surface microbiome of a subway environment.

RESULTS

The train microbiome was characterized by both culture-based and culture-independent molecular methods, including 16S rRNA NGS and real-time qPCR microarray, for profiling the train bacteriome and its resistome and to identify and quantify specific human pathogens. SARS-CoV-2 presence was also assessed in parallel using digital droplet PCR. The results showed a clear and significant decrease in bacterial and fungal pathogens (p < 0.001) as well as of SARS-CoV-2 presence (p < 0.01), in the PBS-treated train compared with the chemically disinfected control train. In addition, NGS profiling evidenced diverse clusters in the population of air vs. surface while demonstrating the specific action of PBS against pathogens rather than the entire train bacteriome.

CONCLUSIONS

The data presented here provide the first direct assessment of the impact of different sanitation procedures on the subway microbiome, allowing a better understanding of its composition and dynamics and showing that a biological sanitation approach may be highly effective in counteracting pathogens and AMR spread in our increasingly urbanized and interconnected environment. Video Abstract.

Holobiont Urbanism: sampling urban beehives reveals cities' metagenomes

BACKGROUND

Over half of the world's population lives in urban areas with, according to the United Nations, nearly 70% expected to live in cities by 2050. Our cities are built by and for humans, but are also complex, adaptive biological systems involving a diversity of other living species. The majority of these species are invisible and constitute the city's microbiome. Our design decisions for the built environment shape these invisible populations, and as inhabitants we interact with them on a constant basis. A growing body of evidence shows us that human health and well-being are dependent on these interactions. Indeed, multicellular organisms owe meaningful aspects of their development and phenotype to interactions with the microorganisms-bacteria or fungi-with which they live in continual exchange and symbiosis. Therefore, it is meaningful to establish microbial maps of the cities we inhabit. While the processing and sequencing of environmental microbiome samples can be high-throughput, gathering samples is still labor and time intensive, and can require mobilizing large numbers of volunteers to get a snapshot of the microbial landscape of a city.

RESULTS

Here we postulate that honeybees may be effective collaborators in gathering samples of urban microbiota, as they forage daily within a 2-mile radius of their hive. We describe the results of a pilot study conducted with three rooftop beehives in Brooklyn, NY, where we evaluated the potential of various hive materials (honey, debris, hive swabs, bee bodies) to reveal information as to the surrounding metagenomic landscape, and where we conclude that the bee debris are the richest substrate. Based on these results, we profiled 4 additional cities through collected hive debris: Sydney, Melbourne, Venice and Tokyo. We show that each city displays a unique metagenomic profile as seen by honeybees. These profiles yield information relevant to hive health such as known bee symbionts and pathogens. Additionally, we show that this method can be used for human pathogen surveillance, with a proof-of-concept example in which we recover the majority of virulence factor genes for Rickettsia felis, a pathogen known to be responsible for "cat scratch fever".

CONCLUSIONS

We show that this method yields information relevant to hive health and human health, providing a strategy to monitor environmental microbiomes on a city scale. Here we present the results of this study, and discuss them in terms of architectural implications, as well as the potential of this method for epidemic surveillance.

Niche-Based Microbial Community Assemblage in Urban Transit Systems and the Influence of City Characteristics

Microbiota residing on the urban transit systems (UTSs) can be shared by travelers and have niche-specific assemblage. However, it remains unclear how the assemblages are influenced by city characteristics, rendering city-specific and microbial-aware urban planning challenging. Here, we analyzed 3,359 UTS microbial samples collected from 16 cities around the world. We found the stochastic process dominated in all UTS microbiota assemblages, with the explanation rate (R2) of the neutral community model (NCM) higher than 0.7. Moreover, city characteristics predominantly drove such assemblage, largely responsible for the variation in the stochasticity ratio (50.1%). Furthermore, by utilizing an artificial intelligence model, we quantified the ability of UTS microbes in discriminating between cities and found that the ability was also strongly affected by city characteristics, especially climate and continent. From these, we found that although the NCM R2 of the New York City UTS microbiota was 0.831, the accuracy of the microbial-based city characteristic classifier was higher than 0.9. This is the first study to demonstrate the effects of city characteristics on the UTS microbiota assemblage, paving the way for city-specific and microbial-aware applications. IMPORTANCE We analyzed the urban transit system microbiota assemblage across 16 cities. The stochastic process was dominant in the urban transit system microbiota assemblage. The urban transit system microbe's ability in discriminating between cities was quantified using transfer learning based on random forest (RF) methods. Certain urban transit system microbes were strongly affected by city characteristics.

Ecosystem Microbiome Science

The microbiome contributes to multiple ecosystem functions and services through its interactions with a complex environment and other organisms. To date, however, most microbiome studies have been carried out on individual hosts or particular environmental compartments. This greatly limits a comprehensive understanding of the processes and functions performed by the microbiome and its dynamics at an ecosystem level. We propose that the theory and tools of ecosystem ecology be used to investigate the connectivity of microorganisms and their interactions with the biotic and abiotic environment within entire ecosystems and to examine their contributions to ecosystem services. Impacts of natural and anthropogenic stressors on ecosystems will likely cause cascading effects on the microbiome and lead to unpredictable outcomes, such as outbreaks of emerging infectious diseases or changes in mutualistic interactions. Despite enormous advances in microbial ecology, we are yet to study microbiomes of ecosystems as a whole. Doing so would establish a new framework for microbiome study: Ecosystem Microbiome Science. The advent and application of molecular and genomic technologies, together with data science and modeling, will accelerate progress in this field.

Ethical Challenges Associated with Pathogen and Host Genetics in Infectious Disease

The Covid-19 pandemic has demonstrated the potential of genomic technologies for the detection and surveillance of infectious diseases. Pathogen genomics is likely to play a major role in the future of research and clinical implementation of genomic technologies. However, unlike human genetics, the specific ethical and social challenges associated with the implementation of infectious disease genomics has received comparatively little attention. In this paper, we contribute to this literature, focusing on the potential consequences for individuals and communities of the use of these technologies. We concentrate on areas of challenges related to privacy, stigma, discrimination and the return of results in the cases of the surveillance of known pathogens, metagenomics and host genomics.

Dynamics of Microbial Community and Potential Microbial Pollutants in Shopping Malls

Shopping malls offer various niches for microbial populations, potentially serving as sources and reservoirs for the spread of microorganisms of public health concern. However, knowledge about the microbiome and the distribution of human pathogens in malls is largely unknown. Here, we examine the microbial community dynamics and genotypes of potential pathogens from floor and escalator surfaces in shopping malls and adjacent road dusts and greenbelt soils. The distribution pattern of microbial communities is driven primarily by habitats and seasons. A significant enrichment of human-associated microbiota in the indoor environment indicates that human interactions with surfaces might be another strong driver for mall microbiomes. Neutral community models suggest that the microbial community assembly is strongly driven by stochastic processes. Distinct performances of microbial taxonomic signatures for environmental classifications indicate the consistent differences of microbial communities of different seasons/habitats and the strong anthropogenic effect on homogenizing microbial communities of shopping malls. Indoor environments harbored higher concentrations of human pathogens than outdoor samples, also carrying a high proportion of antimicrobial resistance-associated multidrug efflux genes and virulence genes. These findings enhanced the understanding of the microbiome in the built environment and the interactions between humans and the built environment, providing a basis for tracking biothreats and communicable diseases and developing sophisticated early warning systems. IMPORTANCE Shopping malls are distinct microbial environments which can facilitate a constant transmission of microorganisms of public health concern between humans and the built environment or between human and human. Despite extensive investigation of the natural environmental microbiome, no comprehensive profile of microbial ecology has been reported in malls. Characterizing microbial distribution, potential pathogens, and antimicrobial resistance will enhance our understanding of how these microbial communities are formed, maintained, and transferred and help establish a baseline for biosurveillance of potential public health threats in malls.

Metagenome-assembled genomes indicate that antimicrobial resistance genes are highly prevalent among urban bacteria and multidrug and glycopeptide resistances are ubiquitous in most taxa

Introduction

Every year, millions of deaths are associated with the increased spread of antimicrobial resistance genes (ARGs) in bacteria. With the increasing urbanization of the global population, the spread of ARGs in urban bacteria has become a more severe threat to human health.

Methods

In this study, we used metagenome-assembled genomes (MAGs) recovered from 1,153 urban metagenomes in multiple urban locations to investigate the fate and occurrence of ARGs in urban bacteria. Additionally, we analyzed the occurrence of these ARGs on plasmids and estimated the virulence of the bacterial species.

Results

Our results showed that multidrug and glycopeptide ARGs are ubiquitous among urban bacteria. Additionally, we analyzed the deterministic effects of phylogeny on the spread of these ARGs and found ARG classes that have a non-random distribution within the phylogeny of our recovered MAGs. However, few ARGs were found on plasmids and most of the recovered MAGs contained few virulence factors.

Discussion

Our results suggest that the observed non-random spreads of ARGs are not due to the transfer of plasmids and that most of the bacteria observed in the study are unlikely to be virulent. Additional research is needed to evaluate whether the ubiquitous and widespread ARG classes will become entirely prevalent among urban bacteria and how they spread among phylogenetically distinct species.

Urban Microbiomes in Narita, Chiba, Japan: Shotgun Metagenome Sequences of a Train Station

Here, we performed shotgun metagenome sequencing of swab samples collected on floors at a train station in Narita City, Chiba, Japan. The taxonomic analysis revealed that Actinobacteria and Proteobacteria were the dominant phyla. The data will contribute to insight into the microbiome community on the surfaces of urban built environments.

Trends in forensic microbiology: From classical methods to deep learning

Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology.

TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles

BACKGROUND

Metagenomic taxonomic profiling aims to predict the identity and relative abundance of taxa in a given whole-genome sequencing metagenomic sample. A recent surge in computational methods that aim to accurately estimate taxonomic profiles, called taxonomic profilers, has motivated community-driven efforts to create standardized benchmarking datasets and platforms, standardized taxonomic profile formats, and a benchmarking platform to assess tool performance. While this standardization is essential, there is currently a lack of tools to visualize the standardized output of the many existing taxonomic profilers. Thus, benchmarking studies rely on a single-value metrics to compare performance of tools and compare to benchmarking datasets. This is one of the major problems in analyzing metagenomic profiling data, since single metrics, such as the F1 score, fail to capture the biological differences between the datasets.

FINDINGS

Here we report the development of TAMPA (Taxonomic metagenome profiling evaluation), a robust and easy-to-use method that allows scientists to easily interpret and interact with taxonomic profiles produced by the many different taxonomic profiler methods beyond the standard metrics used by the scientific community. We demonstrate the unique ability of TAMPA to generate a novel biological hypothesis by highlighting the taxonomic differences between samples otherwise missed by commonly utilized metrics.

CONCLUSION

In this study, we show that TAMPA can help visualize the output of taxonomic profilers, enabling biologists to effectively choose the most appropriate profiling method to use on their metagenomics data. TAMPA is available on GitHub, Bioconda, and Galaxy Toolshed at https://github.com/dkoslicki/TAMPA and is released under the MIT license.

Comparative Genomics of the Genus Pseudomonas Reveals Host- and Environment-Specific Evolution

Each Earth ecosystem has unique microbial communities. Pseudomonas bacteria have evolved to occupy a plethora of different ecological niches, including living hosts, such as animals and plants. Many genes necessary for the Pseudomonas-niche interaction and their encoded functions remain unknown. Here, we describe a comparative genomic study of 3,274 genomes with 19,056,667 protein-coding sequences from Pseudomonas strains isolated from diverse environments. We detected functional divergence of Pseudomonas that depends on the niche. Each group of strains from a certain environment harbored a distinctive set of metabolic pathways or functions. The horizontal transfer of genes, which mainly proceeded between closely related taxa, was dependent on the isolation source. Finally, we detected thousands of undescribed proteins and functions associated with each Pseudomonas lifestyle. This research represents an effort to reveal the mechanisms underlying the ecology, pathogenicity, and evolution of Pseudomonas, and it will enable clinical, ecological, and biotechnological advances. IMPORTANCE Microbes play important roles in the health of living beings and in the environment. The knowledge of these functions may be useful for the development of new clinical and biotechnological applications and the restoration and preservation of natural ecosystems. However, most mechanisms implicated in the interaction of microbes with the environment remain poorly understood; thus, this field of research is very important. Here, we try to understand the mechanisms that facilitate the differential adaptation of Pseudomonas-a large and ubiquitous bacterial genus-to the environment. We analyzed more than 3,000 Pseudomonas genomes and searched for genetic patterns that can be related with their coevolution with different hosts (animals, plants, or fungi) and environments. Our results revealed that thousands of genes and genetic features are associated with each niche. Our data may be useful to develop new technical and theoretical advances in the fields of ecology, health, and industry.

The Microbiome of the Built Environment: The Nexus for Urban Regeneration for the Cities of Tomorrow

Built environments are, for most of us, our natural habitat. In the last 50 years, the built-up area has more than doubled, with a massive biodiversity loss. The undeniable benefits of a city providing all the basic needs to a growing population showed longer-term and less obvious costs to human health: autoimmune and non-communicable diseases, as well as antimicrobial resistance, have reached unprecedented and alarming levels. Humans coevolved with microbes, and this long-lasting alliance is affected by the loss of connection with natural environments, misuse of antibiotics, and highly sanitized environments. Our aim is to direct the focus onto the microbial communities harbored by the built environments we live in. They represent the nexus for urban regeneration, which starts from a healthy environment. Planning a city means considering, in a two-fold way, the ecosystem health and the multidimensional aspects of wellbeing, including social, cultural, and aesthetic values. The significance of this perspective is inspiring guidelines and strategies for the urban regeneration of the cities of tomorrow, exploiting the invaluable role of microbial biodiversity and the ecosystem services that it could provide to create the robust scientific knowledge that is necessary for a bioinformed design of buildings and cities for healthy and sustainable living.

MTSv: rapid alignment-based taxonomic classification and high-confidence metagenomic analysis

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.

Seasonal variations of the airborne microbial assemblages of the Seoul subway, South Korea from 16S and ITS gene profiles with chemical analysis

In this study, we determined the seasonal airborne microbial diversity profiles at SMRT stations by sequencing the 16S rRNA and ITS. Particulate matter samples were collected from air purifiers installed in the platform area of the SMRT subway stations. Three stations that included the most crowded one were selected for the sampling. The sampling was done at each season during 2019. After extracting the total DNA from all seasonal samples, PCR was performed with Illumina overhang adapter primers for the V3-V4 region of the 16S rRNA gene and ITS2 region of the ITS gene. The amplified products were further purified, and sequencing libraries were made. Sequencing was carried with the Illumina Miseq Sequencing system (Illumina, USA) followed by in-depth diversity analyses. The elemental composition of the particulate matter samples collected from the different subway stations were obtained using a WD-XRF spectrometer. The SMRT microbiome showed extensive taxonomic diversity with the most common bacterial genera at the subway stations associated with the skin. Overall, the stations included in this study harbored different phylogenetic communities based on α- and β-diversity comparisons. Microbial assemblages also varied depending upon the season in which the samples were taken and the station. Major elements present at the subway stations were from aerosols generated between wheels and brake cushions and between the catenaries and the pantographs. This study shows that the microbial composition of the SMRT subway stations comes from a diverse combination of environmental and human sources, the season and the lifestyle of commuters.

Metagenomic characterization of bacterial community and antibiotic resistance genes found in the mass transit system in Seoul, South Korea

Mass transit systems, including subways and buses, are useful environments for studying the urban microbiome, as the vast majority of populations in urban areas use public transportation. Microbial communities in urban environments include both human- and environment-associated bacteria that play roles in health and pathogen transmission. In this study, we used shotgun metagenomic sequencing to profile microbial communities sampled from various surfaces found in subway stations and bus stops within the Seoul mass transit system. The metagenomic approach and network analysis were used to investigate broad-spectrum antibiotic resistance genes (ARGs) and their co-occurrence patterns. We uncovered 598 bacterial species in 76 samples collected from various surfaces within the Seoul mass transit system. All samples were dominated by the potential human pathogen Salmonella enterica (40 %) and the human skin bacterium Cutibacterium acnes (19 %). Significantly abundant biomarkers detected in subway station samples were associated with bacteria typically found in the human oral cavity and respiratory tract, whereas biomarkers detected in bus stop samples were associated with bacteria commonly found in soil, water, and plants. Temperature and location had significant effects on microbial community structure and diversity. In total, 41 unique ARG subtypes were identified, associated with single-drug or multidrug resistance to clinically important and extensively used antibiotics, including aminoglycosides, carbapenem, glycopeptide, and sulfonamides. We revealed that Seoul subway stations and bus stops possess unique microbiomes containing potential human pathogens and ARGs. These findings provide insights for refining location-specific responses to reduce exposure to potentially causative agents of infectious diseases, improving public health.

Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign

A coordinated observational and modelling campaign targeting biogenic aerosols in the air was performed during spring 2021 at two locations in Northern Europe: Helsinki (Finland) and Siauliai (Lithuania), approximately 500 km from each other in north-south direction. The campaign started on March 1, 2021 in Siauliai (12 March in Helsinki) and continued till mid-May in Siauliai (end of May in Helsinki), thus recording the transition of the atmospheric biogenic aerosols profile from winter to summer. The observations included a variety of samplers working on different principles. The core of the program was based on 2- and 2.4--hourly sampling in Helsinki and Siauliai, respectively, with sticky slides (Hirst 24-h trap in Helsinki, Rapid-E slides in Siauliai). The slides were subsequently processed extracting the DNA from the collected aerosols, which was further sequenced using the 3-rd generation sequencing technology. The core sampling was accompanied with daily and daytime sampling using standard filter collectors. The hourly aerosol concentrations at the Helsinki monitoring site were obtained with a Poleno flow cytometer, which could recognize some of the aerosol types. The sampling campaign was supported by numerical modelling. For every sample, SILAM model was applied to calculate its footprint and to predict anthropogenic and natural aerosol concentrations, at both observation sites. The first results confirmed the feasibility of the DNA collection by the applied techniques: all but one delivered sufficient amount of DNA for the following analysis, in over 40% of the cases sufficient for direct DNA sequencing without the PCR step. A substantial variability of the DNA yield has been noticed, generally not following the diurnal variations of the total-aerosol concentrations, which themselves showed variability not related to daytime. An expected upward trend of the biological material amount towards summer was observed but the day-to-day variability was large. The campaign DNA analysis produced the first high-resolution dataset of bioaerosol composition in the North-European spring. It also highlighted the deficiency of generic DNA databases in applications to atmospheric biota: about 40% of samples were not identified with standard bioinformatic methods.

Applications of massively parallel sequencing in forensic genetics

Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning

The COVID-19 pandemic has emphasized the importance of accurate detection of known and emerging pathogens. However, robust characterization of pathogenic sequences remains an open challenge. To address this need we developed SeqScreen, which accurately characterizes short nucleotide sequences using taxonomic and functional labels and a customized set of curated Functions of Sequences of Concern (FunSoCs) specific to microbial pathogenesis. We show our ensemble machine learning model can label protein-coding sequences with FunSoCs with high recall and precision. SeqScreen is a step towards a novel paradigm of functionally informed synthetic DNA screening and pathogen characterization, available for download at www.gitlab.com/treangenlab/seqscreen .

A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments

Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and enable the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we introduce SemiBin, an open source tool that uses deep siamese neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of reconstructing high-quality bins that are outside the reference dataset. Using simulated and real microbiome datasets from several different habitats from GMGCv1 (Global Microbial Gene Catalog), including the human gut, non-human guts, and environmental habitats (ocean and soil), we show that SemiBin outperforms existing state-of-the-art binning methods. In particular, compared to other methods, SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species.

Where environmental microbiome meets its host: subway and passenger microbiome relationships

Subways are urban transport systems with high capacity. Every day around the world, there are more than 150 million subway passengers. Since 2013, thousands of microbiome samples from various subways worldwide have been sequenced. Skin bacteria and environmental organisms dominate the subway microbiomes. The literature has revealed common bacterial groups in subway systems; even so, it is possible to identify cities by their microbiome. Low-frequency bacteria are responsible for specific bacterial fingerprints of each subway system. Furthermore, daily subway commuters leave their microbial clouds and interact with other passengers. Microbial exchange is quite fast; the hand microbiome changes within minutes, and after cleaning the handrails, the bacteria are re-established within minutes. To investigate new taxa and metabolic pathways of subway microbial communities, several high-quality metagenomic-assembled genomes (MAG) have been described. Subways are harsh environments unfavorable for microorganism growth. However, recent studies have observed a wide diversity of viable and metabolically active bacteria. Understanding which bacteria are living, dormant, or dead allows us to propose realistic ecological interactions. Questions regarding the relationship between humans and the subway microbiome, particularly the microbiome effects on personal and public health, remain unanswered. This review summarizes our knowledge of subway microbiomes and their relationship with passenger microbiomes.

Efficacy of antimicrobial and anti-viral coated air filters to prevent the spread of airborne pathogens

The COVID-19 pandemic has demonstrated the real need for mechanisms to control the spread of airborne respiratory pathogens. Thus, preventing the spread of disease from pathogens has come to the forefront of the public consciousness. This has brought an increasing demand for novel technologies to prioritise clean air. In this study we report on the efficacy of novel biocide treated filters and their antimicrobial activity against bacteria, fungi and viruses. The antimicrobial filters reported here are shown to kill pathogens, such as Candida albicans, Escherichia coli and MRSA in under 15 min and to destroy SARS-CoV-2 viral particles in under 30 s following contact with the filter. Through air flow rate testing, light microscopy and SEM, the filters are shown to maintain their structure and filtration function. Further to this, the filters are shown to be extremely durable and to maintain antimicrobial activity throughout the operational lifetime of the product. Lastly, the filters have been tested in field trials onboard the UK rail network, showing excellent efficacy in reducing the burden of microbial species colonising the air conditioning system.

Residential bacteria and fungi identified by high-throughput sequencing and childhood respiratory health

The objective of this study was to examine and compare environmental microbiota from dust and children's respiratory health outcomes at ages seven and twelve. At age seven, in-home visits were conducted for children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Floor dust was collected and analyzed for bacterial (16 S rRNA gene) and fungal (internal transcribed spacer region) microbiota. Respiratory outcomes, including physician-diagnosed asthma, wheeze, rhinitis, and aeroallergen sensitivity were assessed by physical examination and caregiver-report at ages seven and twelve. The associations between dust microbiota and respiratory outcomes were evaluated using Permanova, DESeq, and weighted quantile sum (WQS) regression models. Four types of WQS regression models were run to identify mixtures of fungi or bacteria that were associated with the absence or presence of health outcomes. For alpha or beta diversity of fungi and bacteria, no significant associations were found with respiratory health outcomes. DESeq identified specific bacterial and fungal indicator taxa that were higher or lower with the presence of different health outcomes. Most individual indicator fungal species were lower with asthma and wheeze and higher with aeroallergen positivity and rhinitis, whereas bacterial data was less consistent. WQS regression models demonstrated that a combination of species might influence health outcomes. Several heavily weighted species had a strong influence on the models, and therefore, created a microbial community that was associated with the absence or presence of asthma, wheeze, rhinitis, and aeroallergen+. Weights for specific species within WQS regression models supported indicator taxa findings. Health outcomes might be more influenced by the composition of a complex mixture of bacterial and fungal species in the indoor environment than by the absence or presence of individual species. This study demonstrates that WQS is a useful tool in evaluating mixtures in relation to potential health effects.

Inactivation of MS2 bacteriophage on copper film deployed in high touch areas of a public transport system

Although SARS-CoV-2 is primarily an airborne risk, the COVID-19 pandemic also highlighted the need for self-disinfection surfaces that could withstand the demand of high occupant densities characteristic of public transportation systems. The aim of this study was to evaluate the durability and antiviral activity of a copper film deployed for 90 days in two high touch locations within an active metropolitan bus and railcar. The antiviral efficacy of this copper film after being deployed in transit vehicles for 90 days (deployed copper film) was then compared to new (unused) copper film to determine if frequent touches and cleaning protocols could decrease the efficacy of the copper films. Deployed copper film, new copper film, and aluminium foil (positive control) coupons were inoculated with ~1 × 10⁶ MS2 virus particles, allowed a contact time of either 5- or 10-min, and analysed for residual viral infectiousness. On both new and deployed copper films, MS2 was completely inactivated (≥5 log reduction) at both time points. These results suggest that the copper film may provide the durability demanded by high touch public spaces while maintaining the antiviral activity necessary to reduce exposure risk and viral transmission via surfaces in public transportation settings.

Is Peracetic Acid Fumigation Effective in Public Transportation?

The COVID-19 pandemic made more people aware of the danger of viruses and bacteria, which is why disinfection began to be used more and more often. Epidemiological safety must be ensured not only in gathering places, but also in home and work environments. It is especially challenging in public transportation, which is a perfect environment for the spread of infectious disease. Therefore, the aim of the study was the identification of bacteria in crowded places and the evaluation of the effect of fumigation with peracetic acid (PAA) in public transportation. Inactivation of microorganisms in buses and long-distance coaches was carried out using an automatic commercial fogging device filled with a solution of peracetic acid stabilized with acetic acid (AA) and hydrogen peroxide (H₂O₂). Before and after disinfection, samples were taken for microbiological tests. The most prevalent bacteria were Micrococcus luteus and Bacillus licheniformis.Staphylococcus epidermidis was only present in buses, whereas Staphylococcus hominis and Exiguobacterium acetylicum were only present in coaches. Statistical analysis showed a significant reduction in the number of microorganisms in samples taken from different surfaces after disinfection in vehicles. The overall effectiveness of disinfection was 81.7% in buses and 66.5% in coaches. Dry fog fumigation with peracetic acid is an effective method of disinfecting public transport vehicles.

Antimicrobial Photodynamic Coatings Reduce the Microbial Burden on Environmental Surfaces in Public Transportation—A Field Study in Buses

Millions of people use public transportation daily worldwide and frequently touch surfaces, thereby producing a reservoir of microorganisms on surfaces increasing the risk of transmission. Constant occupation makes sufficient cleaning difficult to achieve. Thus, an autonomous, permanent, antimicrobial coating (AMC) could keep down the microbial burden on such surfaces. A photodynamic AMC was applied to frequently touched surfaces in buses. The microbial burden (colony forming units, cfu) was determined weekly and compared to equivalent surfaces in buses without AMC (references). The microbial burden ranged from 0–209 cfu/cm² on references and from 0–54 cfu/cm² on AMC. The means were 13.4 ± 29.6 cfu/cm² on references and 4.5 ± 8.4 cfu/cm² on AMC (p < 0.001). The difference in microbial burden on AMC and references was almost constant throughout the study. Considering a hygiene benchmark of 5 cfu/cm², the data yield an absolute risk reduction of 22.6% and a relative risk reduction of 50.7%. In conclusion, photodynamic AMC kept down the microbial burden, reducing the risk of transmission of microorganisms. AMC permanently and autonomously contributes to hygienic conditions on surfaces in public transportation. Photodynamic AMC therefore are suitable for reducing the microbial load and closing hygiene gaps in public transportation.

Microbiological Characteristics of Some Stations of Moscow Subway

Simple Summary

Public transport facilities, including subway systems, provide the most suitable conditions for the transfer of microorganisms between people and the environment, contributing to the pathogenic potential of the urban habitat. Investigation of microbiome diversity and description of its characteristic properties, e.g., antibiotic-resistance profiles, leads to understanding of these interactions. In this study, we aimed to conduct an extended analysis of the bioaerosol and surface microbiome of the Moscow subway, using 16S rRNA gene sample sequencing and classical microbiology methods. The microbiomes of two subway stations (Novokosino and Cherkizovskaya) were reconstructed which differ in terms of passenger traffic and duration of exploitation. It was shown that most bacterial genera were ubiquitous; however, the unique genera were presented in aerosol samples. The relatively older Cherkizovskaya station possessed greater diversity in antibiotic resistance among the identified microorganisms compared to Novokosino station. We also provided a comparative analysis of these results with the previously published data, which allowed us to identify the distribution of microorganisms associated with the human microbiome and the environment regardless of the seasonal fluctuations. The obtained results provide valuable information on the diversity of bacterial communities in the Moscow subway, one of the most socially important facilities in metropolitan areas.

Abstract

The subway is one of the most actively used means of transport in the traffic infrastructure of large metropolitan areas. More than seven million passengers use the Moscow subway every day, which promotes the exchange of microorganisms between people and the surrounding subway environment. In this research, a study of the bacterial communities of two Moscow subway stations was conducted and the common subway microbiome was determined. However, there were differences in microbiological and antibiotic-resistance profiles, depending on the station. The station’s operational period since opening correlated with the taxonomic diversity and resistance of the identified bacteria. Moreover, differences between aerosol and surface bacterial communities were found at the two subway stations, indicating the importance of diversified sampling during the microbiome profiling of public areas. In this study, we also compared our data with previously published results obtained for the Moscow subway. Despite sample collection at different stations and seasons, we showed the presence of 15 common genera forming the core microbiome of the Moscow subway, which represents human commensal species, as well as widespread microorganisms from the surrounding environment.

The source and fate of Mycobacterium tuberculosis complex in wastewater and possible routes of transmission

BACKGROUND

The Mycobacterium tuberculosis complex (MTBC) consists of causative agents of both human and animal tuberculosis and is responsible for over 10 million annual infections globally. Infections occur mainly through airborne transmission, however, there are possible indirect transmissions through a faecal-oral route which is poorly reported. This faecal-oral transmission could be through the occurrence of the microbe in environments such as wastewater. This manuscript, therefore, reviews the source and fate of MTBC in the wastewater environment, including the current methods in use and the possible risks of infections.

RESULTS

The reviewed literature indicates that about 20% of patients with pulmonary TB may have extra-pulmonary manifestations such as GITB, resulting in shedding in feaces and urine. This could potentially be the reason for the detection of MTBC in wastewater. MTBC concentrations of up to 5.5 × 105 (±3.9 × 105) copies/L of untreated wastewater have been reported. Studies have indicated that wastewater may provide these bacteria with the required nutrients for their growth and could potentially result in environmental transmission. However, 98.6 (± 2.7) %, removal during wastewater treatment, through physical-chemical decantation (primary treatment) and biofiltration (secondary treatment) has been reported. Despite these reports, several studies observed the presence of MTBC in treated wastewater via both culture-dependent and molecular techniques.

CONCLUSION

The detection of viable MTBC cells in either treated or untreated wastewater, highlights the potential risks of infection for wastewater workers and communities close to these wastewater treatment plants. The generation of aerosols during wastewater treatment could be the main route of transmission. Additionally, direct exposure to the wastewater containing MTBC could potentially contribute to indirect transmissions which may lead to pulmonary or extra-pulmonary infections. This calls for the implementation of risk reduction measures aimed at protecting the exposed populations.

Fungal allergic sensitisation in young rural Zimbabwean children: Gut mycobiome and seroreactivity characteristics

Background

The prevalence of allergic diseases has increased over the last few decades, with sensitisation to fungal allergens and gut microbiome dysbiosis implicated in this trend. The fungal community in the gut (mycobiome) has yet to be characterised and related to fungal allergic sensitisation. Thus, we characterised the gut mycobiome and related it to fungal sensitisation and seroreactivity among Zimbabwean children. We further determined the effect of host age, sex, Schistosoma haematobium infection and mycobiome composition on fungal sensitisation and seroreactivity.

Methods

Using shotgun metagenomic sequencing, we characterised the gut microbiome of stool samples of 116 preschool aged children (PSAC) (≤5 years old, 57(49.1%) male and 59 (50.9%) female). Sensitisation to common fungi in Zimbabwe was assessed using skin prick tests (SPTs). Allergen-specific IgM, IgA, IgG, IgE and IgG4 antibodies were quantified by ELISA. We analysed the relationship between fungal genera and SPT reactivity by ANOVA; fungal genera and IgE antibody reactivity by linear regression; variation in mycobiome abundance with host and environmental factors by PERMANOVA; SPT reactivity and host and environmental factors by logistic regression; seroreactivity and host and environmental factors by ANOVA.

Results

The mycobiome formed <1% of the sequenced gut microbiome and 228 fungal genera were identified. The most abundant genera detected were Protomyces, Taphrina, and Aspergillus. S.haematobium infection had a significant effect on fungal genera. Prevalence of SPT sensitisation to ≥1 fungal species was 96%, and individuals were frequently sensitised to Saccharomyces cerevisiae. Antibodies were detected in 100% of the population. There was no relationship between mycobiome abundance and IgE titres or IgE/IgG4 ratios for each fungal species; no significant differences between SPT reactivity and abundance of fungal species except for S. cerevisiae; and fungal seroreactivity did not significantly differ with age. There were some sex (m>f for, Epicoccum nigrum and Penicillium chrysogenum) and SPT reactivity -related differences in seroreactivity.

Conclusion

This is the first comprehensive characterisation of gut mycobiome and fungal allergic sensitisation of rural children in Zimbabwe. Although reported allergic disease is low there is a high percentage of sensitisation. Further studies with larger populations are required to understand the role of the mycobiome in allergic diseases.

Surveillance and prevalence of antimicrobial resistant bacteria from public settings within urban built environments: Challenges and opportunities for hygiene and infection control

Antimicrobial resistant (AMR) bacteria present one of the biggest threats to public health; this must not be forgotten while global attention is focussed on the COVID-19 pandemic. Resistant bacteria have been demonstrated to be transmittable to humans in many different environments, including public settings in urban built environments where high-density human activity can be found, including public transport, sports arenas and schools. However, in comparison to healthcare settings and agriculture, there is very little surveillance of AMR in the built environment outside of healthcare settings and wastewater. In this review, we analyse the existing literature to aid our understanding of what surveillance has been conducted within different public settings and identify what this tells us about the prevalence of AMR. We highlight the challenges that have been reported; and make recommendations for future studies that will help to fill knowledge gaps present in the literature.

Usefulness of Microbiome for Forensic Geolocation: A Review

Forensic microbiomics is a promising tool for crime investigation. Geolocation, which connects an individual to a certain place or location by microbiota, has been fairly well studied in the literature, and several applications have been found. The aim of this review is to highlight the main findings in this field, including the current sample storage, DNA extraction, sequencing and data analysis techniques that are being used, and its potential applications in human trafficking and ancient DNA studies. Second, the challenges and limitations of forensic microbiomics and geolocation are emphasised, providing recommendations for the establishment of this tool in the forensic science community.

Genome-resolved metagenomics using environmental and clinical samples

Recent advances in high-throughput sequencing technologies and computational methods have added a new dimension to metagenomic data analysis i.e. genome-resolved metagenomics. In general terms, it refers to the recovery of draft or high-quality microbial genomes and their taxonomic classification and functional annotation. In recent years, several studies have utilized the genome-resolved metagenome analysis approach and identified previously unknown microbial species from human and environmental metagenomes. In this review, we describe genome-resolved metagenome analysis as a series of four necessary steps: (i) preprocessing of the sequencing reads, (ii) de novo metagenome assembly, (iii) genome binning and (iv) taxonomic and functional analysis of the recovered genomes. For each of these four steps, we discuss the most commonly used tools and the currently available pipelines to guide the scientific community in the recovery and subsequent analyses of genomes from any metagenome sample. Furthermore, we also discuss the tools required for validation of assembly quality as well as for improving quality of the recovered genomes. We also highlight the currently available pipelines that can be used to automate the whole analysis without having advanced bioinformatics knowledge. Finally, we will highlight the most widely adapted and actively maintained tools and pipelines that can be helpful to the scientific community in decision making before they commence the analysis.

New approaches for metagenome assembly with short reads

In recent years, the use of longer range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic data sets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

Colliding and interacting microbiomes and microbial communities - consequences for human health

Living 'things' coexist with microorganisms, known as the microbiota/microbiome that provides essential physiological functions to its host. Despite this reliance, the microbiome is malleable and can be altered by several factors including birth-mode, age, antibiotics, nutrition, and disease. In this minireview, we consider how other microbiomes and microbial communities impact the host microbiome and the host through the concept of microbiome collisions (initial exposures) and interactions. Interactions include changes in host microbiome composition and functionality and/or host responses. Understanding the impact of other microbiomes and microbial communities on the microbiome and host are important considering the decline in human microbiota diversity in the developed world - paralleled by the surge of non-communicable, inflammatory-based diseases. Thus, surrounding ourselves with rich and diverse beneficial microbiomes and microbial communities to collide and interact with should help to diminish the loss in microbial diversity and protect from certain diseases. In the same vein, our microbiomes not only influence our health but potentially the health of those close to us. We also consider strategies for enhanced host microbiome collisions and interactions through the surrounding environment that ensure increased microbiome diversity and functionality contributing to enhanced symbiotic return to the host in terms of health benefit.

Bacterial colonization dynamics and antibiotic resistance gene dissemination in the hospital environment after first patient occupancy: a longitudinal metagenetic study

BACKGROUND

Humans spend the bulk of their time in indoor environments. This space is shared with an indoor ecosystem of microorganisms, which are in continuous exchange with the human inhabitants. In the particular case of hospitals, the environmental microorganisms may influence patient recovery and outcome. An understanding of the bacterial community structure in the hospital environment is pivotal for the prevention of hospital-acquired infections and the dissemination of antibiotic resistance genes. In this study, we performed a longitudinal metagenetic approach in a newly opened ward at the Charité Hospital (Berlin) to characterize the dynamics of the bacterial colonization process in the hospital environment after first patient occupancy.

RESULTS

The sequencing data showed a site-specific taxonomic succession, which led to stable community structures after only a few weeks. This data was further supported by network analysis and beta-diversity metrics. Furthermore, the fast colonization process was characterized by a significant increase of the bacterial biomass and its alpha-diversity. The compositional dynamics could be linked to the exchange with the patient microbiota. Over a time course of 30 weeks, we did not detect a rise of pathogenic bacteria in the hospital environment, but a significant increase of antibiotic resistance determinants on the hospital floor.

CONCLUSIONS

The results presented in this study provide new insights into different aspects of the environmental microbiome in the clinical setting, and will help to adopt infection control strategies in hospitals and health care-related buildings. Video Abstract.

ORFograph: search for novel insecticidal protein genes in genomic and metagenomic assembly graphs

BACKGROUND

Since the prolonged use of insecticidal proteins has led to toxin resistance, it is important to search for novel insecticidal protein genes (IPGs) that are effective in controlling resistant insect populations. IPGs are usually encoded in the genomes of entomopathogenic bacteria, especially in large plasmids in strains of the ubiquitous soil bacteria, Bacillus thuringiensis (Bt). Since there are often multiple similar IPGs encoded by such plasmids, their assemblies are typically fragmented and many IPGs are scattered through multiple contigs. As a result, existing gene prediction tools (that analyze individual contigs) typically predict partial rather than complete IPGs, making it difficult to conduct downstream IPG engineering efforts in agricultural genomics.

METHODS

Although it is difficult to assemble IPGs in a single contig, the structure of the genome assembly graph often provides clues on how to combine multiple contigs into segments encoding a single IPG.

RESULTS

We describe ORFograph, a pipeline for predicting IPGs in assembly graphs, benchmark it on (meta)genomic datasets, and discover nearly a hundred novel IPGs. This work shows that graph-aware gene prediction tools enable the discovery of greater diversity of IPGs from (meta)genomes.

CONCLUSIONS

We demonstrated that analysis of the assembly graphs reveals novel candidate IPGs. ORFograph identified both already known genes "hidden" in assembly graphs and potential novel IPGs that evaded existing tools for IPG identification. As ORFograph is fast, one could imagine a pipeline that processes many (meta)genomic assembly graphs to identify even more novel IPGs for phenotypic testing than would previously be inaccessible by traditional gene-finding methods. While here we demonstrated the results of ORFograph only for IPGs, the proposed approach can be generalized to any class of genes. Video abstract.

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Characterization of nucleic acids from extracellular vesicle-enriched human sweat

Background

The human sweat is a mixture of secretions from three types of glands: eccrine, apocrine, and sebaceous. Eccrine glands open directly on the skin surface and produce high amounts of water-based fluid in response to heat, emotion, and physical activity, whereas the other glands produce oily fluids and waxy sebum. While most body fluids have been shown to contain nucleic acids, both as ribonucleoprotein complexes and associated with extracellular vesicles (EVs), these have not been investigated in sweat. In this study we aimed to explore and characterize the nucleic acids associated with sweat particles.

Results

We used next generation sequencing (NGS) to characterize DNA and RNA in pooled and individual samples of EV-enriched sweat collected from volunteers performing rigorous exercise. In all sequenced samples, we identified DNA originating from all human chromosomes, but only the mitochondrial chromosome was highly represented with 100% coverage. Most of the DNA mapped to unannotated regions of the human genome with some regions highly represented in all samples. Approximately 5 % of the reads were found to map to other genomes: including bacteria (83%), archaea (3%), and virus (13%), identified bacteria species were consistent with those commonly colonizing the human upper body and arm skin. Small RNA-seq from EV-enriched pooled sweat RNA resulted in 74% of the trimmed reads mapped to the human genome, with 29% corresponding to unannotated regions. Over 70% of the RNA reads mapping to an annotated region were tRNA, while misc. RNA (18,5%), protein coding RNA (5%) and miRNA (1,85%) were much less represented. RNA-seq from individually processed EV-enriched sweat collection generally resulted in fewer percentage of reads mapping to the human genome (7–45%), with 50–60% of those reads mapping to unannotated region of the genome and 30–55% being tRNAs, and lower percentage of reads being rRNA, LincRNA, misc. RNA, and protein coding RNA.

Conclusions

Our data demonstrates that sweat, as all other body fluids, contains a wealth of nucleic acids, including DNA and RNA of human and microbial origin, opening a possibility to investigate sweat as a source for biomarkers for specific health parameters.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07733-9.

Ultra-accurate microbial amplicon sequencing with synthetic long reads

BACKGROUND

Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge.

METHODS

Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads.

RESULTS

LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens.

CONCLUSIONS

The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics. Video abstract.