Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Current status of microbial source tracking applications in constructed wetlands serving as nature-based solutions for water management and wastewater treatment

Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

Atmospheric dispersal shapes rapid bacterial colonization of Icelandic Lava Rocks

Microorganisms released into the atmosphere by various disturbances can travel significant distances before depositing, yet their impact on community assembly remains unclear. To address this, we examined atmospheric and lithospheric bacterial communities in 179 samples collected at two distinct Icelandic volcanic sites: a small volcanic island Surtsey, and a volcanic highland Fimmvörðuháls using 16S rRNA amplicon sequencing. Airborne microbial communities were similar between sites while significant differences emerged in the communities on lava rocks after 1-year exposure. SourceTracker analysis revealed distinct bacterial populations in the atmosphere and the lava rocks with surrounding soil contributed more significantly to lava rock microbial composition. Nevertheless, shared genera among air, rocks, and local sources, suggested potential exchange between these environments. The prevalent genera shared between rocks and potential sources exhibited stress-resistant properties, likely helping their survival during air transportation and facilitating their colonization of the rocks. We hypothesize that the atmosphere serves as a conduit for locally sourced microbes and stress-resistant distant-sourced microbes. Additionally, bacterial communities on the lava rocks of Fimmvörðuháls showed remarkable similarity after 1 and 9 years of exposure, suggesting rapid establishment. Our study reveals that atmospheric deposition significantly influences bacterial community formation, potentially influencing ecosystem dynamics and microbial communities' resilience.

Metagenomic analysis of microbial communities and antibiotic resistant genes in the Tijuana river, and potential sources

The Tijuana River is a transborder river that flows northwest across the border from Baja California in Mexico into Southern California before discharging into the Pacific Ocean. The river is frequently contaminated with raw sewage due to inadequate sanitary infrastructure in Tijuana. To assess the type and degree of microbial contamination, water samples were collected monthly from a near-border and an estuarine site from August 2020 until May 2021. A portion of each sample was used for epifluorescent microscopy and DNA was extracted directly from the rest for shotgun metagenomic sequencing. After sequence quality checking and processing, we used the rapid taxonomic identifier tool Kaiju to characterize the microbial diversity of the metagenomes and matched the sequences against the Comprehensive Antibiotic Resistance Database (CARD) to examine antimicrobial resistance genes (ARGs). Bacterial and viral-like particle (VLP) abundance was consistently higher in the near-border samples than in the estuarine samples, while alpha diversity (within sample biodiversity) was higher in estuarine samples. Beta-diversity analysis found clear compositional separation between samples from the two sites, and the near-border samples were more dissimilar to one another than were the estuarine sites. Near-border samples were dominated by fecal-associated bacteria and bacteria associated with sewage sludge, while estuarine sites were dominated by marine bacteria. ARGs were more abundant at the near-border site, but were also readily detectable in the estuarine samples, and the most abundant ARGs had multi-resistance to beta-lactam antibiotics. SourceTracker analysis identified human feces and sewage sludge to be the largest contributors to the near-border samples, while marine waters dominated estuarine samples except for two sewage overflow dates with high fecal contamination. Overall, our research determined human sewage microbes to be common in the Tijuana River, and the prevalence of ARGs confirms the importance of planned infrastructure treatment upgrades for environmental health.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Holistic View and Novel Perspective on Ruminal and Extra-Gastrointestinal Methanogens in Cattle

Despite the extensive research conducted on ruminal methanogens and anti-methanogenic intervention strategies over the last 50 years, most of the currently researched enteric methane (CH4) abatement approaches have shown limited efficacy. This is largely because of the complex nature of animal production and the ruminal environment, host genetic variability of CH4 production, and an incomplete understanding of the role of the ruminal microbiome in enteric CH4 emissions. Recent sequencing-based studies suggest the presence of methanogenic archaea in extra-gastrointestinal tract tissues, including respiratory and reproductive tracts of cattle. While these sequencing data require further verification via culture-dependent methods, the consistent identification of methanogens with relatively greater frequency in the airway and urogenital tract of cattle, as well as increasing appreciation of the microbiome-gut-organ axis together highlight the potential interactions between ruminal and extra-gastrointestinal methanogenic communities. Thus, a traditional singular focus on ruminal methanogens may not be sufficient, and a holistic approach which takes into consideration of the transfer of methanogens between ruminal, extra-gastrointestinal, and environmental microbial communities is of necessity to develop more efficient and long-term ruminal CH4 mitigation strategies. In the present review, we provide a holistic survey of the methanogenic archaea present in different anatomical sites of cattle and discuss potential seeding sources of the ruminal methanogens.

Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities

BACKGROUND

The gut microbiome has been linked to many diseases with sex bias including autoimmune, metabolic, neurological, and reproductive disorders. While numerous studies report sex differences in fecal microbial communities, the role of the reproductive axis in this differentiation is unclear and it is unknown how sex differentiation affects microbial diversity in specific regions of the small and large intestine.

METHODS

We used a genetic hypogonadal mouse model that does not produce sex steroids or go through puberty to investigate how sex and the reproductive axis impact bacterial diversity within the intestine. Using 16S rRNA gene sequencing, we analyzed alpha and beta diversity and taxonomic composition of fecal and intestinal communities from the lumen and mucosa of the duodenum, ileum, and cecum from adult female (n = 20) and male (n = 20) wild-type mice and female (n = 17) and male (n = 20) hypogonadal mice.

RESULTS

Both sex and reproductive axis inactivation altered bacterial composition in an intestinal section and niche-specific manner. Hypogonadism was significantly associated with bacteria from the Bacteroidaceae, Eggerthellaceae, Muribaculaceae, and Rikenellaceae families, which have genes for bile acid metabolism and mucin degradation. Microbial balances between males and females and between hypogonadal and wild-type mice were also intestinal section-specific. In addition, we identified 3 bacterial genera (Escherichia Shigella, Lachnoclostridium, and Eggerthellaceae genus) with higher abundance in wild-type female mice throughout the intestinal tract compared to both wild-type male and hypogonadal female mice, indicating that activation of the reproductive axis leads to female-specific differentiation of the gut microbiome. Our results also implicated factors independent of the reproductive axis (i.e., sex chromosomes) in shaping sex differences in intestinal communities. Additionally, our detailed profile of intestinal communities showed that fecal samples do not reflect bacterial diversity in the small intestine.

CONCLUSIONS

Our results indicate that sex differences in the gut microbiome are intestinal niche-specific and that sampling feces or the large intestine may miss significant sex effects in the small intestine. These results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

decOM: similarity-based microbial source tracking of ancient oral samples using k-mer-based methods

BACKGROUND

The analysis of ancient oral metagenomes from archaeological human and animal samples is largely confounded by contaminant DNA sequences from modern and environmental sources. Existing methods for Microbial Source Tracking (MST) estimate the proportions of environmental sources, but do not perform well on ancient metagenomes. We developed a novel method called decOM for Microbial Source Tracking and classification of ancient and modern metagenomic samples using k-mer matrices.

RESULTS

We analysed a collection of 360 ancient oral, modern oral, sediment/soil and skin metagenomes, using stratified five-fold cross-validation. decOM estimates the contributions of these source environments in ancient oral metagenomic samples with high accuracy, outperforming two state-of-the-art methods for source tracking, FEAST and mSourceTracker.

CONCLUSIONS

decOM is a high-accuracy microbial source tracking method, suitable for ancient oral metagenomic data sets. The decOM method is generic and could also be adapted for MST of other ancient and modern types of metagenomes. We anticipate that decOM will be a valuable tool for MST of ancient metagenomic studies. Video Abstract.

Edible flora in pre-Columbian Caribbean coprolites: Expected and unexpected data

Coprolites, or mummified feces, are valuable sources of information on ancient cultures as they contain ancient DNA (aDNA). In this study, we analyzed ancient plant DNA isolated from coprolites belonging to two pre-Columbian cultures (Huecoid and Saladoid) from Vieques, Puerto Rico, using shotgun metagenomic sequencing to reconstruct diet and lifestyles. We also analyzed DNA sequences of putative phytopathogenic fungi, likely ingested during food consumption, to further support dietary habits. Our findings show that pre-Columbian Caribbean cultures had a diverse diet consisting of maize (Zea mays), sweet potato (Ipomoea batatas), chili peppers (Capsicum annuum), peanuts (Arachis spp.), papaya (Carica papaya), tomato (Solanum lycopersicum) and, very surprisingly cotton (Gossypium barbadense) and tobacco (Nicotiana sylvestris). Modelling of putative phytopathogenic fungi and plant interactions confirmed the potential consumption of these plants as well as edible fungi, particularly Ustilago spp., which suggest the consumption of maize and huitlacoche. These findings suggest that a variety of dietary, medicinal, and hallucinogenic plants likely played an important role in ancient human subsistence and societal customs. We compared our results with coprolites found in Mexico and the United States, as well as present-day faeces from Mexico, Peru, and the United States. The results suggest that the diet of pre-Columbian cultures resembled that of present-day hunter-gatherers, while agriculturalists exhibited a transitional state in dietary lifestyles between the pre-Columbian cultures and larger scale farmers and United States individuals. Our study highlights differences in dietary patterns related to human lifestyles and provides insight into the flora present in the pre-Columbian Caribbean area. Importantly, data from ancient fecal specimens demonstrate the importance of ancient DNA studies to better understand pre-Columbian populations.

Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

A Comprehensive Review for the Surveillance of Human Pathogenic Microorganisms in Shellfish

Bivalve molluscan shellfish have been consumed for centuries. Being filter feeders, they may bioaccumulate some microorganisms present in coastal water, either naturally or through the discharge of human or animal sewage. Despite regulations set up to avoid microbiological contamination in shellfish, human outbreaks still occur. After providing an overview showing their implication in disease, this review aims to highlight the diversity of the bacteria or enteric viruses detected in shellfish species, including emerging pathogens. After a critical discussion of the available methods and their limitations, we address the interest of technological developments using genomics to anticipate the emergence of pathogens. In the coming years, further research needs to be performed and methods need to be developed in order to design the future of surveillance and to help risk assessment studies, with the ultimate objective of protecting consumers and enhancing the microbial safety of bivalve molluscan shellfish as a healthy food.

The Skin Microbiome: Current Techniques, Challenges, and Future Directions

Skin acts as a barrier that promotes the colonization of bacteria, fungi, archaea, and viruses whose membership and function may differ depending on the various specialized niches or micro-environments of the skin. The group of microorganisms inhabiting the skin, also known as the skin microbiome, offers protection against pathogens while actively interacting with the host's immune system. Some members of the skin microbiome can also act as opportunistic pathogens. The skin microbiome is influenced by factors such as skin site, birth mode, genetics, environment, skin products, and skin conditions. The association(s) of the skin microbiome with health and disease has (have) been identified and characterized via culture-dependent and culture-independent methods. Culture-independent methods (such as high-throughput sequencing), in particular, have expanded our understanding of the skin microbiome's role in maintaining health or promoting disease. However, the intrinsic challenges associated with the low microbial biomass and high host content of skin microbiome samples have hindered advancements in the field. In addition, the limitations of current collection and extraction methods and biases derived from sample preparation and analysis have significantly influenced the results and conclusions of many skin microbiome studies. Therefore, the present review discusses the technical challenges associated with the collection and processing of skin microbiome samples, the advantages and disadvantages of current sequencing approaches, and potential future areas of focus for the field.

SNV-FEAST: microbial source tracking with single nucleotide variants

Elucidating the sources of a microbiome can provide insight into the ecological dynamics responsible for the formation of these communities. Source tracking approaches to date leverage species abundance information; however, single nucleotide variants (SNVs) may be more informative because of their high specificity to certain sources. To overcome the computational burden of utilizing all SNVs for a given sample, we introduce a novel method to identify signature SNVs for source tracking. Signature SNVs used as input into a previously designed source tracking algorithm, FEAST, can more accurately estimate contributions than species and provide novel insights, demonstrated in three case studies.

Distribution characteristics of oral microbiota and its relationship with intestinal microbiota in patients with type 2 diabetes mellitus

Introduction

Type 2 diabetes mellitus (T2DM) has a high incidence rate globally, increasing the burden of death, disability, and the economy worldwide. Previous studies have found that the compositions of oral and intestinal microbiota changed respectively in T2DM; whether the changes were associated or interacted between the two sites and whether there were some associations between T2DM and the ectopic colonization of oral microbiota in the gut still need to be identified.

Research design and methods

We performed a cross-sectional observational study; 183 diabetes and 74 controls were enrolled. We used high-throughput sequencing technology to detect the V3-V4 region of 16S rRNA in oral and stool samples. The Source Tracker method was used to identify the proportion of the intestinal microbiota that ectopic colonized from the oral cavity.

Results

The oral marker bacteria of T2DM were found, such as Actinobacteria, Streptococcus, Rothia, and the intestinal marker bacteria were Bifidobacterium, Streptococcus, and Blautia at the genus level. Among them, Actinobacteria and Blautia played a vital role in different symbiotic relationships of oral and intestinal microbiota. The commonly distributed bacteria, such as Firmicutes, Bacteroidetes, and Actinobacteria, were found in both oral and intestine. Moreover, the relative abundance and composition of bacteria were different between the two sites. The glycine betaine degradation I pathway was the significantly up-regulated pathway in the oral and intestinal flora of T2DM. The main serum indexes related to oral and intestinal flora were inflammatory. The relative abundance of Proteobacteria in the intestine and the Spirochete in oral was positively correlated, and the correlation coefficient was the highest, was 0.240 (P<0.01). The proportion of ectopic colonization of oral flora in the gut of T2DM was 2.36%.

Conclusion

The dysbacteriosis exited in the oral and intestine simultaneously, and there were differences and connections in the flora composition at the two sites in T2DM. Ectopic colonization of oral flora in the intestine might relate to T2DM. Further, clarifying the oral-gut-transmitting bacteria can provide an essential reference for diagnosing and treating T2DM in the future.

Maternal Rumen Bacteriota Shapes the Offspring Rumen Bacteriota, Affecting the Development of Young Ruminants

The maternal rumen microbiota can affect the infantile rumen microbiota and likely offspring growth, and some rumen microbes are heritable and are associated with host traits. However, little is known about the heritable microbes of the maternal rumen microbiota and their role in and effect on the growth of young ruminants. From analyzing the ruminal bacteriota from 128 Hu sheep dams and their 179 offspring lambs, we identified the potential heritable rumen bacteria and developed random forest prediction models to predict birth weight, weaning weight, and preweaning gain of the young ruminants using rumen bacteria as predictors. We showed that the dams tended to shape the bacteriota of the offspring. About 4.0% of the prevalent amplicon sequence variants (ASVs) of rumen bacteria were heritable (h2 > 0.2 and P < 0.05), and together they accounted for 4.8% and 31.5% of the rumen bacteria in relative abundance in the dams and the lambs, respectively. Heritable bacteria classified to Prevotellaceae appeared to play a key role in the rumen niche and contribute to rumen fermentation and the growth performance of lambs. Lamb growth traits could be successfully predicted using some maternal ASVs, and the accuracy of the predictive models was improved when some ASVs from both dams and their offspring were included. IMPORTANCE Using a study design that enabled direct comparison of the rumen microbiota between sheep dams and their lambs, between littermates, and between sheep dams and lambs from other mothers, we identified the heritable subsets of rumen bacteriota in Hu sheep, some of which may play important roles in affecting the growth traits of young lambs. Some maternal rumen bacteria could help predict the growth traits of the young offspring, and they may assist in breeding of and selection for high-performance sheep.

Metagenomic Analysis of Microbial Contamination in the U.S. Portion of the Tijuana River Watershed

The Tijuana River watershed is binational, flowing from Tijuana, Mexico into San Diego and Imperial Beach, USA. Aging sewage and stormwater infrastructure in Tijuana has not kept pace with population growth, causing overflows into this watershed during major rainfall or equipment failures. The public health consequences of this impaired watershed on the surrounding communities remain unknown. Here, we performed untargeted metagenomic sequencing to better characterize the sewage contamination in the Tijuana River, identifying potential pathogens and molecular indicators of antibiotic resistance in surface waters. In 2019-2020, water samples were collected within 48 h of major rainfall events at five transborder flow sites and at the mouth of the river in the US portion of the Tijuana River and estuary. After filtration, DNA was extracted and sequenced, and sequences were run through the Kaiju taxonomic classification program. A pathogen profile of the most abundant disease-causing microbes and viruses present in each of the samples was constructed, and specific markers of fecal contamination were identified and linked to each site. Results from diversity analysis between the sites showed clear distinction as well as similarities between sites and dates, and antibiotic-resistant genes were found at each site. This serves as a baseline characterization of microbial exposures to these local communities.

Genomic ancestry, diet and microbiomes of Upper Palaeolithic hunter-gatherers from San Teodoro cave

Recent improvements in the analysis of ancient biomolecules from human remains and associated dental calculus have provided new insights into the prehistoric diet and genetic diversity of our species. Here we present a multi-omics study, integrating metagenomic and proteomic analyses of dental calculus, and human ancient DNA analysis of the petrous bones of two post-Last Glacial Maximum (LGM) individuals from San Teodoro cave (Italy), to reconstruct their lifestyle and the post-LGM resettlement of Europe. Our analyses show genetic homogeneity in Sicily during the Palaeolithic, representing a hitherto unknown Italian genetic lineage within the previously identified Villabruna cluster. We argue that this lineage took refuge in Italy during the LGM, followed by a subsequent spread to central-western Europe. Analysis of dental calculus showed a diet rich in animal proteins which is also reflected on the oral microbiome composition. Our results demonstrate the power of this approach in the study of prehistoric humans and will enable future research to reach a more holistic understanding of the population dynamics and ecology.

Bacterial communities in co-cultured fish intestines and rice field soil irrigated with aquaculture wastewater

In some regions, integrated rice-fish farms have been developed to balance the needs of aquaculture wastewater discharge and rice field irrigation. In this type of aqua-agriculture system, soil is irrigated with aquaculture wastewater, and intestinal bacteria in cultured fish species likely impact soil bacteria through irrigation. However, little is known about the relationship between soil bacteria and intestinal bacteria in some carp species commonly co-cultured in some Asian regions. Therefore, we co-cultured five carp species in aquaculture ponds and used the aquaculture wastewater to irrigate rice fields for over 5 years, and then compared carp intestinal bacterial communities with rice field soil bacterial communities. The results from analysis of similarity and SourceTracker analysis showed that a low similarity (R = 0.7908, P = 0.001) and contribution (an average of 9.9% of bacterial genera) of intestinal bacteria to soil bacterial communities although 77.5% of soil bacterial genera were shared by intestinal bacteria. Our results also indicated that intestinal bacteria in the numerically dominant fish species in the co-culture system do not necessarily impact soil bacteria more significantly than those of less abundant carp species, and that intestinal bacterial communities in one single fish species may impact certain soil bacterial phyla more significantly than others. Our results provide a better understanding of the impact of aquaculture wastewater on rice fields and will be helpful for the development of this type of aqua-agriculture system.

Towards standardized and reproducible research in skin microbiomes

Skin is a complex organ serving a critical role as a barrier and mediator of interactions between the human body and its environment. Recent studies have uncovered how resident microbial communities play a significant role in maintaining the normal healthy function of the skin and the immune system. In turn, numerous host-associated and environmental factors influence these communities' composition and diversity across the cutaneous surface. In addition, specific compositional changes in skin microbiota have also been connected to the development of several chronic diseases. The current era of microbiome research is characterized by its reliance on large data sets of nucleotide sequences produced with high-throughput sequencing of sample-extracted DNA. These approaches have yielded new insights into many previously uncharacterized microbial communities. Application of standardized practices in the study of skin microbial communities could help us understand their complex structures, functional capacities, and health associations and increase the reproducibility of the research. Here, we overview the current research in human skin microbiomes and outline challenges specific to their study. Furthermore, we provide perspectives on recent advances in methods, analytical tools and applications of skin microbiomes in medicine and forensics.

Tracking bacterial pollution at a marine wastewater outfall site - A case study from Norway

Coastal marine environments are increasingly affected by anthropogenic impacts, such as the release of sewage at outfall sites and agricultural run-off. Fecal pollution introduced to the sea through these activities poses risks of spreading microbial diseases and disseminating antibiotic resistant bacteria and their genes. The study area of this research, Bore beach, is situated between two such point sources, an outfall site where treated sewage is released 1 km off the coast and a stream that carries run-off from an agricultural area to the northern end of the beach. In order to investigate whether and to what extent fecal contamination from the sewage outfall reached the beach, we used microbial source tracking, based on whole community analysis. Samples were collected from sea water at varying distances from the sewage outfall site and along the beach, as well as from the sewage effluent and the stream. Amplicon sequencing of 16S rRNA genes from all the collected samples was carried out at two time points (June and September). In addition, the seawater at the sewage outfall site and the sewage effluent were subject to shotgun metagenomics. To estimate the contribution of the sewage effluent and the stream to the microbial communities at Bore beach, we employed SourceTracker2, a program that uses a Bayesian algorithm to perform such quantification. The SourceTracker2 results suggested that the sewage effluent is likely to spread fecal contamination towards the beach to a greater extent than anticipated based on the prevailing sea current. The estimated mixing proportions of sewage at the near-beach site (P4) were 0.22 and 0.035% in June and September, respectively. This was somewhat below that stream's contribution in June (0.028%) and 10-fold higher than the stream's contribution in September (0.004%). Our analysis identified a sewage signal in all the tested seawater samples.

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches

The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the niches where samples originate. However, current methods face challenges when source tracking is scaled up. Here, we introduce a deep learning method based on the Ontology-aware Neural Network approach, ONN4MST, for large-scale source tracking. ONN4MST outperformed other methods with near-optimal accuracy when source tracking among 125,823 samples from 114 niches. ONN4MST also has a broad spectrum of applications. Overall, this study represents the first model-based method for source tracking among sub-million microbial community samples from hundreds of niches, with superior speed, accuracy, and interpretability. ONN4MST is available at https://github.com/HUST-NingKang-Lab/ONN4MST.

Species-Resolved Metagenomics of Kindergarten Microbiomes Reveal Microbial Admixture Within Sites and Potential Microbial Hazards

Microbiomes on surfaces in kindergartens, the intermediate transfer medium for microbial exchange, can exert significant impact on the hygiene and wellbeing of young children, both individually and as a community. Here employing 2bRAD-M, a novel species-resolved metagenomics approach for low-biomass microbiomes, we surveyed over 100 samples from seven frequently contacted surfaces by children, plus individual children’s palms, in two kindergartens. Microbiome compositions, although kindergarten-specific, were grouped closely based on the type of surface within each kindergarten. Extensive microbial admixture were found among the various sampled sites, likely facilitated by contact with children’s hands. Notably, bacterial species with potential human health concerns and potentially antibiotic-resistant, although found across all sampled locations, were predominantly enriched on children’s hands instead of on the environmental sites. This first species-resolved kindergarten microbiome survey underscores the importance of good hand hygiene practices in kindergartens and provides insights into better managing hygiene levels and minimizing spread of harmful microbes in susceptible indoor environments.

Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis

Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2 × 2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after 6 weeks of treatment, versus 2 of 11 non-pretreated patients (log odds ratio: 1.69, 95% confidence interval: −0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer.

Relationships Between Diurnal Changes of Tongue Coating Microbiota and Intestinal Microbiota

The oral cavity and the intestine are the main distribution locations of human digestive bacteria. Exploring the relationships between the tongue coating and gut microbiota, the influence of the diurnal variations of the tongue coating microbiota on the intestinal microbiota can provide a reference for the development of the disease diagnosis and monitoring, as well as the medication time. In this work, a total of 39 healthy college students were recruited. We collected their tongue coating microbiota which was collected before and after sleep and fecal microbiota. The diurnal variations of tongue coating microbiota are mainly manifested on the changes in diversity and relative abundance. There are commensal bacteria in the tongue coating and intestines, especially Prevotella which has the higher proportion in both sites. The relative abundance of Prevotella in the tongue coating before sleep has a positive correlation with intestinal Prevotella; the r is 0.322 (p < 0.05). Bacteroides in the intestine had the most bacteria associated with the tongue coating and had the highest correlation coefficient with Veillonella in the oral cavity, which was 0.468 (p < 0.01). These results suggest that the abundance of the same flora in the two sites may have a common change trend. The SourceTracker results show that the proportion of intestinal bacteria sourced from tongue coating is less than 1%. It indicates that oral flora is difficult to colonize in the intestine in healthy people. This will provide a reference for the study on the oral and intestinal microbiota in diseases.

Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of β-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.

Metagenome-Wide Analysis of Rural and Urban Surface Waters and Sediments in Bangladesh Identifies Human Waste as a Driver of Antibiotic Resistance

In many low- and middle-income countries, antibiotic-resistant bacteria spread in the environment due to inadequate treatment of wastewater and the poorly regulated use of antibiotics in agri- and aquaculture. Here, we characterized the abundance and diversity of antibiotic-resistant bacteria and antibiotic resistance genes in surface waters and sediments in Bangladesh through quantitative culture of extended-spectrum beta-lactamase (ESBL)-producing coliforms and shotgun metagenomics. Samples were collected from highly urbanized settings (n = 7), rural ponds with a history of aquaculture-related antibiotic use (n = 11), and rural ponds with no history of antibiotic use (n = 6). ESBL-producing coliforms were found to be more prevalent in urban samples than in rural samples. Shotgun sequencing showed that sediment samples were dominated by the phylum Proteobacteria (on average, 73.8% of assigned reads), while in the water samples, Cyanobacteria were the predominant phylum (on average, 60.9% of assigned reads). Antibiotic resistance genes were detected in all samples, but their abundance varied 1,525-fold between sites, with the highest levels of antibiotic resistance genes being present in urban surface water samples. The abundance of antibiotic resistance genes was significantly correlated (R² = 0.73; P = 8.9 × 10⁻¹⁵) with the abundance of bacteria originating from the human gut, which suggests that the release of untreated sewage is a driver for the spread of environmental antibiotic resistance genes in Bangladesh, particularly in highly urbanized settings.

IMPORTANCE Low- and middle-income countries (LMICs) have higher burdens of multidrug-resistant infections than high-income countries, and there is thus an urgent need to elucidate the drivers of the spread of antibiotic-resistant bacteria in LMICs. Here, we study the diversity and abundance of antibiotic resistance genes in surface water and sediments from rural and urban settings in Bangladesh. We found that urban surface waters are particularly rich in antibiotic resistance genes, with a higher number of them associated with plasmids, indicating that they are more likely to spread horizontally. The abundance of antibiotic resistance genes was strongly correlated with the abundance of bacteria that originate from the human gut, suggesting that uncontrolled release of human waste is a major driver for the spread of antibiotic resistance in the urban environment. Improvements in sanitation in LMICs may thus be a key intervention to reduce the dissemination of antibiotic-resistant bacteria.

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

Analysis on herbal medicines utilized for treatment of COVID-19

As coronavirus disease 2019 (COVID-19) pandemic poses a substantial global public health threat, traditional Chinese medicine (TCM) was used in 91.50% of the COVID-19 cases in China, showing encouraging results in improving symptom management and reducing the deterioration, mortality, and recurrence rates. A total of 166 modified herbal formulae consisting of 179 single herbal medicines were collected for treating COVID-19 in China. Glycyrrhizae Radix et Rhizome, Scutellariae Radix, and Armeniacae Semen Amarum are the most frequently utilized in clinics, most of which are antipyretic (47, 26.26%), expectorant and cough-suppressing (22, 12.29%), and dampness-resolving (21, 11.73%) from traditional descriptions. A total of 1212 chemical components containing β-sitosterol, stigmasterol, and quercetin were primarily selected. Additionally, using complex system entropy and unsupervised hierarchical clustering, 8 core herbal combinations and 10 new formulae emerged as potentially useful candidates for COVID-19. Finally, following scaffold analysis, self-organizing mapping (SOM) and cluster analysis, 12 clusters of molecules yielded 8 pharmacophore families of structures that were further screened as pharmacological targets in human metabolic pathways for inhibiting coronavirus. This article aims to make more easily accessible and share historical herbal knowledge used in contemporary treatments in a modern manner to assist researchers contain the global spread of COVID-19.