Physiological Basis for Xenotransplantation from Genetically-Modified Pigs to Humans: A Review

The collective efforts of scientists over multiple decades have led to advancements in molecular and cellular biology-based technologies including genetic engineering and animal cloning, that are now being harnessed to enhance the suitability of pig organs for xenotransplantation into humans. Using organs sourced from pigs with multiple gene deletions and human transgene insertions, investigators have overcome formidable immunological and physiological barriers in pig-to-non-human primate (NHP) xenotransplantation and achieved prolonged pig xenograft survival. These studies informed the design of Revivicor's (Revivicor Inc, Blacksburg, VA) genetically engineered pig with 10 genetic modifications (10 GE) (including the inactivation of 4 endogenous porcine genes and insertion of 6 human transgenes) whose hearts and kidneys have now been studied in preclinical human xenotransplantation models using brain-dead recipients. Additionally, the first two clinical cases of pig-to-human heart xenotransplantation were recently performed using hearts from this 10 GE pig at the University of Maryland. While this review focuses on xenotransplantation of hearts and kidneys, multiple organs, tissues, and cell-types from genetically engineered pigs will provide much-needed therapeutic interventions in the future.

Inflammation-driven deaminase deregulation fuels human pre-leukemia stem cell evolution

Inflammation-dependent base deaminases promote therapeutic resistance in many malignancies. However, their roles in human pre-leukemia stem cell (pre-LSC) evolution to acute myeloid leukemia stem cells (LSCs) had not been elucidated. Comparative whole-genome and whole-transcriptome sequencing analyses of FACS-purified pre-LSCs from myeloproliferative neoplasm (MPN) patients reveal APOBEC3C upregulation, an increased C-to-T mutational burden, and hematopoietic stem and progenitor cell (HSPC) proliferation during progression, which can be recapitulated by lentiviral APOBEC3C overexpression. In pre-LSCs, inflammatory splice isoform overexpression coincides with APOBEC3C upregulation and ADAR1p150-induced A-to-I RNA hyper-editing. Pre-LSC evolution to LSCs is marked by STAT3 editing, STAT3β isoform switching, elevated phospho-STAT3, and increased ADAR1p150 expression, which can be prevented by JAK2/STAT3 inhibition with ruxolitinib or fedratinib or lentiviral ADAR1 shRNA knockdown. Conversely, lentiviral ADAR1p150 expression enhances pre-LSC replating and STAT3 splice isoform switching. Thus, pre-LSC evolution to LSCs is fueled by primate-specific APOBEC3C-induced pre-LSC proliferation and ADAR1-mediated splicing deregulation.

An unsupervised learning approach to identify novel signatures of health and disease from multimodal data

BACKGROUND

Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease signatures.

METHODS

We collected 1385 data features from diverse modalities, including metabolome, microbiome, genetics, and advanced imaging, from 1253 individuals and from a longitudinal validation cohort of 1083 individuals. We utilized a combination of unsupervised machine learning methods to identify multimodal biomarker signatures of health and disease risk.

RESULTS

Our method identified a set of cardiometabolic biomarkers that goes beyond standard clinical biomarkers. Stratification of individuals based on the signatures of these biomarkers identified distinct subsets of individuals with similar health statuses. Subset membership was a better predictor for diabetes than established clinical biomarkers such as glucose, insulin resistance, and body mass index. The novel biomarkers in the diabetes signature included 1-stearoyl-2-dihomo-linolenoyl-GPC and 1-(1-enyl-palmitoyl)-2-oleoyl-GPC. Another metabolite, cinnamoylglycine, was identified as a potential biomarker for both gut microbiome health and lean mass percentage. We identified potential early signatures for hypertension and a poor metabolic health outcome. Additionally, we found novel associations between a uremic toxin, p-cresol sulfate, and the abundance of the microbiome genera Intestinimonas and an unclassified genus in the Erysipelotrichaceae family.

CONCLUSIONS

Our methodology and results demonstrate the potential of multimodal data integration, from the identification of novel biomarker signatures to a data-driven stratification of individuals into disease subtypes and stages-an essential step towards personalized, preventative health risk assessment.

Interplay between the human gut microbiome and host metabolism

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.

Direct Transfer of a Mycoplasma mycoides Genome to Yeast Is Enhanced by Removal of the Mycoides Glycerol Uptake Factor Gene glpF

We previously discovered that intact bacterial chromosomes can be directly transferred to a yeast host cell where they can propagate as centromeric plasmids by fusing bacterial cells with S accharomyces cerevisiae spheroplasts. Inside the host any desired number of genetic changes can be introduced into the yeast centromeric plasmid to produce designer genomes that can be brought to life using a genome transplantation protocol. Earlier research demonstrated that the removal of restriction-systems from donor bacteria, such as Mycoplasma mycoides, Mycoplasma capricolum, or Haemophilus influenzae increased successful genome transfers. These findings suggested that other genetic factors might also impact the bacteria-to-yeast genome transfer process. In this study, we demonstrated that the removal of a particular genetic factor, the glycerol uptake facilitator protein gene glpF from M. mycoides, significantly increased direct genome transfer by up to 21-fold. Additionally, we showed that intact bacterial cells were endocytosed by yeast spheroplasts producing organelle-like structures within these yeast cells. These might lead to the possibility of creating novel synthetic organelles.

Profound Perturbation of the Metabolome in Obesity Is Associated with Health Risk

Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials.

Novel insight into the genetic basis of high-altitude pulmonary hypertension in Kyrgyz highlanders

The Central Asian Kyrgyz highland population provides a unique opportunity to address genetic diversity and understand the genetic mechanisms underlying high-altitude pulmonary hypertension (HAPH). Although a significant fraction of the population is unaffected, there are susceptible individuals who display HAPH in the absence of any lung, cardiac or hematologic disease. We report herein the analysis of the whole-genome sequencing of healthy individuals compared with HAPH patients and other controls (total n = 33). Genome scans reveal selection signals in various regions, encompassing multiple genes from the first whole-genome sequences focusing on HAPH. We show here evidence of three candidate genes MTMR4, TMOD3 and VCAM1 that are functionally associated with well-known molecular and pathophysiological processes and which likely lead to HAPH in this population. These processes are (a) dysfunctional BMP signaling, (b) disrupted tissue repair processes and (c) abnormal endothelial cell function. Whole-genome sequence of well-characterized patients and controls and using multiple statistical tools uncovered novel candidate genes that belong to pathways central to the pathogenesis of HAPH. These studies on high-altitude human populations are pertinent to the understanding of sea level diseases involving hypoxia as a main element of their pathophysiology.

New Insights into the Genetic Basis of Monge's Disease and Adaptation to High-Altitude

Human high-altitude (HA) adaptation or mal-adaptation is explored to understand the physiology, pathophysiology, and molecular mechanisms that underlie long-term exposure to hypoxia. Here, we report the results of an analysis of the largest whole-genome-sequencing of Chronic Mountain Sickness (CMS) and nonCMS individuals, identified candidate genes and functionally validated these candidates in a genetic model system (Drosophila). We used PreCIOSS algorithm that uses Haplotype Allele Frequency score to separate haplotypes carrying the favored allele from the noncarriers and accordingly, prioritize genes associated with the CMS or nonCMS phenotype. Haplotypes in eleven candidate regions, with SNPs mostly in nonexonic regions, were significantly different between CMS and nonCMS subjects. Closer examination of individual genes in these regions revealed the involvement of previously identified candidates (e.g., SENP1) and also unreported ones SGK3, COPS5, PRDM1, and IFT122 in CMS. Remarkably, in addition to genes like SENP1, SGK3, and COPS5 which are HIF-dependent, our study reveals for the first time HIF-independent gene PRDM1, indicating an involvement of wider, nonHIF pathways in HA adaptation. Finally, we observed that down-regulating orthologs of these genes in Drosophila significantly enhanced their hypoxia tolerance. Taken together, the PreCIOSS algorithm, applied on a large number of genomes, identifies the involvement of both new and previously reported genes in selection sweeps, highlighting the involvement of multiple hypoxia response systems. Since the overwhelming majority of SNPs are in nonexonic (and possibly regulatory) regions, we speculate that adaptation to HA necessitates greater genetic flexibility allowing for transcript variability in response to graded levels of hypoxia.

Paternally inherited cis-regulatory structural variants are associated with autism

The genetic basis of autism spectrum disorder (ASD) is known to consist of contributions from de novo mutations in variant-intolerant genes. We hypothesize that rare inherited structural variants in cis-regulatory elements (CRE-SVs) of these genes also contribute to ASD. We investigated this by assessing the evidence for natural selection and transmission distortion of CRE-SVs in whole genomes of 9274 subjects from 2600 families affected by ASD. In a discovery cohort of 829 families, structural variants were depleted within promoters and untranslated regions, and paternally inherited CRE-SVs were preferentially transmitted to affected offspring and not to their unaffected siblings. The association of paternal CRE-SVs was replicated in an independent sample of 1771 families. Our results suggest that rare inherited noncoding variants predispose children to ASD, with differing contributions from each parent.

Tuning Gene Activity by Inducible and Targeted Regulation of Gene Expression in Minimal Bacterial Cells

Functional genomics studies in minimal mycoplasma cells enable unobstructed access to some of the most fundamental processes in biology. Conventional transposon bombardment and gene knockout approaches often fail to reveal functions of genes that are essential for viability, where lethality precludes phenotypic characterization. Conditional inactivation of genes is effective for characterizing functions central to cell growth and division, but tools are limited for this purpose in mycoplasmas. Here we demonstrate systems for inducible repression of gene expression based on clustered regularly interspaced short palindromic repeats-mediated interference (CRISPRi) in Mycoplasma pneumoniae and synthetic Mycoplasma mycoides, two organisms with reduced genomes actively used in systems biology studies. In the synthetic cell, we also demonstrate inducible gene expression for the first time. Time-course data suggest rapid kinetics and reversible engagement of CRISPRi. Targeting of six selected endogenous genes with this system results in lowered transcript levels or reduced growth rates that agree with lack or shortage of data in previous transposon bombardment studies, and now produces actual cells to analyze. The ksgA gene encodes a methylase that modifies 16S rRNA, rendering it vulnerable to inhibition by the antibiotic kasugamycin. Targeting the ksgA gene with CRISPRi removes the lethal effect of kasugamycin and enables cell growth, thereby establishing specific and effective gene modulation with our system. The facile methods for conditional gene activation and inactivation in mycoplasmas open the door to systematic dissection of genetic programs at the core of cellular life.

Identification of Misclassified ClinVar Variants via Disease Population Prevalence

There is a significant interest in the standardized classification of human genetic variants. We used whole-genome sequence data from 10,495 unrelated individuals to contrast population frequency of pathogenic variants to the expected population prevalence of the disease. Analyses included the ACMG-recommended 59 gene-condition sets for incidental findings and 463 genes associated with 265 OrphaNet conditions. A total of 25,505 variants were used to identify patterns of inflation (i.e., excess genetic risk and misclassification). Inflation increases as the level of evidence supporting the pathogenic nature of the variant decreases. We observed up to 11.5% of genetic disorders with inflation in pathogenic variant sets and up to 92.3% for the variant set with conflicting interpretations. This improved to 7.7% and 57.7%, respectively, after filtering for disease-specific allele frequency. The patterns of inflation were replicated using public data from more than 138,000 genomes. The burden of rare variants was a main contributing factor of the observed inflation, indicating collective misclassified rare variants. We also analyzed the dynamics of re-classification of variant pathogenicity in ClinVar over time, which indicates progressive improvement in variant classification. The study shows that databases include a significant proportion of wrongly ascertained variants; however, it underscores the critical role of ClinVar to contrast claims and foster validation across submitters.

Acetaminophen (Paracetamol) Use Modifies the Sulfation of Sex Hormones

Background

Acetaminophen (paracetamol) is one of the most common medications used for management of pain in the world. There is lack of consensus about the mechanism of action, and concern about the possibility of adverse effects on reproductive health.

Methods

We first established the metabolome profile that characterizes use of acetaminophen, and we subsequently trained and tested a model that identified metabolomic differences across samples from 455 individuals with and without acetaminophen use. We validated the findings in a European ancestry adult twin cohort of 1880 individuals (TwinsUK), and in a study of 1235 individuals of African American and Hispanic ancestry. We used genomics to elucidate the mechanisms targeted by acetaminophen.

Findings

We identified a distinctive pattern of depletion of sulfated sex hormones with use of acetaminophen across all populations. We used a Mendelian randomization approach to characterize the role of Sulfotransferase Family 2A Member 1 (SULT2A1) as the site of the interaction. Although CYP3A7-CYP3A51P variants also modified levels of some sulfated sex hormones, only acetaminophen use phenocopied the effect of genetic variants of SULT2A1. Overall, acetaminophen use, age, gender and SULT2A1 and CYP3A7-CYP3A51P genetic variants are key determinants of variation in levels of sulfated sex hormones in blood. The effect of taking acetaminophen on sulfated sex hormones was roughly equivalent to the effect of 35 years of aging.

Interpretation

These findings raise concerns of the impact of acetaminophen use on hormonal homeostasis. In addition, it modifies views on the mechanism of action of acetaminophen in pain management as sulfated sex hormones can function as neurosteroids and modify nociceptive thresholds.

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We use metabolome analysis of 3570 individuals to identify the effect of acetaminophen on metabolic processes.

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Acetaminophen use is associated with decrease sulfation of sexual hormones.

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These findings are relevant in the context of current debate on the use of acetaminophen during pregnancy

Despite decades-long use of acetaminophen, there is an incomplete understanding of the mechanism of action, and of the potential for adverse metabolic effects. Recent epidemiological and animal work supports an effect of acetaminophen on reproductive processes and hormonal homeostasis. We observe a consistent and reproducible effect of acetaminophen use on the levels of sulfated sex hormones. This is relevant to the investigation of hormonal homeostasis during pregnancy – acetaminophen is the most commonly used analgesic by pregnant women. It also opens the door to investigating the role of sulfated hormones in pain management.

Genetic risk, dysbiosis, and treatment stratification using host genome and gut microbiome in inflammatory bowel disease

OBJECTIVES

Inflammatory bowel diseases (IBD), comprised of Crohn's disease (CD) and ulcerative colitis (UC), are characterized by a complex pathophysiology that is thought to result from an aberrant immune response to a dysbiotic luminal microbiota in genetically susceptible individuals. New technologies support the joint assessment of host-microbiome interaction.

METHODS

Using whole genome sequencing and shotgun metagenomics, we studied the clinical features, host genome, and stool microbial metagenome of 85 IBD patients, and compared the results to 146 control individuals. Genetic risk scores, computed on 159 single nucleotide variants, and human leukocyte antigen (HLA) types differentiated IBD patients from healthy controls.

RESULTS

Genetic risk was associated with the need for use of biologics in IBD and, modestly, with the composition of the gut microbiome. As compared with healthy controls, IBD patients had hallmarks of stool microbiome dysbiosis, with loss of a diversified core microbiome, enrichment and depletion of specific bacteria, and enrichment of bacterial virulence factors.

CONCLUSIONS

We show that genetic risk may have a role in early risk stratification in the care of IBD patients and propose that expression of virulence factors in a dysbiotic microbiome may contribute to pathogenesis in IBD.

Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes

Short tandem repeats (STRs) are hyper-mutable sequences in the human genome. They are often used in forensics and population genetics and are also the underlying cause of many genetic diseases. There are challenges associated with accurately determining the length polymorphism of STR loci in the genome by next-generation sequencing (NGS). In particular, accurate detection of pathological STR expansion is limited by the sequence read length during whole-genome analysis. We developed TREDPARSE, a software package that incorporates various cues from read alignment and paired-end distance distribution, as well as a sequence stutter model, in a probabilistic framework to infer repeat sizes for genetic loci, and we used this software to infer repeat sizes for 30 known disease loci. Using simulated data, we show that TREDPARSE outperforms other available software. We sampled the full genome sequences of 12,632 individuals to an average read depth of approximately 30× to 40× with Illumina HiSeq X. We identified 138 individuals with risk alleles at 15 STR disease loci. We validated a representative subset of the samples (n = 19) by Sanger and by Oxford Nanopore sequencing. Additionally, we validated the STR calls against known allele sizes in a set of GeT-RM reference cell-line materials (n = 6). Several STR loci that are entirely guanine or cytosines (G or C) have insufficient read evidence for inference and therefore could not be assayed precisely by TREDPARSE. TREDPARSE extends the limit of STR size detection beyond the physical sequence read length. This extension is critical because many of the disease risk cutoffs are close to or beyond the short sequence read length of 100 to 150 bases.

Fine population structure analysis method for genomes of many

Fine population structure can be examined through the clustering of individuals into subpopulations. The clustering of individuals in large sequence datasets into subpopulations makes the calculation of subpopulation specific allele frequency possible, which may shed light on selection of candidate variants for rare diseases. However, as the magnitude of the data increases, computational burden becomes a challenge in fine population structure analysis. To address this issue, we propose fine population structure analysis (FIPSA), which is an individual-based non-parametric method for dissecting fine population structure. FIPSA maximizes the likelihood ratio of the contingency table of the allele counts multiplied by the group. We demonstrated that its speed and accuracy were superior to existing non-parametric methods when the simulated sample size was up to 5,000 individuals. When applied to real data, the method showed high resolution on the Human Genome Diversity Project (HGDP) East Asian dataset. FIPSA was independently validated on 11,257 human genomes. The group assignment given by FIPSA was 99.1% similar to those assigned based on supervised learning. Thus, FIPSA provides high resolution and is compatible with a real dataset of more than ten thousand individuals.

Identification of individuals by trait prediction using whole-genome sequencing data

Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.

Gut Microbiome-Based Metagenomic Signature for Non-invasive Detection of Advanced Fibrosis in Human Nonalcoholic Fatty Liver Disease

The presence of advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is the most important predictor of liver mortality. There are limited data on the diagnostic accuracy of gut microbiota-derived signature for predicting the presence of advanced fibrosis. In this prospective study, we characterized the gut microbiome compositions using whole-genome shotgun sequencing of DNA extracted from stool samples. This study included 86 uniquely well-characterized patients with biopsy-proven NAFLD, of which 72 had mild/moderate (stage 0-2 fibrosis) NAFLD, and 14 had advanced fibrosis (stage 3 or 4 fibrosis). We identified a set of 40 features (p < 0.006), which included 37 bacterial species that were used to construct a Random Forest classifier model to distinguish mild/moderate NAFLD from advanced fibrosis. The model had a robust diagnostic accuracy (AUC 0.936) for detecting advanced fibrosis. This study provides preliminary evidence for a fecal-microbiome-derived metagenomic signature to detect advanced fibrosis in NAFLD.

Utilization of defined microbial communities enables effective evaluation of meta-genomic assemblies

BACKGROUND

Metagenomics is the study of the microbial genomes isolated from communities found on our bodies or in our environment. By correctly determining the relation between human health and the human associated microbial communities, novel mechanisms of health and disease can be found, thus enabling the development of novel diagnostics and therapeutics. Due to the diversity of the microbial communities, strategies developed for aligning human genomes cannot be utilized, and genomes of the microbial species in the community must be assembled de novo. However, in order to obtain the best metagenomic assemblies, it is important to choose the proper assembler. Due to the rapidly evolving nature of metagenomics, new assemblers are constantly created, and the field has not yet agreed on a standardized process. Furthermore, the truth sets used to compare these methods are either too simple (computationally derived diverse communities) or complex (microbial communities of unknown composition), yielding results that are hard to interpret. In this analysis, we interrogate the strengths and weaknesses of five popular assemblers through the use of defined biological samples of known genomic composition and abundance. We assessed the performance of each assembler on their ability to reassemble genomes, call taxonomic abundances, and recreate open reading frames (ORFs).

RESULTS

We tested five metagenomic assemblers: Omega, metaSPAdes, IDBA-UD, metaVelvet and MEGAHIT on known and synthetic metagenomic data sets. MetaSPAdes excelled in diverse sets, IDBA-UD performed well all around, metaVelvet had high accuracy in high abundance organisms, and MEGAHIT was able to accurately differentiate similar organisms within a community. At the ORF level, metaSPAdes and MEGAHIT had the least number of missing ORFs within diverse and similar communities respectively.

CONCLUSIONS

Depending on the metagenomics question asked, the correct assembler for the task at hand will differ. It is important to choose the appropriate assembler, and thus clearly define the biological problem of an experiment, as different assemblers will give different answers to the same question.

The blood DNA virome in 8,000 humans

The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

Novel sequencing technologies offer insight into the virome in human samples. Here, we identify the viral DNA sequences in blood of over 8,000 individuals undergoing whole genome sequencing. This approach serves to identify 94 viruses; however, many are shown to reflect widespread DNA contamination of commercial reagents or of environmental origin. While this represents a significant limitation to reliably identify novel viruses infecting humans, we could confidently detect sequences and quantify abundance of 19 human viruses in 42% of individuals. Ancestry, sex, and age were important determinants of viral prevalence. This large study calls attention on the challenge of interpreting next generation sequencing data for the identification of novel viruses. However, it serves to categorize the abundance of human DNA viruses using an unbiased technique.

The Human Microbiome and Cancer

Recent scientific advances have significantly contributed to our understanding of the complex connection between the microbiome and cancer. Our bodies are continuously exposed to microbial cells, both resident and transient, as well as their byproducts, including toxic metabolites. Circulation of toxic metabolites may contribute to cancer onset or progression at locations distant from where a particular microbe resides. Moreover, microbes may migrate to other locations in the human body and become associated with tumor development. Several case-control metagenomics studies suggest that dysbiosis in the commensal microbiota is also associated with inflammatory disorders and various cancer types throughout the body. Although the microbiome influences carcinogenesis through mechanisms independent of inflammation and immune system, the most recognizable link is between the microbiome and cancer via the immune system, as the resident microbiota plays an essential role in activating, training, and modulating the host immune response. Immunologic dysregulation is likely to provide mechanistic explanations as to how our microbiome influences cancer development and cancer therapies. In this review, we discuss recent developments in understanding the human gut microbiome's relationship with cancer and the feasibility of developing novel cancer diagnostics based on microbiome profiles. Cancer Prev Res; 10(4); 226-34. ©2017 AACR.

A robust ambient temperature collection and stabilization strategy: Enabling worldwide functional studies of the human microbiome

As reports on possible associations between microbes and the host increase in number, more meaningful interpretations of this information require an ability to compare data sets across studies. This is dependent upon standardization of workflows to ensure comparability both within and between studies. Here we propose the standard use of an alternate collection and stabilization method that would facilitate such comparisons. The DNA Genotek OMNIgene∙Gut Stool Microbiome Kit was compared to the currently accepted community standard of freezing to store human stool samples prior to whole genome sequencing (WGS) for microbiome studies. This stabilization and collection device allows for ambient temperature storage, automation, and ease of shipping/transfer of samples. The device permitted the same data reproducibility as with frozen samples, and yielded higher recovery of nucleic acids. Collection and stabilization of stool microbiome samples with the DNA Genotek collection device, combined with our extraction and WGS, provides a robust, reproducible workflow that enables standardized global collection, storage, and analysis of stool for microbiome studies.

One step engineering of the small-subunit ribosomal RNA using CRISPR/Cas9

Bacteria are indispensable for the study of fundamental molecular biology processes due to their relatively simple gene and genome architecture. The ability to engineer bacterial chromosomes is quintessential for understanding gene functions. Here we demonstrate the engineering of the small-ribosomal subunit (16S) RNA of Mycoplasma mycoides, by combining the CRISPR/Cas9 system and the yeast recombination machinery. We cloned the entire genome of M. mycoides in yeast and used constitutively expressed Cas9 together with in vitro transcribed guide-RNAs to introduce engineered 16S rRNA genes. By testing the function of the engineered 16S rRNA genes through genome transplantation, we observed surprising resilience of this gene to addition of genetic elements or helix substitutions with phylogenetically-distant bacteria. While this system could be further used to study the function of the 16S rRNA, one could envision the “simple” M. mycoides genome being used in this setting to study other genetic structures and functions to answer fundamental questions of life.

Designer diatom episomes delivered by bacterial conjugation

Eukaryotic microalgae hold great promise for the bioproduction of fuels and higher value chemicals. However, compared with model genetic organisms such as Escherichia coli and Saccharomyces cerevisiae, characterization of the complex biology and biochemistry of algae and strain improvement has been hampered by the inefficient genetic tools. To date, many algal species are transformable only via particle bombardment, and the introduced DNA is integrated randomly into the nuclear genome. Here we describe the first nuclear episomal vector for diatoms and a plasmid delivery method via conjugation from Escherichia coli to the diatoms Phaeodactylum tricornutum and Thalassiosira pseudonana. We identify a yeast-derived sequence that enables stable episome replication in these diatoms even in the absence of antibiotic selection and show that episomes are maintained as closed circles at copy number equivalent to native chromosomes. This highly efficient genetic system facilitates high-throughput functional characterization of algal genes and accelerates molecular phytoplankton research.

Bacterial genome reduction using the progressive clustering of deletions via yeast sexual cycling

The availability of genetically tractable organisms with simple genomes is critical for the rapid, systems-level understanding of basic biological processes. Mycoplasma bacteria, with the smallest known genomes among free-living cellular organisms, are ideal models for this purpose, but the natural versions of these cells have genome complexities still too great to offer a comprehensive view of a fundamental life form. Here we describe an efficient method for reducing genomes from these organisms by identifying individually deletable regions using transposon mutagenesis and progressively clustering deleted genomic segments using meiotic recombination between the bacterial genomes harbored in yeast. Mycoplasmal genomes subjected to this process and transplanted into recipient cells yielded two mycoplasma strains. The first simultaneously lacked eight singly deletable regions of the genome, representing a total of 91 genes and ∼10% of the original genome. The second strain lacked seven of the eight regions, representing 84 genes. Growth assay data revealed an absence of genetic interactions among the 91 genes under tested conditions. Despite predicted effects of the deletions on sugar metabolism and the proteome, growth rates were unaffected by the gene deletions in the seven-deletion strain. These results support the feasibility of using single-gene disruption data to design and construct viable genomes lacking multiple genes, paving the way toward genome minimization. The progressive clustering method is expected to be effective for the reorganization of any mega-sized DNA molecules cloned in yeast, facilitating the construction of designer genomes in microbes as well as genomic fragments for genetic engineering of higher eukaryotes.

Genomes and gene expression across light and productivity gradients in eastern subtropical Pacific microbial communities

Transitions in community genomic features and biogeochemical processes were examined in surface and subsurface chlorophyll maximum (SCM) microbial communities across a trophic gradient from mesotrophic waters near San Diego, California to the oligotrophic Pacific. Transect end points contrasted in thermocline depth, rates of nitrogen and CO2 uptake, new production and SCM light intensity. Relative to surface waters, bacterial SCM communities displayed greater genetic diversity and enrichment in putative sulfur oxidizers, multiple actinomycetes, low-light-adapted Prochlorococcus and cell-associated viruses. Metagenomic coverage was not correlated with transcriptional activity for several key taxa within Bacteria. Low-light-adapted Prochlorococcus, Synechococcus, and low abundance gamma-proteobacteria enriched in the>3.0-μm size fraction contributed disproportionally to global transcription. The abundance of these groups also correlated with community functions, such as primary production or nitrate uptake. In contrast, many of the most abundant bacterioplankton, including SAR11, SAR86, SAR112 and high-light-adapted Prochlorococcus, exhibited low levels of transcriptional activity and were uncorrelated with rate processes. Eukaryotes such as Haptophytes and non-photosynthetic Aveolates were prevalent in surface samples while Mamielles and Pelagophytes dominated the SCM. Metatranscriptomes generated with ribosomal RNA-depleted mRNA (total mRNA) coupled to in vitro polyadenylation compared with polyA-enriched mRNA revealed a trade-off in detection eukaryotic organelle and eukaryotic nuclear origin transcripts, respectively. Gene expression profiles of SCM eukaryote populations, highly similar in sequence identity to the model pelagophyte Pelagomonas sp. CCMP1756, suggest that pelagophytes are responsible for a majority of nitrate assimilation within the SCM.

Rescue of mutant fitness defects using in vitro reconstituted designer transposons in Mycoplasma mycoides

With only hundreds of genes contained within their genomes, mycoplasmas have become model organisms for precise understanding of cellular processes, as well as platform organisms for predictable engineering of microbial functions for mission-critical applications. Despite the availability of “whole genome writing” in Mycoplasma mycoides, some traditional methods for genetic engineering are underdeveloped in mycoplasmas. Here we demonstrate two facile transposon-mediated approaches for introducing genes into the synthetic cell based on M. mycoides. The marker-less approach involves preparing a fragment containing only a small genomic region of interest with flanking transposase-binding sites, followed by in vitro transposase loading and introduction into the cells. The marker-driven approach involves cloning an open reading frame (ORF) of interest into a vector containing a marker for mycoplasma transformation, as well as sites for transposase loading and random genomic integration. An innovative feature of this construct is to use a single promoter to express the transformation marker and the introduced ORF. The marker-driven approach can be conveniently applied to any exogenous or synthetic gene without any information on the effect of the gene on the strain, whereas the marker-less approach requires that the fragment has a recognizable effect. Using the marker-less method, we found that a region containing the nusG gene rescues a slow growth phenotype of a strain containing a larger deletion encompassing this gene. Using the marker-driven approach, we better defined this finding, thereby establishing that nusG is required for a normal growth rate in synthetic M. mycoides. These methods are suitable for complementation tests to identify genes responsible for assorted functions lacking in deletion mutants. These approaches are also expected to facilitate rapid testing of various natural and engineered genes or gene clusters from numerous sources in M. mycoides.

Functional tradeoffs underpin salinity-driven divergence in microbial community composition

Bacterial community composition and functional potential change subtly across gradients in the surface ocean. In contrast, while there are significant phylogenetic divergences between communities from freshwater and marine habitats, the underlying mechanisms to this phylogenetic structuring yet remain unknown. We hypothesized that the functional potential of natural bacterial communities is linked to this striking divide between microbiomes. To test this hypothesis, metagenomic sequencing of microbial communities along a 1,800 km transect in the Baltic Sea area, encompassing a continuous natural salinity gradient from limnic to fully marine conditions, was explored. Multivariate statistical analyses showed that salinity is the main determinant of dramatic changes in microbial community composition, but also of large scale changes in core metabolic functions of bacteria. Strikingly, genetically and metabolically different pathways for key metabolic processes, such as respiration, biosynthesis of quinones and isoprenoids, glycolysis and osmolyte transport, were differentially abundant at high and low salinities. These shifts in functional capacities were observed at multiple taxonomic levels and within dominant bacterial phyla, while bacteria, such as SAR11, were able to adapt to the entire salinity gradient. We propose that the large differences in central metabolism required at high and low salinities dictate the striking divide between freshwater and marine microbiomes, and that the ability to inhabit different salinity regimes evolved early during bacterial phylogenetic differentiation. These findings significantly advance our understanding of microbial distributions and stress the need to incorporate salinity in future climate change models that predict increased levels of precipitation and a reduction in salinity.

Synthetic generation of influenza vaccine viruses for rapid response to pandemics

During the 2009 H1N1 influenza pandemic, vaccines for the virus became available in large quantities only after human infections peaked. To accelerate vaccine availability for future pandemics, we developed a synthetic approach that very rapidly generated vaccine viruses from sequence data. Beginning with hemagglutinin (HA) and neuraminidase (NA) gene sequences, we combined an enzymatic, cell-free gene assembly technique with enzymatic error correction to allow rapid, accurate gene synthesis. We then used these synthetic HA and NA genes to transfect Madin-Darby canine kidney (MDCK) cells that were qualified for vaccine manufacture with viral RNA expression constructs encoding HA and NA and plasmid DNAs encoding viral backbone genes. Viruses for use in vaccines were rescued from these MDCK cells. We performed this rescue with improved vaccine virus backbones, increasing the yield of the essential vaccine antigen, HA. Generation of synthetic vaccine seeds, together with more efficient vaccine release assays, would accelerate responses to influenza pandemics through a system of instantaneous electronic data exchange followed by real-time, geographically dispersed vaccine production.

A metagenomic framework for the study of airborne microbial communities

Understanding the microbial content of the air has important scientific, health, and economic implications. While studies have primarily characterized the taxonomic content of air samples by sequencing the 16S or 18S ribosomal RNA gene, direct analysis of the genomic content of airborne microorganisms has not been possible due to the extremely low density of biological material in airborne environments. We developed sampling and amplification methods to enable adequate DNA recovery to allow metagenomic profiling of air samples collected from indoor and outdoor environments. Air samples were collected from a large urban building, a medical center, a house, and a pier. Analyses of metagenomic data generated from these samples reveal airborne communities with a high degree of diversity and different genera abundance profiles. The identities of many of the taxonomic groups and protein families also allows for the identification of the likely sources of the sampled airborne bacteria.

Assembly of eukaryotic algal chromosomes in yeast

BACKGROUND

Synthetic genomic approaches offer unique opportunities to use powerful yeast and Escherichia coli genetic systems to assemble and modify chromosome-sized molecules before returning the modified DNA to the target host. For example, the entire 1 Mb Mycoplasma mycoides chromosome can be stably maintained and manipulated in yeast before being transplanted back into recipient cells. We have previously demonstrated that cloning in yeast of large (> ~ 150 kb), high G + C (55%) prokaryotic DNA fragments was improved by addition of yeast replication origins every ~100 kb. Conversely, low G + C DNA is stable (up to at least 1.8 Mb) without adding supplemental yeast origins. It has not been previously tested whether addition of yeast replication origins similarly improves the yeast-based cloning of large (>150 kb) eukaryotic DNA with moderate G + C content. The model diatom Phaeodactylum tricornutum has an average G + C content of 48% and a 27.4 Mb genome sequence that has been assembled into chromosome-sized scaffolds making it an ideal test case for assembly and maintenance of eukaryotic chromosomes in yeast.

RESULTS

We present a modified chromosome assembly technique in which eukaryotic chromosomes as large as ~500 kb can be assembled from cloned ~100 kb fragments. We used this technique to clone fragments spanning P. tricornutum chromosomes 25 and 26 and to assemble these fragments into single, chromosome-sized molecules. We found that addition of yeast replication origins improved the cloning, assembly, and maintenance of the large chromosomes in yeast. Furthermore, purification of the fragments to be assembled by electroelution greatly increased assembly efficiency.

CONCLUSIONS

Entire eukaryotic chromosomes can be successfully cloned, maintained, and manipulated in yeast. These results highlight the improvement in assembly and maintenance afforded by including yeast replication origins in eukaryotic DNA with moderate G + C content (48%). They also highlight the increased efficiency of assembly that can be achieved by purifying fragments before assembly.

Candidate phylum TM6 genome recovered from a hospital sink biofilm provides genomic insights into this uncultivated phylum

The "dark matter of life" describes microbes and even entire divisions of bacterial phyla that have evaded cultivation and have yet to be sequenced. We present a genome from the globally distributed but elusive candidate phylum TM6 and uncover its metabolic potential. TM6 was detected in a biofilm from a sink drain within a hospital restroom by analyzing cells using a highly automated single-cell genomics platform. We developed an approach for increasing throughput and effectively improving the likelihood of sampling rare events based on forming small random pools of single-flow-sorted cells, amplifying their DNA by multiple displacement amplification and sequencing all cells in the pool, creating a "mini-metagenome." A recently developed single-cell assembler, SPAdes, in combination with contig binning methods, allowed the reconstruction of genomes from these mini-metagenomes. A total of 1.07 Mb was recovered in seven contigs for this member of TM6 (JCVI TM6SC1), estimated to represent 90% of its genome. High nucleotide identity between a total of three TM6 genome drafts generated from pools that were independently captured, amplified, and assembled provided strong confirmation of a correct genomic sequence. TM6 is likely a Gram-negative organism and possibly a symbiont of an unknown host (nonfree living) in part based on its small genome, low-GC content, and lack of biosynthesis pathways for most amino acids and vitamins. Phylogenomic analysis of conserved single-copy genes confirms that TM6SC1 is a deeply branching phylum.

Sequencing of isolated sperm cells for direct haplotyping of a human genome

There is increasing evidence that the phenotypic effects of genomic sequence variants are best understood in terms of variant haplotypes rather than as isolated polymorphisms. Haplotype analysis is also critically important for uncovering population histories and for the study of evolutionary genetics. Although the sequencing of individual human genomes to reveal personal collections of sequence variants is now well established, there has been slower progress in the phasing of these variants into pairs of haplotypes along each pair of chromosomes. Here, we have developed a distinct approach to haplotyping that can yield chromosome-length haplotypes, including the vast majority of heterozygous single-nucleotide polymorphisms (SNPs) in an individual human genome. This approach exploits the haploid nature of sperm cells and employs a combination of genotyping and low-coverage sequencing on a short-read platform. In addition to generating chromosome-length haplotypes, the approach can directly identify recombination events (averaging 1.1 per chromosome) with a median resolution of <100 kb.

Metagenomic exploration of viruses throughout the Indian Ocean

The characterization of global marine microbial taxonomic and functional diversity is a primary goal of the Global Ocean Sampling Expedition. As part of this study, 19 water samples were collected aboard the Sorcerer II sailing vessel from the southern Indian Ocean in an effort to more thoroughly understand the lifestyle strategies of the microbial inhabitants of this ultra-oligotrophic region. No investigations of whole virioplankton assemblages have been conducted on waters collected from the Indian Ocean or across multiple size fractions thus far. Therefore, the goals of this study were to examine the effect of size fractionation on viral consortia structure and function and understand the diversity and functional potential of the Indian Ocean virome. Five samples were selected for comprehensive metagenomic exploration; and sequencing was performed on the microbes captured on 3.0-, 0.8- and 0.1 µm membrane filters as well as the viral fraction (<0.1 µm). Phylogenetic approaches were also used to identify predicted proteins of viral origin in the larger fractions of data from all Indian Ocean samples, which were included in subsequent metagenomic analyses. Taxonomic profiling of viral sequences suggested that size fractionation of marine microbial communities enriches for specific groups of viruses within the different size classes and functional characterization further substantiated this observation. Functional analyses also revealed a relative enrichment for metabolic proteins of viral origin that potentially reflect the physiological condition of host cells in the Indian Ocean including those involved in nitrogen metabolism and oxidative phosphorylation. A novel classification method, MGTAXA, was used to assess virus-host relationships in the Indian Ocean by predicting the taxonomy of putative host genera, with Prochlorococcus, Acanthochlois and members of the SAR86 cluster comprising the most abundant predictions. This is the first study to holistically explore virioplankton dynamics across multiple size classes and provides unprecedented insight into virus diversity, metabolic potential and virus-host interactions.

Sequence analysis of a complete 1.66 Mb Prochlorococcus marinus MED4 genome cloned in yeast

Marine cyanobacteria of the genus Prochlorococcus represent numerically dominant photoautotrophs residing throughout the euphotic zones in the open oceans and are major contributors to the global carbon cycle. Prochlorococcus has remained a genetically intractable bacterium due to slow growth rates and low transformation efficiencies using standard techniques. Our recent successes in cloning and genetically engineering the AT-rich, 1.1 Mb Mycoplasma mycoides genome in yeast encouraged us to explore similar methods with Prochlorococcus. Prochlorococcus MED4 has an AT-rich genome, with a GC content of 30.8%, similar to that of Saccharomyces cerevisiae (38%), and contains abundant yeast replication origin consensus sites (ACS) evenly distributed around its 1.66 Mb genome. Unlike Mycoplasma cells, which use the UGA codon for tryptophane, Prochlorococcus uses the standard genetic code. Despite this, we observed no toxic effects of several partial and 15 whole Prochlorococcus MED4 genome clones in S. cerevisiae. Sequencing of a Prochlorococcus genome purified from yeast identified 14 single base pair missense mutations, one frameshift, one single base substitution to a stop codon and one dinucleotide transversion compared to the donor genomic DNA. We thus provide evidence of transformation, replication and maintenance of this 1.66 Mb intact bacterial genome in S. cerevisiae.

Assembly of large, high G+C bacterial DNA fragments in yeast

The ability to assemble large pieces of prokaryotic DNA by yeast recombination has great application in synthetic biology, but cloning large pieces of high G+C prokaryotic DNA in yeast can be challenging. Additional considerations in cloning large pieces of high G+C DNA in yeast may be related to toxic genes, to the size of the DNA, or to the absence of yeast origins of replication within the sequence. As an example of our ability to clone high G+C DNA in yeast, we chose to work with Synechococcus elongatus PCC 7942, which has an average G+C content of 55%. We determined that no regions of the chromosome are toxic to yeast and that S. elongatus DNA fragments over ~200 kb are not stably maintained. DNA constructs with a total size under 200 kb could be readily assembled, even with 62 kb of overlapping sequence between pieces. Addition of yeast origins of replication throughout allowed us to increase the total size of DNA that could be assembled to at least 454 kb. Thus, cloning strategies utilizing yeast recombination with large, high G+C prokaryotic sequences should include yeast origins of replication as a part of the design process.

Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage

Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25-1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition.