Automated centrifugal microfluidic system for the preparation of adaptor-ligated sequencing libraries.

The intensive workload associated with the preparation of high-quality DNA libraries remains a key obstacle toward widespread deployment of sequencing technologies in remote and resource-limited areas. We describe the development of single-use microfluidic devices driven by an advanced pneumatic centrifugal microfluidic platform, the PowerBlade, to automate the preparation of Illumina-compatible libraries based on adaptor ligation methodology. The developed on-chip workflow includes enzymatic DNA fragmentation coupled to end-repair, adaptor ligation, first DNA cleanup, PCR amplification, and second DNA cleanup. This complex workflow was successfully integrated into simple thermoplastic microfluidic devices that are amenable to mass production with injection molding. The system was validated by preparing, on chip, libraries from a mixture of genomic DNA extracted from three common foodborne pathogens (Listeria monocytogenes, Escherichia coli and Salmonella enterica serovar Typhimurium) and comparing them with libraries made via a manual procedure. The two types of libraries were found to exhibit similar quality control metrics (including genome coverage, assembly, and relative abundances) and led to nearly uniform coverage independent of GC content. This microfluidic technology offers a time-saving and cost-effective alternative to manual procedures and robotic-based automation, making it suitable for deployment in remote environments where technical expertise and resources might be scarce. Specifically, it facilitates field practices that involve mid- to low-throughput sequencing, such as tasks related to foodborne pathogen detection, characterization, and microbial profiling.

Community composition and the environment modulate the population dynamics of type VI secretion in human gut bacteria.

Understanding the relationship between the composition of the human gut microbiota and the ecological forces shaping it is of great importance; however, knowledge of the biogeographical and ecological relationships between physically interacting taxa is limited. Interbacterial antagonism may play an important role in gut community dynamics, yet the conditions under which antagonistic behaviour is favoured or disfavoured by selection in the gut are not well understood. Here, using genomics, we show that a species-specific type VI secretion system (T6SS) repeatedly acquires inactivating mutations in Bacteroides fragilis in the human gut. This result implies a fitness cost to the T6SS, but we could not identify laboratory conditions under which such a cost manifests. Strikingly, experiments in mice illustrate that the T6SS can be favoured or disfavoured in the gut depending on the strains and species in the surrounding community and their susceptibility to T6SS antagonism. We use ecological modelling to explore the conditions that could underlie these results and find that community spatial structure modulates interaction patterns among bacteria, thereby modulating the costs and benefits of T6SS activity. Our findings point towards new integrative models for interrogating the evolutionary dynamics of type VI secretion and other modes of antagonistic interaction in microbiomes.

Prolonged delays in human microbiota transmission after a controlled antibiotic perturbation.

Humans constantly encounter new microbes, but few become long-term residents of the adult gut microbiome. Classical theories predict that colonization is determined by the availability of open niches, but it remains unclear whether other ecological barriers limit commensal colonization in natural settings. To disentangle these effects, we used a controlled perturbation with the antibiotic ciprofloxacin to investigate the dynamics of gut microbiome transmission in 22 households of healthy, cohabiting adults. Colonization was rare in three-quarters of antibiotic-taking subjects, whose resident strains rapidly recovered in the week after antibiotics ended. In contrast, the remaining antibiotic-taking subjects exhibited lasting responses, with extensive species losses and transient expansions of potential opportunistic pathogens. These subjects experienced elevated rates of commensal colonization, but only after long delays: many new colonizers underwent sudden, correlated expansions months after the antibiotic perturbation. Furthermore, strains that had previously transmitted between cohabiting partners rarely recolonized after antibiotic disruptions, showing that colonization displays substantial historical contingency. This work demonstrates that there remain substantial ecological barriers to colonization even after major microbiome disruptions, suggesting that dispersal interactions and priority effects limit the pace of community change.

Persistent delay in maturation of the developing gut microbiota in infants with cystic fibrosis.

The healthy human infant gut microbiome undergoes stereotypical changes in taxonomic composition between birth and maturation to an adult-like stable state. During this time, extensive communication between microbiota and the host immune system contributes to health status later in life. Although there are many reported associations between microbiota compositional alterations and disease in adults, less is known about how microbiome development is altered in pediatric diseases. One pediatric disease linked to altered gut microbiota composition is cystic fibrosis (CF), a multi-organ genetic disease involving impaired chloride secretion across epithelia and heightened inflammation both in the gut and at other body sites. Here, we use shotgun metagenomics to profile the strain-level composition and developmental dynamics of the infant fecal microbiota from several CF and non-CF longitudinal cohorts spanning from birth to greater than 36 months of life. We identify a set of keystone species whose prevalence and abundance reproducibly define microbiota development in early life in non-CF infants, but are missing or decreased in relative abundance in infants with CF. The consequences of these CF-specific differences in gut microbiota composition and dynamics are a delayed pattern of microbiota maturation, persistent entrenchment in a transitional developmental phase, and subsequent failure to attain an adult-like stable microbiota. We also detect the increased relative abundance of oral-derived bacteria and higher levels of fungi in CF, features that are associated with decreased gut bacterial density in inflammatory bowel diseases. Our results define key differences in the gut microbiota during ontogeny in CF and suggest the potential for directed therapies to overcome developmental delays in microbiota maturation.

Community composition and the environment modulate the population dynamics of type VI secretion in human gut bacteria.

Understanding the relationship between the composition of the human gut microbiota and the ecological forces shaping it is of high importance as progress towards therapeutic modulation of the microbiota advances. However, given the inaccessibility of the gastrointestinal tract, our knowledge of the biogeographical and ecological relationships between physically interacting taxa has been limited to date. It has been suggested that interbacterial antagonism plays an important role in gut community dynamics, but in practice the conditions under which antagonistic behavior is favored or disfavored by selection in the gut environment are not well known. Here, using phylogenomics of bacterial isolate genomes and analysis of infant and adult fecal metagenomes, we show that the contact-dependent type VI secretion system (T6SS) is repeatedly lost from the genomes of Bacteroides fragilis in adults compare to infants. Although this result implies a significant fitness cost to the T6SS, but we could not identify in vitro conditions under which such a cost manifests. Strikingly, however, experiments in mice illustrated that the B. fragilis T6SS can be favored or disfavored in the gut environment, depending on the strains and species in the surrounding community and their susceptibility to T6SS antagonism. We use a variety of ecological modeling techniques to explore the possible local community structuring conditions that could underlie the results of our larger scale phylogenomic and mouse gut experimental approaches. The models illustrate robustly that the pattern of local community structuring in space can modulate the extent of interactions between T6SS-producing, sensitive, and resistant bacteria, which in turn control the balance of fitness costs and benefits of performing contact-dependent antagonistic behavior. Taken together, our genomic analyses, in vivo studies, and ecological theory point toward new integrative models for interrogating the evolutionary dynamics of type VI secretion and other predominant modes of antagonistic interaction in diverse microbiomes.

A Bayesian method for identifying associations between response variables and bacterial community composition.

Determining associations between intestinal bacteria and continuously measured physiological outcomes is important for understanding the bacteria-host relationship but is not straightforward since abundance data (compositional data) are not normally distributed. To address this issue, we developed a fully Bayesian linear regression model (BRACoD; Bayesian Regression Analysis of Compositional Data) with physiological measurements (continuous data) as a function of a matrix of relative bacterial abundances. Bacteria can be classified as operational taxonomic units or by taxonomy (genus, family, etc.). Bacteria associated with the physiological measurement were identified using a Bayesian variable selection method: Stochastic Search Variable Selection. The output is a list of inclusion probabilities ([Formula: see text]) and coefficients that indicate the strength of the association ([Formula: see text]) for each bacterial taxa. Tests with simulated communities showed that adopting a cut point value of [Formula: see text] ≥ 0.3 for identifying included bacteria optimized the true positive rate (TPR) while maintaining a false positive rate (FPR) of ≤ 5%. At this point, the chances of identifying non-contributing bacteria were low and all well-established contributors were included. Comparison with other methods showed that BRACoD (at [Formula: see text] ≥ 0.3) had higher precision and a higher TPR than a commonly used center log transformed LASSO procedure (clr-LASSO) as well as higher TPR than an off-the-shelf Spike and Slab method after center log transformation (clr-SS). BRACoD was also less likely to include non-contributing bacteria that merely correlate with contributing bacteria. Analysis of a rat microbiome experiment identified 47 operational taxonomic units that contributed to fecal butyrate levels. Of these, 31 were positively and 16 negatively associated with butyrate. Consistent with their known role in butyrate metabolism, most of these fell within the Lachnospiraceae and Ruminococcaceae. We conclude that BRACoD provides a more precise and accurate method for determining bacteria associated with a continuous physiological outcome compared to clr-LASSO. It is more sensitive than a generalized clr-SS algorithm, although it has a higher FPR. Its ability to distinguish genuine contributors from correlated bacteria makes it better suited to discriminating bacteria that directly contribute to an outcome. The algorithm corrects for the distortions arising from compositional data making it appropriate for analysis of microbiome data.

Application of natural language processing algorithms for extracting information from news articles in event-based surveillance.

The focus of this article is the application of natural language processing (NLP) for information extraction in event-based surveillance (EBS) systems. We describe common information extraction applications from open-source news articles and media sources in EBS systems, methods, value in public health, challenges and emerging developments.

MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline.

BACKGROUND: Microbial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community's constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems. RESULTS: Here we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality. CONCLUSIONS: MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.

Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries.

BACKGROUND: Salmonella enterica is a leading cause of foodborne illness worldwide resulting in considerable public health and economic costs. Testing for the presence of this pathogen in food is often hampered by the presence of background microflora that may present as Salmonella (false positives). False positive isolates belonging to the genus Citrobacter can be difficult to distinguish from Salmonella due to similarities in their genetics, cell surface antigens, and other phenotypes. In order to understand the genetic basis of these similarities, a comparative genomic approach was used to define the pan-, core, accessory, and unique coding sequences of a representative population of Salmonella and Citrobacter strains. RESULTS: Analysis of the genomic content of 58 S. enterica strains and 37 Citrobacter strains revealed the presence of 31,130 and 1540 coding sequences within the pan- and core genome of this population. Amino acid sequences unique to either Salmonella (n = 1112) or Citrobacter (n = 195) were identified and revealed potential niche-specific adaptations. Phylogenetic network analysis of the protein families encoded by the pan-genome indicated that genetic exchange between Salmonella and Citrobacter may have led to the acquisition of similar traits and also diversification within the genera. CONCLUSIONS: Core genome analysis suggests that the Salmonella enterica and Citrobacter populations investigated here share a common evolutionary history. Comparative analysis of the core and pan-genomes was able to define the genetic features that distinguish Salmonella from Citrobacter and highlight niche specific adaptations.

Human gut bacteria contain acquired interbacterial defence systems.

The human gastrointestinal tract consists of a dense and diverse microbial community, the composition of which is intimately linked to health. Extrinsic factors such as diet and host immunity are insufficient to explain the constituents of this community, and direct interactions between co-resident microorganisms have been implicated as important drivers of microbiome composition. The genomes of bacteria derived from the gut microbiome contain several pathways that mediate contact-dependent interbacterial antagonism1-3. Many members of the Gram-negative order Bacteroidales encode the type VI secretion system (T6SS), which facilitates the delivery of toxic effector proteins into adjacent cells4,5. Here we report the occurrence of acquired interbacterial defence (AID) gene clusters in Bacteroidales species that reside within the human gut microbiome. These clusters encode arrays of immunity genes that protect against T6SS-mediated intra- and inter-species bacterial antagonism. Moreover, the clusters reside on mobile elements, and we show that their transfer is sufficient to confer resistance to toxins in vitro and in gnotobiotic mice. Finally, we identify and validate the protective capability of a recombinase-associated AID subtype (rAID-1) that is present broadly in Bacteroidales genomes. These rAID-1 gene clusters have a structure suggestive of active gene acquisition and include predicted immunity factors of toxins derived from diverse organisms. Our data suggest that neutralization of contact-dependent interbacterial antagonism by AID systems helps to shape human gut microbiome ecology.

Competitive lottery-based assembly of selected clades in the human gut microbiome.

BACKGROUND: While the composition of the gut microbiome has now been well described by several large-scale studies, models that can account for the range of microbiome compositions that have been observed are still lacking. One model that has been well studied in macro communities and that could be useful for understanding microbiome assembly is the competitive lottery model. This model posits that groups of organisms from a regional pool of species are able to colonize the same niche and that the first species to arrive will take over the entire niche, excluding other group members. RESULTS: Here, we examined whether this model also plays a role in the assembly of the human gut microbiome, defining measures to identify groups of organisms whose distribution across samples conforms to the competitive lottery schema. Applying this model to multiple datasets with thousands of human gut microbiome samples, we identified several taxonomic groups that exhibit a lottery-like distribution, including the Akkermansia, Dialister, and Phascolarctobacterium genera. We validated that these groups exhibit lottery-like assembly in multiple independent microbiome datasets confirming that this assembly schema is universal and not cohort specific. Examining the distribution of species from these groups in the gut microbiome of developing infants, we found that the initial lottery winner can be replaced by a different member of the group. We further found that species from lottery-like groups tend to have fewer genes in their genomes, suggesting more specialized species that are less able to engage in niche differentiation. CONCLUSIONS: Combined, our findings highlight the complex and dynamic process through which microbial communities assemble and suggest that different phylogenetic groups may follow different models during this process.

The Landscape of Type VI Secretion across Human Gut Microbiomes Reveals Its Role in Community Composition.

Although gut microbiome composition is well defined, the mechanisms underlying community assembly remain poorly understood. Bacteroidales possess three genetic architectures (GA1-3) of the type VI secretion system (T6SS), an effector delivery pathway that mediates interbacterial competition. Here we define the distribution and role of GA1-3 in the human gut using metagenomic analysis. We find that adult microbiomes harbor limited effector and cognate immunity genes, suggesting selection for compatibility at the species (GA1 and GA2) and strain (GA3) levels. Bacteroides fragilis GA3 is known to mediate potent inter-strain competition, and we observe GA3 enrichment among strains colonizing infant microbiomes, suggesting competition early in life. Additionally, GA3 is associated with increased Bacteroides abundance, indicating that this system confers an advantage in Bacteroides-rich ecosystems. Collectively, these analyses uncover the prevalence of T6SS-dependent competition and reveal its potential role in shaping human gut microbial composition.

Taxonomically Restricted Genes with Essential Functions Frequently Play Roles in Chromosome Segregation in Caenorhabditis elegans and Saccharomyces cerevisiae.

Genes encoding essential components of core cellular processes are typically highly conserved across eukaryotes. However, a small proportion of essential genes are highly taxonomically restricted; there appear to be no similar genes outside the genomes of highly related species. What are the functions of these poorly characterized taxonomically restricted genes (TRGs)? Systematic screens in Saccharomyces cerevisiae and Caenorhabditis elegans previously identified yeast or nematode TRGs that are essential for viability and we find that these genes share many molecular features, despite having no significant sequence similarity. Specifically, we find that those TRGs with essential phenotypes have an expression profile more similar to highly conserved genes, they have more protein-protein interactions and more protein disorder. Surprisingly, many TRGs play central roles in chromosome segregation; a core eukaryotic process. We thus find that genes that appear to be highly evolutionarily restricted do not necessarily play roles in species-specific biological functions but frequently play essential roles in core eukaryotic processes.

A broadly distributed toxin family mediates contact-dependent antagonism between gram-positive bacteria.

The Firmicutes are a phylum of bacteria that dominate numerous polymicrobial habitats of importance to human health and industry. Although these communities are often densely colonized, a broadly distributed contact-dependent mechanism of interbacterial antagonism utilized by Firmicutes has not been elucidated. Here we show that proteins belonging to the LXG polymorphic toxin family present in Streptococcus intermedius mediate cell contact- and Esx secretion pathway-dependent growth inhibition of diverse Firmicute species. The structure of one such toxin revealed a previously unobserved protein fold that we demonstrate directs the degradation of a uniquely bacterial molecule required for cell wall biosynthesis, lipid II. Consistent with our functional data linking LXG toxins to interbacterial interactions in S. intermedius, we show that LXG genes are prevalent in the human gut microbiome, a polymicrobial community dominated by Firmicutes. We speculate that interbacterial antagonism mediated by LXG toxins plays a critical role in shaping Firmicute-rich bacterial communities.

Exploring Quantitative Yeast Phenomics with Single-Cell Analysis of DNA Damage Foci.

A significant challenge of functional genomics is to develop methods for genome-scale acquisition and analysis of cell biological data. Here, we present an integrated method that combines genome-wide genetic perturbation of Saccharomyces cerevisiae with high-content screening to facilitate the genetic description of sub-cellular structures and compartment morphology. As proof of principle, we used a Rad52-GFP marker to examine DNA damage foci in ∼20 million single cells from ∼5,000 different mutant backgrounds in the context of selected genetic or chemical perturbations. Phenotypes were classified using a machine learning-based automated image analysis pipeline. 345 mutants were identified that had elevated numbers of DNA damage foci, almost half of which were identified only in sensitized backgrounds. Subsequent analysis of Vid22, a protein implicated in the DNA damage response, revealed that it acts together with the Sgs1 helicase at sites of DNA damage and preferentially binds G-quadruplex regions of the genome. This approach is extensible to numerous other cell biological markers and experimental systems.

High-Content Screening for Quantitative Cell Biology.

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future.

Natural Variation in Gene Expression Modulates the Severity of Mutant Phenotypes.

Many mutations cause genetic disorders. However, two people inheriting the same mutation often have different severity of symptoms, and this is partly genetic. The effects of genetic background on mutant phenotypes are poorly understood, but predicting them is critical for personalized medicine. To study this phenomenon comprehensively and systematically, we used RNAi to compare loss-of-function phenotypes for ∼1,400 genes in two isolates of C. elegans and find that ∼20% of genes differ in the severity of phenotypes in these two genetic backgrounds. Crucially, this effect of genetic background on the severity of both RNAi and mutant phenotypes can be predicted from variation in the expression levels of the affected gene. This is also true in mammalian cells, suggesting it is a general property of genetic networks. We suggest that differences in the manifestation of mutant phenotypes between individuals are largely the result of natural variation in gene expression.

Prediction of steps in the evolution of variola virus host range.

Variola virus, the agent of smallpox, has a severely restricted host range (humans) but a devastatingly high mortality rate. Although smallpox has been eradicated by a World Health Organization vaccination program, knowledge of the evolutionary processes by which human super-pathogens such as variola virus arise is important. By analyzing the evolution of variola and other closely related poxviruses at the level of single nucleotide polymorphisms we detected a hotspot of genome variation within the smallpox ortholog of the vaccinia virus O1L gene, which is known to be necessary for efficient replication of vaccinia virus in human cells. These mutations in the variola virus ortholog and the subsequent loss of the functional gene from camelpox virus and taterapox virus, the two closest relatives of variola virus, strongly suggest that changes within this region of the genome may have played a key role in the switch to humans as a host for the ancestral virus and the subsequent host-range restriction that must have occurred to create the phenotype exhibited by smallpox.

Comparative RNAi screens in C. elegans and C. briggsae reveal the impact of developmental system drift on gene function.

Although two related species may have extremely similar phenotypes, the genetic networks underpinning this conserved biology may have diverged substantially since they last shared a common ancestor. This is termed Developmental System Drift (DSD) and reflects the plasticity of genetic networks. One consequence of DSD is that some orthologous genes will have evolved different in vivo functions in two such phenotypically similar, related species and will therefore have different loss of function phenotypes. Here we report an RNAi screen in C. elegans and C. briggsae to identify such cases. We screened 1333 genes in both species and identified 91 orthologues that have different RNAi phenotypes. Intriguingly, we find that recently evolved genes of unknown function have the fastest evolving in vivo functions and, in several cases, we identify the molecular events driving these changes. We thus find that DSD has a major impact on the evolution of gene function and we anticipate that the C. briggsae RNAi library reported here will drive future studies on comparative functional genomics screens in these nematodes.

The majority of animal genes are required for wild-type fitness.

Almost all eukaryotic genes are conserved, suggesting that they have essential functions. However, only a minority of genes have detectable loss-of-function phenotypes in experimental assays, and multiple theories have been proposed to explain this discrepancy. Here, we use RNA-mediated interference in C. elegans to examine how knockdown of any gene affects the overall fitness of worm populations. Whereas previous studies typically assess phenotypes that are detectable by eye after a single generation, we monitored growth quantitatively over several generations. In contrast to previous estimates, we find that, in these multigeneration population assays, the majority of genes affect fitness, and this suggests that genetic networks are not robust to mutation. Our results demonstrate that, in a single environmental condition, most animal genes play essential roles. This is a higher proportion than for yeast genes, and we suggest that the source of negative selection is different in animals and in unicellular eukaryotes.