TET2 Drives 5hmc Marking of GATA6 and Epigenetically Defines Pancreatic Ductal Adenocarcinoma Transcriptional Subtypes.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) is characterized by advanced disease stage at presentation, aggressive disease biology, and resistance to therapy, resulting in an extremely poor 5-year survival rate of <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression, but exactly why is unclear and is hindered by the technical limitations of analyzing clinical samples. METHODS: We performed genome-wide epigenetic mapping of DNA modifications 5-methylcytosine and 5-hydroxymethylcytosine (5hmc) using oxidative bisulfite sequencing from formalin-embedded sections. We identified overlap with transcriptional signatures in formalin-fixed, paraffin-embedded tissue from resected patients, via bioinformatics using iCluster and mutational profiling and confirmed them in vivo. RESULTS: We found that aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci, including GATA6, which promote differentiated classical pancreatic subtypes. We showed that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5-methylcytosine hydroxylase TET2. Furthermore, we found that SMAD4 directly supports TET2 levels in classical pancreatic tumors, and loss of SMAD4 expression was associated with reduced 5hmc, GATA6, and squamous-like tumors. Importantly, enhancing TET2 stability using metformin and vitamin C/ascorbic acid restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. CONCLUSIONS: We identified epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data showed that restoring epigenetic control increases biomarkers of classical pancreatic tumors that are associated with improved therapeutic responses and survival.

Using DNA testing for the precise, definite, and low-cost diagnosis of sickle cell disease and other Haemoglobinopathies: findings from Tanzania.

BACKGROUND: Sickle cell disease (SCD) is an important cause of under-five mortality. Tanzania is the 5th country in the world with the highest births prevalence of SCD individuals. Significant advances in the neonatal diagnosis of SCD using rapid point-of-care testing have been made. However genetic confirmation is still required for positive cases, in uncertain cases, in multiply transfused patients, to resolve compound heterozygosity (Hb S/ ß0 Thal or Hb S/ ß+ thal) not uncommon in the coastal regions of East Africa and increasingly also for pre-marital counselling and potentially for future curative approaches such as gene therapy. The currently available DNA tests are prohibitively expensive. Here, we describe an easy-to-use, affordable and accurate ß-globin sequencing approach that can be easily integrated within existing NBS for SCD and other haemoglobinopathies especially in Low- and Middle-income Countries. AIM: To evaluate an affordable DNA technology for the diagnosis of Sickle cell disease and other haemoglobinopathies in a resource-limited setting. METHODS: Laboratory-based validation study was conducted by Muhimbili University of Health and Allied Sciences and the University of Oxford involving sequencing of the entire ß -haemoglobin locus using the Oxford Nanopore MinION platform. A total number of 36 Dried blood spots and whole blood samples were subjected to conventional protein-based methods (isoelectric focusing, HPLC), and/or sequenced by the Sanger method as comparators. RESULTS: Sequencing results for SCD using the MinION were 100% concordant with those from the Sanger method. In addition, the long-read DNA sequencing method enabled the resolution of cases with unusual phenotypes which make up 1% of all children in Tanzania. The cost is £11/ sample for consumables, which is cheaper compared to other sequencing platforms. CONCLUSIONS: This is the first report of a comprehensive single DNA assay as a definitive diagnostic test for SCD and other haemoglobinopathies. The test is fast, precise, accurate and affordable.

Microbial biogeography and ecology of the mouth and implications for periodontal diseases.

In humans, the composition of microbial communities differs among body sites and between habitats within a single site. Patterns of variation in the distribution of organisms across time and space are referred to as "biogeography." The human oral cavity is a critical observatory for exploring microbial biogeography because it is spatially structured, easily accessible, and its microbiota has been linked to the promotion of both health and disease. The biogeographic features of microbial communities residing in spatially distinct, but ecologically similar, environments on the human body, including the subgingival crevice, have not yet been adequately explored. The purpose of this paper is twofold. First, we seek to provide the dental community with a primer on biogeographic theory, highlighting its relevance to the study of the human oral cavity. We summarize what is known about the biogeographic variation of dental caries and periodontitis and postulate that disease occurrence reflects spatial patterning in the composition and structure of oral microbial communities. Second, we present a number of methods that investigators can use to test specific hypotheses using biogeographic theory. To anchor our discussion, we apply each method to a case study and examine the spatial variation of the human subgingival microbiota in 2 individuals. Our case study suggests that the composition of subgingival communities may conform to an anterior-to-posterior gradient within the oral cavity. The gradient appears to be structured by both deterministic and nondeterministic processes, although additional work is needed to confirm these findings. A better understanding of biogeographic patterns and processes will lead to improved efficacy of dental interventions targeting the oral microbiota.

Interhost dispersal alters microbiome assembly and can overwhelm host innate immunity in an experimental zebrafish model.

The diverse collections of microorganisms associated with humans and other animals, collectively referred to as their "microbiome," are critical for host health, but the mechanisms that govern their assembly are poorly understood. This has made it difficult to identify consistent host factors that explain variation in microbiomes across hosts, despite large-scale sampling efforts. While ecological theory predicts that the movement, or dispersal, of individuals can have profound and predictable consequences on community assembly, its role in the assembly of animal-associated microbiomes remains underexplored. Here, we show that dispersal of microorganisms among hosts can contribute substantially to microbiome variation, and is able to overwhelm the effects of individual host factors, in an experimental test of ecological theory. We manipulated dispersal among wild-type and immune-deficient myd88 knockout zebrafish and observed that interhost dispersal had a large effect on the diversity and composition of intestinal microbiomes. Interhost dispersal was strong enough to overwhelm the effects of host factors, largely eliminating differences between wild-type and immune-deficient hosts, regardless of whether dispersal occurred within or between genotypes, suggesting dispersal can independently alter the ecology of microbiomes. Our observations are consistent with a predictive model that assumes metacommunity dynamics and are likely mediated by dispersal-related microbial traits. These results illustrate the importance of microbial dispersal to animal microbiomes and motivate its integration into the study of host-microbe systems.

Clinical-grade validation of whole genome sequencing reveals robust detection of low-frequency variants and copy number alterations in CLL.

The 100 000 Genome Project aims to develop a diagnostics platform by introducing whole genome sequencing (WGS) into clinical practice. Samples from patients with chronic lymphocytic leukaemia were subjected to WGS. WGS detection of single nucleotide variants and insertion/deletions were validated by targeted next generation sequencing showing high concordance (96·3%), also for detection of sub-clonal variants and low-frequency TP53 variants. Copy number alteration detection was verified by fluorescent in situ hybridisation and genome-wide single nucleotide polymorphism array (concordances of 86·7% and 92·9%, respectively), confirming adequate sensitivity by WGS. Our results confirm that WGS can provide comprehensive genomic characterisation for clinical trials, drug discovery and, ultimately, precision medicine.

Presence of multiple recurrent mutations confers poor trial outcome of relapsed/refractory CLL.

Although TP53, NOTCH1, and SF3B1 mutations may impair prognosis of patients with chronic lymphocytic leukemia (CLL) receiving frontline therapy, the impact of these mutations or any other, alone or in combination, remains unclear at relapse. The genome of 114 relapsed/refractory patients included in prospective trials was screened using targeted next-generation sequencing of the TP53, SF3B1, ATM, NOTCH1, XPO1, SAMHD1, MED12, BIRC3, and MYD88 genes. We performed clustering according to both number and combinations of recurrent gene mutations. The number of genes affected by mutation was ≥ 2, 1, and 0 in 43 (38%), 49 (43%), and 22 (19%) respectively. Recurrent combinations of ≥ 2 mutations of TP53, SF3B1, and ATM were found in 22 (19%) patients. This multiple-hit profile was associated with a median progression-free survival of 12 months compared with 22.5 months in the remaining patients (P = .003). Concurrent gene mutations are frequent in patients with relapsed/refractory CLL and are associated with worse outcome.

SAMHD1 is mutated recurrently in chronic lymphocytic leukemia and is involved in response to DNA damage.

SAMHD1 is a deoxynucleoside triphosphate triphosphohydrolase and a nuclease that restricts HIV-1 in noncycling cells. Germ-line mutations in SAMHD1 have been described in patients with Aicardi-Goutières syndrome (AGS), a congenital autoimmune disease. In a previous longitudinal whole genome sequencing study of chronic lymphocytic leukemia (CLL), we revealed a SAMHD1 mutation as a potential founding event. Here, we describe an AGS patient carrying a pathogenic germ-line SAMHD1 mutation who developed CLL at 24 years of age. Using clinical trial samples, we show that acquired SAMHD1 mutations are associated with high variant allele frequency and reduced SAMHD1 expression and occur in 11% of relapsed/refractory CLL patients. We provide evidence that SAMHD1 regulates cell proliferation and survival and engages in specific protein interactions in response to DNA damage. We propose that SAMHD1 may have a function in DNA repair and that the presence of SAMHD1 mutations in CLL promotes leukemia development.

Impact of isolated germline JAK2V617I mutation on human hematopoiesis.

The association between somatic JAK2 mutation and myeloproliferative neoplasms (MPNs) is now well established. However, because JAK2 mutations are associated with heterogeneous clinical phenotypes and often occur as secondary genetic events, some aspects of JAK2 mutation biology remain to be understood. We recently described a germline JAK2V617I mutation in a family with hereditary thrombocytosis and herein characterize the hematopoietic and signaling impact of JAK2V617I. Through targeted sequencing of MPN-associated mutations, exome sequencing, and clonality analysis, we demonstrate that JAK2V617I is likely to be the sole driver mutation in JAK2V617I-positive individuals with thrombocytosis. Phenotypic hematopoietic stem cells (HSCs) were increased in the blood and bone marrow of JAK2V617I-positive individuals and were sustained at higher levels than controls after xenotransplantation. In signaling and transcriptional assays, JAK2V617I demonstrated more activity than wild-type JAK2 but substantially less than JAK2V617F. After cytokine stimulation, JAK2V617I resulted in markedly increased downstream signaling compared with wild-type JAK2 and comparable with JAK2V617F. These findings demonstrate that JAK2V617I induces sufficient cytokine hyperresponsiveness in the absence of other molecular events to induce a homogeneous MPN-like phenotype. We also provide evidence that the JAK2V617I mutation may expand the HSC pool, providing insights into both JAK2 mutation biology and MPN disease pathogenesis.

Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns.

Chronic lymphocytic leukemia is characterized by relapse after treatment and chemotherapy resistance. Similarly, in other malignancies leukemia cells accumulate mutations during growth, forming heterogeneous cell populations that are subject to Darwinian selection and may respond differentially to treatment. There is therefore a clinical need to monitor changes in the subclonal composition of cancers during disease progression. Here, we use whole-genome sequencing to track subclonal heterogeneity in 3 chronic lymphocytic leukemia patients subjected to repeated cycles of therapy. We reveal different somatic mutation profiles in each patient and use these to establish probable hierarchical patterns of subclonal evolution, to identify subclones that decline or expand over time, and to detect founder mutations. We show that clonal evolution patterns are heterogeneous in individual patients. We conclude that genome sequencing is a powerful and sensitive approach to monitor disease progression repeatedly at the molecular level. If applied to future clinical trials, this approach might eventually influence treatment strategies as a tool to individualize and direct cancer treatment.

Proteomic changes induced by longevity-promoting interventions in mice.

Using mouse models and high-throughput proteomics, we conducted an in-depth analysis of the proteome changes induced in response to seven interventions known to increase mouse lifespan. This included two genetic mutations, a growth hormone receptor knockout (GHRKO mice) and a mutation in the Pit-1 locus (Snell dwarf mice), four drug treatments (rapamycin, acarbose, canagliflozin, and 17α-estradiol), and caloric restriction. Each of the interventions studied induced variable changes in the concentrations of proteins across liver, kidney, and gastrocnemius muscle tissue samples, with the strongest responses in the liver and limited concordance in protein responses across tissues. To the extent that these interventions promote longevity through common biological mechanisms, we anticipated that proteins associated with longevity could be identified by characterizing shared responses across all or multiple interventions. Many of the proteome alterations induced by each intervention were distinct, potentially implicating a variety of biological pathways as being related to lifespan extension. While we found no protein that was affected similarly by every intervention, we identified a set of proteins that responded to multiple interventions. These proteins were functionally diverse but tended to be involved in peroxisomal oxidation and metabolism of fatty acids. These results provide candidate proteins and biological mechanisms related to enhancing longevity that can inform research on therapeutic approaches to promote healthy aging.

Mutations in SETBP1 are recurrent in myelodysplastic syndromes and often coexist with cytogenetic markers associated with disease progression.

Whole exome sequencing was performed in a patient with myelodysplastic syndrome before and after progression to acute myeloid leukaemia. Mutations in several genes, including SETBP1, were identified following leukaemic transformation. Screening of 328 patients with myeloid disorders revealed SETBP1 mutations in 14 patients (4·3%), 7 of whom had -7/del(7q) and 3 had i(17)(q10), cytogenetic markers associated with shortened overall survival and increased risk of leukaemic evolution. SETBP1 mutations were frequently acquired at the time of leukaemic evolution, coinciding with increase of leukaemic blasts. These data suggest that SETBP1 mutations may play a role in MDS and chronic myelomonocytic leukaemia disease progression.

Targeted re-sequencing analysis of 25 genes commonly mutated in myeloid disorders in del(5q) myelodysplastic syndromes.

Interstitial deletion of chromosome 5q is the most common chromosomal abnormality in myelodysplastic syndromes. The catalogue of genes involved in the molecular pathogenesis of myelodysplastic syndromes is rapidly expanding and next-generation sequencing technology allows detection of these mutations at great depth. Here we describe the design, validation and application of a targeted next-generation sequencing approach to simultaneously screen 25 genes mutated in myeloid malignancies. We used this method alongside single nucleotide polymorphism-array technology to characterize the mutational and cytogenetic profile of 43 cases of early or advanced del(5q) myelodysplastic syndromes. A total of 29 mutations were detected in our cohort. Overall, 45% of early and 66.7% of advanced cases had at least one mutation. Genes with the highest mutation frequency among advanced cases were TP53 and ASXL1 (25% of patients each). These showed a lower mutation frequency in cases of 5q- syndrome (4.5% and 13.6%, respectively), suggesting a role in disease progression in del(5q) myelodysplastic syndromes. Fifty-two percent of mutations identified were in genes involved in epigenetic regulation (ASXL1, TET2, DNMT3A and JAK2). Six mutations had allele frequencies <20%, likely below the detection limit of traditional sequencing methods. Genomic array data showed that cases of advanced del(5q) myelodysplastic syndrome had a complex background of cytogenetic aberrations, often encompassing genes involved in myeloid disorders. Our study is the first to investigate the molecular pathogenesis of early and advanced del(5q) myelodysplastic syndromes using next-generation sequencing technology on a large panel of genes frequently mutated in myeloid malignancies, further illuminating the molecular landscape of del(5q) myelodysplastic syndromes.

Probabilistic Approach to Low Strain Rate Atomistic Simulations of Ultimate Tensile Strength of Polymer Crystals.

Molecular dynamics simulations of the tensile ultimate properties of polymer crystals require the use of empirical potentials that model bond dissociation. However, fully reactive potentials are computationally expensive such that reactive simulations cannot reach the low strain rates of typical experiments. Here, we present a hybrid approach that uses the simplicity of a classical, nonreactive potential, information from bond dissociation energy calculations, and a probabilistic expression that mimics bond breaking. The approach is demonstrated for poly(p-phenylene terephthalamide) and, with one tunable parameter, the calculated tensile ultimate stress matches that obtained using a fully reactive simulation at high strain rates. Then, the hybrid simulations are run at much lower strain rates where the ultimate tensile stress is strain rate-independent and consistent with the expected experimental range.

Methanol-Assisted ADMET Polymerization of Semiaromatic Amides.

A method for the acyclic diene metathesis polymerization of semiaromatic amides is described. The procedure uses second-generation Grubbs' catalyst and N-cyclohexyl-2-pyrrolidone (CHP), a high boiling, polar solvent capable of solubilizing both monomer and polymer. The addition of methanol to the reaction was found to significantly increase polymer molar mass although the role of the alcohol is currently not understood. Hydrogenation with hydrogen gas and Wilkinson's catalyst resulted in near-quantitative saturation. All polymers synthesized here exhibit a hierarchical semicrystalline morphology driven by ordering of aromatic amide groups via strong nonbonded interactions. Furthermore, the melting points can be tuned over a >100 °C range by precise substitution at just one of the backbone positions on each mer (<5% of the total).

Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features.

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom's 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia.

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19.

BACKGROUND: Non-pharmaceutical interventions such as social distancing, school closures and travel restrictions are often implemented to control outbreaks of infectious diseases. For influenza in schools, the Center of Disease Control (CDC) recommends that febrile students remain isolated at home until they have been fever-free for at least one day and a related policy is recommended for SARS-CoV-2 (COVID-19). Other authors proposed using a school week of four or fewer days of in-person instruction for all students to reduce transmission. However, there is limited evidence supporting the effectiveness of these interventions. METHODS: We introduced a mathematical model of school outbreaks that considers both intervention methods. Our model accounts for the school structure and schedule, as well as the time-progression of fever symptoms and viral shedding. The model was validated on outbreaks of seasonal and pandemic influenza and COVID-19 in schools. It was then used to estimate the outbreak curves and the proportion of the population infected (attack rate) under the proposed interventions. RESULTS: For influenza, the CDC-recommended one day of post-fever isolation can reduce the attack rate by a median (interquartile range) of 29 (13-59)%. With 2 days of post-fever isolation the attack rate could be reduced by 70 (55-85)%. Alternatively, shortening the school week to 4 and 3 days reduces the attack rate by 73 (64-88)% and 93 (91-97)%, respectively. For COVID-19, application of post-fever isolation policy was found to be less effective and reduced the attack rate by 10 (5-17)% for a 2-day isolation policy and by 14 (5-26)% for 14 days. A 4-day school week would reduce the median attack rate in a COVID-19 outbreak by 57 (52-64)%, while a 3-day school week would reduce it by 81 (79-83)%. In both infections, shortening the school week significantly reduced the duration of outbreaks. CONCLUSIONS: Shortening the school week could be an important tool for controlling influenza and COVID-19 in schools and similar settings. Additionally, the CDC-recommended post-fever isolation policy for influenza could be enhanced by requiring two days of isolation instead of one.

Effectiveness of Isolation Policies in Schools: Evidence from a Mathematical Model of Influenza and COVID-19.

BACKGROUND: Non-pharmaceutical interventions such as social distancing, school closures and travel restrictions are often implemented to control outbreaks of infectious diseases. For influenza in schools, the Center of Disease Control (CDC) recommends that febrile students remain isolated at home until they have been fever-free for at least one day and a related policy is recommended for SARS-CoV2 (COVID-19). Other authors proposed using a school week of four or fewer days of in-person instruction for all students to reduce transmission. However, there is limited evidence supporting the effectiveness of these interventions. METHODS: We introduced a mathematical model of school outbreaks that considers both intervention methods. Our model accounts for the school structure and schedule, as well as the time-progression of fever symptoms and viral shedding. The model was validated on outbreaks of seasonal and pandemic influenza and COVID-19 in schools. It was then used to estimate the outbreak curves and the proportion of the population infected (attack rate) under the proposed interventions. RESULTS: For influenza, the CDC-recommended one day of post-fever isolation can reduce the attack rate by a median (interquartile range) of 29 (13 - 59)%. With two days of post-fever isolation the attack rate could be reduced by 70 (55 - 85)%. Alternatively, shortening the school week to four and three days reduces the attack rate by 73 (64 - 88)% and 93 (91 - 97)%, respectively. For COVID-19, application of post-fever isolation policy was found to be less effective and reduced the attack rate by 10 (5 - 17)% for a two-day isolation policy and by 14 (5 - 26)% for 14 days. A four-day school week would reduce the median attack rate in a COVID-19 outbreak by 57 (52 - 64)%, while a three-day school week would reduce it by 81 (79 - 83)%. In both infections, shortening the school week significantly reduced the duration of outbreaks. CONCLUSIONS: Shortening the school week could be an important tool for controlling influenza and COVID-19 in schools and similar settings. Additionally, the CDC-recommended post-fever isolation policy for influenza could be enhanced by requiring two days of isolation instead of one.

Microbiota assembly, structure, and dynamics among Tsimane horticulturalists of the Bolivian Amazon.

Selective and neutral forces shape human microbiota assembly in early life. The Tsimane are an indigenous Bolivian population with infant care-associated behaviors predicted to increase mother-infant microbial dispersal. Here, we characterize microbial community assembly in 47 infant-mother pairs from six Tsimane villages, using 16S rRNA gene amplicon sequencing of longitudinal stool and tongue swab samples. We find that infant consumption of dairy products, vegetables, and chicha (a fermented drink inoculated with oral microbes) is associated with stool microbiota composition. In stool and tongue samples, microbes shared between mothers and infants are more abundant than non-shared microbes. Using a neutral model of community assembly, we find that neutral processes alone explain the prevalence of 79% of infant-colonizing microbes, but explain microbial prevalence less well in adults from river villages with more regular access to markets. Our results underscore the importance of neutral forces during microbiota assembly. Changing lifestyle factors may alter traditional modes of microbiota assembly by decreasing the role of neutral processes.

Addressing the challenges of modeling the scattering from bottlebrush polymers in solution.

Small-angle scattering measurements of complex macromolecules in solution are used to establish relationships between chemical structure and conformational properties. Interpretation of the scattering data requires an inverse approach where a model is chosen and the simulated scattering intensity from that model is iterated to match the experimental scattering intensity. This raises challenges in the case where the model is an imperfect approximation of the underlying structure, or where there are significant correlations between model parameters. We examine three bottlebrush polymers (consisting of polynorbornene backbone and polystyrene side chains) in a good solvent using a model commonly applied to this class of polymers: the flexible cylinder model. Applying a series of constrained Monte-Carlo Markov Chain analyses demonstrates the severity of the correlations between key parameters and the presence of multiple close minima in the goodness of fit space. We demonstrate that a shape-agnostic model can fit the scattering with significantly reduced parameter correlations and less potential for complex, multimodal parameter spaces. We provide recommendations to improve the analysis of complex macromolecules in solution, highlighting the value of Bayesian methods. This approach provides richer information for understanding parameter sensitivity compared to methods which produce a single, best fit.