Effects of Macromolecular Crowding on Protein Conformational Changes

Many protein functions can be directly linked to conformational changes. Inside cells, the equilibria and transition rates between different conformations may be affected by macromolecular crowding. We have recently developed a new approach for modeling crowding effects, which enables an atomistic representation of “test” proteins. Here this approach is applied to study how crowding affects the equilibria and transition rates between open and closed conformations of seven proteins: yeast protein disulfide isomerase (yPDI), adenylate kinase (AdK), orotidine phosphate decarboxylase (ODCase), Trp repressor (TrpR), hemoglobin, DNA β-glucosyltransferase, and Ap4A hydrolase. For each protein, molecular dynamics simulations of the open and closed states are separately run. Representative open and closed conformations are then used to calculate the crowding-induced changes in chemical potential for the two states. The difference in chemical-potential change between the two states finally predicts the effects of crowding on the population ratio of the two states. Crowding is found to reduce the open population to various extents. In the presence of crowders with a 15 Å radius and occupying 35% of volume, the open-to-closed population ratios of yPDI, AdK, ODCase and TrpR are reduced by 79%, 78%, 62% and 55%, respectively. The reductions for the remaining three proteins are 20–44%. As expected, the four proteins experiencing the stronger crowding effects are those with larger conformational changes between open and closed states (e.g., as measured by the change in radius of gyration). Larger proteins also tend to experience stronger crowding effects than smaller ones [e.g., comparing yPDI (480 residues) and TrpR (98 residues)]. The potentials of mean force along the open-closed reaction coordinate of apo and ligand-bound ODCase are altered by crowding, suggesting that transition rates are also affected. These quantitative results and qualitative trends will serve as valuable guides for expected crowding effects on protein conformation changes inside cells

Exome Sequencing Reveals a Phenotype Modifying Variant inZNF528in Primary Osteoporosis With aCOL1A2Deletion

We studied a family with severe primary osteoporosis carrying a heterozygous p.Arg8Phefs*14 deletion in COL1A2, leading to haploinsufficiency. Three affected individuals carried the mutation and presented nearly identical spinal fractures but lacked other typical features of either osteogenesis imperfecta or Ehlers-Danlos syndrome. Although mutations leading to haploinsufficiency in COL1A2 are rare, mutations in COL1A1 that lead to less protein typically result in a milder phenotype. We hypothesized that other genetic factors may contribute to the severe phenotype in this family. We performed whole-exome sequencing in five family members and identified in all three affected individuals a rare nonsense variant (c.1282C > T/p.Arg428*, rs150257846) in ZNF528. We studied the effect of the variant using qPCR and Western blot and its subcellular localization with immunofluorescence. Our results indicate production of a truncated ZNF528 protein that locates in the cell nucleus as per the wild-type protein. ChIP and RNA sequencing analyses on ZNF528 and ZNF528-c.1282C > T indicated that ZNF528 binding sites are linked to pathways and genes regulating bone morphology. Compared with the wild type, ZNF528-c.1282C > T showed a global shift in genomic binding profile and pathway enrichment, possibly contributing to the pathophysiology of primary osteoporosis. We identified five putative target genes for ZNF528 and showed that the expression of these genes is altered in patient cells. In conclusion, the variant leads to expression of truncated ZNF528 and a global change of its genomic occupancy, which in turn may lead to altered expression of target genes. ZNF528 is a novel candidate gene for bone disorders and may function as a transcriptional regulator in pathways affecting bone morphology and contribute to the phenotype of primary osteoporosis in this family together with the COL1A2 deletion. (c) 2020 The Authors.Journal of Bone and Mineral Researchpublished by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).Peer reviewe

Sequencing by Hybridization of Long Targets

Sequencing by Hybridization (SBH) reconstructs an n-long target DNA sequence from its biochemically determined l-long subsequences. In the standard approach, the length of a uniformly random sequence that can be unambiguously reconstructed is limited to due to repetitive subsequences causing reconstruction degeneracies. We present a modified sequencing method that overcomes this limitation without the need for different types of biochemical assays and is robust to error

A novel and well-defined benchmarking method for second generation read mapping

Background Second generation sequencing technologies yield DNA sequence data at ultra high-throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. The assessment of the quality of read mapping results is not straightforward and has not been formalized so far. Hence, it has not been easy to compare different read mapping approaches in a unified way and to determine which program is the best for what task. Results We present a new benchmark method, called Rabema (Read Alignment BEnchMArk), for read mappers. It consists of a strict definition of the read mapping problem and of tools to evaluate the result of arbitrary read mappers supporting the SAM output format. Conclusions We show the usefulness of the benchmark program by performing a comparison of popular read mappers. The tools supporting the benchmark are licensed under the GPL and available from http://www.seqan.de/projects/rabema.html

A Didactic Model of Macromolecular Crowding Effects on Protein Folding

A didactic model is presented to illustrate how the effect of macromolecular crowding on protein folding and association is modeled using current analytical theory and discrete molecular dynamics. While analytical treatments of crowding may consider the effect as a potential of average force acting to compress a polypeptide chain into a compact state, the use of simulations enables the presence of crowding reagents to be treated explicitly. Using an analytically solvable toy model for protein folding, an approximate statistical thermodynamic method is directly compared to simulation in order to gauge the effectiveness of current analytical crowding descriptions. Both methodologies are in quantitative agreement under most conditions, indication that both current theory and simulation methods are capable of recapitulating aspects of protein folding even by utilizing a simplistic protein model

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the <it>r</it>²LD statistic have gained popularity because <it>r</it>²is directly related to statistical power to detect disease associations. Most of existing <it>r</it>²based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>Results</p> <p>We propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when <it>r</it>²≥ 0.9.</p> <p>Conclusions</p> <p>Generating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.</p

Genetic variations in APPL2 are associated with overweight and obesity in a Chinese population with normal glucose tolerance

<p>Abstract</p> <p>Background</p> <p>APPL1 and APPL2 are two adaptor proteins, which can mediate adiponectin signaling via binding to N terminus of adiponectin receptors in muscle cells. Genes encoding adiponectin and adiponectin receptors contribute to insulin resistance and the risk of obesity, and genetic variants of <it>APPL1 </it>are associated with body fat distribution. However, the association between genetic variations of <it>APPL2 </it>and metabolic traits remains unknown. In the current study, we aimed to test the impacts of <it>APPL2 </it>genetic variants on obesity in a Chinese population with normal glucose tolerance.</p> <p>Methods</p> <p>We genotyped six single nucleotide polymorphisms (SNPs) in <it>APPL2 </it>in 1,808 non-diabetic subjects. Overweight and obesity were defined by body mass index (BMI). Obesity-related anthropometric parameters were measured, including height, weight, waist circumference, hip circumference. BMI and waist-hip ratio (WHR) were calculated.</p> <p>Results</p> <p>We found significant evidence of association with overweight/obesity for rs2272495 and rs1107756. rs2272495 C allele and rs1107756 T allele both conferred a higher risk of being overweight and obese (OR 1.218, 95% CI 1.047-1.416, <it>p </it>= 0.011 for rs2272495; OR 1.166, 95% CI 1.014-1.341, <it>p </it>= 0.031 for rs1107756). After adjusting multiple comparisons, only the effect of rs2272495 on overweight/obesity remained to be significant (empirical <it>p </it>= 0.043). Moreover, we investigated the effects of these SNPs on obesity-related quantitative traits in all participants. rs2272495 was associated with BMI (<it>p </it>= 0.015), waist circumference (<it>p </it>= 0.006), hip circumference (<it>p </it>= 0.025) as well as WHR (<it>p </it>= 0.047) under a recessive model. Similar associations were found for rs1107756 except for WHR.</p> <p>Conclusion</p> <p>This study suggests that genetic variations in <it>APPL2 </it>are associated with overweight and obesity in Chinese population with normal glucose tolerance.</p

Lack of association between genetic polymorphisms within DUSP12 - ATF6 locus and glucose metabolism related traits in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Genome-wide linkage studies in multiple ethnic populations found chromosome 1q21-q25 was the strongest and most replicable linkage signal in the human chromosome. Studies in Pima Indian, Caucasians and African Americans identified several SNPs in <it>DUSP12 </it>and <it>ATF6</it>, located in chromosome 1q21-q23, were associated with type 2 diabetes.</p> <p>Methods</p> <p>We selected 19 single nucleotide polymorphisms (SNPs) that could tag 98% of the SNPs with minor allele frequencies over 0.1 within <it>DUSP12-ATF6 </it>region. These SNPs were genotyped in a total of 3,700 Chinese Han subjects comprising 1,892 type 2 diabetes patients and 1,808 controls with normal glucose regulation.</p> <p>Results</p> <p>None of the SNPs and haplotypes showed significant association to type 2 diabetes in our samples. No association between the SNPs and quantitative traits was observed either.</p> <p>Conclusions</p> <p>Our data suggests common SNPs within <it>DUSP12</it>-<it>ATF6 </it>locus may not play a major role in glucose metabolism in the Chinese.</p

Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model

<p>Abstract</p> <p>Background</p> <p>Antibodies directed against haemagglutinin, measured by the haemagglutination inhibition (HI) assay are essential to protective immunity against influenza infection. An HI titre of 1:40 is generally accepted to correspond to a 50% reduction in the risk of contracting influenza in a susceptible population, but limited attempts have been made to further quantify the association between HI titre and protective efficacy.</p> <p>Methods</p> <p>We present a model, using a meta-analytical approach, that estimates the level of clinical protection against influenza at any HI titre level. Source data were derived from a systematic literature review that identified 15 studies, representing a total of 5899 adult subjects and 1304 influenza cases with interval-censored information on HI titre. The parameters of the relationship between HI titre and clinical protection were estimated using Bayesian inference with a consideration of random effects and censorship in the available information.</p> <p>Results</p> <p>A significant and positive relationship between HI titre and clinical protection against influenza was observed in all tested models. This relationship was found to be similar irrespective of the type of viral strain (A or B) and the vaccination status of the individuals.</p> <p>Conclusion</p> <p>Although limitations in the data used should not be overlooked, the relationship derived in this analysis provides a means to predict the efficacy of inactivated influenza vaccines when only immunogenicity data are available. This relationship can also be useful for comparing the efficacy of different influenza vaccines based on their immunological profile.</p