An efficient visualization tool for the analysis of protein mutation matrices

<p>Abstract</p> <p>Background</p> <p>It is useful to develop a tool that would effectively describe protein mutation matrices specifically geared towards the identification of mutations that produce either wanted or unwanted effects, such as an increase or decrease in affinity, or a predisposition towards misfolding. Here, we describe a tool where such mutations are efficiently identified, categorized and visualized. To categorize the mutations, amino acids in a mutation matrix are arrang according to one of three sets of physicochemical characteristics, namely hydrophilicity, size and polarizability, and charge and polarity. The magnitude and frequences of mutations for an alignment are subsequently described using color information and scaling factors.</p> <p>Results</p> <p>To illustrate the capabilities of our approach, the technique is used to visualize and to compare mutation patterns in evolving sequences with diametrically opposite characteristics. Results show the emergence of distinct patterns not immediately discernible from the raw matrices.</p> <p>Conclusion</p> <p>Our technique enables effective categorization and visualization of mutations by using specifically-arranged mutation matrices. This tool has a number of possible applications in protein engineering, notably in simplifying the identification of mutations and/or mutation trends that are associated with specific engineered protein characteristics and behavior.</p

PM₁₀-bound trace elements in pan-European urban atmosphere

Although many studies have discussed the impact of Europe's air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM10 in urban atmosphere. This study compiled long-term (2013–2022) measurements of speciation of ambient urban PM10 from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM10 in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types. The sampling campaigns were conducted using standardized protocols to ensure data comparability. In each country, PM10 samples were collected over a fixed period using high-volume air samplers. The analysis encompassed the spatio-temporal distribution of TEs, and relationships between TEs at each site. Results indicated an annual average for the sum of 20 TEs of 90 ± 65 ng/m3, with TR and IN sites exhibiting the highest concentrations (130 ± 66 and 131 ± 80 ng/m3, respectively). Seasonal variability in TEs concentrations, influenced by emission sources and meteorology, revealed significant differences (p &lt; 0.05) across all monitoring sites. Estimation of TE concentrations highlighted distinct ratios between non-carcinogenic and carcinogenic metals, with Zn (40 ± 49 ng/m3), Ti (21 ± 29 ng/m3), and Cu (23 ± 35 ng/m3) dominating non-carcinogenic TEs, while Cr (5 ± 7 ng/m3), and Ni (2 ± 6 ng/m3) were prominent among carcinogenic ones. Correlations between TEs across diverse locations and seasons varied, in agreement with differences in emission sources and meteorological conditions. This study provides valuable insights into TEs in pan-European urban atmosphere, contributing to a comprehensive dataset for future environmental protection policies

The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

<p>Abstract</p> <p>Background</p> <p>All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences.</p> <p>Results</p> <p>The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%.</p> <p>Conclusions</p> <p>This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.</p

Posttraumatic growth (PTG) and posttraumatic depreciation (PTD) across ten countries: Global validation of the PTG-PTD theoretical model

info:eu-repo/semantics/publishedVersio

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Zoonotic "Enterocytozoon bieneusi" genotypes in free-ranging and farmed wild ungulates in Spain

Microsporidia comprises a diverse group of obligate, intracellular, and spore-forming parasites that infect a wide range of animals. Among them, Enterocytozoon bieneusi is the most frequently reported species in humans and other mammals and birds. Data on the epidemiology of E. bieneusi in wildlife are limited. Hence, E. bieneusi was investigated in eight wild ungulate species present in Spain (genera Ammotragus, Capra, Capreolus, Cervus, Dama, Ovis, Rupicapra, and Sus) by molecular methods. Faecal samples were collected from free-ranging (n = 1058) and farmed (n = 324) wild ungulates from five Spanish bioregions. The parasite was detected only in red deer (10.4%, 68/653) and wild boar (0.8%, 3/359). Enterocytozoon bieneusi infections were more common in farmed (19.4%, 63/324) than in wild (1.5%, 5/329) red deer. A total of 11 genotypes were identified in red deer, eight known (BEB6, BEB17, EbCar2, HLJD-V, MWC_d1, S5, Type IV, and Wildboar3) and three novel (DeerSpEb1, DeerSpEb2, and DeerSpEb3) genotypes. Mixed genotype infections were detected in 15.9% of farmed red deer. Two genotypes were identified in wild boar, a known (Wildboar3) and a novel (WildboarSpEb1) genotypes. All genotypes identified belonged to E. bieneusi zoonotic Groups 1 and 2. This study provides the most comprehensive epidemiological study of E. bieneusi in Spanish ungulates to date, representing the first evidence of the parasite in wild red deer populations worldwide. Spanish wild boars and red deer are reservoir of zoonotic genotypes of E. bieneusi and might play an underestimated role in the transmission of this microsporidian species to humans and other animal

Potent acyl-CoA synthetase 10 inhibitors kill <i>Plasmodium falciparum</i> by disrupting triglyceride formation

Identifying how small molecules act to kill malaria parasites can lead to new chemically validated targets. By pressuring Plasmodium falciparum asexual blood stage parasites with three novel structurally-unrelated antimalarial compounds (MMV665924, MMV019719 and MMV897615), and performing whole-genome sequence analysis on resistant parasite lines, we identify multiple mutations in the P. falciparum acyl-CoA synthetase (ACS) genes PfACS10 (PF3D7_0525100, M300I, A268D/V, F427L) and PfACS11 (PF3D7_1238800, F387V, D648Y, and E668K). Allelic replacement and thermal proteome profiling validates PfACS10 as a target of these compounds. We demonstrate that this protein is essential for parasite growth by conditional knockdown and observe increased compound susceptibility upon reduced expression. Inhibition of PfACS10 leads to a reduction in triacylglycerols and a buildup of its lipid precursors, providing key insights into its function. Analysis of the PfACS11 gene and its mutations point to a role in mediating resistance via decreased protein&nbsp;stability