Ecological drivers of CRISPR immune systems.

CRISPR-Cas is the only known adaptive immune system of prokaryotes. It is a powerful defense system against mobile genetic elements such as bacteriophages. While CRISPR-Cas systems can be found throughout the prokaryotic tree of life, they are distributed unevenly across taxa and environments. Since adaptive immunity is more useful in environments where pathogens persist or reoccur, the density and/or diversity of the host/pathogen community may drive the uneven distribution of CRISPR system. We directly tested hypotheses connecting CRISPR incidence with prokaryotic density/diversity by analyzing 16S rRNA and metagenomic data from publicly available environmental sequencing projects. In terms of density, we found that CRISPR systems are significantly favored in lower abundance (less dense) taxa and disfavored in higher abundance taxa, at least in marine environments. When we extended this work to compare taxonomic diversity between samples, we found CRISPR system incidence strongly correlated with diversity in human oral environments. Together, these observations confirm that, at least in certain types of environments, the prokaryotic ecological context indeed plays a key role in selecting for CRISPR immunity. Importance: 2Microbes must constantly defend themselves against viral pathogens, and a large proportion of prokaryotes do so using the highly effective CRISPR-Cas adaptive immune system. However, many prokaryotes do not. We investigated the ecological factors behind this uneven distribution of CRISPR-Cas immune systems in natural microbial populations. We found strong patterns linking CRISPR-Cas systems to prokaryotic density within ocean environments and to prokaryotic diversity within human oral environments. Our study validates previous within-lab experimental results that suggested these factors might be important and confirms that local environment and ecological context interact to select for CRISPR immunity.

GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren's Disease.

Sjögren's Disease (SjD) is a systemic autoimmune disease without a clear etiology or effective therapy. Utilizing unbiased single-cell and spatial transcriptomics to analyze human minor salivary glands in health and disease we developed a comprehensive understanding of the cellular landscape of healthy salivary glands and how that landscape changes in SjD patients. We identified novel seromucous acinar cell types and identified a population of PRR4+CST3+WFDC2- seromucous acinar cells that are particularly targeted in SjD. Notably, GZMK+CD8 T cells, enriched in SjD, exhibited a cytotoxic phenotype and were physically associated with immune-engaged epithelial cells in disease. These findings shed light on the immune response's impact on transitioning acinar cells with high levels of secretion and explain the loss of this specific cell population in SjD. This study explores the complex interplay of varied cell types in the salivary glands and their role in the pathology of Sjögren's Disease.

Evolution of the Growth Hormone Gene Duplication in Passerine Birds.

Birds of the order Passeriformes represent the most speciose order of land vertebrates. Despite strong scientific interest in this super-radiation, genetic traits unique to passerines are not well characterized. A duplicate copy of growth hormone (GH) is the only gene known to be present in all major lineages of passerines, but not in other birds. GH genes plausibly influence extreme life history traits that passerines exhibit, including the shortest embryo-to-fledging developmental period of any avian order. To unravel the implications of this GH duplication, we investigated the molecular evolution of the ancestral avian GH gene (GH or GH1) and the novel passerine GH paralog (GH2), using 497 gene sequences extracted from 342 genomes. Passerine GH1 and GH2 are reciprocally monophyletic, consistent with a single duplication event from a microchromosome onto a macrochromosome in a common ancestor of extant passerines. Additional chromosomal rearrangements have changed the syntenic and potential regulatory context of these genes. Both passerine GH1 and GH2 display substantially higher rates of nonsynonymous codon change than non-passerine avian GH, suggesting positive selection following duplication. A site involved in signal peptide cleavage is under selection in both paralogs. Other sites under positive selection differ between the two paralogs, but many are clustered in one region of a 3D model of the protein. Both paralogs retain key functional features and are actively but differentially expressed in two major passerine suborders. These phenomena suggest that GH genes may be evolving novel adaptive roles in passerine birds.

Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations.

Infectious zoonotic diseases are a threat to wildlife conservation and global health. They are especially a concern for wild apes, which are vulnerable to many human infectious diseases. As ecotourism, deforestation, and great ape field research increase, the threat of human-sourced infections to wild populations becomes more substantial and could result in devastating population declines. The endangered mountain gorillas (Gorilla beringei beringei) of the Virunga Massif in east-central Africa suffer periodic disease outbreaks and are exposed to infections from human-sourced pathogens. It is important to understand the possible risks of disease introduction and spread in this population and how human contact may facilitate disease transmission. Here we present and evaluate an individual-based, stochastic, discrete-time disease transmission model to predict epidemic outcomes and better understand health risks to the Virunga mountain gorilla population. To model disease transmission we have derived estimates for gorilla contact, interaction, and migration rates. The model shows that the social structure of gorilla populations plays a profound role in governing disease impacts with subdivided populations experiencing less than 25% of the outbreak levels of a single homogeneous population. It predicts that gorilla group dispersal and limited group interactions are strong factors in preventing widespread population-level outbreaks of infectious disease after such diseases have been introduced into the population. However, even a moderate amount of human contact increases disease spread and can lead to population-level outbreaks.

Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.

Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency of YFV-specific memory CD8 T cells and deuterium enrichment in those cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.1% per day, ∼ double the estimated values for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically.

Exploring the functional composition of the human microbiome using a hand-curated microbial trait database.

BACKGROUND: Even when microbial communities vary wildly in their taxonomic composition, their functional composition is often surprisingly stable. This suggests that a functional perspective could provide much deeper insight into the principles governing microbiome assembly. Much work to date analyzing the functional composition of microbial communities, however, relies heavily on inference from genomic features. Unfortunately, output from these methods can be hard to interpret and often suffers from relatively high error rates. RESULTS: We built and analyzed a domain-specific microbial trait database from known microbe-trait pairs recorded in the literature to better understand the functional composition of the human microbiome. Using a combination of phylogentically conscious machine learning tools and a network science approach, we were able to link particular traits to areas of the human body, discover traits that determine the range of body areas a microbe can inhabit, and uncover drivers of metabolic breadth. CONCLUSIONS: Domain-specific trait databases are an effective compromise between noisy methods to infer complex traits from genomic data and exhaustive, expensive attempts at database curation from the literature that do not focus on any one subset of taxa. They provide an accurate account of microbial traits and, by limiting the number of taxa considered, are feasible to build within a reasonable time-frame. We present a database specific for the human microbiome, in the hopes that this will prove useful for research into the functional composition of human-associated microbial communities.

Selection influences naive CD8+ TCR-ß repertoire sharing.

Within each individual, the adaptive immune system generates a repertoire of cells expressing receptors capable of recognizing diverse potential pathogens. The theoretical diversity of the T-cell receptor (TCR) repertoire exceeds the actual size of the T-cell population in an individual by several orders of magnitude - making the observation of identical TCRs in different individuals extremely improbable if all receptors were equally likely. Despite this disparity between the theoretical and the realized diversity of the repertoire, these 'public' receptor sequences have been identified in autoimmune, cancer and pathogen interaction contexts. Biased generation processes explain the presence of public TCRs in the naive repertoire, but do not adequately explain the different abundances of these public TCRs. We investigate and characterize the distribution of genomic TCR-ß sequences of naive CD8+ T cells from three genetically identical mice, comparing non-productive (non-functional sequences) and productive sequences. We find public TCR-ß sequences at higher abundances compared with unshared sequences in the productive, but not in the non-productive, repertoire. We show that neutral processes such as recombination biases, codon degeneracy and generation probability do not fully account for these differences, and conclude that thymic or peripheral selection plays an important role in increasing the abundances of public TCR-ß sequences.

Avoidance of Self during CRISPR Immunization.

The battle between microbes and their viruses is ancient and ongoing. Clustered regularly interspaced short palindromic repeat (CRISPR) immunity, the first and, to date, only form of adaptive immunity found in prokaryotes, represents a flexible mechanism to recall past infections while also adapting to a changing pathogenic environment. Critical to the role of CRISPR as an adaptive immune mechanism is its capacity for self versus non-self recognition when acquiring novel immune memories. Yet, CRISPR systems vary widely in both how and to what degree they can distinguish foreign from self-derived genetic material. We document known and hypothesized mechanisms that bias the acquisition of immune memory towards non-self targets. We demonstrate that diversity is the rule, with many widespread but no universal mechanisms for self versus non-self recognition.

Network-Based Prediction of Novel CRISPR-Associated Genes in Metagenomes.

A diversity of clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems provide adaptive immunity to bacteria and archaea through recording "memories" of past viral infections. Recently, many novel CRISPR-associated proteins have been discovered via computational studies, but those studies relied on biased and incomplete databases of assembled genomes. We avoided these biases and applied a network theory approach to search for novel CRISPR-associated genes by leveraging subtle ecological cooccurrence patterns identified from environmental metagenomes. We validated our method using existing annotations and discovered 32 novel CRISPR-associated gene families. These genes span a range of putative functions, with many potentially regulating the response to infection.IMPORTANCE Every branch on the tree of life, including microbial life, faces the threat of viral pathogens. Over the course of billions of years of coevolution, prokaryotes have evolved a great diversity of strategies to defend against viral infections. One of these is the CRISPR adaptive immune system, which allows microbes to "remember" past infections in order to better fight them in the future. There has been much interest among molecular biologists in CRISPR immunity because this system can be repurposed as a tool for precise genome editing. Recently, a number of comparative genomics approaches have been used to detect novel CRISPR-associated genes in databases of genomes with great success, potentially leading to the development of new genome-editing tools. Here, we developed novel methods to search for these distinct classes of genes directly in environmental samples ("metagenomes"), thus capturing a more complete picture of the natural diversity of CRISPR-associated genes.

Linking high GC content to the repair of double strand breaks in prokaryotic genomes.

Genomic GC content varies widely among microbes for reasons unknown. While mutation bias partially explains this variation, prokaryotes near-universally have a higher GC content than predicted solely by this bias. Debate surrounds the relative importance of the remaining explanations of selection versus biased gene conversion favoring GC alleles. Some environments (e.g. soils) are associated with a high genomic GC content of their inhabitants, which implies that either high GC content is a selective adaptation to particular habitats, or that certain habitats favor increased rates of gene conversion. Here, we report a novel association between the presence of the non-homologous end joining DNA double-strand break repair pathway and GC content; this observation suggests that DNA damage may be a fundamental driver of GC content, leading in part to the many environmental patterns observed to-date. We discuss potential mechanisms accounting for the observed association, and provide preliminary evidence that sites experiencing higher rates of double-strand breaks are under selection for increased GC content relative to the genomic background.

Visualization and prediction of CRISPR incidence in microbial trait-space to identify drivers of antiviral immune strategy.

Bacteria and archaea are locked in a near-constant battle with their viral pathogens. Despite previous mechanistic characterization of numerous prokaryotic defense strategies, the underlying ecological drivers of different strategies remain largely unknown and predicting which species will take which strategies remains a challenge. Here, we focus on the CRISPR immune strategy and develop a phylogenetically-corrected machine learning approach to build a predictive model of CRISPR incidence using data on over 100 traits across over 2600 species. We discover a strong but hitherto-unknown negative interaction between CRISPR and aerobicity, which we hypothesize may result from interference between CRISPR-associated proteins and non-homologous end-joining DNA repair due to oxidative stress. Our predictive model also quantitatively confirms previous observations of an association between CRISPR and temperature. Finally, we contrast the environmental associations of different CRISPR system types (I, II, III) and restriction modification systems, all of which act as intracellular immune systems.

Biological Sexing of a 4000-Year-Old Egyptian Mummy Head to Assess the Potential of Nuclear DNA Recovery from the Most Damaged and Limited Forensic Specimens.

High throughput sequencing (HTS) has been used for a number of years in the field of paleogenomics to facilitate the recovery of small DNA fragments from ancient specimens. Recently, these techniques have also been applied in forensics, where they have been used for the recovery of mitochondrial DNA sequences from samples where traditional PCR-based assays fail because of the very short length of endogenous DNA molecules. Here, we describe the biological sexing of a ~4000-year-old Egyptian mummy using shotgun sequencing and two established methods of biological sex determination (RX and RY), by way of mitochondrial genome analysis as a means of sequence data authentication. This particular case of historical interest increases the potential utility of HTS techniques for forensic purposes by demonstrating that data from the more discriminatory nuclear genome can be recovered from the most damaged specimens, even in cases where mitochondrial DNA cannot be recovered with current PCR-based forensic technologies. Although additional work remains to be done before nuclear DNA recovered via these methods can be used routinely in operational casework for individual identification purposes, these results indicate substantial promise for the retrieval of probative individually identifying DNA data from the most limited and degraded forensic specimens.

Immune loss as a driver of coexistence during host-phage coevolution.

Bacteria and their viral pathogens face constant pressure for augmented immune and infective capabilities, respectively. Under this reciprocally imposed selective regime, we expect to see a runaway evolutionary arms race, ultimately leading to the extinction of one species. Despite this prediction, in many systems host and pathogen coexist with minimal coevolution even when well-mixed. Previous work explained this puzzling phenomenon by invoking fitness tradeoffs, which can diminish an arms race dynamic. Here we propose that the regular loss of immunity by the bacterial host can also produce host-phage coexistence. We pair a general model of immunity with an experimental and theoretical case study of the CRISPR-Cas immune system to contrast the behavior of tradeoff and loss mechanisms in well-mixed systems. We find that, while both mechanisms can produce stable coexistence, only immune loss does so robustly within realistic parameter ranges.

Selective Maintenance of Multiple CRISPR Arrays Across Prokaryotes.

Prokaryotes are under nearly constant attack by viral pathogens. To protect against this threat of infection, bacteria and archaea have evolved a wide array of defense mechanisms, singly and in combination. While immune diversity in a single organism likely reduces the chance of pathogen evolutionary escape, it remains puzzling why many prokaryotes also have multiple, seemingly redundant, copies of the same type of immune system. Here, we focus on the highly flexible CRISPR adaptive immune system, which is present in multiple copies in a surprising 28% of the prokaryotic genomes in RefSeq. We use a comparative genomics approach looking across all prokaryotes to demonstrate that on average, organisms are under selection to maintain more than one CRISPR array. Given this surprising conclusion, we consider several hypotheses concerning the source of selection and include a theoretical analysis of the possibility that a trade-off between memory span and learning speed could select for both "long-term memory" and "short-term memory" CRISPR arrays.

Genome-wide ancestry of 17th-century enslaved Africans from the Caribbean.

Between 1500 and 1850, more than 12 million enslaved Africans were transported to the New World. The vast majority were shipped from West and West-Central Africa, but their precise origins are largely unknown. We used genome-wide ancient DNA analyses to investigate the genetic origins of three enslaved Africans whose remains were recovered on the Caribbean island of Saint Martin. We trace their origins to distinct subcontinental source populations within Africa, including Bantu-speaking groups from northern Cameroon and non-Bantu speakers living in present-day Nigeria and Ghana. To our knowledge, these findings provide the first direct evidence for the ethnic origins of enslaved Africans, at a time for which historical records are scarce, and demonstrate that genomic data provide another type of record that can shed new light on long-standing historical questions.

Initial viral load determines the magnitude of the human CD8 T cell response to yellow fever vaccination.

CD8 T cells are a potent tool for eliminating intracellular pathogens and tumor cells. Thus, eliciting robust CD8 T-cell immunity is the basis for many vaccines under development. However, the relationship between antigen load and the magnitude of the CD8 T-cell response is not well-described in a human immune response. Here we address this issue by quantifying viral load and the CD8 T-cell response in a cohort of 80 individuals immunized with the live attenuated yellow fever vaccine (YFV-17D) by sampling peripheral blood at days 0, 1, 2, 3, 5, 7, 9, 11, 14, 30, and 90. When the virus load was below a threshold (peak virus load < 225 genomes per mL, or integrated virus load < 400 genome days per mL), the magnitude of the CD8 T-cell response correlated strongly with the virus load (R(2) ∼ 0.63). As the virus load increased above this threshold, the magnitude of the CD8 T-cell responses saturated. Recent advances in CD8 T-cell-based vaccines have focused on replication-incompetent or single-cycle vectors. However, these approaches deliver relatively limited amounts of antigen after immunization. Our results highlight the requirement that T-cell-based vaccines should deliver sufficient antigen during the initial period of the immune response to elicit a large number of CD8 T cells that may be needed for protection.

Two ancient human genomes reveal Polynesian ancestry among the indigenous Botocudos of Brazil.

Understanding the peopling of the Americas remains an important and challenging question. Here, we present (14)C dates, and morphological, isotopic and genomic sequence data from two human skulls from the state of Minas Gerais, Brazil, part of one of the indigenous groups known as 'Botocudos'. We find that their genomic ancestry is Polynesian, with no detectable Native American component. Radiocarbon analysis of the skulls shows that the individuals had died prior to the beginning of the 19th century. Our findings could either represent genomic evidence of Polynesians reaching South America during their Pacific expansion, or European-mediated transport.

Genome sequence of a 45,000-year-old modern human from western Siberia.

We present the high-quality genome sequence of a ∼45,000-year-old modern human male from Siberia. This individual derives from a population that lived before-or simultaneously with-the separation of the populations in western and eastern Eurasia and carries a similar amount of Neanderthal ancestry as present-day Eurasians. However, the genomic segments of Neanderthal ancestry are substantially longer than those observed in present-day individuals, indicating that Neanderthal gene flow into the ancestors of this individual occurred 7,000-13,000 years before he lived. We estimate an autosomal mutation rate of 0.4 × 10(-9) to 0.6 × 10(-9) per site per year, a Y chromosomal mutation rate of 0.7 × 10(-9) to 0.9 × 10(-9) per site per year based on the additional substitutions that have occurred in present-day non-Africans compared to this genome, and a mitochondrial mutation rate of 1.8 × 10(-8) to 3.2 × 10(-8) per site per year based on the age of the bone.

A population biological approach to understanding the maintenance and loss of the T-cell repertoire during aging.

The adaptive immune system requires a diverse T-cell repertoire to be able to respond to a wide variety of pathogens. Worryingly, the repertoire diversity declines dramatically in old age. As thymic output generates novel T cells, the conventional view holds that a decrease in this output with age is responsible for the loss in the repertoire. However, many additional factors affect the repertoire such as homeostatic turnover and antigen-dependent expansion in response to infection. Mathematical models taking a population biology perspective are important tools for understanding how the interplay between these factors affects the immune repertoire. These models suggest that thymic decline is not a major factor but rather that some combination of virus-induced proliferation and T-cell-intrinsic genetic or epigenetic changes gives rise to the oligoclonal expansions that cause the decline in T-cell diversity. We also discuss consequences for strategies to rejuvenate the immune repertoire in old age.