MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Identification of Campylobacter jejuni and Campylobacter coli genes contributing to oxidative stress response using TraDIS analysis.

BACKGROUND: Campylobacter jejuni and Campylobacter coli are the major causative agents of bacterial gastroenteritis worldwide and are known obligate microaerophiles. Despite being sensitive to oxygen and its reduction products, both species are readily isolated from animal food products kept under atmospheric conditions where they face high oxygen tension levels. RESULTS: In this study, Transposon Directed Insertion-site Sequencing (TraDIS) was used to investigate the ability of one C. jejuni strain and two C. coli strains to overcome oxidative stress, using H2O2 to mimic oxidative stress. Genes were identified that were required for oxidative stress resistance for each individual strain but also allowed a comparison across the three strains. Mutations in the perR and ahpC genes were found to increase Campylobacter tolerance to H2O2. The roles of these proteins in oxidative stress were previously known in C. jejuni, but this data indicates that they most likely play a similar role in C. coli. Mutation of czcD decreased Campylobacter tolerance to H2O2. The role of CzcD, which functions as a zinc exporter, has not previously been linked to oxidative stress. The TraDIS data was confirmed using defined deletions of perR and czcD in C. coli 15-537360. CONCLUSIONS: This is the first study to investigate gene fitness in both C. jejuni and C. coli under oxidative stress conditions and highlights both similar roles for certain genes for both species and highlights other genes that have a role under oxidative stress.

Plasma protein signatures of adult asthma.

BACKGROUND: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma. METHODS: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)). RESULTS: Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis. CONCLUSION: This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.

A Bayesian approach to Mendelian randomization using summary statistics in the univariable and multivariable settings with correlated pleiotropy.

Mendelian randomization uses genetic variants as instrumental variables to make causal inferences on the effect of an exposure on an outcome. Due to the recent abundance of high-powered genome-wide association studies, many putative causal exposures of interest have large numbers of independent genetic variants with which they associate, each representing a potential instrument for use in a Mendelian randomization analysis. Such polygenic analyses increase the power of the study design to detect causal effects; however, they also increase the potential for bias due to instrument invalidity. Recent attention has been given to dealing with bias caused by correlated pleiotropy, which results from violation of the "instrument strength independent of direct effect" assumption. Although methods have been proposed that can account for this bias, a number of restrictive conditions remain in many commonly used techniques. In this paper, we propose a Bayesian framework for Mendelian randomization that provides valid causal inference under very general settings. We propose the methods MR-Horse and MVMR-Horse, which can be performed without access to individual-level data, using only summary statistics of the type commonly published by genome-wide association studies, and can account for both correlated and uncorrelated pleiotropy. In simulation studies, we show that the approach retains type I error rates below nominal levels even in high-pleiotropy scenarios. We demonstrate the proposed approaches in applied examples in both univariable and multivariable settings, some with very weak instruments.

An attacin antimicrobial peptide, Hill_BB_C10074, from Hermetia illucens with anti-Pseudomonas aeruginosa activity.

BACKGROUND: There is a global need to develop new therapies to treat infectious diseases and tackle the rise in antimicrobial resistance. To date, the larvae of the Black Solider Fly, Hermetia illucens, have the largest repertoire of antimicrobial peptides derived from insects. Antimicrobial peptides are of particular interest in the exploration of alternative antimicrobials due to their potent action and reduced propensity to induce resistance compared with more traditional antibiotics. RESULTS: The predicted attacin from H. illucens, Hill_BB_C10074, was first identified in the transcriptome of H. illucens populations that had been fed a plant-oil based diet. In this study, recombinant Hill_BB_C10074 (500 µg/mL), was found to possess potent antimicrobial activity against the serious Gram-negative pathogen, Pseudomonas aeruginosa. Sequence and structural homology modelling predicted that Hill_BB_C10074 formed a homotrimeric complex that may form pores in the Gram-negative bacterial outer membrane. In vitro experiments defined the antimicrobial action of Hill_BB_C10074 against P. aeruginosa and transmission electron microscopy and electrochemical impedance spectroscopy confirmed the outer membrane disruptive power of Hill_BB_C10074 which was greater than the clinically relevant antibiotic, polymyxin B. CONCLUSIONS: Combining predictive tools with in vitro approaches, we have characterised Hill_BB_C10074 as an important insect antimicrobial peptide and promising candidate for the future development of clinical antimicrobials.

Mendelian randomization for nephrologists.

Confounding is a major limitation of observational studies. Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. With the emergence of large-scale genome-wide association studies in nephrology over the past decade, MR has become a popular method to establish causal inferences. However, MR is a complex and challenging methodology that requires careful consideration to ensure robust results. This review article aims to summarize the basic concepts of MR, its application and relevance in nephrology, and the methodological challenges and limitations as well as discuss the current guidelines for design and reporting. With reference to a clinically relevant example of examining the causal relationship between the estimated glomerular filtration rate and cancer, this review outlines the key steps to conducting an MR study, including the key considerations and potential pitfalls at each step. These include defining the clinical question, selecting the data sources, identifying and refining appropriate genetic variants by considering linkage disequilibrium and associations with potential confounders, harmonization of variants across data sets, validation of the genetic instrument by assessing its strength, estimation of the causal effects, confirming the validity of the findings, and interpreting and reporting results.

Genetically Predicted Vegetable Intake and Cardiovascular Diseases and Risk Factors: An Investigation with Mendelian Randomization.

BACKGROUND: The associations between vegetable intake and cardiovascular diseases have been demonstrated in observational studies, but less sufficiently in randomized trials. Mendelian randomization has been considered a promising alternative in causal inference. The separate effects of cooked and raw vegetable intake remain unclear. This study aimed to investigate the associations between cooked and raw vegetable intake with cardiovascular outcomes using MR. METHODS: We identified 15 and 28 genetic variants statistically and biologically associated with cooked and raw vegetable intake, respectively, from previous genome-wide association studies, which were used as instrumental variables to estimate associations with coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF). The independent effects of genetically predicted cooked and raw vegetable intake were examined using multivariable MR analysis. We performed one-sample and two-sample MR analyses and combined their results using meta-analysis. Bonferroni correction was applied for multiple comparisons. We performed two-sample MR analysis for cardiometabolic risk factors (serum lipids, blood pressure, body mass index, and glycemic traits) to explore the potential mechanisms. RESULTS: In the MR meta-analysis of 1.2 million participants, we found null evidence for associations between genetically predicted cooked and raw vegetable intake with CHD, HF, or AF. Raw vegetable intake was nominally associated with stroke (odds ratio [95% confidence interval] 0.82 [0.69-0.98] per 1 daily serving increase, p = 0.03), but this association did not pass the corrected significance level. We found consistently null evidence for associations with serum lipids, blood pressure, body mass index, or glycemic traits. CONCLUSIONS: We found null evidence for associations between genetically predicted vegetable intake with CHD, AF, HF, or cardiometabolic risk factors in this MR study. Raw vegetable intake may reduce risk of stroke, but this warrants more research. True associations between vegetable intake and CVDs cannot be completely ruled out, and future investigations are required for causal inference in nutritional research.

Application of TraDIS to define the core essential genome of Campylobacter jejuni and Campylobacter coli.

Campylobacter species are the major cause of bacterial gastroenteritis. As there is no effective vaccine, combined with the rapid increase in antimicrobial resistant strains, there is a need to identify new targets for intervention. Essential genes are those that are necessary for growth and/or survival, making these attractive targets. In this study, comprehensive transposon mutant libraries were created in six C. jejuni strains, four C. coli strains and one C. lari and C. hyointestinalis strain, allowing for those genes that cannot tolerate a transposon insertion being called as essential. Comparison of essential gene lists using core genome analysis can highlight those genes which are common across multiple strains and/or species. Comparison of C. jejuni and C. coli, the two species that cause the most disease, identified 316 essential genes. Genes of interest highlighted members of the purine pathway being essential for C. jejuni whilst also finding that a functional potassium uptake system is essential. Protein-protein interaction networks using these essential gene lists also highlighted proteins in the purine pathway being major 'hub' proteins which have a large number of interactors across the network. When adding in two more species (C. lari and C. hyointestinalis) the essential gene list reduces to 261. Within these 261 essential genes, there are many genes that have been found to be essential in other bacteria. These include htrB and PEB4, which have previously been found as core virulence genes across Campylobacter species in other studies. There were 21 genes which have no known function with eight of these being associated with the membrane. These surface-associated essential genes may provide attractive targets. The essential gene lists presented will help to prioritise targets for the development of novel therapeutic and preventative interventions.

Enterohemorrhagic Escherichia coli responds to gut microbiota metabolites by altering metabolism and activating stress responses.

Enterohemorrhagic Escherichia coli (EHEC) is a major cause of severe bloody diarrhea, with potentially lethal complications, such as hemolytic uremic syndrome. In humans, EHEC colonizes the colon, which is also home to a diverse community of trillions of microbes known as the gut microbiota. Although these microbes and the metabolites that they produce represent an important component of EHEC's ecological niche, little is known about how EHEC senses and responds to the presence of gut microbiota metabolites. In this study, we used a combined RNA-Seq and Tn-Seq approach to characterize EHEC's response to metabolites from an in vitro culture of 33 human gut microbiota isolates (MET-1), previously demonstrated to effectively resolve recurrent Clostridioides difficile infection in human patients. Collectively, the results revealed that EHEC adjusts to growth in the presence of microbiota metabolites in two major ways: by altering its metabolism and by activating stress responses. Metabolic adaptations to the presence of microbiota metabolites included increased expression of systems for maintaining redox balance and decreased expression of biotin biosynthesis genes, reflecting the high levels of biotin released by the microbiota into the culture medium. In addition, numerous genes related to envelope and oxidative stress responses (including cpxP, spy, soxS, yhcN, and bhsA) were upregulated during EHEC growth in a medium containing microbiota metabolites. Together, these results provide insight into the molecular mechanisms by which pathogens adapt to the presence of competing microbes in the host environment, which ultimately may enable the development of therapies to enhance colonization resistance and prevent infection.

Using genetic association data to guide drug discovery and development: Review of methods and applications.

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

High-Throughput Mutagenesis Reveals a Role for Antimicrobial Resistance- and Virulence-Associated Mobile Genetic Elements in Staphylococcus aureus Host Adaptation.

Methicillin-resistant Staphylococcus aureus (MRSA) clonal-complex 398 (CC398) is the dominant livestock-associated (LA) MRSA lineage in European livestock and an increasing cause of difficult-to-treat human disease. LA-CC398 MRSA evolved from a diverse human-associated methicillin-sensitive population, and this transition from humans to livestock was associated with three mobile genetic elements (MGEs). In this study, we apply transposon-directed insertion site sequencing (TraDIS), a high-throughput transposon mutagenesis approach, to investigate genetic signatures that contribute to LA-CC398 causing disease in humans. We identified 26 genes associated with LA-CC398 survival in human blood and 47 genes in porcine blood. We carried out phylogenetic reconstruction on 1,180 CC398 isolates to investigate the genetic context of all identified genes. We found that all genes associated with survival in human blood were part of the CC398 core genome, while 2/47 genes essential for survival in porcine blood were located on MGEs. Gene SAPIG0966 was located on the previously identified Tn916 transposon carrying a tetracycline resistance gene, which has been shown to be stably inherited within LA-CC398. Gene SAPIG1525 was carried on a phage element, which in part, matched phiSa2wa_st1, a previously identified bacteriophage carrying the Panton-Valentine leucocidin (PVL) virulence factor. Gene deletion mutants constructed in two LA-CC398 strains confirmed that the SAPIG0966 carrying Tn916 and SAPIG1525 were important for CC398 survival in porcine blood. Our study shows that MGEs that carry antimicrobial resistance and virulence genes could have a secondary function in bacterial survival in blood and may be important for host adaptation. IMPORTANCE CC398 is the dominant type of methicillin-resistant Staphylococcus aureus (MRSA) in European livestock and a growing cause of human infections. Previous studies have suggested MRSA CC398 evolved from human-associated methicillin-sensitive Staphylococcus aureus and is capable of rapidly readapting to human hosts while maintaining antibiotic resistance. Using high-throughput transposon mutagenesis, our study identified 26 and 47 genes important for MRSA CC398 survival in human and porcine blood, respectively. Two of the genes important for MRSA CC398 survival in porcine blood were located on mobile genetic elements (MGEs) carrying resistance or virulence genes. Our study shows that these MGEs carrying antimicrobial resistance and virulence genes could have a secondary function in bacterial survival in blood and may be important for blood infection and host adaptation.

Development and validation of a CRISPR interference system for gene regulation in Campylobacter jejuni.

BACKGROUND: Campylobacter spp. are the leading cause of bacterial food-borne illness in humans worldwide, with Campylobacter jejuni responsible for 80% of these infections. There is an urgent need to understand fundamental C. jejuni biology for the development of new strategies to prevent and treat infections. The range of molecular tools available to regulate gene expression in C. jejuni is limited, which in turn constrains our ability to interrogate the function of essential and conditionally essential genes. We have addressed this by developing and utilising a CRISPR-based interference system known as CRISPRi in C. jejuni to control gene expression. To achieve this, a catalytically inactive ("dead") cas9 and sgRNA backbone from the Streptococcus pyogenes CRISPRi system was combined with C. jejuni-derived promoters of predetermined expression activities to develop a CRISPRi-based repression tool in C. jejuni strains M1Cam and 81-176. RESULTS: The CRISPRi tool was validated through successful repression of the arylsulphatase-encoding gene astA using a range of sgRNA target sequences spanning the astA gene. The tool was also applied to target astA in an M1Cam CRISPR-Cas9 deletion strain, which showed that the presence of an endogenous CRISPR-Cas9 system did not affect the activity of the CRISPRi-based repression tool. The tool was further validated against the hippicurase-encoding gene hipO. Following this, the flagella genes flgR, flaA, flaB and both flaA and flaB were targeted for CRISPRi-based repression, which resulted in varying levels of motility reduction and flagella phenotypes as determined by phenotypical assays and transmission electron microscopy (TEM). CONCLUSIONS: This is the first report of a CRISPRi-based tool in C. jejuni, which will provide a valuable resource to the Campylobacter community.

Modification of avian pathogenic Escherichia coli χ7122 lipopolysaccharide increases accessibility to glycoconjugate antigens.

BACKGROUND: Worldwide, an estimated 70.7 billion broilers were produced in 2020. With the reduction in use of prophylactic antibiotics as a result of consumer pressure and regulatory oversight alternative approaches, such as vaccination, are required to control bacterial infections. A potential way to produce a multivalent vaccine is via the generation of a glycoconjugate vaccine which consists of an antigenic protein covalently linked to an immunogenic carbohydrate. Protein-glycan coupling technology (PGCT) is an approach to generate glycoconjugates using enzymes that can couple proteins and glycan when produced in bacterial cells. Previous studies have used PGCT to generate a live-attenuated avian pathogenic Escherichia coli (APEC) strain capable of N-glycosylation of target proteins using a chromosomally integrated Campylobacter jejuni pgl locus. However, this proved ineffective against C. jejuni challenge. RESULTS: In this study we demonstrate the lack of surface exposure of glycosylated protein in APEC strain χ7122 carrying the pgl locus. Furthermore, we hypothesise that this may be due to the complex cell-surface architecture of E. coli. To this end, we removed the lipopolysaccharide O-antigen of APEC χ7122 pgl+ via deletion of the wecA gene and demonstrate increased surface exposure of glycosylated antigens (NetB and FlpA) in this strain. We hypothesise that increasing the surface expression of the glycosylated protein would increase the chance of host immune cells being exposed to the glycoconjugate, and therefore the generation of an efficacious immune response would be more likely. CONCLUSIONS: Our results demonstrate an increase in cell surface exposure and therefore accessibility of glycosylated antigens upon removal of lipopolysaccharide antigen from the APEC cell surface.

Substrate Utilisation and Energy Metabolism in Non-Growing Campylobacter jejuni M1cam.

Campylobacter jejuni, the major cause of bacterial foodborne illness, is also a fastidious organism that requires strict growth requirements in the laboratory. Our aim was to study substrate utilisation and energy metabolism in non-growing C. jejuni to investigate the ability of these bacteria to survive so effectively in the food chain. We integrated phenotypic microarrays and genome-scale metabolic modelling (GSM) to investigate the survival of C. jejuni on 95 substrates. We further investigated the underlying metabolic re-adjustment associated with varying energy demands on each substrate. We identified amino acids, organic acids and H2, as single substrates supporting survival without growth. We identified several different mechanisms, which were used alone or in combination, for ATP production: substrate-level phosphorylation via acetate kinase, the TCA cycle, and oxidative phosphorylation via the electron transport chain that utilised alternative electron donors and acceptors. The benefit of ATP production through each of these mechanisms was associated with the cost of enzyme investment, nutrient availability and/or O2 utilisation. C. jejuni can utilise a wide range of substrates as energy sources, including organic acids commonly used for marination or preservation of ingredients, which might contribute to the success of their survival in changing environments.

HAM-ART: An optimised culture-free Hi-C metagenomics pipeline for tracking antimicrobial resistance genes in complex microbial communities.

Shotgun metagenomics is a powerful tool to identify antimicrobial resistance (AMR) genes in microbiomes but has the limitation that extrachromosomal DNA, such as plasmids, cannot be linked with the host bacterial chromosome. Here we present a comprehensive laboratory and bioinformatics pipeline HAM-ART (Hi-C Assisted Metagenomics for Antimicrobial Resistance Tracking) optimised for the generation of metagenome-assembled genomes including both chromosomal and extrachromosomal AMR genes. We demonstrate the performance of the pipeline in a study comparing 100 pig faecal microbiomes from low- and high-antimicrobial use pig farms (organic and conventional farms). We found significant differences in the distribution of AMR genes between low- and high-antimicrobial use farms including a plasmid-borne lincosamide resistance gene exclusive to high-antimicrobial use farms in three species of Lactobacilli. The bioinformatics pipeline code is available at https://github.com/lkalmar/HAM-ART.

Tatajuba: exploring the distribution of homopolymer tracts.

Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialized bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and help predict their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source licence GNU GPLv3.

PglB function and glycosylation efficiency is temperature dependent when the pgl locus is integrated in the Escherichia coli chromosome.

BACKGROUND: Campylobacter is an animal and zoonotic pathogen of global importance, and a pressing need exists for effective vaccines, including those that make use of conserved polysaccharide antigens. To this end, we adapted Protein Glycan Coupling Technology (PGCT) to develop a versatile Escherichia coli strain capable of generating multiple glycoconjugate vaccine candidates against Campylobacter jejuni. RESULTS: We generated a glycoengineering E. coli strain containing the conserved C. jejuni heptasaccharide coding region integrated in its chromosome as a model glycan. This methodology confers three advantages: (i) reduction of plasmids and antibiotic markers used for PGCT, (ii) swift generation of many glycan-protein combinations and consequent rapid identification of the most antigenic proteins or peptides, and (iii) increased genetic stability of the polysaccharide coding-region. In this study, by using the model glycan expressing strain, we were able to test proteins from C. jejuni, Pseudomonas aeruginosa (both Gram-negative), and Clostridium perfringens (Gram-positive) as acceptors. Using this pgl integrant E. coli strain, four glycoconjugates were readily generated. Two glycoconjugates, where both protein and glycan are from C. jejuni (double-hit vaccines), and two glycoconjugates, where the glycan antigen is conjugated to a detoxified toxin from a different pathogen (single-hit vaccines). Because the downstream application of Live Attenuated Vaccine Strains (LAVS) against C. jejuni is to be used in poultry, which have a higher body temperature of 42 °C, we investigated the effect of temperature on protein expression and glycosylation in the E. coli pgl integrant strain. CONCLUSIONS: We determined that glycosylation is temperature dependent and that for the combination of heptasaccharide and carriers used in this study, the level of PglB available for glycosylation is a step limiting factor in the glycosylation reaction. We also demonstrated that temperature affects the ability of PglB to glycosylate its substrates in an in vitro glycosylation assay independent of its transcriptional level.

Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity.

Clustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.

An efficient and robust approach to Mendelian randomization with measured pleiotropic effects in a high-dimensional setting.

Valid estimation of a causal effect using instrumental variables requires that all of the instruments are independent of the outcome conditional on the risk factor of interest and any confounders. In Mendelian randomization studies with large numbers of genetic variants used as instruments, it is unlikely that this condition will be met. Any given genetic variant could be associated with a large number of traits, all of which represent potential pathways to the outcome which bypass the risk factor of interest. Such pleiotropy can be accounted for using standard multivariable Mendelian randomization with all possible pleiotropic traits included as covariates. However, the estimator obtained in this way will be inefficient if some of the covariates do not truly sit on pleiotropic pathways to the outcome. We present a method that uses regularization to identify which out of a set of potential covariates need to be accounted for in a Mendelian randomization analysis in order to produce an efficient and robust estimator of a causal effect. The method can be used in the case where individual-level data are not available and the analysis must rely on summary-level data only. It can be used where there are any number of potential pleiotropic covariates up to the number of genetic variants less one. We show the results of simulation studies that demonstrate the performance of the proposed regularization method in realistic settings. We also illustrate the method in an applied example which looks at the causal effect of urate plasma concentration on coronary heart disease.