Communicating computational workflows in a regulatory environment.

The volume of nucleic acid sequence data has exploded recently, amplifying the challenge of transforming data into meaningful information. Processing data can require an increasingly complex ecosystem of customized tools, which increases difficulty in communicating analyses in an understandable way yet is of sufficient detail to enable informed decisions or repeats. This can be of particular interest to institutions and companies communicating computations in a regulatory environment. BioCompute Objects (BCOs; an instance of pipeline documentation that conforms to the IEEE 2791-2020 standard) were developed as a standardized mechanism for analysis reporting. A suite of BCOs is presented, representing interconnected elements of a computation modeled after those that might be found in a regulatory submission but are shared publicly - in this case a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines.

Very early life microbiome and metabolome correlates with primary vaccination variability in children.

IMPORTANCE: We show that simultaneous study of stool and nasopharyngeal microbiome reveals divergent timing and patterns of maturation, suggesting that local mucosal factors may influence microbiome composition in the gut and respiratory system. Antibiotic exposure in early life as occurs commonly, may have an adverse effect on vaccine responsiveness. Abundance of gut and/or nasopharyngeal bacteria with the machinery to produce lipopolysaccharide-a toll-like receptor 4 agonist-may positively affect future vaccine protection, potentially by acting as a natural adjuvant. The increased levels of serum phenylpyruvic acid in infants with lower vaccine-induced antibody levels suggest an increased abundance of hydrogen peroxide, leading to more oxidative stress in low vaccine-responding infants.

Vaccine Hyporesponse Induced by Individual Antibiotic Treatment in Mice and Non-Human Primates Is Diminished upon Recovery of the Gut Microbiome.

Emerging evidence demonstrates a connection between microbiome composition and suboptimal response to vaccines (vaccine hyporesponse). Harnessing the interaction between microbes and the immune system could provide novel therapeutic strategies for improving vaccine response. Currently we do not fully understand the mechanisms and dynamics by which the microbiome influences vaccine response. Using both mouse and non-human primate models, we report that short-term oral treatment with a single antibiotic (vancomycin) results in the disruption of the gut microbiome and this correlates with a decrease in systemic levels of antigen-specific IgG upon subsequent parenteral vaccination. We further show that recovery of microbial diversity before vaccination prevents antibiotic-induced vaccine hyporesponse, and that the antigen specific IgG response correlates with the recovery of microbiome diversity. RNA sequencing analysis of small intestine, spleen, whole blood, and secondary lymphoid organs from antibiotic treated mice revealed a dramatic impact on the immune system, and a muted inflammatory signature is correlated with loss of bacteria from Lachnospiraceae, Ruminococcaceae, and Clostridiaceae. These results suggest that microbially modulated immune pathways may be leveraged to promote vaccine response and will inform future vaccine design and development strategies.

The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.

Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas, machine learning has excelled in natural language processing. As such methods have excelled at understanding written languages (e.g. English), they are also being applied to biological problems to better understand the "genomic language". In this review we focus on recent advances in applying machine learning to natural products and genomics, and how those advances are improving our understanding of natural product biology, chemistry, and drug discovery. We discuss machine learning applications in genome mining (identifying biosynthetic signatures in genomic data), predictions of what structures will be created from those genomic signatures, and the types of activity we might expect from those molecules. We further explore the application of these approaches to data derived from complex microbiomes, with a focus on the human microbiome. We also review challenges in leveraging machine learning approaches in the field, and how the availability of other "omics" data layers provides value. Finally, we provide insights into the challenges associated with interpreting machine learning models and the underlying biology and promises of applying machine learning to natural product drug discovery. We believe that the application of machine learning methods to natural product research is poised to accelerate the identification of new molecular entities that may be used to treat a variety of disease indications.

EukRef-excavates: seven curated SSU ribosomal RNA gene databases.

The small subunit ribosomal RNA (SSU rRNA) gene is a widely used molecular marker to study the diversity of life. Sequencing of SSU rRNA gene amplicons has become a standard approach for the investigation of the ecology and diversity of microbes. However, a well-curated database is necessary for correct classification of these data. While available for many groups of Bacteria and Archaea, such reference databases are absent for most eukaryotes. The primary goal of the EukRef project (eukref.org) is to close this gap and generate well-curated reference databases for major groups of eukaryotes, especially protists. Here we present a set of EukRef-curated databases for the excavate protists-a large assemblage that includes numerous taxa with divergent SSU rRNA gene sequences, which are prone to misclassification. We identified 6121 sequences, 625 of which were obtained from cultures, 3053 from cell isolations or enrichments and 2419 from environmental samples. We have corrected the classification for the majority of these curated sequences. The resulting publicly available databases will provide phylogenetically based standards for the improved identification of excavates in ecological and microbiome studies, as well as resources to classify new discoveries in excavate diversity.

Longitudinal Comparison of Bacterial Diversity and Antibiotic Resistance Genes in New York City Sewage.

Bacterial resistance to antibiotics is a pressing health issue around the world, not only in health care settings but also in the community and environment, particularly in crowded urban populations. The aim of our work was to characterize the microbial populations in sewage and the spread of antibiotic resistance within New York City (NYC). Here, we investigated the structure of the microbiome and the prevalence of antibiotic resistance genes in raw sewage samples collected from the fourteen NYC Department of Environmental Protection wastewater treatment plants, distributed across the five NYC boroughs. Sewage, a direct output of anthropogenic activity and a reservoir of microbes, provides an ecological niche to examine the spread of antibiotic resistance. Taxonomic diversity analysis revealed a largely similar and stable bacterial population structure across all the samples, which was found to be similar over three time points in an annual cycle, as well as in the five NYC boroughs. All samples were positive for the presence of the seven antibiotic resistance genes tested, based on real-time quantitative PCR assays, with higher levels observed for tetracycline resistance genes at all time points. For five of the seven genes, abundances were significantly higher in May than in February and August. This study provides characteristics of the NYC sewage resistome in the context of the overall bacterial populations.IMPORTANCE Urban sewage or wastewater is a diverse source of bacterial growth, as well as a hot spot for the development of environmental antibiotic resistance, which can in turn influence the health of the residents of the city. As part of a larger study to characterize the urban New York City microbial metagenome, we collected raw sewage samples representing three seasonal time points spanning the five boroughs of NYC and went on to characterize the microbiome and the presence of a range of antibiotic resistance genes. Through this study, we have established a baseline microbial population and antibiotic resistance abundance in NYC sewage which can prove to be very useful in studying the load of antibiotic usage, as well as for developing effective measures in antibiotic stewardship.

Patterns of protist diversity associated with raw sewage in New York City.

Protists are ubiquitous components of terrestrial and aquatic environments, as well as animal and human microbiomes. Despite this, little is known about protists in urban environments. The ~7400-mile sewer system of New York City (NYC) collects human waste from ~8 million human inhabitants as well as from animals, street runoff, and groundwater, providing an ideal system to study these microbes. We used 18S rRNA amplicon sequencing and shotgun metagenomic sequencing to profile raw sewage microbial communities. Raw sewage samples were collected over a 12-month period from 14 treatment plants of the five NYC boroughs, and compared with samples from other environments including soil, stormwater, and sediment. Sewage contained a diverse protist community dominated by free-living clades, and communities were highly differentiated across environments. Seasonal differences in protist composition were observed; however, network analysis and functional profiling demonstrated that sewage communities were robust and functionally consistent. Protists typically associated with human and animal guts or feces were frequently detected. Abundance of these parasites varied significantly both spatially and temporally, suggesting that spikes could reflect trends in the source population. This underscores sewage as a valuable model system for monitoring patterns in urban microbes and provides a baseline protist metagenome of NYC.

Overlapping Community Compositions of Gut and Fecal Microbiomes in Lab-Reared and Field-Collected German Cockroaches.

German cockroaches, Blattella germanica (Blattodea: Ectobiidae), are human commensals that move freely between food and waste, disseminating bacteria, including potential pathogens, through their feces. However, the relationship between the microbial communities of the cockroach gut and feces is poorly understood. We analyzed the V4 region of the 16S rRNA gene and the V9 region of the 18S rRNA gene by next-generation sequencing (NGS) to compare the bacterial and protist diversities in guts versus feces and males versus females, as well as assess variation across cockroach populations. Cockroaches harbored a diverse array of bacteria, and 80 to 90% of the operational taxonomic units (OTUs) were shared between the feces and gut. Lab-reared and field-collected cockroaches had distinct microbiota, and whereas lab-reared cockroaches had relatively conserved communities, considerable variation was observed in the microbial community composition of cockroaches collected in different apartments. Nonetheless, cockroaches from all locations shared some core bacterial taxa. The eukaryotic community in the feces of field-collected cockroaches was found to be more diverse than that in lab-reared cockroaches. These results demonstrate that cockroaches disseminate their gut microbiome in their feces, and they underscore the important contribution of the cockroach fecal microbiome to the microbial diversity of cockroach-infested homes.IMPORTANCE The German cockroach infests diverse human-built structures, including homes and hospitals. It produces potent allergens that trigger asthma and disseminates opportunistic pathogens in its feces. A comprehensive understanding of gut and fecal microbial communities of cockroaches is essential not only to understand their contribution to the biology of the cockroach, but also for exploring their clinical relevance. In this study, we compare the diversity of bacteria and eukaryotes in the cockroach gut and feces and assess the variation in the gut microbiota across cockroach populations.

An 18S rRNA Workflow for Characterizing Protists in Sewage, with a Focus on Zoonotic Trichomonads.

Microbial eukaryotes (protists) are important components of terrestrial and aquatic environments, as well as animal and human microbiomes. Their relationships with metazoa range from mutualistic to parasitic and zoonotic (i.e., transmissible between humans and animals). Despite their ecological importance, our knowledge of protists in urban environments lags behind that of bacteria, largely due to a lack of experimentally validated high-throughput protocols that produce accurate estimates of protist diversity while minimizing non-protist DNA representation. We optimized protocols for detecting zoonotic protists in raw sewage samples, with a focus on trichomonad taxa. First, we investigated the utility of two commonly used variable regions of the 18S rRNA marker gene, V4 and V9, by amplifying and Sanger sequencing 23 different eukaryotic species, including 16 protist species such as Cryptosporidium parvum, Giardia intestinalis, Toxoplasma gondii, and species of trichomonad. Next, we optimized wet-lab methods for sample processing and Illumina sequencing of both regions from raw sewage collected from a private apartment building in New York City. Our results show that both regions are effective at identifying several zoonotic protists that may be present in sewage. A combination of small extractions (1 mL volumes) performed on the same day as sample collection, and the incorporation of a vertebrate blocking primer, is ideal to detect protist taxa of interest and combat the effects of metazoan DNA. We expect that the robust, standardized methods presented in our workflow will be applicable to investigations of protists in other environmental samples, and will help facilitate large-scale investigations of protistan diversity.

Filthy lucre: A metagenomic pilot study of microbes found on circulating currency in New York City.

BACKGROUND: Paper currency by its very nature is frequently transferred from one person to another and represents an important medium for human contact with-and potential exchange of-microbes. In this pilot study, we swabbed circulating $1 bills obtained from a New York City bank in February (Winter) and June (Summer) 2013 and used shotgun metagenomic sequencing to profile the communities found on their surface. Using basic culture conditions, we also tested whether viable microbes could be recovered from bills. RESULTS: Shotgun metagenomics identified eukaryotes as the most abundant sequences on money, followed by bacteria, viruses and archaea. Eukaryotic assemblages were dominated by human, other metazoan and fungal taxa. The currency investigated harbored a diverse microbial population that was dominated by human skin and oral commensals, including Propionibacterium acnes, Staphylococcus epidermidis and Micrococcus luteus. Other taxa detected not associated with humans included Lactococcus lactis and Streptococcus thermophilus, microbes typically associated with dairy production and fermentation. Culturing results indicated that viable microbes can be isolated from paper currency. CONCLUSIONS: We conducted the first metagenomic characterization of the surface of paper money in the United States, establishing a baseline for microbes found on $1 bills circulating in New York City. Our results suggest that money amalgamates DNA from sources inhabiting the human microbiome, food, and other environmental inputs, some of which can be recovered as viable organisms. These monetary communities may be maintained through contact with human skin, and DNA obtained from money may provide a record of human behavior and health. Understanding these microbial profiles is especially relevant to public health as money could potentially mediate interpersonal transfer of microbes.

Microbial Community Patterns Associated with Automated Teller Machine Keypads in New York City.

In densely populated urban environments, the distribution of microbes and the drivers of microbial community assemblages are not well understood. In sprawling metropolitan habitats, the "urban microbiome" may represent a mix of human-associated and environmental taxa. Here we carried out a baseline study of automated teller machine (ATM) keypads in New York City (NYC). Our goal was to describe the biodiversity and biogeography of both prokaryotic and eukaryotic microbes in an urban setting while assessing the potential source of microbial assemblages on ATM keypads. Microbial swab samples were collected from three boroughs (Manhattan, Queens, and Brooklyn) during June and July 2014, followed by generation of Illumina MiSeq datasets for bacterial (16S rRNA) and eukaryotic (18S rRNA) marker genes. Downstream analysis was carried out in the QIIME pipeline, in conjunction with neighborhood metadata (ethnicity, population, age groups) from the NYC Open Data portal. Neither the 16S nor 18S rRNA datasets showed any clustering patterns related to geography or neighborhood demographics. Bacterial assemblages on ATM keypads were dominated by taxonomic groups known to be associated with human skin communities (Actinobacteria, Bacteroides, Firmicutes, and Proteobacteria), although SourceTracker analysis was unable to identify the source habitat for the majority of taxa. Eukaryotic assemblages were dominated by fungal taxa as well as by a low-diversity protist community containing both free-living and potentially pathogenic taxa (Toxoplasma, Trichomonas). Our results suggest that ATM keypads amalgamate microbial assemblages from different sources, including the human microbiome, eukaryotic food species, and potentially novel extremophilic taxa adapted to air or surfaces in the built environment. DNA obtained from ATM keypads may thus provide a record of both human behavior and environmental sources of microbes. IMPORTANCE Automated teller machine (ATM) keypads represent a specific and unexplored microhabitat for microbial communities. Although the number of built environment and urban microbial ecology studies has expanded greatly in recent years, the majority of research to date has focused on mass transit systems, city soils, and plumbing and ventilation systems in buildings. ATM surfaces, potentially retaining microbial signatures of human inhabitants, including both commensal taxa and pathogens, are interesting from both a biodiversity perspective and a public health perspective. By focusing on ATM keypads in different geographic areas of New York City with distinct population demographics, we aimed to characterize the diversity and distribution of both prokaryotic and eukaryotic microbes, thus making a unique contribution to the growing body of work focused on the "urban microbiome." In New York City, the surface area of urban surfaces in Manhattan far exceeds the geographic area of the island itself. We have only just begun to describe the vast array of microbial taxa that are likely to be present across diverse types of urban habitats.

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

The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for harmless genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can reveal a station's history, such as marine-associated bacteria in a hurricane-flooded station. Some evidence of pathogens was found (Bacillus anthracis), but a lack of reported cases in NYC suggests that the pathogens represent a normal, urban microbiome. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of cities.

What is the importance of zoonotic trichomonads for human health?

Trichomonads are common parasites of many vertebrate and invertebrate species, with four species classically recognized as human parasites: Dientamoeba fragilis, Pentatrichomonas hominis, Trichomonas vaginalis, and Trichomonas tenax. The latter two species are considered human-specific; by contrast, D. fragilis and P. hominis have been isolated from domestic and farm mammals, demonstrating a wide host range and potential zoonotic origin. Several new studies have highlighted the zoonotic dimension of trichomonads. First, species typically known to infect birds and domestic mammals have been identified in human clinical samples. Second, several phylogenetic analyses have identified animal-derived trichomonads as close sister taxa of the two human-specific species. It is our opinion, therefore, that these observations prompt further investigation into the importance of zoonotic trichomonads for human health.