Biology subjects

Harrison, S.

Publications and source records attributed to Harrison, S..

31 records · Page 2Linked to original sources

bioRxiv2021

A prebiotic basis for ATP as the universal energy currency

ATP is universally conserved as the principal energy currency in cells, driving metabolism through phosphorylation and condensation reactions. Such deep conservation suggests that ATP arose at an early stage of biochemical evolution. Yet purine synthesis requires six phosphorylation steps linked to ATP hydrolysis. This autocatalytic requirement for ATP to synthesize ATP implies the need for an earlier prebiotic ATP-equivalent, which could drive protometabolism before purine synthesis. Why this early phosphorylating agent was replaced, and specifically with ATP rather than other nucleotide triphosphates, remains a mystery. Here we show that the deep conservation of ATP reflects its prebiotic chemistry in relation to another universally conserved intermediate, acetyl phosphate, which bridges between thioester and phosphate metabolism by linking acetyl CoA to the substrate-level phosphorylation of ADP. We confirm earlier results showing that acetyl phosphate can phosphorylate ADP to ATP at nearly 20 % yield in water in the presence of Fe3+ ions. We then show that Fe3+ and acetyl phosphate are surprisingly favoured: a panel of other prebiotically relevant ions and minerals did not catalyze ADP phosphorylation; nor did a number of other potentially prebiotic phosphorylating agents. Only carbamoyl phosphate showed some modest phosphorylating activity. Critically, we show that acetyl phosphate does not phosphorylate other nucleotide diphosphates or free pyrophosphate in water. The phosphorylation of ADP monomers seems to be favoured by the interaction between the N6 amino group on the adenine ring with Fe3+ coupled to acetyl phosphate. Our findings suggest that the reason ATP is universally conserved across life is that its formation is chemically favoured in aqueous solution under mild prebiotic conditions.

biochemistry↗

bioRxiv2020

A prevalent focused human antibody response to the influenza hemagglutinin head interface

Novel animal influenza viruses emerge, initiate pandemics and become endemic seasonal variants that have evolved to escape from prevalent herd immunity. These processes often outpace vaccine-elicited protection. Focusing immune responses on conserved epitopes may impart durable immunity. We describe a focused, protective antibody response, abundant in memory and serum repertoires, to a conserved region at the influenza hemagglutinin head interface. Structures of eleven examples, eight reported here, from seven human donors demonstrate the convergence of responses on a single epitope. The eleven are genetically diverse, with one class having a common, IG{kappa}V1-39, light chain. All of the antibodies bind HAs from multiple serotypes. The lack of apparent genetic restriction and potential for elicitation by more than one serotype may explain their abundance. We define the head interface as a major target of broadly protective antibodies with the potential to influence the outcomes of influenza infection.

immunology↗

bioRxiv2020

Organoid-in-a-column coupled on-line with liquid chromatography-mass spectrometry

Organoids, i.e. laboratory-grown organ models developed from stem cells, are emerging tools for studying organ physiology, disease modeling and drug development. On-line analysis of organoids with mass spectrometry would provide analytical versatility and automation. To achieve these features with robust hardware, we have loaded liquid chromatography column housings with induced pluripotent stem cell (iPSC) derived liver organoids and coupled the "organ-in-a-column" units on-line with liquid chromatography-mass spectrometry (LC-MS). Liver organoids were co-loaded with glass beads to achieve an even distribution of organoids throughout the column while preventing clogging. The liver organoids were interrogated "on column" with heroin, followed by on-line monitoring of the drugs phase 1 metabolism. Enzymatic metabolism of heroin produced in the "organ-in-a-column" units was detected and monitored using a triple quadrupole MS instrument, serving as a proof-of-concept for on-line coupling of liver organoids and mass spectrometry. Taken together, the technology allows direct integration of liver organoids with LC-MS, allowing selective and automated tracking of drug metabolism over time.

bioengineering↗

bioRxiv2020

Electromembrane extraction and mass spectrometry for liver organoid drug metabolism studies

Liver organoids are emerging tools for precision drug development and toxicity screening. We demonstrate that electromembrane extraction (EME) based on electrophoresis across an oil membrane is suited for segregating selected organoid-derived drug metabolites prior to mass spectrometry (MS)-based measurements. EME, allowed drugs and drug metabolites to be separated from cell medium components (albumin, etc.) that could interfere with subsequent measurements. Multi-well EME (Parallel-EME) holding 100 L solutions allowed for simple and repeatable monitoring of heroin phase I metabolism kinetics. Organoid Parallel-EME extracts were compatible with ultrahigh-performance liquid chromatography (UHPLC) used to separate the analytes prior to detection. Taken together, liver organoids are well-matched with EME followed by MS-based measurements.

biochemistry↗

bioRxiv2019

Structure of HIV-1 Env bound with the Fab of antibody PG16

The HIV-1 envelope protein (Env) is the target of neutralizing antibodies and the template for vaccine immunogen design. The dynamic conformational equilibrium of trimeric Env influences its antigenicity and potential immunogenicity. Antibodies that bind at the trimer apex stabilize a \"closed\" conformation characteristic of the most difficult to neutralize isolates. A goal of vaccine development is therefore to mimic the closed conformation in a designed immunogen. A disulfide-stabilized, trimeric Env ectodomain -- the \"SOSIP\" construct -- has many of the relevant properties; it is also particularly suitable for structure determination. Some single-molecule studies have, however, suggested that the SOSIP trimer is not a good representation of Env on the surface of a virion or an infected cell. We isolated Env (fully cleaved to gp120 and gp41) from the surface of expressing cells using tagged, apex-binding Fab PG16 and determined the structure of the PG16-Env complex by cryo-EM to an overall resolution of 4.6 [A]. Placing the only purification tag on the Fab ensured that the isolated Env was continuously stabilized in its closed, native conformation. The Env structure in this complex corresponds closely to the SOSIP structures determined by both x-ray crystallography and cryo-EM. Although the membrane-interacting elements are not resolved in our reconstruction, we can make inferences about the connection between ectodomain and membrane-proximal external region (MPER) by reference to the published cryo-tomography structure of an Env \"spike\" and the NMR structure of the MPER-transmembrane segment. We discuss these results in view of the conflicting interpretations in the literature.

immunology↗

bioRxiv2019

The structure of the yeast Ctf3 complex

Kinetochores are the chromosomal attachment points for spindle microtubules. They are also signaling hubs that control major cell cycle transitions and coordinate chromosome folding. Most well-studied eukaryotes rely on a conserved set of factors, which are divided among two loosely-defined groups, for these functions. Outer kinetochore proteins contact microtubules or regulate this contact directly. Inner kinetochore proteins designate the kinetochore assembly site by recognizing a specialized nucleosome containing the H3 variant Cse4/CENP-A. We previously determined the structure, resolved by cryo-electron microscopy (cryo-EM), of the yeast Ctf19 complex (Ctf19c, homologous to the vertebrate CCAN), providing a high-resolution view of inner kinetochore architecture. We now extend these observations by reporting a near-atomic model of the Ctf3 complex, the outermost Ctf19c sub-assembly seen in our original cryo-EM density. The model is sufficiently well-determined by the new data to enable molecular interpretation of Ctf3 recruitment and function.

cell biology↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2019

The causal effect of adiposity on hospital costs: Mendelian Randomization analysis of over 300,000 individuals from the UK Biobank

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Many existing estimates of this association are affected by endogeneity bias caused by simultaneity, measurement error and omitted variables. The contribution of this study is to avoid this bias by using a novel identification strategy - random germline genetic variation in an instrumental variable analysis - to identify the presence and magnitude of the causal effect of BMI on inpatient hospital costs. We also use data on genetic variants to undertake much richer testing of the sensitivity of results to potential violations of the instrumental variable assumptions than is possible with existing approaches. Using data on over 300,000 individuals, we found effect sizes for the marginal unit of BMI more than 50% larger than multivariable effect sizes. These effects attenuated under sensitivity analyses, but remained larger than multivariable estimates for all but one estimator. There was little evidence for non-linear effects of BMI on hospital costs. Within-family estimates, intended to address dynastic biases, were null but suffered from low power. This paper is the first to use genetic variants in a Mendelian Randomization framework to estimate the causal effect of BMI (or any other disease/trait) on healthcare costs. This type of analysis can be used to inform the cost-effectiveness of interventions and policies targeting the prevention and treatment of overweight and obesity, and for setting research priorities.

epidemiology↗

bioRxiv2019

Clades of huge phage from across Earth’s ecosystems

Phage typically have small genomes and depend on their bacterial hosts for replication. DNA sequenced from many diverse ecosystems revealed hundreds of huge phage genomes, between 200 kbp and 716 kbp in length. Thirty-four genomes were manually curated to completion, including the largest phage genomes yet reported. Expanded genetic repertoires include diverse and new CRISPR-Cas systems, tRNAs, tRNA synthetases, tRNA modification enzymes, translation initiation and elongation factors, and ribosomal proteins. Phage CRISPR-Cas systems have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phage may repurpose bacterial CRISPR-Cas systems to eliminate competing phage. We phylogenetically define major clades of huge phage from human and other animal microbiomes, oceans, lakes, sediments, soils and the built environment. We conclude that their large gene inventories reflect a conserved biological strategy, observed over a broad bacterial host range and across Earths ecosystems.

microbiology↗

bioRxiv2019

Using genetic instruments to estimate interactions in Mendelian Randomization studies

BACKGROUNDThe interactive effect of two exposures on an outcome can be confounded. We demonstrate the use of Mendelian Randomization (MR) to estimate unconfounded additive interactions. METHODSUsing simulation, we test an extension to multivariable MR using two-stage least squares to estimate the additive interaction between two continuous exposures on a continuous outcome, including scenarios where one exposure has a causal effect on the other (mediation). The interaction parameters were set to be one third of the main effects parameters to impose a limit on the variance explained by interaction terms. We compare the performance of the two-stage least squares estimator to a Factorial MR design, in which genetic risk scores for each exposure are dichotomised to create four groups, akin to a factorial randomized controlled trial. As an illustrative example, we apply factorial MR and the 2SLS estimator to the interactive effect of education and BMI on systolic blood pressure in UK Biobank. RESULTSOur simulations demonstrate that factorial MR has very low statistical power; 5-7% at N=50,000 and 8-23% at N=500,000 across the range of parameters tested. The two-stage least squares estimator had higher power to detect interactions than factorial MR and a lower type I error. For N=500,000, the two-stage least squares estimator had a power ranging from 29.7-92.9% and a type I error ranging from 4-6%. 95% Monte Carlo confidence intervals suggested that the estimator was unbiased to a reasonable degree of accuracy at this sample size. In comparison, the power at N=50,000 was 7-55%. CONCLUSIONSA two-stage least squares estimator using genetic risk scores for each exposure is a more powerful alternative for detecting an unconfounded additive interaction of two exposures on an outcome than existing approaches that rely on dichotomising genetic risk scores, but it requires a large sample size and instruments of adequate strength.

epidemiology↗

bioRxiv2019

Effects of body mass index on relationship status, social contact, and socioeconomic position: Mendelian Randomization study in UK Biobank

ObjectiveTo assess whether body mass index (BMI) has a causal effect on social and socioeconomic factors, including whether both high and low BMI can be detrimental.\n\nDesignMendelian Randomization, using genetic variants for BMI to obtain unconfounded estimates, and non-linear Mendelian Randomization.\n\nSettingUK Biobank.\n\nParticipants378,244 men and women of European ancestry, mean age 57 (SD 8 years).\n\nMain outcome measuresTownsend deprivation index, income, age completed full time education, degree level education, job class, employment status, cohabiting relationship status, participation in leisure and social activities, visits from friends and family, and having someone to confide in.\n\nResultsHigher BMI was causally associated with higher deprivation, lower income, fewer years of education, lower odds of degree-level education and skilled employment. For example, a 1 SD higher genetically-determined BMI (4.8kg/m2 in UK Biobank) was associated with {pound}1,660 less income per annum [95%CI: {pound}950, {pound}2,380]. Non-linear Mendelian Randomization provided evidence that both low BMI (bottom decile, <22kg/m2) and high BMI (top seven deciles, >24.6kg/m2) can increase deprivation and reduce income. In men only, higher BMI was related to lower participation in leisure and social activities. There was no evidence of causal effects of BMI on visits from friends and family or in having someone to confide in. Non-linear Mendelian Randomization analysis showed that low BMI (bottom three deciles, <23.5kg/m2) reduces the odds of cohabiting with a partner or spouse for men, whereas high BMI (top two deciles, >30.7kg/m2) reduces the odds of cohabitation with a partner or spouse for women.\n\nConclusionsBMI affects social and socioeconomic outcomes, with both high and low BMI being detrimental for some measures of SEP. This suggests that in addition to health benefits, maintaining healthy ranges of BMI across the population could have benefits both for individuals and society.

epidemiology↗

bioRxiv2018

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5xl0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.\n\nTo demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

genetics↗

bioRxiv2018

Recommendations for Interpreting the Loss of Function PVS1 ACMG/AMP Variant Criteria

The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria. This guideline includes a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on the specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about the variant type, its location within the gene, or any additional evidence for the likelihood of a true null effect. Furthermore, the ACMG/AMP guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be used are still missing. Here, as part of the Clinical Genomic Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Groups goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 rule using detailed guidance addressing all the above-mentioned gaps. We evaluate the performance of the refined rule using heterogeneous types of loss of function variants (n = 56) curated by seven disease-specific groups across ten genes. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.\n\nGRANT NUMBERSResearch reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834. LGB was supported by the Intramural Research Program of the NHGRI grant number HG200359 09.

genomics↗