Plasmids have a key role in the horizontal transfer of genes among bacteria. Although plasmids are catalysts for bacterial evolution, it is challenging to understand how they can persist in bacterial ...populations over the long term because of the burden they impose on their hosts (the 'plasmid paradox'). This paradox is especially perplexing in the case of 'small' plasmids, which are unable to self-transfer by conjugation. Here, for the first time, we investigate how interactions between co-infecting plasmids influence plasmid persistence. Using an experimental model system based on interactions between a diverse assemblage of 'large' plasmids and a single small plasmid, pNI105, in the pathogenic bacterium Pseudomonas aeruginosa, we demonstrate that positive epistasis minimizes the cost associated with carrying multiple plasmids over the short term and increases the stability of the small plasmid over a longer time scale. In support of these experimental data, bioinformatic analysis showed that associations between small and large plasmids are more common than would be expected owing to chance alone across a range of families of bacteria; more generally, we find that co-infection with multiple plasmids is more common than would be expected owing to chance across a wide range of bacterial phyla. Collectively, these results suggest that positive epistasis promotes plasmid stability in bacterial populations. These findings pave the way for future mechanistic studies aimed at elucidating the molecular mechanisms of plasmid-plasmid interaction, and evolutionary studies aimed at understanding how the coevolution of plasmids drives the spread of plasmid-encoded traits.
Interferon-α (IFN-α) is essential for antiviral immunity, but in the absence of matrix metalloproteinase-12 (MMP-12) or IκBα (encoded by NFKBIA) we show that IFN-α is retained in the cytosol of ...virus-infected cells and is not secreted. Our findings suggest that activated IκBα mediates the export of IFN-α from virus-infected cells and that the inability of cells in Mmp12(-/-) but not wild-type mice to express IκBα and thus export IFN-α makes coxsackievirus type B3 infection lethal and renders respiratory syncytial virus more pathogenic. We show here that after macrophage secretion, MMP-12 is transported into virus-infected cells. In HeLa cells MMP-12 is also translocated to the nucleus, where it binds to the NFKBIA promoter, driving transcription. We also identified dual-regulated substrates that are repressed both by MMP-12 binding to the substrate's gene exons and by MMP-12-mediated cleavage of the substrate protein itself. Whereas intracellular MMP-12 mediates NFKBIA transcription, leading to IFN-α secretion and host protection, extracellular MMP-12 cleaves off the IFN-α receptor 2 binding site of systemic IFN-α, preventing an unchecked immune response. Consistent with an unexpected role for MMP-12 in clearing systemic IFN-α, treatment of coxsackievirus type B3-infected wild-type mice with a membrane-impermeable MMP-12 inhibitor elevates systemic IFN-α levels and reduces viral replication in pancreas while sparing intracellular MMP-12. These findings suggest that inhibiting extracellular MMP-12 could be a new avenue for the development of antiviral treatments.
Our understanding of the evolutionary consequences of mutation relies heavily on estimates of the rate and fitness effect of spontaneous mutations generated by mutation accumulation (MA) experiments. ...We performed a classic MA experiment in which frequent sampling of MA lines was combined with whole genome resequencing to develop a high-resolution picture of the effect of spontaneous mutations in a hypermutator (ΔmutS) strain of the bacterium Pseudomonas aeruginosa. After ∼644 generations of mutation accumulation, MA lines had accumulated an average of 118 mutations, and we found that average fitness across all lines decayed linearly over time. Detailed analyses of the dynamics of fitness change in individual lines revealed that a large fraction of the total decay in fitness (42.3%) was attributable to the fixation of rare, highly deleterious mutations (comprising only 0.5% of fixed mutations). Furthermore, we found that at least 0.64% of mutations were beneficial and probably fixed due to positive selection. The majority of mutations that fixed (82.4%) were base substitutions and we failed to find any signatures of selection on nonsynonymous or intergenic mutations. Short indels made up a much smaller fraction of the mutations that were fixed (17.4%), but we found evidence of strong selection against indels that caused frameshift mutations in coding regions. These results help to quantify the amount of natural selection present in microbial MA experiments and demonstrate that changes in fitness are strongly influenced by rare mutations of large effect.
Many drugs show promise in animal models but fail in human clinical trials due to lack of efficacy. Retrospective studies have found that proteins are more likely to make successful drug targets if ...they have been linked to the relevant disease by human genetic studies. We have published genome-wide association studies (GWASes) for Parkinson's disease (PD) and schizophrenia (SCZ), testing for an association between disease status and millions of single nucleotide polymorphisms (SNPs). Although >300 genomic regions were identified for these diseases, the causal genes in many of these regions remain unknown. We propose using state-of-the-art statistical genetics tools to identify these causal genes and explore their potential as drug targets.
Most GWASes attempt to define the smallest possible set of SNPs that is likely to contain the causal variant (the credible set) in each identified region. However, they typically do not take advantage of information regarding the function of these SNPs. PolyFun, a well-established machine learning method, will be used to identify the features of SNPs (187 tested) that are associated with PD and SCZ risk (e.g., degree of evolutionary conservation). This information will then be used as a Bayesian prior to generate improved credible sets and map putative causal SNPs to putative causal genes (e.g., SNPs located in promoters). In addition to this SNP-centric approach, a similar gene-centric approach will be employed. PoPS, a recently-published machine learning method, will be used to identify the features of genes (>57,000 tested) that are associated with PD and SCZ risk (e.g., expression in brain). The genes that are most likely to affect disease risk will be identified based on their features. By combining these SNP-centric and gene-centric methods we will pinpoint causal genes in as-of-yet unresolved GWAS regions.
As a positive control, we will present PolyFun and PoPS results for PD and SCZ loci that have previously been successfully fine-mapped. In addition, we will present results for loci that have not been successfully fine-mapped, focusing on loci where a single putative causal gene is nominated with high confidence.
Here we propose using cutting edge computational techniques to identify causal variants and genes in GWAS loci for PD and SCZ. Our findings may help identify novel drug targets for these diseases and may lead to the development of new pharmacological approaches.
Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of ...rare PD variants. We assessed a total of 27,590 PD cases, 6701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies. The meta-analysis resulted in five significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. Another eight variants are strong candidate variants for their association with PD. Here, we provide the largest rare variant meta-analysis to date, providing information on confirmed and newly identified variants for their association with PD using several large databases. Additionally we also show the complexities of studying rare variants in large-scale cohorts.
Abstract
Spouses may affect each other’s sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep ...duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = −0.11; −0.12, −0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (−0.15; −0.26, −0.04) and snoring (−0.15; −0.27, −0.04). Findings support the notion that an individual’s sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.
Irritable bowel syndrome (IBS) results from disordered brain-gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive ...health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (r
> 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain-gut interactions underlying IBS.
Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's ...disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.
Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian ...randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.
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